Networking Projects – ElysiumPro

Networking Projects ElysiumPro

Networking Projects

CSE Projects, ECE Projects
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N Networking is the construction, design and use of a network that includes cabling, hub, bridge, switch, router, and so forth. ElysiumPro offers an extensive list of project ideas on Networking for students. Most of the Networking projects are done by java programming.
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1Utility 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.
2Accurate 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.
3Optimally 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.
4Energy 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.
5Capacity of Hybrid Wireless Networks with Long-Range Social Contacts Behavior
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.
6ROSE: 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.
7Exploring 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.
8Optimal 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.
9Tunable QoS-Aware Network Survivability
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.
10Throughput-Optimal Multihop 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.
11eICIC 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.
12Design 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.
13FACT: Fine-Grained Adaptation of Carrier Sense Threshold in IEEE 802.11 WLANs
A fine-grained carrier sense threshold (CST) adaptation method, which controls CST, depending on both the interferer and destination nodes, is proposed to improve spatial reuse in wireless local area networks (WLANs). The proposed method utilizes predefined functions in the WLAN standard, thus making itself easily implementable in commercial WLAN devices. A supplementary clear channel assessment (CCA) method is also proposed to further enhance network performance by reducing CCA overhead. The performance of the proposed methods is comparatively evaluated via ns-3 simulation. Simulation results show that the proposed methods significantly improve network throughput compared with the legacy method in a two-cell environment.
14Backhaul Resource Allocation for Existing and Newly Arrived Moving Small Cells
Cellular users in moving vehicles such as buses and trains have been suffering from quality-of-service (QoS) issues. Small-cell access points (SAPs) can be deployed in the vehicles to combat this problem. We call the SAPs deployed in vehicles moving SAPs (M-SAPs). With a small cell, two links are created in the macrocell, namely, the access link and the backhaul link. The macrocell may work as the backhaul for an M-SAP. Due to the mobility of the vehicle, an M-SAP will be entering and leaving the macrocell, and the backhaul connection will be changing. As the backhaul is wireless, resources will be required for data transmission from the macrocell to M-SAP, in addition to resources required for transmission from M-SAP to the user. In the existing research, backhaul resources are reserved for the newly arrived M-SAPs and not optimally utilized. In this paper, we study the allocation of orthogonal frequency-division multiple-access (OFDMA) resources (resource blocks and transmission power) to macrocell users and the backhaul of M-SAPs in the downlink of the network. Both the existing and newly arrived M-SAPs are considered in the macrocell. The objective is to maximize the achievable data rate of the newly arrived M-SAPs in the macrocell under the constraint that the minimum required achievable data rates of the existing macrocell users and the M-SAPs are satisfied.
15Delay Analysis of Physical-Layer Key Generation in Dynamic Roadside-to-Vehicle Networks
Secret key generation by extracting the shared randomness in a wireless fading channel is a promising way to ensure wireless communication security. Previous studies only consider key generation in static networks, but real-world key establishments are usually dynamic. In this paper, for the first time, we investigate the pairwise key generation in dynamic wireless networks with a center node and random arrival users (e.g., roadside units (RSUs) with vehicles). We establish the key generation model for these kinds of networks. We propose a method based on discrete Markov chain to calculate the average time a user will spend on waiting and completing the key generation, called average key generation delay (AKGD). Our method can tackle both serial and parallel key generation scheduling under various conditions. We propose a novel scheduling method, which exploits wireless broadcast characteristic to reduce AKGD and probing energy. We conduct extensive simulations to show the effectiveness of our model and method. The analytical and simulation results match each other.
16Backhaul-Aware User Association and Resource Allocation for Energy-Constrained HetNets
Growing attention has been paid to renewable- or hybrid-energy-powered heterogeneous networks (HetNets). In this paper, focusing on backhaul-aware joint user association and resource allocation for this type of HetNets, we formulate an online optimization problem to maximize the network utility reflecting proportional fairness. Since user association and resource allocation are tightly coupled not only on resource consumption of the base stations (BSs) but in the constraints of their available energy and backhaul as well, the closed-form solution is quite difficult to obtain. Thus, we solve the problem distributively by employing certain decomposition methods. Specifically, at first, by adopting the primal decomposition method, we decompose the original problem into a lower level resource-allocation problem for each BS and a higher level user-association problem. For the optimal resource allocation, we prove that a BS either assigns equal normalized resources or provides an equal long-term service rate to its served users. Then, the user-association problem is solved by the Lagrange dual decomposition method, and a completely distributed algorithm is developed. Moreover, applying results of the subgradient method, we demonstrate the convergence of the proposed distributed algorithm. Furthermore, to efficiently and reliably apply the proposed algorithm to the future wireless networks with an extremely dense BS deployment, we design a virtual user association and resource allocation scheme based on the software-defined networking architecture. Finally, numerical results validate the convergence of the proposed algorithm and the significant improvement on network utility, load balancing, and user fairness.
17Secrecy-Optimized Resource Allocation for Device-to-Device Communication Underlaying Heterogeneous Networks
Device-to-device (D2D) communications have recently attracted much attention for the potential capability to improve spectral efficiency (SE) underlaying the existing heterogeneous networks (HetNets). Due to no sophisticated control, D2D-worked user equipments (DUEs) themselves cannot resist eavesdropping or security attacks. It is urgent to maximize the secure capacity for both cellular users and DUEs. This paper formulates the radio resource-allocation problem to maximize the secure capacity of DUEs for D2D communication underlaying HetNets, which consist of high-power nodes (HPNs) and low-power nodes (LPNs). The optimization objective function with transmit bit rate and power constraints, which is nonconvex and hard to directly derive, is first transformed into a matrix form. Then, the equivalent convex form of the optimization problem is derived according to Perron-Frobenius theory. A heuristic iterative algorithm based on the proximal theory is proposed to solve this equivalent convex problem through evaluating the proximal operator of the Lagrange function. Numerical results show that the proposed radio resource-allocation solution significantly improves the secure capacity with a fast convergence speed.
18Power-Aware Maximization of Ergodic Capacity in D2D Underlay Networks
Device-to-device (D2D) underlay networks enable high data rates and low end-to-end delay and improve spectral/energy efficiency and offload cellular traffic. However, D2D communication also results in interference between CUs and D2D terminals, negatively impacting capacity. Is there a critical set of system parameters (density of D2D users (DUs), cellular base stations (BSs), transmit power, etc.) that can ensure that the benefits of D2D underlay operation can outweigh its drawbacks? We seek to address this fundamental question in the context of the tradeoff between ergodic capacity and power consumption. Toward this end, we first quantify the ergodic capacity metric for a realistic network where D2D pairs are spaced randomly and experience Rician fading. Based on a stochastic-geometry-based network model, we derive, for the first time, closed-form results for ergodic capacity of both cellular users (CUs) and DUs. Second, we identify the D2D user density and transmit power that maximizes the ergodic capacity of the network. Specifically, a two-stage scheme is proposed to optimize ergodic capacity while minimizing overall power consumption. The results from this analysis provide a framework to uncover desirable system design parameters that offer the best gains in terms of capacity.
19Cooperative Store–Carry–Forward Scheme for Intermittently Connected Vehicular Networks
Intermittently connected vehicular networks (ICVNs) consist of stationary roadside units (RSUs) deployed along the highway and mobile vehicles. ICVNs are generally infrastructure constrained with a long inter-RSU distance, leading to large dark areas and transmission outage. In this paper, we propose a novel cooperative store-carry-forward (CSCF) scheme to reduce the transmission outage time of vehicles in the dark areas. The CSCF scheme utilizes bidirectional vehicle streams and selects two vehicles in both directions to serve as relays successively for the target vehicle via inter-RSU cooperation. Compared with the existing schemes, simulation results demonstrate that the proposed CSCF scheme has a great advantage in reducing transmission outage time.
20Energy-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.
21Secure Communication via a Wireless Energy Harvesting Untrusted Relay
The broadcast nature of the wireless medium allows unintended users to eavesdrop on confidential information transmission. In this regard, we investigate the problem of secure communication between a source and a destination via a wireless energy harvesting untrusted node that acts as a helper to relay the information; however, the source and destination nodes wish to keep the information confidential from the relay node. To realize the positive secrecy rate, we use destination-assisted jamming. Being an energy-starved node, the untrusted relay harvests energy from the received radio-frequency (RF) signals, which include the source's information signal and the destination's jamming signal. Thus, we utilize the jamming signal efficiently by leveraging it as a useful energy source. At the relay, to enable energy harvesting and information processing, we adopt power splitting (PS) and time switching (TS) policies. To evaluate the secrecy performance of this proposed scenario, we derive analytical expressions for two important metrics, viz., the secrecy outage probability and the ergodic secrecy rate. The numerical analysis reveals design insights into the effects of different system parameters such as PS ratio, energy harvesting time, target secrecy rate, transmit signal-to-noise ratio (SNR), relay location, and energy conversion efficiency factor, on secrecy performance. Specifically, the PS policy achieves better optimal secrecy outage probability and optimal ergodic secrecy rate than that of the TS policy at higher target secrecy rate and transmit SNR, respectively.
22Toward Efficient Electric-Vehicle Charging Using VANET-Based Information Dissemination
The design of an efficient charging management system for on-the-move electric vehicles (EVs) has become an emerging research problem in future connected vehicle applications, given their mobility uncertainties. Major technical challenges here involve decision-making intelligence for the selection of charging stations (CSs) and the corresponding communication infrastructure for necessary information dissemination between the power grid and mobile EVs. In this paper, we propose a holistic solution that aims to create a high impact on the improvement of end users' driving experiences (e.g., to minimize EVs' charging waiting time during their journeys) and charging efficiency at the power grid side. In particular, the CS selection decision on where to charge is made by individual EVs for privacy and scalability benefits. The communication framework is based on a mobile publish/subscribe (P/S) paradigm to efficiently disseminate CS condition information to EVs that are on the move. To circumvent the rigidity of having stationary roadside units (RSUs) for information dissemination, we promote the concept of mobility as a service (MaaS) by exploiting the mobility of public transportation vehicles (e.g., buses) to bridge the information flow to EVs, given their opportunistic encounters. We analyze various factors affecting the possibility for EVs to access CS information via opportunistic vehicle-to-vehicle (V2V) communications, and we demonstrate the advantage of introducing buses as mobile intermediaries for information dissemination, based on a common EV charging management system under the Helsinki city scenario.
23Power–Delay Tradeoff in Wireless Powered Communication Networks
In this paper, we investigate the power-delay tradeoff for the newly emerging wireless powered communication networks, in which wireless powered devices (WPDs) harvest energy from a power station via wireless energy transfer in the downlink and then communicate with an information receiving station in the uplink. Each WPD is equipped with an energy buffer and a data buffer to store the random harvested energy and the bursty data arrivals, respectively. To minimize the time-averaged power consumption, a stochastic optimization problem is formulated subject to both constraints of data queue stability and harvested energy availability. By employing Lyapunov optimization theory, we transform the stochastic optimization problem into a series of deterministic problems, where each is further proved to become the standard convex optimization problem and, hence, can be effectively and optimally solved by standard convex optimization techniques. Correspondingly, we propose an Online Power and TIMe Allocation (Optima) algorithm, which requires no a priori distribution knowledge of channel states and data arrivals. Most importantly, the proposed algorithm achieves the power-delay tradeoff as [O(1/V ), O(V )], with V being a system control parameter, and provides a significant method to control the power-delay performance on demand in system design. Simulation results verify the theoretical analysis and validate the effectiveness of the proposed algorithm.
24A Novel Approach for Efficient Usage of Intrusion Detection System in Mobile Ad Hoc Networks
Mobile ad hoc networks (MANETs) are self-configuring infrastructureless dynamic wireless networks in which the nodes are resource constrained. Intrusion detection systems (IDSs) are used in MANETs to monitor activities to detect any intrusion in the otherwise vulnerable network. In this paper, we present efficient schemes for analyzing and optimizing the time duration for which the IDSs need to remain active in a MANET. A probabilistic model is proposed, which makes use of cooperation between IDSs among neighborhood nodes to reduce their individual active time. Typically, an IDS has to run all the time on every node to oversee network behavior. This can turn out to be a costly overhead for a battery-powered mobile device in terms of power and computational resources. Hence, in this work, our aim is to reduce the duration of active time of the IDSs without compromising their effectiveness. To validate our proposed approach, we model the interactions between IDSs as a multiplayer cooperative game in which the players have partially cooperative and partially conflicting goals. We theoretically analyze this game and support it with simulation results.
25Energy-Efficient Scheduling for mmWave Backhauling of Small Cells in Heterogeneous Cellular Networks
Heterogeneous cellular networks (HCNs) are emerging as a promising candidate for the fifth-generation (5G) mobile network. With base stations (BSs) of small cells densely deployed, the cost-effective, flexible, and green backhaul solution has become one of the most urgent and critical challenges. With vast amounts of spectrum available, wireless backhaul in the millimeter-wave (mmWave) band is able to provide transmission rates of several gigabits per second. The mmWave backhaul utilizes beamforming to achieve directional transmission, and concurrent transmissions under low interlink interference can be enabled to improve network capacity. To achieve an energy-efficient solution for mmWave backhauling, we first formulate the problem of minimizing the energy consumption via concurrent transmission scheduling and power control into a mixed integer nonlinear program (MINLP). Then, we develop an energy-efficient and practical mmWave backhauling scheme, which consists of the maximum independent set (MIS)-based scheduling algorithm and the power control algorithm. We also theoretically analyze the conditions that our scheme reduces energy consumption, as well as the choice of the interference threshold. Through extensive simulations under various traffic patterns and system parameters, we demonstrate the superior performance of our scheme in terms of energy efficiency and analyze the choice of the interference threshold under different traffic loads, BS distributions, and the maximum transmission power.
26Toward Efficient Mechanisms for Mobile Crowd sensing
Mobile crowdsensing systems aim to provide various novel applications by employing pervasive smartphones. A key factor to enable such systems is substantial participation of normal smartphone users, which requires effective incentive mechanisms. In this paper, we investigate incentive mechanisms for online scenarios, where users arrive and interact with a task requester in a random order, and they have preferences (e.g., photographing) or limits (e.g., travel distance) over the sensing tasks. In existing online mechanisms, the task requester has limited power in assigning tasks to the selected users, i.e., it has to pay for all of the tasks specified by the selected users, although some of these tasks are of little value. To accommodate this, we investigate a more flexible setting, where the requester can actively assign most valuable tasks to the selected users. We design two online incentive mechanisms motivated by a sampling-accepting process and weighted maximum matching. We prove that the designed mechanisms achieve computational efficiency, individual rationality, budget feasibility, truthfulness, consumer sovereignty, and constant competitiveness. By carrying out extensive experiments on two real-world geographical datasets, we demonstrate the practical applicability of the proposed mechanisms.
27Understanding the Impact of Employing Relay Node on Wireless Networks
Cooperative transmission (CT) has been proposed to effectively improve the communication performance like the transmission rate. This is because a relay node (RN) has the advantage of providing more cooperation diversity and a better two-hop cooperation channel than a one-hop direct transmission channel. To this aim, various RN selection algorithms are researched and proposed. Although the benefit of employing RN to wireless networks has been well studied, unfortunately, it introduces some adverse effect at the same time. In this paper, one of these adverse impacts as flow-level cooperation competition (FCC) incurred by RN in CT mode has been investigated. The main problem of FCC is that it may lead to CT mode that is not as beneficial as expected. Considering the pros and cons, an RN in a multiple-hop wireless networks with a game theoretic framework is analyzed, and its performance is investigated. Following this, a Nash equilibrium based strategy is proposed in the process of employing an RN. With this technique, a maximum system performance is achieved, namely, the Nash equilibrium cooperative transmission strategy (NECTS). NECTS guarantees the gain of each flow but also effectively maximizes system performance. Simulation results show that NECTS uses the advantage of cooperative communications but avoids the unnecessary competition. Therefore, the proposed NECTS outperforms the conventional methods.
28Information-Centric Networks with Correlated Mobility
The information-centric networking (ICN), which is an important research direction of future internet architecture, has gained lots of attention from the research community. This paper investigates the impact of a correlated mobility on the throughput and delay performance of mobile ad hoc networks (MANETs) under information-centric environments, where the main concern of nodes is to retrieve contents stored by other nodes. Based on the degree of correlation among nodes, we consider two network regimes, i.e., the cluster-dense regime and cluster-sparse regime. In each regime, we study two mobility time scales: 1) fast mobility, where node mobility is at the same time scale as packet transmissions, and 2) slow mobility, where node mobility is at a much slower time scale than the packet transmissions. In each regime, we characterize the network performance under fast mobility and slow mobility, respectively. Our results indicate that 1)
29Secrecy Capacity Scaling of Large-Scale Networks with Social Relationships
Due to the nature of a wireless medium, a wireless channel is susceptible to malicious nodes, which encourages the consideration of secrecy in many applications such as satellite networks, social networking services, etc. Motivated by the social characteristic that makes nodes more likely to communicate with nearby neighbors, we study the secrecy capacity of large-scale wireless networks with social relationships. We consider two distributions of legitimate nodes: They are homogeneously placed based on a Poisson point process (PPP), or they are inhomogeneously distributed as multiclustering topology. In particular, we consider two scenarios: 1) the noncolluding case, where each eavesdropper decodes its receiving message independently; and 2) the colluding case, where eavesdroppers can cooperate to decode the message. We adopt a rank-based model to describe the social characteristic and investigate its impact on the secrecy capacity using the technique of self-interference cancelation. We employ a passive attack model, where eavesdroppers can only listen to transmissions among legitimate nodes. Our important findings include the following: 1) In the noncolluding case, secrecy capacity is not influenced by eavesdroppers in order sense, but it varies with the density of eavesdroppers and social impacts in the colluding case. 2) The proposed scheme can achieve optimal secrecy throughput neglecting polylogarithmic factor in homogeneous wireless networks.
30Energy-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.
31Medium Access for Concurrent Traffic in Wireless Body Area Networks: Protocol Design and Analysis
Wireless body area networks have been deployed to monitor the health condition of patients. In these applications, multiple sensors are required to report real-time data to the sink such that a physician can diagnose accurately, particularly for intensive care patients, which boosts the convergecast traffic load and increases the collision probability. However, the existing protocols cannot effectively operate under such concurrent traffic load. To bridge this gap, we present a novel two-phase receiver-initiated medium access control (MAC) protocol for concurrent traffic based on asynchronous duty cycling, which is called C-MAC. Technically, C-MAC in the first phase employs carrier-sense multiple access with collision avoidance of the IEEE 802.15.6 standard and designs an ordering-based communication algorithm to effectively avoid collisions. Moreover, C-MAC enables sensor nodes to switch to standby mode to avoid idle listening and overhearing in the second phase. Furthermore, theoretically, we explicitly formulate the mathematical expressions of the random delay and energy consumption of C-MAC. Finally, we conduct extensive numerical analysis and simulation to demonstrate the correctness of theoretical results and the better effectiveness and efficiency of C-MAC than that of RI-MAC and A-MAC in terms of transmission delay and energy consumption.
32Medium 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.
33AFLAS: An Adaptive Frame Length Aggregation Scheme for Vehicular Networks
Vehicular ad hoc networks (VANETs) experience large-scale high-speed mobility and volatile topology. VANETs may therefore experience intermittent connections and may occasionally be unable to guarantee end-to-end connections. This gives the medium access control (MAC) layer the opportunity to adapt its transmission strategy to the current unstable wireless connections to improve transmission efficiency. In this paper, we propose an adaptive frame length aggregation scheme (AFLAS) for VANETs, which is designed to improve transmission efficiency and increase data throughput. In our scheme, the incoming data packets from higher layers are queued separately in the MAC layer to wait for transmission opportunities. Suitable aggregation frame lengths are calculated according to the current wireless status and applied in the MAC layer at the onset of data transmissions. In this paper, we analyze and apply our AFLAS strategy to two current frame aggregation schemes in IEEE 802.11. We also report on the performance evaluation of our scheme. Our results exhibit significant improvement results in data throughput, retransmissions, overheads, and transmission efficiency in comparison with nonadaptive aggregation schemes.
34Performance 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.
35P2S: 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.
36Energy-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.
37Coverage Contribution Area based k-Coverage for Wireless Sensor Networks
Coverage is a primary metric for ensuring the quality of services (QoSs) provided by a wireless sensor network (WSN). In this paper, we focus on the k-coverage problem, which requires a selection of a minimum subset of nodes among the deployed ones such that each point in the target region is covered by at least k nodes. We present both centralized and distributed protocols to tackle this fundamental problem. Our protocols are based on a novel concept of Coverage Contribution Area (CCA), which helps to get a lower sensor spatial density. Furthermore, our protocols take the residual energies of the sensors into consideration. This consideration combining with the low sensor spatial density ensures that our protocols can prolong the network lifetime to a greater extent, which is crucial to WSNs due to the limited energy supply and the difficulties for energy recharging. We also conduct extensive simulations to verify our proposed algorithms, and the results show that they are superior over existing ones.
38Mobile 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.
39Identification 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.
40Energy-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.
41Aggregated 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.
42Simultaneous 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.
43Zoning 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.
44Statistical 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.
45Optimal 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.
46Throughput of QoS Guaranteed Wireless Systems with/without Channel State Information
In this paper, we investigate the throughput of wireless systems in the presence of random data arrivals and quality of service (QoS) requirements, which are statistically characterized by the queueing-bound violation probability. By combining the concepts of effective capacity and effective bandwidth, we propose a unified analytical framework to investigate the achievable throughput. Employing the proposed unified framework, we further acquire the explicit expressions of the throughput of QoS guaranteed wireless systems with the channel state information (CSI) known/unknown at the transmitter. Specifically, the acquired throughput is characterized by the firstand second-order statistics of the random data arrivals, and it is shown that the QoS requirements affect the throughput by the second-order statistics of the random data arrivals and the random data transmissions. In addition, our theoretical analysis demonstrates that the throughput under QoS constraints is tighter than the conventional stable throughput, and that the first-order statistic of the random data arrivals is sufficient to characterize the throughput when the system can tolerate an arbitrarily long queueing delay. In particular, we prove that the queueing-bound violation probability decays exponentially with the queueing-bound. Finally, simulation results corroborate the theoretical analysis.
47Using 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.
48Analysis 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.
49Utility Maximization for Multimedia Data Dissemination in Large-Scale VANETs
With the increasing demand of media-rich entertainment and location-aware services from people on the road, how to disseminate the multimedia data in large-scale Vehicular Ad-Hoc Networks (VANETs) efficiently and reliably is a pressing issue. Due to the high mobility, large scale, and limited contact time between vehicles, it is quite challenging to support the multimedia data dissemination in VANETs. In this paper, we first utilize a hybrid framework to model the VANETs to address the mobility and scalability issues. Then, we formulate a utility-based maximization problem to find the best delivery strategy and select an optimal path for the multimedia data dissemination, where the utility function has taken the delivery delay, Quality of Services (QoS), and storage cost into consideration. With rigorous analysis, we obtain the closed-form of the expected utility of a path, and then obtain the optimal solution of the problem with the convex optimization theory. Finally, we conduct trace-driven simulations to evaluate the performance of the proposed algorithm with real traces collected by taxis in Shanghai. The simulation results demonstrate the rigorousness of our theoretical analysis, and the effectiveness of the proposed solution.
50Route 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.

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