Wireless Network Projects – ElysiumPro

Wireless Network Projects ElysiumPro

Wireless Network Projects

CSE Projects, ECE Projects
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W Wireless Networking is a method by which homes, telecommunication networks and business installations avoid the costly process of introducing cables into a building. We offer projects implementing Bio-gadgets, Zigbee, WSN, and wireless RF energy transfer.
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1Practical 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.

2Energy-Harvesting-Aided Spectrum Sensing and Data Transmission in Heterogeneous Cognitive Radio Sensor Network
The incorporation of cognitive radio (CR) and energy harvesting (EH) capabilities in wireless sensor networks enables spectrum and energy-efficient heterogeneous CR sensor networks (HCRSNs). The new networking paradigm of HCRSNs consists of EH-enabled spectrum sensors and battery-powered data sensors. Spectrum sensors can cooperatively scan the licensed spectrum for available channels, whereas data sensors monitor an area of interest and transmit sensed data to the sink over those channels. In this paper, we propose a resource-allocation solution for the HCRSN to achieve the sustainability of spectrum sensors and conserve the energy of data sensors. The proposed solution is achieved by two algorithms that operate in tandem: a spectrum sensor scheduling (SSS) algorithm and a data sensor resource allocation (DSRA) algorithm. The SSS algorithm allocates channels to spectrum sensors such that the average detected available time for the channels is maximized, while the EH dynamics are considered and primary user (PU) transmissions are protected. The DSRA algorithm allocates the transmission time, power, and channels such that the energy consumption of the data sensors is minimized. Extensive simulation results demonstrate that the energy consumption of the data sensors can be significantly reduced, while maintaining the sustainability of the spectrum sensors.

3Sparsity Based Efficient Cross-Correlation Techniques in Sensor Networks
Cross-correlation is a popular signal processing technique used in numerous location tracking systems for obtaining reliable range information. However, its efficient design and practical implementation has not yet been achieved on mote platforms that are typical in wireless sensor network due to resource constrains. In this paper, we propose StructS-XCorr: cross-correlation via structured sparse representation, a new computing framework for ranging based on l1 -norm minimization [1] and structured sparsity. The key idea is to compress the ranging signal samples on the mote by efficient random projections and transfer them to a central device; where a convex optimization process estimates the range by exploiting the sparse signal structure in the proposed correlation dictionary. Through theoretical validation, extensive empirical studies and experiments on an end-to-end acoustic ranging system implemented on resource limited off-the-shelf sensor nodes, we show that the proposed framework can achieve up to two orders of magnitude better performance compared to other approaches such as working on DCT domain and downsampling. Compared to the standard cross-correlation, it is able to obtain range estimates with a bias of 2-6 cm with 30 percent and approximately 100 cm with 5 percent compressed measurements. Its structured sparsity model is able to improve the ranging accuracy by 40 percent under challenging recovery conditions (such as high compression factor and low signal-to-noise ratio) by overcoming limitations due to dictionary coherence.

4Energy-Efficient Localization and Tracking of Mobile Devices in Wireless Sensor Networks
Wireless sensor networks (WSNs) are effective for locating and tracking people and objects in various industrial environments. Since energy consumption is critical to prolonging the lifespan of WSNs, we propose an energy-efficient LOcalization and Tracking (eLOT) system, using low-cost and portable hardware to enable highly accurate tracking of targets. Various fingerprint based approaches for localization and tracking are implemented in eLOT. To achieve high energy efficiency, a network-level scheme coordinating collision and interference is proposed. On the other hand, based on the location information, mobile devices in eLOT can quickly associate with the specific channel in a given area, while saving energy by avoiding unnecessary transmission. Finally, a platform based on TI CC2530 and the Linux operating system is built to demonstrate the effectiveness of our proposed scheme in terms of localization accuracy and energy efficiency.

5Load-Balanced Opportunistic Routing for Duty-Cycled Wireless Sensor Networks
In duty-cycled wireless sensor networks running asynchronous MAC protocols, the time when a sender waits for its receiver to wake up and receive the packet is the major source of energy consumption. Opportunistic routing can reduce the sender wait time by allowing multiple candidate receivers, but by doing that it suffers from redundant packet forwarding due to multiple receivers waking up at the same time. Thus, the number of forwarders should be controlled in a way that overall forwarding cost is minimized considering both sender wait time and cost of redundant packet forwarding. Also, in order to prolong network lifetime, candidate forwarders should be selected so that load is balanced among nodes. We propose ORR, an opportunistic routing protocol that addresses the two issues. First, the optimal number of forwarders is calculated based on forwarding cost estimation, which is derived from duty cycle and network topology. Second, the metric used for selecting forwarders considers residual energy so that more traffic is guided through nodes with larger remaining energy. The resulting routing protocol is proven to avoid loops and shown to achieve longer network lifetime compared to other protocols regardless of duty cycle and network topology.

6Performance Evaluation of an Adaptive Channel Allocation Technique for Cognitive Wireless Sensor Networks
This paper deals with a cognitive overlay IEEE 802.15.4e wireless sensor network relying on a low-complexity spectrum sensing technique. In particular, the paper critically compares two spectrum sensing schemes with the aim of identifying the most appropriate solution in terms of performance and implementation complexity. Furthermore, the paper provides an analytical framework to investigate the cognitive overlay IEEE 802.15.4e wireless sensor network behavior in terms of throughput, packet dropping probability, and energy efficiency. The obtained results clearly highlight the good behavior of the proposed approach without burdensome cost or complexity and its advantages for several emerging applications such as those supported by fog computing architecture.

7Distributed Clustering-Task Scheduling for Wireless Sensor Networks Using Dynamic Hyper Round Policy
Prolonging the network life cycle is an essential requirement for many types of Wireless Sensor Network (WSN) applications. Dynamic clustering of sensors into groups is a popular strategy to maximize the network lifetime and increase scalability. In this strategy, to achieve the sensor nodes’ load balancing, with the aim of prolonging lifetime, network operations are split into rounds, i.e. fixed time intervals. Clusters are configured for the current round and reconfigured for the next round so that the costly role of the cluster head is rotated among the network nodes, i.e. Round-Based Policy (RBP). This load balancing approach potentially extends the network lifetime. However, the imposed overhead, due to the clustering in every round, wastes network energy resources. This paper proposes a distributed energy-efficient scheme to cluster a WSN, i.e. Dynamic Hyper Round Policy (DHRP), which schedules clustering-task to extend the network lifetime and reduce energy consumption. Although DHRP is applicable to any data gathering protocols that value energy efficiency, a Simple Energyefficient Data Collecting (SEDC) protocol is also presented to evaluate the usefulness of DHRP and calculate the end-to-end energy consumption. Experimental results demonstrate that SEDC with DHRP is more effective than two well-known clustering protocols, HEED and M-LEACH, for prolonging the network lifetime and achieving energy conservation.

8Path Finding for Maximum Value of Information in Multi-modal Underwater Wireless Sensor Networks
We consider underwater multi-modal wireless sensor networks (UWSNs) suitable for applications on submarine surveillance and monitoring, where nodes offload data to a mobile autonomous underwater vehicle (AUV) via optical technology, and coordinate using acoustic communication. Sensed data are associated with a value, decaying in time. In this scenario, we address the problem of finding the path of the AUV so that the Value of Information (VoI) of the data delivered to a sink on the surface is maximized. We define a Greedy and Adaptive AUV Path-finding (GAAP) heuristic that drives the AUV to collect data from nodes depending on the VoI of their data. For benchmarking the performance of AUV path-finding heuristics, we define an integer linear programming (ILP) formulation that accurately models the considered scenario, deriving a path that drives the AUV to collect and deliver data with the maximum VoI. In our experiments GAAP consistently delivers more than 80% of the theoretical maximum VoI determined by the ILP model. We also compare the performance of GAAP with that of other strategies for driving the AUV among sensing nodes, namely, random paths, TSP-based paths and a “lawn mower”-like strategy. Our results show that GAAP always outperforms every other heuristic in terms of delivered VoI, also obtaining higher energy efficiency.

9ROSE: Robustness Strategy for Scale-Free Wireless Sensor Networks
Due to the recent proliferation of cyber-attacks, improving the robustness of wireless sensor networks (WSNs), so that they can withstand node failures has become a critical issue. Scale-free WSNs are important, because they tolerate random attacks very well; however, they can be vulnerable to malicious attacks, which particularly target certain important nodes. To address this shortcoming, this paper first presents a new modeling strategy to generate scale-free network topologies, which considers the constraints in WSNs, such as the communication range and the threshold on the maximum node degree. Then, ROSE, a novel robustness enhancing algorithm for scale-free WSNs, is proposed. Given a scale-free topology, ROSE exploits the position and degree information of nodes to rearrange the edges to resemble an onion-like structure, which has been proven to be robust against malicious attacks. Meanwhile, ROSE keeps the degree of each node in the topology unchanged such that the resulting topology remains scale-free. The extensive experimental results verify that our new modeling strategy indeed generates scale-free network topologies for WSNs, and ROSE can significantly improve the robustness of the network topologies generated by our modeling strategy. Moreover, we compare ROSE with two existing robustness enhancing algorithms, showing that ROSE outperforms both.

10P2S: A Primary and Passer-by Scheduling Algorithm for On-demand Charging Architecture in Wireless Rechargeable Sensor Networks
As the interdiscipline of wireless communication and control engineering, the cooperative charging issue in Wireless Rechargeable Sensor Networks (WRSNs) is a popular researching problem. With the help of wireless power transfer technology, electrical energy can be transferred from wireless charging vehicles to sensors, providing a new paradigm to prolong the network lifetime. However, existing techniques on cooperative charging usually take the periodical and deterministic approach, but neglect the influences of the non-deterministic factors such as topological changes and node failures, making them unsuitable for large-scale WRSNs. In this paper, we develop a Primary and Passer-by Scheduling (P2S) algorithm for on-demand charging architecture for large-scale WRSNs. In P2S, task interdependency is utilized to enhance charging efficiency. We exploit a local searching algorithm, in which nearby nodes on the way to primary nodes, the targets of Wireless Charging Vehicle’s (WCV’s) current movement, will be charged as passer-by nodes. Such a strategy not only makes full use of the available remaining time of a charging deadline, but also solves the complex scheduling problem with spatial and temporal task interdependency. Analysis and simulations are conducted to show the superiority of our scheme, revealing that P2S has a higher survival rate, throughput, as well as other performance metrics.

11Energy-Efficient Localization and Tracking of Mobile Devices in Wireless Sensor Networks
Wireless sensor networks (WSNs) are effective for locating and tracking people and objects in various industrial environments. Since energy consumption is critical to prolonging the lifespan of WSNs, we propose an energy-efficient LOcalization and Tracking (eLOT) system, using low-cost and portable hardware to enable highly accurate tracking of targets. Various fingerprint based approaches for localization and tracking are implemented in eLOT. To achieve high energy efficiency, a network-level scheme coordinating collision and interference is proposed. On the other hand, based on the location information, mobile devices in eLOT can quickly associate with the specific channel in a given area, while saving energy by avoiding unnecessary transmission. Finally, a platform based on TI CC2530 and the Linux operating system is built to demonstrate the effectiveness of our proposed scheme in terms of localization accuracy and energy efficiency.

12Channel-Aware Polling-Based MAC Protocol for Body Area Networks: Design and Analysis
Body area networks (BANs) enable wearable/implanted devices to exchange information or collect monitored data. The channel quality of a link in a BAN is typically highly dynamic, since sensors equipped on a human body usually move with gesture, posture, or mobility. Therefore, existing sleep-wake-up scheduling mechanisms used in traditional static sensor networks could be very inefficient in a BAN, because they do not consider channel fluctuation of body sensors. Sensors might be waked up to transmit during bad channel conditions, leading to transmission failures and energy waste. To remedy this inefficiency, this paper proposes a Channel-aware Polling-based MAC protocol CPMAC. Our design only wakes sensors up and triggers them to transmit when the channel is strong enough to ensure fast and reliable transmissions. We further analyze the energy consumption and derive a queueing model to estimate the probability of completing all data transmissions of all sensors in our CPMAC. Benefiting from these analyses, we are able to optimize energy efficiency of our CPMAC by adapting the number of polling periods in a superframe to dynamic traffic demands and channel fluctuation. Our simulation results show that, as compared with TDMA-based scheduling and the IEEE 802.15.6 CSMA/CA protocol, CPMAC significantly improves energy efficiency and, meanwhile, keeps the latency short.

13Mobile Charging in Wireless-Powered Sensor Networks: Optimal Scheduling and Experimental Implementation
Wireless radio frequency (RF) energy transfer is a promising technology to provide a reliability-guaranteed power supply for wireless sensor networks. In this paper, we consider a special wireless-powered sensor network consisting of a mobile energy station that can travel through a pre-planned path to charge wireless-powered sensors located in the considered area. We develop a hardware platform using off-the-shelf RF energy transfer hardware equipment to evaluate the practical performance of wireless sensor networks powered by RF energy transfer. We establish an empirical model based on our developed platform and use the empirical model to jointly optimize path planning and mobile charge scheduling for wireless-powered sensor networks. We derive the optimal policy for the mobile energy station to optimize its decisions about the path that it will travel and the subset of sensors to charge during each time period. Numerical results show that our derived policy significantly improves the performance of wireless sensor networks in different practical scenarios.

14Identification of the Optimum Relocalization Time in the Mobile Wireless Sensor Network Using Time-Bounded Relocalization Methodology
Contrary to the static sensor network that requires one-time localization, a mobile wireless sensor network (MWSN) requires an estimation of the optimum time to retrigger the localization of the network to accurately identify the sensor location after certain movements. However, triggering relocalization at predefined time intervals without proper consideration of the dynamic movement of sensors is insubstantial and results in poor resource management. In this paper, a new algorithm called time-bounded relocalization is proposed to identify the optimum relocalization time for the entire MWSN using the time-bounded localization method based on the analysis of the sensors' mobility pattern. In the proposed algorithm, the optimum retriggering time across the entire network can be calculated in two phases: local and global relocalizations. In the first phase, an island-based clustering method is used to estimate the local relocalization time. Next, the estimated local times are then used to decide on the optimum global relocalization time based on the statistical property of the estimated local times. For these calculations, a probabilistic model of the random waypoint (RWP) is selected. The soundness of the proposed algorithm is initially validated by deriving the probabilistic model of the optimum retriggering time, and its accuracy is checked by the Cramer-Rao lower bound (CRLB). The proposed algorithm is then extensively tested by computer simulation using practical network parameters, including the number of nodes, the size of the network, and various sizes of islands, depending on the sensor mobility, to yield the respective optimum relocalization time. The simulation results show that by using the identified optimum relocalization time, the location estimation error can be reduced by up to 32% for the RWP model, as compared with the case of using fixed relocalization time.

15Energy-Harvesting-Aided Spectrum Sensing and Data Transmission in Heterogeneous Cognitive Radio Sensor Network
The incorporation of cognitive radio (CR) and energy harvesting (EH) capabilities in wireless sensor networks enables spectrum and energy-efficient heterogeneous CR sensor networks (HCRSNs). The new networking paradigm of HCRSNs consists of EH-enabled spectrum sensors and battery-powered data sensors. Spectrum sensors can cooperatively scan the licensed spectrum for available channels, whereas data sensors monitor an area of interest and transmit sensed data to the sink over those channels. In this paper, we propose a resource-allocation solution for the HCRSN to achieve the sustainability of spectrum sensors and conserve the energy of data sensors. The proposed solution is achieved by two algorithms that operate in tandem: a spectrum sensor scheduling (SSS) algorithm and a data sensor resource allocation (DSRA) algorithm. The SSS algorithm allocates channels to spectrum sensors such that the average detected available time for the channels is maximized, while the EH dynamics are considered and primary user (PU) transmissions are protected. The DSRA algorithm allocates the transmission time, power, and channels such that the energy consumption of the data sensors is minimized. Extensive simulation results demonstrate that the energy consumption of the data sensors can be significantly reduced, while maintaining the sustainability of the spectrum sensors.

16Aggregated Packet Transmission in Duty-Cycled WSNs: Modeling and Performance Evaluation
Duty cycling (DC) is a popular technique for energy conservation in wireless sensor networks (WSNs) that allows nodes to wake up and sleep periodically. Typically, a single-packet transmission (SPT) occurs per cycle, leading to possibly long delay. With aggregated packet transmission (APT), nodes transmit a batch of packets in a single cycle. The potential benefits brought by an APT scheme include shorter delay, higher throughput, and higher energy efficiency. In the literature, different analytical models have been proposed to evaluate the performance of SPT schemes. However, no analytical models for the APT mode on synchronous DC medium access control (MAC) mechanisms exist. In this paper, we first develop a 3-D discrete-time Markov chain (DTMC) model to evaluate the performance of an APT scheme with packet retransmission enabled. The proposed model captures the dynamics of the state of the queue of nodes and the retransmission status and the evolution of the number of active nodes in the network, i.e., nodes with a nonempty queue. We then study the number of retransmissions needed to transmit a packet successfully. Based on the observations, we develop another less-complex DTMC model with infinite retransmissions, which embodies only two dimensions. Furthermore, we extend the 3-D model into a 4-D model by considering error-prone channel conditions. The proposed models are adopted to determine packet delay, throughput, packet loss, energy consumption, and energy efficiency. Furthermore, the analytical models are validated through discrete-event-based simulations. Numerical results show that an APT scheme achieves substantially better performance than its SPT counterpart in terms of delay, throughput, packet loss, and energy efficiency and that the developed analytical models reveal precisely the behavior of the APT scheme.

17Simultaneous Wireless Information and Power Transfer in Cooperative Relay Networks with Rate less Codes
This paper investigates the simultaneous wireless information and power transfer (SWIPT) in cooperative relay networks, where a relay harvests energy from the radio frequency (RF) signals transmitted by a source and then uses the harvested energy to assist the information transmission from the source to its destination. Both source and relay transmissions use rateless codes (RCs), which allow the destination to employ any of the two information receiving strategies, i.e., the mutual information accumulation (IA) and the energy accumulation (EA). The SWIPT-enabled relay employs three different SWIPT receiver architectures, the ideal receiver, and two practical receivers (i.e., the power splitting (PS) receiver and the time switch (TS) receiver). Accordingly, three relaying protocols, namely, the ideal protocol, PS protocol, and TS protocol, are presented. To explore the system performance limits with these three protocols, optimization problems are formulated to maximize their achievable information rates. For the ideal protocol, explicit expressions of the optimal solutions are derived. For the PS protocol, a linear-search algorithm is designed to solve the nonconvex problems. For the TS protocol, two solving methods are presented. Numerical experiments are carried out to validate our analysis and algorithms, which show that, with the same SWIPT receiver, the IA-based system outperforms the EA-based system, whereas with the same information receiving strategy, the PS protocol outperforms the TS protocol. Moreover, compared with nonrateless-coded systems, the proposed protocols exhibit considerable performance gains. Moreover, the effects of the relay position on system performance are also discussed, which provides insights on SWIPT-enabled relay systems.

18Zoning and Relaying-Based MAC Protocol with RF Recharging
Radio-frequency (RF) recharging can extend maintenance-free operation of wireless sensor networks. However, the period between recharging is limited by the distance between the most distant sensor node and the master, which sends out recharging pulses. To increase this period, we propose a zoning scheme in which nodes are logically grouped into circular zones centered at the master so that nodes in a given zone send their data to their neighbors in the next closer zone, which act as relays. We describe and analyze a polling Medium Access Control (MAC) protocol that supports zoning and relaying through a probabilistic model of the energy depletion process and a queueing model of the packet transmission process. Our results indicate that zoning extends the time interval between recharge pulses and leads to equalization of node lifetimes, but limits the available data transmission bandwidth as well.

19Statistical Distance Estimation Algorithms with RSS Measurements for Indoor LTE-A Networks
An indoor base station (BS), such as a remote radio head or home eNodeB, is a cost-effective solution to achieve ubiquitous access and positioning functions in indoor Long-Term Evolution Advanced (LTE-A) networks. In this paper, two distance estimation algorithms adopt received signal strength (RSS) to estimate the corresponding distance between a BS and a mobile station. The statistical inference distance estimation (SIDE) algorithm is proposed to provide a consistent distance estimator when the particle number is larger than an inferential theoretic lower bound given a confidence level and an error constraint. Moreover, the particle-based distance estimation (PDE) algorithm is proposed to estimate distance information with the technique of particle filtering under mixed line-of-sight (LOS) and non-line-of-sight (NLOS) conditions in indoor LTE-A networks. Furthermore, the theoretic Crame´r-Rao lower bound (CRLB), considering the variations from fading effects and time-variant channels, is derived as a benchmark to evaluate the precision of distance estimators. The performance of the proposed SIDE algorithm is verified through simulations, and the results fulfill the requirements of different confidence levels and error constraints. Furthermore, the proposed PDE algorithm outperforms other distance estimation schemes and reveals robustness against mixed-sight and time-variant indoor LTE-A networks.

20Optimal Joint Decoding of Correlated Data over Orthogonal Multiple-Access Channels with Memory
Motivated by the structure of basic sensor networks, we study an optimal joint decoding problem in which the real-valued outputs of two correlated Gaussian sources are scalar quantized, bit assigned, and transmitted, without applying channel coding or interleaving, over a multiple-access channel that consists of two orthogonal point-to-point time-correlated Rayleigh fading subchannels used with soft-decision demodulation. Each fading subchannel is modeled by a nonbinary Markov noise discrete channel that was recently shown to effectively represent it. The correlated sources have memory captured by a time-varying correlation coefficient governed by a two-state first-order Markov process. At the receiver side, we design a joint sequence maximum a posteriori (MAP) decoder to exploit the correlation between the two sources, their temporal memory, and the redundancy left in the quantizers' indexes, the channels' soft-decision outputs, and noise memory. Under the simple practical case of using two-level source quantization, we propose a Markov model to estimate the joint behavior of the quantized sources. We then establish necessary and sufficient conditions under which the delay-prone joint sequence MAP decoder can be reduced to a simple instantaneous symbol-by-symbol decoder. We illustrate our analytical results by system simulation and demonstrate that joint MAP decoding can appropriately harness source and channel characteristics to achieve improved signal-to-distortion ratio performance for a wide range of system conditions.

21A Secure and Efficient ID-Based Aggregate Signature Scheme for Wireless Sensor Networks
Affording secure and efficient big data aggregation methods is very attractive in the field of wireless sensor networks (WSNs) research. In real settings, the WSNs have been broadly applied, such as target tracking and environment remote monitoring. However, data can be easily compromised by a vast of attacks, such as data interception and data tampering, etc. In this paper, we mainly focus on data integrity protection, give an identity-based aggregate signature (IBAS) scheme with a designated verifier for WSNs. According to the advantage of aggregate signatures, our scheme not only can keep data integrity, but also can reduce bandwidth and storage cost for WSNs. Furthermore, the security of our IBAS scheme is rigorously presented based on the computational Diffie-Hellman assumption in random oracle model.

22Optimal Placement of Relay Nodes Over Limited Positions in Wireless Sensor Networks
This paper tackles the challenge of optimally placing relay nodes (RNs) in wireless sensor networks given a limited set of positions. The proposed solution consists of: (1) the usage of a realistic physical layer model based on a Rayleigh block-fading channel; (2) the calculation of the signal-to-interference-plus-noise ratio (SINR) considering the path loss, fast fading, and interference; and (3) the usage of a weighted communication graph drawn based on outage probabilities determined from the calculated SINR for every communication link. Overall, the proposed solution aims for minimizing the outage probabilities when constructing the routing tree, by adding a minimum number of RNs that guarantee connectivity. In comparison to the state-of-the art solutions, the conducted simulations reveal that the proposed solution exhibits highly encouraging results at a reasonable cost in terms of the number of added RNs. The gain is proved high in terms of extending the network lifetime, reducing the end-to-end- delay, and increasing the goodput.

23Maximum 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.

24Virtual 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.

25SEND: 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.

26Virtual 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.

27Impact 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.

28Network 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.

29Securing 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.

30Traffic 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.

31A 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.

32Deploy-As-You-Go Wireless Relay Placement: An Optimal Sequential Decision Approach Using the Multi-Relay Channel Model
We use information theoretic achievable rate formulas for the multi-relay channel to study the problem of as-you-go deployment of relay nodes. The achievable rate formulas are for full-duplex radios at the relays and for decode-and-forward relaying. Deployment is done along the straight line joining a source node and a sink node at an unknown distance from the source. The problem is for a deployment agent to walk from the source to the sink, deploying relays as he walks, given the knowledge of the wireless path-loss model, and given that the distance to the sink node is exponentially distributed with known mean. As a precursor to the formulation of the deploy-as-you-go problem, we apply the multi-relay channel achievable rate formula to obtain the optimal power allocation to relays placed along a line, at fixed locations. This permits us to obtain the optimal placement of a given number of nodes when the distance between the source and sink is given. Numerical work for the fixed source-sink distance case suggests that, at low attenuation, the relays are mostly clustered close to the source in order to be able to cooperate among themselves, whereas at high attenuation they are uniformly placed and work as repeaters. We also prove that the effect of path-loss can be entirely mitigated if a large enough number of relays are placed uniformly between the source and the sink. The structure of the optimal power allocation for a given placement of the nodes, then motivates us to formulate the problem of as-you-go placement of relays along a line of exponentially distributed length, and with the exponential path-loss model, so as to minimize a cost function that is additive over hops. The hop cost trades off a capacity limiting term, motivated from the optimal power allocation solution, against the cost of adding a relay node. We formulate the problem as a total cost Markov decision process, establish results for the value function, and provide insights into the placement policy and the performance of the deployed network via numerical exploration.

33Medium Access Control for Wireless Body Area Networks with QoS Provisioning and Energy Efficient Design
With the promising applications in e-Health and entertainment services, wireless body area network (WBAN) has attracted significant interest. One critical challenge for WBAN is to track and maintain the quality of service (QoS), e.g., delivery probability and latency, under the dynamic environment dictated by human mobility. Another important issue is to ensure the energy efficiency within such a resource-constrained network. In this paper, a new medium access control (MAC) protocol is proposed to tackle these two important challenges. We adopt a TDMA-based protocol and dynamically adjust the transmission order and transmission duration of the nodes based on channel status and application context of WBAN. The slot allocation is optimized by minimizing energy consumption of the nodes, subject to the delivery probability and throughput constraints. Moreover, we design a new synchronization scheme to reduce the synchronization overhead. Through developing an analytical model, we analyze how the protocol can adapt to different latency requirements in the healthcare monitoring service. Simulations results show that the proposed protocol outperforms CA-MAC and IEEE 802.15.6 MAC in terms of QoS and energy efficiency under extensive conditions. It also demonstrates more effective performance in highly heterogeneous WBAN.

34Virtual 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.

35Utility Fair Rate Allocation in LTE/802.11 Networks
We consider proportional fair rate allocation in a heterogeneous network with a mix of LTE and 802.11 cells which supports multipath and multihomed operation (simultaneous connection of a user device to multiple LTE base stations and 802.11 access points). We show that the utility fair optimization problem is non-convex but that a global optimum can be found by solving a sequence of convex optimizations in a distributed fashion. The result is a principled approach to offload from LTE to 802.11 and for exploiting LTE/802.11 path diversity to meet user traffic demands.

36Accurate Per-Packet Delay Tomography in Wireless Ad Hoc Networks
In this paper, we study the problem of decomposing the end-to-end delay into the per-hop delay for each packet, in multi-hop wireless ad hoc networks. Knowledge on the per-hop per-packet delay can greatly improve the network visibility and facilitate network measurement and management. We propose Domo, a passive, lightweight, and accurate delay tomography approach to decomposing the packet end-to-end delay into each hop. We first formulate the per packet delay tomography problem into a set of optimization problems by carefully considering the constraints among various timing quantities. At the network side, Domo attaches a small overhead to each packet for constructing constraints of the optimization problems. By solving these optimization problems by semi-definite relaxation at the PC side, Domo is able to estimate the per-hop delays with high accuracy as well as give a upper bound and lower bound for each unknown per-hop delay. We implement Domo and evaluate its performance extensively using both trace-driven studies and large-scale simulations. Results show that Domo significantly outperforms two existing methods, nearly tripling the accuracy of the state-of-the-art.

37Optimally Approximating the Coverage Lifetime of Wireless Sensor Networks
We address a classical problem concerning energy efficiency in sensor networks. In particular, we consider the problem of maximizing the lifetime of coverage of targets in a wireless sensor network with battery-limited sensors. We first show that the problem cannot be approximated within a factor less than lnn by any polynomial time algorithm, where n is the number of targets. This provides closure to the long-standing open problem of showing optimality of previously known lnn approximation algorithms. We also derive a new ln n approximation to the problem by showing the lnn approximation to the related maximum disjoint set cover problem. We show that this approach has many advantages over algorithms in the literature, including a simple and optimal extension that solves the problem with multiple coverage constraints. For the 1-D network topology, where sensors can monitor contiguous line segments of possibly different lengths, we show that the optimal coverage lifetime can be found in polynomial time. Finally, for the 2-D topology in which coverage regions are unit squares, we combine the existing results to derive a 1 + € approximation algorithm for the problem. Extensive simulation experiments validate our theoretical results, showing that our algorithms not only have optimal worst case guarantees but also match the performance of the existing algorithms on special network topologies. In addition, our algorithms sometimes run orders of magnitude faster than the existing state of the art.

38Energy Harvesting Wireless Sensor Node with Temporal Death: Novel Models and Analyses
Energy harvesting wireless sensor network (EH-WSN) is promising in applications, however the frequent occurrence of temporal death of nodes, due to the limited harvesting capability, presents a difficulty in meeting the quality-of-service requirements of the network. For a node with temporal death in an EH-WSN, this paper presents a new model, which consists of, a Markov model to trace the energy harvesting process, a queuing analytical model to model the working mechanism of the sensor node and a continuous fluid process to capture the evolution of the residual energy in the EH-WSN node. Using the Markov fluid queue (MFQ) theory, we discuss various performance aspects of the EH-WSN node with temporal death, including the temporal death occurrence probability, the probability density of the residual energy, the stationary energy consumption, the queue length distribution in the data buffer, the packet blocking probability, and so on. In order to obtain the dropping probability of a given packet, based on the structure of the MFQ, we develop an auxiliary MFQ and derive the formulations of two types of the packet dropping probabilities, i.e., the packet dropping probability due to energy depletion and that due to channel error. Numerical examples are provided to illustrate the theoretical findings, and new insights into understanding the impacts of the parameters on the performance metrics are presented.

39Capacity of Hybrid Wireless Networks with Long-Range Social Contacts Behaviour
Hybrid wireless network is composed of both ad hoc transmissions and cellular transmissions. Under the L-maximum-hop routing policy, flow is transmitted in the ad hoc mode if its source and destination are within L hops away; otherwise, it is transmitted in the cellular mode. Existing works study the hybrid wireless network capacity as a function of L so as to find the optimal L to maximize the network capacity. In this paper, we consider two more factors: traffic model and base station access mode. Different from existing works, which only consider the uniform traffic model, we consider a traffic model with social behavior. We study the impact of traffic model on the optimal routing policy. Moreover, we consider two different access modes: one-hop access (each node directly communicates with base station) and multi-hop access (node may access base station through multiple hops due to power constraint). We study the impact of access mode on the optimal routing policy. Our results show that: 1) the optimal L does not only depend on traffic pattern, but also the access mode; 2) one-hop access provides higher network capacity than multi-hop access at the cost of increasing transmitting power; and 3) under the one-hop access mode, network capacity grows linearly with the number of base stations; however, it does not hold with the multi-hop access mode, and the number of base stations has different effects on network capacity for different traffic models.

40ROSE: Robustness Strategy for Scale-Free Wireless Sensor Networks
Due to the recent proliferation of cyber-attacks, improving the robustness of wireless sensor networks (WSNs), so that they can withstand node failures has become a critical issue. Scale-free WSNs are important, because they tolerate random attacks very well; however, they can be vulnerable to malicious attacks, which particularly target certain important nodes. To address this shortcoming, this paper first presents a new modeling strategy to generate scale-free network topologies, which considers the constraints in WSNs, such as the communication range and the threshold on the maximum node degree. Then, ROSE, a novel robustness enhancing algorithm for scale-free WSNs, is proposed. Given a scale-free topology, ROSE exploits the position and degree information of nodes to rearrange the edges to resemble an onion-like structure, which has been proven to be robust against malicious attacks. Meanwhile, ROSE keeps the degree of each node in the topology unchanged such that the resulting topology remains scale-free. The extensive experimental results verify that our new modeling strategy indeed generates scale-free network topologies for WSNs, and ROSE can significantly improve the robustness of the network topologies generated by our modeling strategy. Moreover, we compare ROSE with two existing robustness enhancing algorithms, showing that ROSE outperforms both.

41Buffer-Aided Relay Selection with Reduced Packet Delay in Cooperative Networks
Applying data buffers at relay nodes significantly improves the outage performance in relay networks, but the performance gain is often at the price of long packet delays. In this paper, a novel relay selection scheme with significantly reduced packet delay is proposed. The outage probability and average packet delay of the proposed scheme under different channel scenarios are analyzed. Simulation results are also given to verify the analysis. The analytical and simulation results show that, compared with non-buffer-aided relay selection schemes, the proposed scheme has not only significant gain in outage performance but also similar average packet delay when the channel signal-to-noise ratio (SNR) is high enough, making it an attractive scheme in practice.

42Robust Cooperative Secure Beam forming for Simultaneous Wireless Information and Power Transfer in Amplify-and-Forward Relay Networks
In this paper, we investigate cooperative secure beamforming for simultaneous wireless information and power transfer (SWIPT) in amplify-and-forward (AF) relay networks. We propose a joint cooperative beamforming (CB) and energy signal (CB-ES) scheme for providing both secure communication and efficient wireless energy transfer. By considering colluding eavesdroppers with imperfect channel state information (CSI), we formulate an optimization problem for maximizing the secrecy rate between the source and the legitimate information receiver (IR) under both the power constraints at the relays and the wireless power transfer constraint at the energy-harvesting receiver (ER). Since such a problem is nonconvex and hard to tackle, we propose a two-level optimization approach that involves a 1-D search and the semidefinite relaxation (SDR) technique to solve this problem. The proposed robust scheme is compared with some other nonrobust schemes, such as a CB and artificial noise (CB-AN) scheme and a perfect scheme. Simulation results show that the proposed robust scheme achieves better worst-case secrecy rate performance than the other nonrobust schemes and the CB-AN scheme, while it approaches the perfect scheme.

43Maximizing Spectral Efficiency for Energy Harvesting-Aware WBAN
In this paper, we investigate the spectral efficiency of a communication link in a wireless body area network (WBAN) capable of harvesting energy from the environment. We consider two scenarios for the transmission which are single- and dual-hop and achieve the power management policy for each scenario. In the first scenario, the aim is to maximize the link's spectral efficiency over N time slots subject to the battery capacity, energy harvesting constraint, and WBAN limitations including power and outage probability. In the second scenario, a decode-and-forward relay node is considered, and a spectral efficiency optimization problem with constraints similar to the first scenario is evaluated. In addition, since the channel distribution information is available at the transmitters, the lower and upper bounds of the average spectral efficiency are also derived in both scenarios. Finally, numerical results corroborate the analytical results.

44Enhancing Heart-Beat-Based Security for mHealth Applications
In heart-beat-based security, a security key is derived from the time difference between consecutive heart beats (the inter-pulse interval, IPI), which may, subsequently, be used to enable secure communication. While heart-beat-based security holds promise in mobile health (mHealth) applications, there currently exists no work that provides a detailed characterization of the delivered security in a real system. In this paper, we evaluate the strength of IPI-based security keys in the context of entity authentication. We investigate several aspects that should be considered in practice, including subjects with reduced heart-rate variability (HRV), different sensor-sampling frequencies, intersensor variability (i.e., how accurate each entity may measure heart beats) as well as average and worst-case-authentication time. Contrary to the current state of the art, our evaluation demonstrates that authentication using multiple, less-entropic keys may actually increase the key strength by reducing the effects of intersensor variability. Moreover, we find that the maximal key strength of a 60-bit key varies between 29.2 bits and only 5.7 bits, depending on the subject's HRV. To improve security, we introduce the inter-multi-pulse interval (ImPI), a novel method of extracting entropy from the heart by considering the time difference between nonconsecutive heart beats. Given the same authentication time, using the ImPI for key generation increases key strength by up to 3.4× (+19.2 bits) for subjects with limited HRV, at the cost of an extended key-generation time of 4.8× (+45 s).

45Exploring Connected Dominating Sets in Energy Harvest Networks
Duty-cycle scheduling is an effective way to balance energy consumptions and prolong network lifetime of wireless sensor networks (WSNs), which usually requires a connected dominating set (CDS) to guarantee network connectivity and coverage. Therefore, the problem of finding the largest number of CDSs is important for WSNs. The previous works always assume all the nodes are non-rechargeable. However, WSNs are now taking advantages of rechargeable nodes to become energy harvest networks (EHNs). To find the largest number of CDSs then becomes completely different. This is the first work to investigate, how to identify the largest number of CDSs in EHNs to prolong network lifetime. The investigated novel problems are proved to be NP-Complete and we propose four approximate algorithms, accordingly. Both the solid theoretical analysis and the extensive simulations are performed to evaluate our algorithms.

46Optimal Power Allocation and Scheduling Under Jamming Attacks
In this paper, we consider a jammed wireless scenario where a network operator aims to schedule users to maximize network performance while guaranteeing a minimum performance level to each user. We consider the case where no information about the position and the triggering threshold of the jammer is available. We show that the network performance maximization problem can be modeled as a finite-horizon joint power control and user scheduling problem, which is NP-hard. To find the optimal solution of the problem, we exploit dynamic programming techniques. We show that the obtained problem can be decomposed, i.e., the power control problem and the user scheduling problem can be sequentially solved at each slot. We investigate the impact of uncertainty on the achievable performance of the system and we show that such uncertainty leads to the well-known exploration-exploitation tradeoff. Due to the high complexity of the optimal solution, we introduce an approximation algorithm by exploiting state aggregation techniques. We also propose a performance-aware online greedy algorithm to provide a low-complexity sub-optimal solution to the joint power control and user scheduling problem under minimum quality-of-service requirements. The efficiency of both solutions is evaluated through extensive simulations, and our results show that the proposed solutions outperform other traditional scheduling policies.

47An Energy-Efficient Adaptive Overlapping Clustering Method for Dynamic Continuous Monitoring in WSNs
Clustering is a key technique to improve energy efficiency in wireless sensor networks (WSNs). In continuous monitoring applications, the clusters should be formed dynamically according to the event development for energy-efficient data gathering. In this paper, an energy-efficient adaptive overlapping clustering (EEAOC) method is proposed in WSNs for continuous monitoring applications. In EEAOC, a 2-logical-coverage overlapping clustering topology is established such that the adjacent sensors in the event area can be grouped into the same cluster for data fusion and the cluster migration operation can be processed without changing the overlapping structure among clusters. Moreover, to further reduce energy consumption, a hybrid data reporting strategy that switches between time-driven and event-driven schemes is introduced based on the QoS requirements in continuous monitoring applications. Simulation results show that EEAOC achieves a longer network lifetime cycle.

48Throughput-Optimal Multi hop Broadcast on Directed Acyclic Wireless Networks
We study the problem of efficiently disseminating packets in multi-hop wireless networks. At each time slot, the network controller activates a set of non-interfering links and forward selected copies of packets on each activated link. The maximum rate of commonly received packets is referred to as the broadcast capacity of the network. Existing policies achieve the broadcast capacity by balancing traffic over a set of spanning trees, which are difficult to maintain in a large and time-varying wireless network. In this paper, we propose a new dynamic algorithm that achieves the broadcast capacity when the underlying network topology is a directed acyclic graph (DAG). This algorithm is decentralized, utilizes local information only, and does not require the use of spanning trees. The principal methodological challenge inherent in this problem is the absence of work-conservation principle due to the duplication of packets, which renders usual queuing modeling inapplicable. We overcome this difficulty by studying relative packet deficits and imposing in-order delivery constraints to every node in the network. We show that in-order delivery is throughput-optimal in DAGs and can be exploited to simplify the design and analysis of optimal algorithms. Our capacity characterization also leads to a polynomial time algorithm for computing the broadcast capacity of any wireless DAG under the primary interference constraints. In addition, we propose a multiclass extension of our algorithm, which can be effectively used for broadcasting in any network with arbitrary topology. Simulation results show that the algorithm has a superior delay performance as compared with the traditional tree-based approaches.

49eICIC Configuration Algorithm with Service Scalability in Heterogeneous Cellular Networks
Interference management is one of the most important issues in heterogeneous cellular networks with multiple macro and pico cells. The enhanced inter cell interference coordination (eICIC) has been proposed to protect downlink pico cell transmissions by mitigating interference from neighboring macro cells. Therefore, the adaptive eICIC configuration problem is critical, which adjusts the parameters including the ratio of almost blank subframes (ABS) and the bias of cell range expansion (RE). This problem is challenging especially for the scenario with multiple coexisting network services, since different services have different user scheduling strategies and different evaluation metrics. By using a general service model, we formulate the eICIC configuration problem with multiple coexisting services as a general form consensus problem with regularization and solve the problem by proposing an efficient optimization algorithm based on the alternating direction method of multipliers. In particular, we perform local RE bias adaptation at service layer, local ABS ratio adaptation at BS layer, and coordination among local solutions for a global solution at a network layer. To provide the service scalability, we encapsulate the service details into the local RE bias adaptation subproblem, which is isolated from the other parts of the algorithm, and we also introduce some implementation examples of the subproblem for different services. The extensive simulation results demonstrate the efficiency of the proposed algorithm and verify the convergence property.

50Design of Surface Acoustic Wave Parafoil Riser Tension Sensor
An increasing demand for the online tension measurement in developing parafoil has arisen. In this paper, a new design for surface acoustic wave (SAW) tension sensor, which can be used to test the parafoil riser tension wirelessly and passively, is discussed. An SAW resonator is used for sensing tension by determining the frequency of the resonant reflection device. In accordance with the test requirements, a nondestructive side-loading tension testing structure is created by which stress analysis and optimization can be operated in ANSYS. To understand the relationship between size and frequency of the antenna in the sensor, a new antenna design called microstrip antenna is proposed following the high frequency structure simulator analysis. The proposed design shows good linearity and sensitivity between the SAW frequency and the riser tension through the actual experiment, which meets the stringent requirement for the shape of the sensor. Thus, the sensor can obtain tension measurement during the operation of the parafoil riser.

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