Mobile Computing Projects – ElysiumPro

Mobile Computing Projects ElysiumPro

Mobile Computing Projects

CSE Projects, ECE Projects
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M Mobile computing involves mobile communication, mobile hardware, and mobile software. It includes ad hoc networks and infrastructure networks, communication properties, protocols, data formats and concrete technologies. We offer projects on mobility patterns, social properties, node mobility, routing mechanism, and defense architecture of mobiles.
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1Virtual Multipath Attack and Defense for Location Distinction in Wireless Networks
In wireless networks, location distinction aims to detect location changes or facilitate authentication of wireless users. To achieve location distinction, recent research has focused on investigating the spatial uncorrelation property of wireless channels. Specifically, differences in wireless channel characteristics are used to distinguish locations or identify location changes. However, we discover a new attack against all existing location distinction approaches that are built on the spatial uncorrelation property of wireless channels. In such an attack, the adversary can easily hide her location changes or impersonate movements by injecting fake wireless channel characteristics into a target receiver. To defend against this attack, we propose a detection technique that utilizes an auxiliary receiver or antenna to identify these fake channel characteristics. We also discuss such attacks and corresponding defenses in OFDM systems. Experimental results on our USRP-based prototype show that the discovered attack can craft any desired channel characteristic with a successful probability of 95.0 percent to defeat spatial uncorrelation based location distinction schemes and our novel detection method achieves a detection rate higher than 91.2 percent while maintaining a very low false alarm rate.

2Spectrum-Aware any path Routing in Multi-Hop Cognitive Radio Networks
The increasing demand of wireless applications has led to the problem of spectrum scarcity. The new networking paradigm is widely known as Dynamic Spectrum Access (DSA). DSA can be realized by use of cognitive radio (CR) technology. A CR provides an opportunistic utilization of an underutilized spectrum to the node with which it is equipped. Usually a nonlicensed user/node is equipped with a CR. Recent research has mainly been focused on Spectrum sensing, sharing, mobility and decision making which allows one to make use available free spectrum blocks opportunistically, but less emphasis have been laid on routing in multi-hope cognitive radio networks (CRNs). The feasibility of a multi-hope CRN depends entirely on routing scheme employed in it, as it ensures end-to-end delivery of data packets. Hence to make CRNs more efficient and prominent, an effective routing layer is required which is aware of the dynamics of CRNs. This work proposes a Spectrum Aware Distance Utilization Routing Protocol for (CRNs). The proposed protocol aims at providing optimal routing paths, which offers high spectrum availability with minimum path length between any pair of Source and Destination, hence enhancing routing in multi-hop CRNs. For optimal path formulation, it uses spectrum availability and link utilization factor. Through extensive simulations the efficiency of the proposed protocol found better than the existing ones.

3Practical Opportunistic Data Collection in Wireless Sensor Networks with Mobile Sinks
Wireless Sensor Networks with Mobile Sinks (WSN-MSs) are considered a viable alternative to the heavy cost of deployment of traditional wireless sensing infrastructures at scale. However, current state-of-the-art approaches perform poorly in practice due to their requirement of mobility prediction and specific assumptions on network topology. In this paper, we focus on lowdelay and high-throughput opportunistic data collection in WSN-MSs with general network topologies and arbitrary numbers of mobile sinks. We first propose a novel routing metric, Contact-Aware ETX (CA-ETX), to estimate the packet transmission delay caused by both packet retransmissions and intermittent connectivity. By implementing CA-ETX in the defacto TinyOS routing standard CTP and the IETF IPv6 routing protocol RPL, we demonstrate that CA-ETX can work seamlessly with ETX. This means that current ETX-based routing protocols for static WSNs can be easily extended to WSN-MSs with minimal modification by using CA-ETX. Further, by combing CA-ETX with the dynamic backpressure routing, we present a throughput-optimal scheme Opportunistic Backpressure Collection (OBC). Both CA-ETX and OBC are lightweight, easy to implement, and require no mobility prediction. Through test-bed experiments and extensive simulations, we show that the proposed schemes significantly outperform current approaches in terms of packet transmission delay, communication overhead, storage overheads, reliability, and scalability.

4RT-Fall: A Real-Time and Contactless Fall Detection System with Commodity WiFi Devices
This paper presents the design and implementation of RT-Fall, a real-time, contactless, low-cost yet accurate indoor fall detection system using the commodity WiFi devices. RT-Fall exploits the phase and amplitude of the fine-grained Channel State Information (CSI) accessible in commodity WiFi devices, and for the first time fulfills the goal of segmenting and detecting the falls automatically in real-time, which allows users to perform daily activities naturally and continuously without wearing any devices on the body. This work makes two key technical contributions. First, we find that the CSI phase difference over two antennas is a more sensitive base signal than amplitude for activity recognition, which can enable very reliable segmentation of fall and fall-like activities. Second, we discover the sharp power profile decline pattern of the fall in the time-frequency domain and further exploit the insight for new feature extraction and accurate fall segmentation/detection. Experimental results in four indoor scenarios demonstrate that RT-fall consistently outperforms the state-of-the-art approach WiFall with 14 percent higher sensitivity and 10 percent higher specificity on average.

5Maximum Link Activation with Cooperative Transmission and Interference Cancellation in Wireless Networks
We address the maximum link activation problem in wireless networks with new features, namely when the transmitters can perform cooperative transmission, and the receivers are able to perform successive interference cancellation. In this new problem setting, which transmitters should transmit and to whom, as well as the optimal cancellation patterns at the receivers, are strongly intertwined. We present contributions along three lines. First, we provide a thorough tractability analysis, proving the NP-hardness as well as identifying tractable cases. Second, for benchmarking purposes, we deploy integer linear programming for achieving global optimum using off-the-shelf optimization methods. Third, to overcome the scalability issue of integer programming, we design a suboptimal but efficient optimization algorithm for the problem in its general form, by embedding maximum-weighted bipartite matching into local search. Numerical results are presented for performance evaluation, to validate the benefit of cooperative transmission and interference cancellation for maximum link activation, and to demonstrate the effectiveness of the proposed algorithm.

6Beyond Overlay: Reaping Mutual Benefits for Primary and Secondary Networks through Node-Level Cooperation
Existing spectrum sharing paradigms have set clear boundaries between the primary and secondary networks. There is either no or very limited node-level cooperation between the primary and secondary networks. In this paper, we develop a new and bold spectrum-sharing paradigm beyond the state of the art for future wireless networks. We explore network cooperation as a new dimension for spectrum sharing between the primary and secondary users. Such network cooperation can be defined as a set of policies under which different degrees of cooperation are to be achieved. The benefits of this paradigm are numerous, as they allow integrating resources from two networks. There are many possible node-level cooperation policies that one can employ under this paradigm. For the purpose of performance study, we consider a specific policy called united cooperation of Primary and Secondary (UPS) networks. UPS allows a complete cooperation between the primary and secondary networks at the node level to relay each other's traffic. As a case study, we consider a problem with the goal of supporting the rate requirement of the primary network traffic while maximizing the throughput of the secondary sessions. For this problem, we develop an optimization model and formulate a combinatorial optimization problem. We also develop an approximation solution based on a piece-wise linearization technique. Simulation results show that UPS offers significantly better throughput performance than that under the interweave paradigm.

7Collaborative Smartphone Sensing Using Overlapping Coalition Formation Games
With the rapid growth of sensor technology, smartphone sensing has become an effective approach to improve the quality of smartphone applications. However, due to time-varying wireless channels and lack of incentives for the users to participate, the quality and quantity of the data uploaded by the smartphone users are not always satisfying. In this paper, we consider a smartphone sensing system in which a platform publicizes multiple tasks, and the smartphone users choose a set of tasks to participate in. In the traditional non-cooperative approach with incentives, each smartphone user gets rewards from the platform as an independent individual and the limit of the wireless channel resources is often omitted. To tackle this problem, we introduce a novel cooperative approach with an overlapping coalition formation game (OCF-game) model, in which the smartphone users can cooperate with each other to form the overlapping coalitions for different sensing tasks. We also utilize a centralized case to describe the upper bound of the system sensing performance. Simulation results show that the cooperative approach achieves a better performance than the non-cooperative one in various situations.

8Geometrical Characterization of Offloading through Wireless LANs
The offloading of cellular traffic through WLAN APs (wireless local area network access points) distributed in a homogeneous Poisson process (HPP) is theoretically evaluated. The probability Pw that a user can use WLAN and the expected number of vertical handovers Nh are evaluated as the basic performance metrics of WLAN AP coverage. Explicit formulas are derived for the metrics, and the fundamental relationships between the metrics and many parameters such as the shape of each WLAN coverage region D1, D2,... are described. These metrics depend on the size and perimeter length of Di but do not depend on their other shape parameters for a convex Di. In addition, it is proven that a disk-shaped Di minimizes Nh for a fixed WLAN coverage size and that Pw is often insensitive to the perimeter length of Di. It is also proven that the Pw of a user at a random location is equal to that moving along a random straight line or a random bounded curve. One hundred empirical location data sets of WLAN APs in Japan, Korea, and the US were used to confirm the theoretical results. Although these locations do not follow an HPP, many theoretical results are shown to be valid. For example, Nh is minimized by a disk-shaped Di. Simultaneously, we find that Pw slightly increases when a slender Di is used for highly clustered AP locations.

9Impact of Full Duplex Scheduling on End-to-End Throughput in Multi-Hop Wireless Networks
There have been some rapid advances on the design of full duplex (FD) transceivers in recent years. Although the benefits of FD have been studied for single-hop wireless communications, its potential on throughput performance in a multi-hop wireless network remains unclear. As for multi-hop networks, a fundamental problem is to compute the achievable end-to-end throughput for one or multiple communication sessions. The goal of this paper is to offer some fundamental understanding on end-to-end throughput performance limits of FD in a multi-hop wireless network. We show that through a rigorous mathematical formulation, we can cast the multi-hop throughput performance problem into a formal optimization problem. Through numerical results, we show that in many cases, the end-to-end session throughput in a FD network can exceed 2x of that in a half-duplex (HD) network. Our finding can be explained by the much larger design space for scheduling that is offered by removing HD constraints in throughput maximization problem. The results in this paper offer some new understandings on the potential benefits of FD for end-to-end session throughput in a multi-hop wireless network.

10Traffic Decorrelation Techniques for Countering a Global Eavesdropper in WSNs
We address the problem of preventing the inference of contextual information in event-driven wireless sensor networks (WSNs). The problem is considered under a global eavesdropper who analyzes low-level RF transmission attributes, such as the number of transmitted packets, inter-packet times, and traffic directionality, to infer event location, its occurrence time, and the sink location. We devise a general traffic analysis method for inferring contextual information by correlating transmission times with eavesdropping locations. Our analysis shows that most existing countermeasures either fail to provide adequate protection, or incur high communication and delay overheads. To mitigate the impact of eavesdropping, we propose resource-efficient traffic normalization schemes. In comparison to the state-of-the-art, our methods reduce the communication overhead by more than 50 percent, and the end-to-end delay by more than 30 percent. To do so, we partition the WSN to minimum connected dominating sets that operate in a round-robin fashion. This allows us to reduce the number of traffic sources active at a given time, while providing routing paths to any node in the WSN. We further reduce packet delay by loosely coordinating packet relaying, without revealing the traffic directionality.

11GDVAN: A New Greedy Behaviour Attack Detection Algorithm for VANETs
Vehicular Ad hoc Networks (VANETs), whose main objective is to provide road safety and enhance the driving conditions, are exposed to several kinds of attacks such as Denial of Service (DoS) attacks which affect the availability of the underlying services for legitimate users. We focus especially on the greedy behavior which has been extensively addressed in the literature for Wireless LAN (WLAN) and for Mobile Ad hoc Networks (MANETs). However, this attack has been much less studied in the context of VANETs. This is mainly because the detection of a greedy behavior is much more difficult for high mobility networks such as VANETs. In this paper, we propose a new detection approach called GDVAN (Greedy Detection for VANETs) for greedy behavior attacks in VANETs. The process to conduct the proposed method mainly consists of two phases, which are namely the suspicion phase and the decision phase. The suspicion phase is based on the linear regression mathematical concept while decision phase is based on a fuzzy logic decision scheme. The proposed algorithm not only detects the existence of a greedy behavior but also establishes a list of the potentially compromised nodes using three newly defined metrics. In addition to being passive, one of the major advantages of our technique is that it can be executed by any node of the network and does not require any modification of the IEEE 802.11p standard. Moreover, the practical effectiveness and efficiency of the proposed approach are corroborated through simulations and experiments.

12Using Wireless Link Dynamics to Extract a Secret Key in Vehicular Scenarios
Securing a wireless channel between any two vehicles is a crucial component of vehicular networks security. This can be done by using a secret key to encrypt the messages. We propose a scheme to allow two cars to extract a shared secret from RSSI (Received Signal Strength Indicator) values in such a way that nearby cars cannot obtain the same key. The key is information-theoretically secure, i.e., it is secure against an adversary with unlimited computing power. Although there are existing solutions of key extraction in the indoor or low-speed environments, the unique channel conditions make them inapplicable to vehicular environments. Our scheme effectively and efficiently handles the high noise and mismatch features of the measured samples so that it can be executed in the noisy vehicular environment. We also propose an online parameter learning mechanism to adapt to different channel conditions. Extensive real-world experiments are conducted to validate our solution.

13Toward a Wearable RFID System for Real-Time Activity Recognition Using Radio Patterns
Elderly care is one of the many applications supported by real-time activity recognition systems. Traditional approaches use cameras, body sensor networks, or radio patterns from various sources for activity recognition. However, these approaches are limited due to ease-of-use, coverage, or privacy preserving issues. In this paper, we present a novel wearable Radio Frequency Identification (RFID) system aims at providing an easy-to-use solution with high detection coverage. Our system uses passive tags which are maintenance-free and can be embedded into the clothes to reduce the wearing and maintenance efforts. A small RFID reader is also worn on the user's body to extend the detection coverage as the user moves. We exploit RFID radio patterns and extract both spatial and temporal features to characterize various activities. We also address the issues of false negative of tag readings and tag/antenna calibration, and design a fast online recognition system. Antenna and tag selection is done automatically to explore the minimum number of devices required to achieve target accuracy. We develop a prototype system which consists of a wearable RFID system and a smartphone to demonstrate the working principles, and conduct experimental studies with four subjects over two weeks. The results show that our system achieves a high recognition accuracy of 93.6 percent with a latency of 5 seconds. Additionally, we show that the system only requires two antennas and four tagged body parts to achieve a high recognition accuracy of 85 percent.

14Propagation- and Mobility-Aware D2D Social Content Replication
Mobile online social network services have seen rapid expansion; thus, the corresponding huge amounts of user-generated social media contents propagating between users via social connections have significantly challenged the traditional content delivery paradigm. First, replicating all the contents generated by users to edge servers that well “fit” the receivers becomes difficult due to limited bandwidth and storage capacities. Motivated by device-to-device (D2D) communication, which allows users with smart devices to transfer content directly, we propose replicating bandwidth-intensive social contents in a device-to-device manner. Based on large-scale measurement studies on social content propagation and user mobility patterns in edge-network regions, we observe the following: (1) Device-to-device replication can significantly help users download social contents from neighboring peers. (2) Both social propagation and mobility patterns affect how contents should be replicated. (3) The replication strategies depend on regional characteristics (e.g., how users move across regions). Using these measurement insights, we propose a propagation and mobility-aware content replication strategy for edge-network regions, in which social contents are assigned to users in edge-network regions according to a joint consideration of social graphs, content propagation, and user mobility. We formulate the replication scheduling as an optimization problem and design a distributed algorithm using only historical, local, and partial information to solve it. Trace-driven experiments further verify the superiority of our proposal: compared with conventional pure-movement-based and popularity-based approaches, our design can significantly improve (2 - 4-fold improvement) the amount of social content successfully delivered via device-to-device replication.

15SEND: A Situation-Aware Emergency Navigation Algorithm with Sensor Networks
When emergencies happen, navigation services that guide people to exits while keeping them away from emergencies are critical in saving lives. To achieve timely emergency navigation, early and automatic detection of potential dangers, and quick response with safe paths to exits are the core requirements, both of which rely on continuous environment monitoring and reliable data transmission. Wireless sensor networks (WSNs) are a natural choice of the infrastructure to support emergency navigation services, given their relatively easy deployment and affordable costs, and the ability of ubiquitous sensing and communication. Although many efforts have been made to WSN-assisted emergency navigation, almost all existing works neglect to consider the hazard levels of emergencies and the evacuation capabilities of exits. Without considering such aspects, existing navigation approaches may fail to keep people farther away from emergencies of high hazard levels and would probably encounter congestions at exits with lower evacuation capabilities. In this paper, we propose SEND, a situation-aware emergency navigation algorithm, which takes the hazard levels of emergencies and the evacuation capabilities of exits into account and provides the mobile users the safest navigation paths accordingly. We formally model the situation-aware emergency navigation problem and establish a hazard potential field in the network, which is theoretically free of local minima. By guiding users following the descend gradient of the hazard potential field, SEND can thereby achieve guaranteed success of navigation and provide optimal safety. The effectiveness of SEND is validated by both experiments and extensive simulations in 2D and 3D scenarios.

16Joint Cell Zooming and Channel Allocation Using C-SAP for Large Action Sets
Optimizing energy consumption is paramount to sustain the growth of cellular networks. One of the approaches to reduce energy consumption is traffic dependent operation of networks. The traffic demand experienced by the network fluctuates over the duration of a day. Therefore, during the periods of low traffic, we may re-configure the network to trade the excess capacity for energy reduction. For example, we may modulate the BS transmit power (Cell Zooming) so as to maintain the desired QoS. However, determining an optimal network configuration is known to be computationally hard. Along with Cell Zooming, it is essential to also consider channel re-assignment, for, when the transmit powers of BSs are changed, the channels allocated to BSs must also be suitably changed. Considering therefore channel allocations also as state variables, the search space over which the optimization should be performed blows up, further complicating the problem. In this paper, we propose a framework to address this problem. The proposed algorithm is suitable for such large search spaces, while the framework is general enough to admit several QoS requirements and sophisticated power consumption models. The underlying mathematical formulation is also applicable in other contexts, and is of independent interest as well.

17Montage: Combine Frames with Movement Continuity for Realtime Multi-User Tracking
In this work, we design and develop Montage for real-time multi-user formation tracking and localization by off-the-shelf smartphones. Montage achieves submeter-level tracking accuracy by integrating temporal and spatial constraints from user movement vectorestimation and distance measuring. In Montage, we designed a suite of novel techniques to surmount a variety of challenges in real-time tracking, without infrastructure and fingerprints, and without any a priori user-specific (e.g., stride-length and phoneplacement) or site-specific (e.g., digitalized map) knowledge: (1) a coded audio tone to support multi-user tracking with minimal latency, in the presence of high noise, multi-path effect, and Doppler Shift, (2) an innovative stride-length and walking direction estimation method without a priori knowledge of user and site, and (3) a vector-based multi-user tracking scheme which connects successive localization snapshots to refine users' locations and generate continuous moving traces. We implemented, deployed, and evaluated Montage in both outdoor and indoor environment. Our experimental results (847 traces from 15 users) show that the stride-length estimated by Montage over all users has error within 9cm, and the moving-direction estimated by Montage is within 20 degrees. For real-time tracking, Montage provides meter-second-level formation tracking accuracy with off-the-shelf mobile phones.

18Analytical Evaluation of Saturation Throughput of a Cognitive WLAN Overlaid on a Time-Scheduled OFDMA Network
In this paper, we analyze the saturation throughput of a cognitive WLAN overlaid on a primary OFDMA TDD network (e.g., LTE or WiMAX). In this scenario, after the contention among the secondary nodes, the winner node transmits its data packet in the empty resource blocks (RBs) of downlink and uplink subframes of the primary network. Regarding the OFDMA structure as well as time-scheduled resources in the primary network, the time duration of opportunities for the secondary network does not follow simple exponential on-off pattern. To model the dynamic behavior of opportunities for secondary nodes as well as contentions to exploit the opportunities, we propose an analytical model comprised of a discrete-time Markov chain and two inter-related open multi-class queueing networks (QNs). The effects of the random number of empty resource blocks at different frames as the result of random amount of download and upload data, random packet transmission time at WLAN, the dependency of the number of empty RBs at consecutive frames, and the details of 802.11 MAC protocol are included in our analytical approach. We include different resource allocations in the primary network in our analysis. Simulation results confirm the accuracy of our analytical approach in different conditions.

19Receiver-Initiated Spectrum Management for Underwater Cognitive Acoustic Network
Cognitive acoustic (CA) is emerging as a promising technique for environment-friendly and spectrum-efficient underwater communications. Due to the unique features of underwater acoustic networks (UANs), traditional spectrum management systems designed for cognitive radio (CR) need an overhaul to work efficiently in underwater environments. In this paper, we propose a receiver-initiated spectrum management (RISM) system for underwater cognitive acoustic networks (UCANs). RISM seeks to improve the performance of UCANs through a collaboration of physical layer and medium access control (MAC) layer. It aims to provide efficient spectrum utilization and data transmissions with a small collision probability for CA nodes, while avoiding harmful interference with both “natural acoustic systems”, such as marine mammals, and “artificial acoustic systems”, like sonars and other UCANs. In addition, to solve the unique challenge of deciding when receivers start to retrieve data from their neighbors, we propose to use a traffic predictor on each receiver to forecast the traffic loads on surrounding nodes. This allows each receiver to dynamically adjust its polling frequency according to the variation of a network traffic. Simulation results show that the performance of RISM with smart polling scheme outperforms the conventional sender-initiated approach in terms of throughput, hop-by-hop delay, and energy efficiency.

20Impact of Full Duplex Scheduling on End-to-End Throughput in Multi-Hop Wireless Networks
There have been some rapid advances on the design of full duplex (FD) transceivers in recent years. Although the benefits of FD have been studied for single-hop wireless communications, its potential on throughput performance in a multi-hop wireless network remains unclear. As for multi-hop networks, a fundamental problem is to compute the achievable end-to-end throughput for one or multiple communication sessions. The goal of this paper is to offer some fundamental understanding on end-to-end throughput performance limits of FD in a multi-hop wireless network. We show that through a rigorous mathematical formulation, we can cast the multi-hop throughput performance problem into a formal optimization problem. Through numerical results, we show that in many cases, the end-to-end session throughput in a FD network can exceed 2x of that in a half-duplex (HD) network. Our finding can be explained by the much larger design space for scheduling that is offered by removing HD constraints in throughput maximization problem. The results in this paper offer some new understandings on the potential benefits of FD for end-to-end session throughput in a multi-hop wireless network.

21Optimal Capacity–Delay Tradeoff in MANETs with Correlation of Node Mobility
In this paper, we analyze the capacity and delay in mobile ad hoc networks (MANETs), considering the correlation of node mobility (correlated mobility). Previous studies on correlated mobility investigated the maximum capacity with the corresponding delay in several subcases; the problem of optimal capacity under various delay constraints (the optimal capacity-delay tradeoff) still remains open. To this end, we deeply explore the characteristics of correlated mobility and figure out the fundamental relationships between the network performance and the scheduling parameters. Based on that, we establish the overall upper bound of the capacity-delay tradeoff in all the subcases of correlated mobility. Then, we try to obtain the achievable lower bound by identifying the optimal scheduling parameters on certain constraints. Results demonstrate the whole picture of how the correlation of node mobility impacts the capacity, the delay, and the corresponding tradeoff between them.

22Network Coding as a Performance Booster for Concurrent Multi-Path Transfer of Data in Multi-Hop Wireless Networks
The emerging use of multi-homed wireless devices along with simultaneous multi-path data transfer offers tremendous potentials to improve the capacity of multi-hop wireless networks. The use of simultaneous data transfer over separate disjoint paths in multi-hop wireless networks to increase network capacity is a less explored subject, mainly because of the challenges it triggers for the reliable transport layer protocols. Reliable transport layer protocols generally use packet sequence number as a mean to ensure delivery. As such, the out-of-order packet arrival in reliable transport layer protocols triggers receiver buffer blocking that causes throughput degradation and prevents the reliable multi-path transport layer protocol to realize its vast potential. This paper focuses on integrating network coding with a reliable multi-path transport layer protocol to resolve the receiver buffer blocking problem. We propose an adaptive network coding mechanism to desensitize the receiver against packet reordering and consequently eliminate the receiver buffer blocking problem. Our state-of-the-art network coding scheme uses a combination of Q-learning and logistic regression for rare data events to control the number of redundant packets based on the network dynamics. We confirmed the veracity of our proposed scheme by a queuing theory based mathematical model. Moreover, the effectiveness of the proposed scheme is demonstrated through simulations and testbed experiments.

23Experimental Evaluation of Impulsive Ultrasonic Intra-Body Communications for Implantable Biomedical Devices
Biomedical systems of miniaturized implantable sensors and actuators interconnected in an intra-body area network could enable revolutionary clinical applications. Given the well-understood limitations of radio frequency (RF) propagation in the human body, in our previous work we investigated the use of ultrasonic waves as an alternative physical carrier of information, and proposed Ultrasonic WideBand (UsWB), an ultrasonic multipath-resilient integrated physical and medium access control (MAC) layer protocol. In this paper, we discuss the design and implementation of a software-defined testbed architecture for ultrasonic intra-body area networks, and propose the first experimental demonstration of the feasibility of ultrasonic communications in tissue mimicking materials. We first discuss in detail our FPGA-based prototype implementation of UsWB. We then demonstrate how the prototype can flexibly trade performance off for power consumption, and achieve, for bit error rates (BER) no higher than 10-6, either (i) high-data rate transmissions up to 700 kbit/s at a transmit power of -14 dBm (˜ 40 µW), or (ii) low-data rate and lower-power transmissions down to -21 dBm (˜ 8 µW) at 70 kbit/s. We demonstrate that the UsWB MAC protocol allows multiple transmitter-receiver pairs to coexist and dynamically adapt the transmission rate according to channel and interference conditions to maximize throughput while satisfying predefined reliability constraints. We also show how UsWB can be used to enable a video monitoring medical application for implantable devices. Finally, we propose (and validate through experiments) a statistical model of small-scale fading for the ultrasonic intra-body channel.

24Channel Selection Algorithm for Cognitive Radio Networks with Heavy-Tailed Idle Times
We consider a multichannel Cognitive Radio Network (CRN), where secondary users sequentially sense channels for opportunistic spectrum access. In this scenario, the Channel Selection Algorithm (CSA) allows secondary users to find a vacant channel with the minimal number of channel switches. Most of the existing CSA literature assumes exponential ON-OFF time distribution for primary user's (PU) channel occupancy pattern. This exponential assumption might be helpful to get performance bounds; but not useful to evaluate the performance of CSA under realistic conditions. An in-depth analysis of independent spectrum measurement traces reveals that wireless channels have typically heavy-tailed PU OFF times. In this paper, we propose an extension to the Predictive CSA framework and its generalization for heavy tailed PU OFF time distribution, which represents realistic scenarios. In particular, we calculate the probability of channel being idle for hyper-exponential OFF times to use in CSA. We implement our proposed CSA framework in a wireless test-bed and comprehensively evaluate its performance by recreating the realistic PU channel occupancy patterns. The proposed CSA shows significant reduction in channel switches and energy consumption as compared to Predictive CSA which always assumes exponential PU ON-OFF times. Through our work, we show the impact of the PU channel occupancy pattern on the performance of CSA in multichannel CRN.

25A Distributed Learning Automata Scheme for Spectrum Management in Self-Organized Cognitive Radio Network
We propose a distributed Learning Automata (LA) for spectrum management problem in Cognitive Radio (CR) networks. The objective is to design intelligent Secondary Users (SUs) which can interact with the RF environment and learn from its different responses through the sensing. It is assumed there is no prior information about the Primary Users (PUs) and other SUs activities while there is no information exchange among SUs. Each SU is empowered with an LA which operates in the RF environment with different responses. That is, the SUs are considered as agents in a self-organized system which select one channel as an action and receive different responses from the environment based on how much their selected actions are favourable or unfavourable. Using these responses, SUs control their accesses to the channels for appropriate spectrum management with the objective to incur less communication delay, less interference with PUs, and less interference with other SUs. The proposed LA-based distributed algorithm is investigated in terms of asymptotic convergence and stability. Simulation results are provided to show the performance of the proposed scheme in terms of SUs’ waiting times, interference with other SUs, and the number of interruptions by PUs during their transmissions, and fairness.

26MoZo: A Moving Zone Based Routing Protocol Using Pure V2V Communication in VANETs
Vehicular Ad-hoc Networks (VANETs) are an emerging field, whereby vehicle-to-vehicle communications can enable many new applications such as safety and entertainment services. Most VANET applications are enabled by different routing protocols. The design of such routing protocols, however, is quite challenging due to the dynamic nature of nodes (vehicles) in VANETs. To exploit the unique characteristics of VANET nodes, we design a moving-zone based architecture in which vehicles collaborate with one another to form dynamic moving zones so as to facilitate information dissemination. We propose a novel approach that introduces moving object modeling and indexing techniques from the theory of large moving object databases into the design of VANET routing protocols. The results of extensive simulation studies carried out on real road maps demonstrate the superiority of our approach compared with both clustering and non-clustering based routing protocols.

27Optimal Cooperative Content Caching and Delivery Policy for Heterogeneous Cellular Networks
To address the explosively growing demand for mobile data services in the 5th generation (5G) mobile communication system, it is important to develop efficient content caching and distribution techniques, aiming at significantly reducing redundant data transmissions and improving content delivery efficiency. In heterogeneous cellular network (HetNet), which has been deemed as a promising architectural technique for 5G, caching some popular content items at femto base-stations (FBSs) and even at user equipment (UE) can be exploited to alleviate the burden of backhaul and to reduce the costly transmissions from the macro base-stations to UEs. In this paper, we develop the optimal cooperative content caching and delivery policy, for which FBSs and UEs are all engaged in local content caching. We formulate the cooperative content caching problem as an integer-linear programming problem, and use hierarchical primal-dual decomposition method to decouple the problem into two level optimization problems, which are solved by using the subgradient method. Furthermore, we design the optimal content delivery policy, which is formulated as an unbalanced assignment problem and solved by using Hungarian algorithm. Numerical results have shown that the proposed cooperative content caching and delivery policy can significantly improve content delivery performance in comparison with existing caching strategies.

28Exploring Tag Distribution in Multi-Reader RFID Systems
Radio Frequency Identification (RFID) brings a revolutionary change in a range of applications by automatically monitoring and tracking products. With the proliferation of RFID-enabled applications, multiple readers are needed for ensuring the full coverage of numerous RFID tags. In this paper, we focus on the tag distribution problem in multi-reader RFID systems. The problem is to fast identify the tag set beneath each reader, which is a fundamental premise of efficient product inventory and management. Only with such tag set information can we localize specific tags in a reader and expedite the tag query information collection. As an RFID system usually contains a large number of tags and multiple readers, the traditional solution to identify tags by individual readers is highly time inefficient. We propose an Inference-Based protocol (IB) that identifies the tag distribution based on information inference rules and the aggregated physical signals to improve operational efficiency. In our protocol, three kinds of inference rules based on internal information reported by a single reader, external information shared by multiple readers, and history information retained by the system are fully exploited to infer tag distribution. With these rules, all readers can cooperatively work together and quickly obtain the tag distribution in the system. We also build a prototype RFID system using the USRP-based reader and WISP programmable tags, and then implement the IB protocol. The experimental results and extended simulations show that IB outperforms the state-of-the-art protocols.

29Spectrum-Energy Efficiency Optimization for Downlink LTE-A for Heterogeneous Networks
Heterogeneous networks have been pointed out to be one of the key network architectures that help increase system capacity and reduce power consumption for efficient communications. Although conceivably, high operational efficiency brings a high profit for mobile service providers, it is noteworthy that the potential for maximizing the profit has not been explored for the heterogeneous environment. This paper investigates profitability for network operators with the spectrum-energy efficiency metric on the downlink of LTE Advanced communication systems. We pursue optimal policies by employing the techniques of cell size zooming, user migration, and sleep mode in the deployment of different base station types. The problem is formulated as a quasiconvex optimization problem and it is transformed into an equivalent form of the MILP problem; the former is solved with a bisection algorithm and the latter is approached by an off-the-shelf software package. Since the formulated optimization problem is NP hard, a sub-optimal approach with a lower computational complexity is also proposed. Numerical analysis through case studies are presented to evaluate the efficiency improvements, and demonstrate the performance of the near-optimal solution.

30Optimal Sleep-Wake Scheduling for Energy Harvesting Smart Mobile Devices
In this paper, we develop optimal sleep/wake scheduling algorithms for smart mobile devices that are powered by batteries and are capable of harvesting energy from the environment. Using a novel combination of the two-timescale Lyapunov optimization approach and weight perturbation, we first design the Optimal Sleep/wake scheduling Algorithm (OSA), which does not require any knowledge of the harvestable energy process. We prove that OSA is able to achieve any system performance that is within O(?) of the optimal, and explicitly compute the required battery size, which is O(1/?). We then extend our results to incorporate system information into algorithm design. Specifically, we develop the Information-aided OSA algorithm (IOSA) by introducing a novel drift augmenting idea in Lyapunov optimization. We show that IOSA is able to achieve the O(?) close-to-optimal utility performance and ensures that the required traffic buffer and energy storage size are O(log (1/?)2) with high probability.

31Channel Selection Algorithm for Cognitive Radio Networks with Heavy-Tailed Idle Times
We consider a multichannel Cognitive Radio Network (CRN), where secondary users sequentially sense channels for opportunistic spectrum access. In this scenario, the Channel Selection Algorithm (CSA) allows secondary users to find a vacant channel with the minimal number of channel switches. Most of the existing CSA literature assumes exponential ON-OFF time distribution for primary user's (PU) channel occupancy pattern. This exponential assumption might be helpful to get performance bounds; but not useful to evaluate the performance of CSA under realistic conditions. An in-depth analysis of independent spectrum measurement traces reveals that wireless channels have typically heavy-tailed PU OFF times. In this paper, we propose an extension to the Predictive CSA framework and its generalization for heavy tailed PU OFF time distribution, which represents realistic scenarios. In particular, we calculate the probability of channel being idle for hyper-exponential OFF times to use in CSA. We implement our proposed CSA framework in a wireless test-bed and comprehensively evaluate its performance by recreating the realistic PU channel occupancy patterns. The proposed CSA shows significant reduction in channel switches and energy consumption as compared to Predictive CSA which always assumes exponential PU ON-OFF times. Through our work, we show the impact of the PU channel occupancy pattern on the performance of CSA in multichannel CRN.

32Stability Analysis of Frame Slotted Aloha Protocol
Frame Slotted Aloha (FSA) protocol has been widely applied in Radio Frequency Identification (RFID) systems as the de facto standard in tag identification. However, very limited work has been done on the stability of FSA despite its fundamental importance both on the theoretical characterization of FSA performance and its effective operation in practical systems. In order to bridge this gap, we devote this paper to investigating the stability properties of p-persistent FSA by focusing on two physical layer models of practical importance, the models with single packet reception and multipacket reception capabilities. Technically, we model the FSA system backlog as a Markov chain with its states being backlog size at the beginning of each frame. The objective is to analyze the ergodicity of the Markov chain and demonstrate its properties in different regions, particularly the instability region. By employing drift analysis, we obtain the closed-form conditions for the stability of FSA and show that the stability region is maximized when the frame length equals the number of packets to be sent in the single packet reception model and the upper bound of stability region is maximized when the ratio of the number of packets to be sent to frame length equals in an order of magnitude the maximum multipacket reception capacity in the multipacket reception model. Furthermore, to characterize system behavior in the instability region, we mathematically demonstrate the existence of transience of the backlog Markov chain. Finally, the analytical results are validated by the numerical experiments.

33Performance-Aware Energy Optimization on Mobile Devices in Cellular Network
In cellular networks, it is important to conserve energy while at the same time satisfying different user performance requirements. In this paper, we first propose a comprehensive metric to capture the user performance cost due to task delay, deadline violation, different application profiles, and user preferences. We prove that finding the energy-optimal scheduling solution while meeting the requirements on the performance cost is NP-hard. Then, we design an adaptive online scheduling algorithm PerES to minimize the total energy cost on data transmissions subject to user performance constraints. We prove that PerES can make the energy consumption arbitrarily close to that of the optimal scheduling solution. Further, we develop offline algorithms to serve as the evaluation benchmark for PerES. The evaluation results demonstrate that PerES achieves average 2.5 times faster convergence speed compared to state-of-art static methods, and also higher performance than peers under various test conditions. Using 821 million traffic flows collected from a commercial cellular carrier, we verify our scheme could achieve on average 32-56 percent energy savings over the total transmission energy with different levels of user experience.

34RSS-Based Ranging by Leveraging Frequency Diversity to Distinguish the Multiple Radio Paths
Among various ranging techniques, Radio Signal Strength (RSS) based approaches attract intensive research interests because of its low cost and wide applicability. RSS-based ranging is prone to be affected by the multipath phenomenon which allows the radio signals to reach the destination through multiple propagation paths. To address this issue, previous works try to profile the environment and refer this profile during run-time. In a practical dynamic environment, however, the profile frequently changes and the painful retraining is needed. Ratherthan such static ways of profiling the environments, in this paper, we tryto accommodate the environmental dynamics automatically in real-time. The key observation is that given a pair of nodes, the RSS at different spectrum channels will be different. This difference carries the valuable phase information of the radio signals. By analyzing these RSS values, we are able to identify the amplitude of signals solely from the Line-of-Sight (LOS) path. This LOS amplitude is a simple function of the path length (the physical distance). We find that the analysis is a typical non-linear curvature fitting problem that has no general routing algorithms. We prove that, this problem format is ill-conditioned which has no stable and trustable solutions. To deal with this issue, we further explore the practical considerations for the problem and modify it to a greatly improved conditioning shape. We solve the problem by numerical iterations and implement these ideas in a real-time indoor tracking system called MuD. MuD employs only three TelosB nodes as anchors. The experiment results show that in a dynamic environment where five people move around, the averaged localization error is about 1 meter. Compared with the traditional RSS-based approaches in dynamic environments, the accuracy improves up to 10 times.

35Load Balancing Under Heavy Traffic in RPL Routing Protocol for Low Power and Lossy Networks
RPL is an IPv6 routing protocol for low-power and lossy networks (LLNs) designed to meet the requirements of a wide range of LLN applications including smart grid AMIs, industrial and environmental monitoring, and wireless sensor networks. RPL allows bidirectional end-to-end IPv6 communication on resource constrained LLN devices, leading to the concept of the Internet of Things (IoT) with thousands and millions of devices interconnected through multihop mesh networks. In this article, we investigate the load balancing and congestion problem of RPL. Specifically, we show that most of the packet losses under heavy traffic are due to congestion, and a serious load balancing problem appears in RPL in terms of routing parent selection. To overcome this problem, this article proposes a simple yet effective queue utilization based RPL (QU-RPL) that achieves load balancing and significantly improves the end-to-end packet delivery performance compared to the standard RPL. QU-RPL is designed for each node to select its parent node considering the queue utilization of its neighbor nodes as well as their hop distances to an LLN border router (LBR). Owing to its load balancing capability, QURPL is very effective in lowering queue losses and increasing the packet delivery ratio. We implement QU-RPL on a low-power embedded platform, and verify all of our findings through experimental measurements on a real testbed of a multihop LLN over IEEE 802.15.4. We present the impact of each design element of QU-RPL on performance in detail, and also show that QU-RPL reduces the queue loss by up to 84 percent and improves the packet delivery ratio by up to 147 percent compared to the standard RPL.

36Network Coding as a Performance Booster for Concurrent Multi-Path Transfer of Data in Multi-Hop Wireless Networks
The emerging use of multi-homed wireless devices along with simultaneous multi-path data transfer offers tremendous potentials to improve the capacity of multi-hop wireless networks. The use of simultaneous data transfer over separate disjoint paths in multi-hop wireless networks to increase network capacity is a less explored subject, mainly because of the challenges it triggers for the reliable transport layer protocols. Reliable transport layer protocols generally use packet sequence number as a mean to ensure delivery. As such, the out-of-order packet arrival in reliable transport layer protocols triggers receiver buffer blocking that causes throughput degradation and prevents the reliable multi-path transport layer protocol to realize its vast potential. This paper focuses on integrating network coding with a reliable multi-path transport layer protocol to resolve the receiver buffer blocking problem. We propose an adaptive network coding mechanism to desensitize the receiver against packet reordering and consequently eliminate the receiver buffer blocking problem. Our state-of-the-art network coding scheme uses a combination of Q-learning and logistic regression for rare data events to control the number of redundant packets based on the network dynamics. We confirmed the veracity of our proposed scheme by a queuing theory based mathematical model. Moreover, the effectiveness of the proposed scheme is demonstrated through simulations and testbed experiments.

37Analysis of Multi-Hop Probabilistic Forwarding for Vehicular Safety Applications on Highways
Safety applications based on the dedicated short-range communication (DSRC) in vehicular networks have very strict performance requirements for safety messages (in terms of delay and packet delivery). However, there is a lack of systematic approach to achieve the performance requirements by leveraging the potential of multi-hop forwarding. This paper proposes a generic multi-hop probabilistic forwarding scheme that achieves these requirements for event-driven safety messages, is compatible with the 802.11 broadcasting protocol and inherits some of the best features of solutions proposed so far for vehicular safety applications. In addition, we develop a unified and comprehensive analytical model to evaluate the performance of the proposed scheme taking into account the effect of hidden terminals, vehicle densities, and the spatial distribution of the multiple forwarders, in a one-dimensional highway scenario. Our numerical experiments confirm the accuracy of the model and demonstrate that the proposed protocol can improve the packet delivery performance by up to 209 percent, while maintaining the delay well below the required threshold. Finally, the utility of the analytical model is demonstrated via an optimal design for the coefficients of a forwarding probability function in the proposed scheme.

38Securing the Backpressure Algorithm for Wireless Networks
The backpressure algorithm is known to provide throughput optimality in routing and scheduling decisions for multi-hop networks with dynamic traffic. The essential assumption in the backpressure algorithm is that all nodes are benign and obey the algorithm rules governing the information exchange and underlying optimization needs. Nonetheless, such an assumption does not always hold in realistic scenarios, especially in the presence of security attacks with intent to disrupt network operations. In this paper, we propose a novel mechanism, called virtual trust queuing, to protect backpressure algorithm based routing and scheduling protocols against various insider threats. Our objective is not to design yet another trust-based routing to heuristically bargain security and performance, but to develop a generic solution with strong guarantees of attack resilience and throughput performance in the backpressure algorithm. To this end, we quantify a node's algorithm-compliance behavior over time and construct a virtual trust queue that maintains deviations of a give node from expected algorithm outcomes. We show that by jointly stabilizing the virtual trust queue and the real packet queue, the backpressure algorithm not only achieves resilience, but also sustains the throughput performance under an extensive set of security attacks. Our proposed solution clears a major barrier for practical deployment of backpressure algorithm for secure wireless applications.

39Multi-Channel Medium Access without Control Channels: A Full Duplex MAC Design
We address the problem of improving the throughput and security of multi-channel MAC (MMAC) protocols. We design a protocol called FD-MMAC that exploits recent advances in full duplex (FD) communications to coordinate channel access in a distributed manner. Compared with prior MMAC designs, our protocol eliminates the use of dedicated in-band or out-of-band control channels for resolving contention, discovering the resident channel of destinations, and performing load balancing. The elimination of the control channel improves spectral efficiency and mitigates denial-of-service attacks that specifically target the exchange of control information. Moreover, FD-MMAC enables the operation of multi-channel exposed terminals. To achieve these goals, we integrate an advanced suite of PHY-layer techniques, including self-interference suppression, error vector magnitude and received power measurements, and signal correlation. We validate the proposed PHY-layer techniques on the NI USRP testbed. Furthermore, we theoretically analyze the throughput performance of FD-MMAC and verify our analysis via packet level simulations. Our results show that FD-MMAC achieves significantly higherthroughput compared with prior art. Finally, we analyze the resilience of FD-MMAC to reactive jamming attacks.

40Near Optimal Data Gathering in Rechargeable Sensor Networks with a Mobile Sink
We study data gathering problem in Rechargeable Sensor Networks (RSNs) with a mobile sink, where rechargeable sensors are deployed into a region of interest to monitor the environment and a mobile sink travels along a pre-defined path to collect data from sensors periodically. In such RSNs, the optimal data gathering is challenging because the required energy consumption for data transmission changes with the movement of the mobile sink and the available energy is time-varying. In this paper, we formulate data gathering problem as a network utility maximization problem, which aims at maximizing the total amount of data collected by the mobile sink while maintaining the fairness of network. Since the instantaneous optimal data gathering scheme changes with time, in order to obtain the globally optimal solution, we first transform the primal problem into an approximate network utility maximization problem by shifting the energy consumption conservation and analyzing necessary conditions for the optimal solution. As a result, each sensor does not need to estimate the amount of harvested energy and the problem dimension is reduced. Then, we propose a Distributed Data Gathering Approach (DDGA), which can be operated distributively by sensors, to obtain the optimal data gathering scheme. Extensive simulations are performed to demonstrate the efficiency of the proposed algorithm.

41Empowering Device-to-Device Networks with Cross-Link Interference Management
Device-to-device (D2D) communications is an emerging service model that is currently under standardization by 3GPP. While D2D offloading has a great potential to relieve increasingly congested cellular networks, its benefits, however, come at a cost, namely interference. Most of the prevailing D2D designs conservatively avoid interference via either spectrum resource allocation or power control. These designs, however, do not exploit spatial degrees of freedom (DoF), which are inherently supported by multiantenna devices. In this work, we present MD2D, a multiuser D2D system that embraces concurrent D2D transmissions, while leveraging MIMO techniques to actively eliminate interference across D2D pairs. MD2D has a systematic methodology that checks whether the antenna combination in a D2D network is capable of eliminating cross-pair interference and, thereby, ensuring interference-free concurrent transmissions. If the interference can be eliminated, then MD2D applies a bucket-based DoF assignment algorithm to determine an effective antenna usage configuration that handles the interference. We evaluate our design via testbed experiments and large-scale simulations. The results show that, as compared to the traditional interference avoidance scheme, MD2D improves the throughput by 87.39 and 218.84 percent in a three-pair testbed and in large-scale simulations, respectively.

42Analytical Evaluation of Saturation Throughput of a Cognitive WLAN Overlaid on a Time-Scheduled OFDMA Network
In this paper, we analyze the saturation throughput of a cognitive WLAN overlaid on a primary OFDMA TDD network (e.g., LTE or WiMAX). In this scenario, after the contention among the secondary nodes, the winner node transmits its data packet in the empty resource blocks (RBs) of downlink and uplink subframes of the primary network. Regarding the OFDMA structure as well as time-scheduled resources in the primary network, the time duration of opportunities for the secondary network does not follow simple exponential on-off pattern. To model the dynamic behavior of opportunities for secondary nodes as well as contentions to exploit the opportunities, we propose an analytical model comprised of a discrete-time Markov chain and two inter-related open multi-class queueing networks (QNs). The effects of the random number of empty resource blocks at different frames as the result of random amount of download and upload data, random packet transmission time at WLAN, the dependency of the number of empty RBs at consecutive frames, and the details of 802.11 MAC protocol are included in our analytical approach. We include different resource allocations in the primary network in our analysis. Simulation results confirm the accuracy of our analytical approach in different conditions.

43Traffic Decorrelation Techniques for Countering a Global Eavesdropper in WSNs
We address the problem of preventing the inference of contextual information in event-driven wireless sensor networks (WSNs). The problem is considered under a global eavesdropper who analyzes low-level RF transmission attributes, such as the number of transmitted packets, inter-packet times, and traffic directionality, to infer event location, its occurrence time, and the sink location. We devise a general traffic analysis method for inferring contextual information by correlating transmission times with eavesdropping locations. Our analysis shows that most existing countermeasures either fail to provide adequate protection, or incur high communication and delay overheads. To mitigate the impact of eavesdropping, we propose resource-efficient traffic normalization schemes. In comparison to the state-of-the-art, our methods reduce the communication overhead by more than 50 percent, and the end-to-end delay by more than 30 percent. To do so, we partition the WSN to minimum connected dominating sets that operate in a round-robin fashion. This allows us to reduce the number of traffic sources active at a given time, while providing routing paths to any node in the WSN. We further reduce packet delay by loosely coordinating packet relaying, without revealing the traffic directionality.

44Anti-Jamming Rendezvous Scheme for Cognitive Radio Networks
In cognitive radio networks (CRNs), channel hopping-based communications are widely used to improve channel utilization. However, channel hopping schemes for CRNs are usually vulnerable to jamming attacks, especially when jammers have cognitive radios to perform channel sensing and fast channel switching. Many mitigating approaches for coping with jamming attacks in wireless communications rely on pre-shared secrets (e.g., pre-shared hopping sequences). In CRNs, pre-sharing secrets between senders and receivers is usually impractical (because neighborhood dynamically changes, and receivers of a broadcast may be unknown to the sender). Hence, anti-jamming channel hopping approaches without pre-shared secrets have gained more and more research interests. However, existing approaches either have unbounded time to rendezvous on an available channel (even no signals of jammers and PUs appear), or require role pre-assignment (SUs should be pre-assigned as a sender or receiver). Role pre-assignment is not applicable to environments where each SU may play a sender and a receiver, simultaneously. In this paper, we propose an antijamming channel hopping scheme, Sec-CH. Sec-CH has bounded time to rendezvous and can work without role pre-assignment.

45A Novel Framework of Multi-Hop Wireless Charging for Sensor Networks Using Resonant Repeaters
Wireless charging has provided a convenient alternative to renew nodes' energy in wireless sensor networks. Due to physical limitations, previous works have only considered recharging a single node at a time, which has limited efficiency and scalability. Recent advances on multi-hop wireless charging is gaining momentum and provides fundamental support to address this problem. However, existing single-node charging designs do not consider and cannot take advantage of such opportunities. In this paper, we propose a new framework to enable multi-hop wireless charging using resonant repeaters. First, we present a realistic model that accounts for detailed physical factors to calculate charging efficiencies. Second, to achieve balance between energy efficiency and data latency, we propose a hybrid data gathering strategy that combines static and mobile data gathering to overcome their respective drawbacks and provide theoretical analysis. Then, we formulate multi-hop recharge schedule into a bi-objective NP-hard optimization problem. We propose a two-step approximation algorithm that first finds the minimum charging cost and then calculates the charging vehicles' moving costs with bounded approximation ratios. Finally, upon discovering more room to reduce the total system cost, we develop a post-optimization algorithm that iteratively adds more stopping locations for charging vehicles to further improve the results while ensuring none of the nodes will deplete battery energy. Our extensive simulations show that the proposed algorithms can handle dynamic energy demands effectively, and can cover at least three times of nodes and reduce service interruption time by an order of magnitude compared to the single-node charging scheme.

46Code, Cache and Deliver on the Move: A Novel Caching Paradigm in Hyper-Dense Small-Cell Networks
Caching popular content files at small-cell base stations (SBSs) has emerged as a promising technique to meet the overwhelming growth in mobile data demand. Despite the plethora of work in this field, a specific aspect has been overlooked. It is assumed that all users remain stationary during data transfer and therefore a complete copy of the requested file can always be downloaded by the associated SBSs. In this work, we revisit the caching problem in realistic environments where moving users intermittently connect to multiple SBSs encountered at different times. Due to connection duration limits, users may download only parts of the requested files. Requests for files that failed to be delivered on time by the SBSs are redirected to the coexisting macro-cell. We introduce an optimization framework that models user movements via random walks on a Markov chain aimed at minimizing the load of the macro-cell. As the main contribution, we put forward a distributed caching paradigm that leverages user mobility predictions and innovative information-mixing methods based on the principle of network coding. Systematic experiments based on measured traces of human mobility patterns demonstrate that our approach can offload 65 percent more macro-cell traffic than existing caching schemes in realistic settings.

47Route or Carry: Motion-Driven Packet Forwarding in Micro Aerial Vehicle Networks
Micro aerial vehicles (MAVs) provide data such as images and videos from an aerial perspective, with data typically transferred to the ground. To establish connectivity in larger areas, a fleet of MAVs may set up an ad-hoc wireless network. Packet forwarding in aerial networks is challenged by unstable link quality and intermittent connectivity caused by MAV movement. We show that signal obstruction by the MAV frame can be alleviated by adapting the MAV platform, even for low-priced MAVs, and the aerial link can be properly characterized by its geographical distance. Based on this link characterization and making use of GPS and inertial sensors on-board of MAVs, we design and implement a motion-driven packet forwarding algorithm. The algorithm unites location-aware end-to-end routing and delay-tolerant forwarding, extended by two predictive heuristics. Given the current location, speed, and orientation of the MAVs, future locations are estimated and used to refine packet forwarding decisions. We study the forwarding algorithm in a field measurement campaign with quadcopters connected over Wi-Fi IEEE 802.11n, complemented by simulation. Our analysis confirms that the proposed algorithm masters intermittent connectivity well, but also discloses inefficiencies of location-aware forwarding. By anticipating motion, such inefficiencies can be counteracted and the forwarding performance can be improved.

48Characterizing the Instantaneous Connectivity of Large-Scale Urban Vehicular Networks
Understanding of the network topology is a basic building block towards the design of efficient networking solutions. In the context of vehicular networks, such a step is especially crucial due to the highly dynamic nature of vehicles that can lead to strong instantaneous variations in the structure of the network. This notwithstanding, and despite the soon-to-come real-world deployment of vehicle-to-vehicle communication technologies, we still lack a clear understanding of vehicular network topological properties. In this paper, we present a complex network analysis of the instantaneous topology of a realistic vehicular network in Cologne, Germany. Our study unveils a poorly connected topology, with very limited availability, reliability, and navigability. We also examine the vehicular network topology in a second scenario, i.e., Zurich, Switzerland. The comparative analysis shows how simplistic mobility models can lead to unrealistic overly connected topologies.

49ART: Adaptive fRequency-Temporal Co-Existing of ZigBee and WiFi
Recent large-scale deployments of wireless sensor networks have posed a high demand on network throughput, forcing all (discrete) orthogonal ZigBee channels to be exploited to enhance transmission parallelism. However, the interference from widely deployed WiFi networks has severely jeopardized the usability of these discrete ZigBee channels, while the existing CSMA-based ZigBee MAC is too conservative to utilize each channel temporally. In this paper, we propose ART (Adaptive fRequency-Temporal co-existing) as a framework consisting of two components: FAVOR (Frequency Allocation for Versatile Occupancy of spectRum) and P-CSMA (Probabilistic CSMA), to improve the co-existence between ZigBee and WiFi in both frequency and temporal perspectives. On one hand, FAVOR allocates continuous (center) frequencies to nodes/links in a near-optimal manner, by innovatively converting the problem into a spatial tessellation problem in a unified frequency-spatial space. This allows ART to fully exploit the “frequency white space” left out by WiFi. On the other hand, ART employs P-CSMA to opportunistically tune the use of CSMA for leveraging the “temporal white space” of WiFi interference, according to real-time assessment of transmission quality. We implement ART in MicaZ platforms, and our extensive experiments strongly demonstrate the efficacy of ART in enhancing both throughput and transmission quality.

50Performance Analysis of Mobile Data Offloading in Heterogeneous Networks
An unprecedented increase in the mobile data traffic volume has been recently reported due to the extensive use of smartphones, tablets, and laptops. This is a major concern for mobile network operators, who are forced to often operate very close to their capacity limits. Recently, different solutions have been proposed to overcome this problem. The deployment of additional infrastructure, the use of more advanced technologies (LTE), or offloading some traffic through Femtocells and WiFi are some of the solutions. Out of these, WiFi presents some key advantages such as its already widespread deployment and low cost. While benefits to operators have already been documented, it is less clear how much and under what conditions the user gains as well. Additionally, the increasingly heterogeneous deployment of cellular networks (partial 4G coverage, small cells, etc.) further complicates the picture regarding both operatorand user-related performance of data offloading. To this end, in this paper we propose a queueing analytic model that can be used to understand the performance improvements achievable by Wi-Fi-based data off loading, as a function of Wi-Fi availability and performance, user mobility and traffic load, and the coverage ratio and respective rates of different cellular technologies available. We validate our theory against simulations for realistic scenarios and parameters, and provide some initial insights as to the offloading gains expected in practice.

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