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Synchronization of bio-inspired pulse-coupled oscillators is receiving increased attention due to its wide applications in sensor networks and wireless communications. However, most existing results are obtained in the absence of malicious attacks. Given the distributed and unattended nature of wireless sensor networks, it is imperative to enhance the resilience of pulse based synchronization against malicious attacks. To achieve this goal, we propose a new pulse based interaction mechanism to improve the resilience of pulse based synchronization. We rigorously characterize the condition for mounting stealthy attacks under the proposed pulse based interaction mechanism and prove analytically that synchronization of legitimate oscillators can be achieved in the presence of multiple stealthy attackers even when the initial phases are unrestricted, i.e., randomly distributed in the entire oscillation period. This is in distinct difference from most existing attack-resilient synchronization algorithms (including the seminal paper from L. Lamport and P. M. Melliar-Smith, “Synchronizing Clocks in the Presence of Faults,” J. ACM, vol. 32, no. 1, pp. 52–78, 1985), which require a priori (almost) synchronization among legitimate nodes. Numerical simulations are given to confirm the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, we study the energy efficiency (EE) optimization for simultaneous wireless information and power transfer in multiple-input-multiple-output two-way amplify-and-forward relay networks, where the energy-constrained relay harvests energy from two sources’ signals by power splitting (PS) scheme to forward the information of two sources. Our objective is to jointly design the sources and relay precoding matrices and the PS ratio to maximize the EE of the network, under the transmit power constraints at sources and relay and the minimum spectral efficiency requirement. We transform the nonconvex precoding and PS design problem into a difference of convex programming and propose an efficient iterative algorithm based on the constrained concave convex procedure to obtain a local optimum. To reduce computational complexity, we propose a generalized singular value decomposition based channel diagonalization scheme to simplify the optimization into a joint source and relay power allocation problem. The alternating optimization method is employed to solve this problem and a suboptimal solution to the EE maximization problem is obtained. Simulation results demonstrate the effectiveness of the proposed schemes. [ABSTRACT FROM AUTHOR]

This paper proposes task-scheduling algorithms designed to save energy in ad hoc networks by using a novel concept of "affinity" as the scheduling metric. This notion of affinity is used to represent the task-linking topology. For one-hop ad hoc networks, we define three types of affinity measures: node affinity, task affinity, and weighted affinity. Node affinity is defined as the weighted sum of incoming and outgoing task flows at each node, and task affinity as the sum of node affinities of source and destination nodes for each task. Based on these affinity measures, we consider three heuristic scheduling algorithms that are executable in real time: 1) affinity-first shortest task scheduling Qat; 2) task-size-first affinity-based scheduling Qta; and 3) task-size weighted-affinity scheduling Qwa. These algorithms have the advantage of making the total duration of the doze state of all the nodes in the network longer than in other conventional schemes, thereby achieving significant power saving (PS). Our simulation experiments suggest that the PS performance of Qwa is comparable to optimal scheduling (which is not implementable in practice for realistic link topologies). We also present a framework for a PS medium-access-control (MAC) protocol in which our scheduling algorithm can be deployed, and we describe how to enhance the existing 802.11 PS MAC to implement our framework. Simulation results demonstrate that our enhanced PS MAC protocol combined with affinity-based scheduling improves power efficiency and throughput significantly over other existing schemes. [ABSTRACT FROM AUTHOR]

In this paper, we consider the exact top-k query problem in wireless sensor networks, i.e., where one seeks to find the k highest reported values as well as the complete set of nodes that reported them. Our primary contribution in this context is EXTOK, a provably correct and topology-independent new filtering-based algorithm for processing exact top-k queries. As a secondary contribution we confirm a previous result of ours by showing that the efficiency of top-k query processing algorithms, including EXTOK, can be further improved by simply choosing a proper underlying logical tree topology. We examine EXTOK's performance with respect to a number of parameters and different logical tree topologies while using both synthetic and real data sets. Our simulation reveal that EXTOK consistently outperforms the current state-of-the-art algorithm by a very significant margin and regardless of the underlying logical tree topology. [ABSTRACT FROM AUTHOR]

In the well-known distributed target-SIR-tracking power control algorithm (TPC), when the system is infeasible (a constrained power vector does not exist to attain target-SIRs), all non-supported users (those who cannot obtain their target-SIRs) transmit at their maximum power. Such users inefficiently consume their energy, and cause interference to others, which increases the number of non-supported users. To deal with this, some non-supported users should decrease their transmit power (the gradual removal problem). We present a distributed power control scheme with gradual soft removal, by which either TPC or OPC (opportunistic power control) is used, depending on whether the ratio of interference-to-path-gain is below or above a threshold that is chosen by each user in a distributed manner. We show that our algorithm converges to a unique fixed-point in both feasible and infeasible systems, and that when the system is infeasible, it results in less outage with significantly less consumed power, as compared to TPC. We also provide a game theoretic analysis of our algorithm by introducing a new pricing when users are selfish. As our algorithm is fully distributed and requires only local information, it can be applied to both cellular and ad hoc networks. Simulation results confirm our analysis. [ABSTRACT FROM PUBLISHER]