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Optimal routing and data aggregation for maximizing lifetime of wireless sensor networks
 Inf. Eng. Dept., Chinese Univ. of Hong Kong, Tech. Rep
, 2005
"... Abstract—An optimal routing and data aggregation scheme for wireless sensor networks is proposed in this paper. The objective is to maximize the network lifetime by jointly optimizing data aggregation and routing. We adopt a model to integrate data aggregation with the underlying routing scheme and ..."
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Abstract—An optimal routing and data aggregation scheme for wireless sensor networks is proposed in this paper. The objective is to maximize the network lifetime by jointly optimizing data aggregation and routing. We adopt a model to integrate data aggregation with the underlying routing scheme and present a smoothing approximation function for the optimization problem. The necessary and sufficient conditions for achieving the optimality are derived and a distributed gradient algorithm is designed accordingly. We show that the proposed scheme can significantly reduce the data traffic and improve the network lifetime. The distributed algorithm can converge to the optimal value efficiently under all network configurations. Index Terms—Data aggregation, maximum lifetime routing, network lifetime, smoothing methods, wireless sensor networks. I.
Lowcomplexity and distributed energy minimization in multihop wireless networks
 Purdue University, Tech. Rep., 2006, available on http://web.ics.purdue.edu/ ∼ llin/paper/ tech06.pdf
, 2007
"... Abstract — In this work, we study the problem of minimizing the total power consumption in a multihop wireless network subject to a given offered load. It is wellknown that the total power consumption of multihop wireless networks can be substantially reduced by jointly optimizing power control, ..."
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Abstract — In this work, we study the problem of minimizing the total power consumption in a multihop wireless network subject to a given offered load. It is wellknown that the total power consumption of multihop wireless networks can be substantially reduced by jointly optimizing power control, link scheduling, and routing. However, the known optimal crosslayer solution to this problem is centralized, and with high computational complexity. In this paper, we develop a lowcomplexity and distributed algorithm that is provably powerefficient. In particular, under the node exclusive interference model, we can show that the total power consumption of our algorithm is at most twice as large as the power consumption of the optimal (but centralized and complex) algorithm. Our algorithm is not only the first such distributed solution with provable performance bound, but its powerefficiency ratio is also tighter than that of another suboptimal centralized algorithm in the literature.
Crosslayer Optimization of Correlated Data Gathering in Wireless Sensor Networks
"... Abstract—We consider the problem of gathering correlated sensor data by a single sink node in a wireless sensor network. We assume that the sensor nodes are energyconstrained and design efficient distributed protocols to maximize the network lifetime. Many existing approaches focus on optimizing th ..."
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Abstract—We consider the problem of gathering correlated sensor data by a single sink node in a wireless sensor network. We assume that the sensor nodes are energyconstrained and design efficient distributed protocols to maximize the network lifetime. Many existing approaches focus on optimizing the routing layer only, but in fact the routing strategy is often coupled with power control in the physical layer and link access in the MAC layer. This paper represents a first effort on network lifetime maximization that jointly considers the three layers. We first assume that link access probabilities are known and consider the joint optimal design of power control and routing. We show that the formulated optimization problem is convex and propose a distributed algorithm, JRPA, for the solution. We also discuss the convergence of JRPA. When the optimal link access probabilities are unknown, as in many practical networks, we generalize the problem formulation to encompass all the three layers of routing, power control, and linklayer random access. In this case, the problem cannot be converted into a convex optimization problem, but there exists a duality gap when the Lagrangian dual method is employed. We propose an efficient heuristic algorithm, JRPRA, to solve the general problem, and show through numerical experiments that it can significantly narrow the gap between the computed and optimal solutions. Moreover, even without a priori knowledge of the best link access probabilities predetermined for JRPA, JRPRA achieves extremely competitive performance with JRPA. Other numerical results are provided to show the convergence of the algorithms and their advantages over existing solutions. I.
A Distributed Algorithm for Joint Sensing and Routing
 in Wireless Networks with NonSteerable Directional Antennas,” IEEE Int. Conference on Network Protocols
, 2006
"... 1 Abstract — In many energyrechargeable wireless sensor networks, sensor nodes must both sense data from the environment, and cooperatively forward sensed data to data sinks. Both data sensing and data forwarding (including data transmission and reception) consume energy at sensor nodes. We present ..."
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1 Abstract — In many energyrechargeable wireless sensor networks, sensor nodes must both sense data from the environment, and cooperatively forward sensed data to data sinks. Both data sensing and data forwarding (including data transmission and reception) consume energy at sensor nodes. We present a distributed algorithm for optimal joint allocation of energy between sensing and communication at each node to maximize overall system utility (i.e., the aggregate amount of information received at the data sinks). We consider this problem in the context of wireless sensor networks with directional, nonsteerable antennas. We first formulate a joint datasensing and datarouting optimization problem with both pernode energyexpenditure constraints, and traditional flow routing/conservation constraints. We then simplify this problem by converting it to an equivalent routing problem, and present a distributed gradientbased algorithm that iteratively adjusts the pernode amount of energy allocated between sensing and communication to reach the systemwide optimum. We prove that our algorithm converges to the maximum system utility. We quantitatively demonstrate the energy balance achieved by this algorithm in a network of small, energyconstrained Xband radars, connected via pointtopoint 802.11 links with nonsteerable directional antennas. I.
Fuzzy Algorithms for Maximum Lifetime Routing in Wireless Sensor Networks1
"... Abstract—We address the maximum lifetime routing problem in wireless sensor networks (WSNs) and propose two online routing algorithms based on fuzzy logic, namely fuzzy maximum lifetime algorithm and fuzzy multiobjective algorithm. The former attempts to maximize the WSN lifetime objective, whereas ..."
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Abstract—We address the maximum lifetime routing problem in wireless sensor networks (WSNs) and propose two online routing algorithms based on fuzzy logic, namely fuzzy maximum lifetime algorithm and fuzzy multiobjective algorithm. The former attempts to maximize the WSN lifetime objective, whereas the latter strives to simultaneously optimize the lifetime as well as the energy consumption objectives. The distinguishing aspect of this work is the novel use of fuzzy membership functions and rules in the design of cost functions for the routing objectives considered in this work. A range of simulation results obtained under various network scenarios show that the proposed approach is superior to a number of other wellknown online routing heuristics, both in terms of the obtained network lifetime as well as the average energy consumption. I.
An online multipath routing algorithm for maximizing lifetime in wireless sensor networks
 in Sixth International Conference on Information Technology: New Generations, ITNG
, 2009
"... We address the maximum lifetime routing problem in wireless sensor networks, and present an online multipath routing algorithm. The proposed algorithm strives to maximize the network lifetime metric by distributing the sourcetosink traffic for a given routing request along a set of paths. Fuzzy m ..."
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We address the maximum lifetime routing problem in wireless sensor networks, and present an online multipath routing algorithm. The proposed algorithm strives to maximize the network lifetime metric by distributing the sourcetosink traffic for a given routing request along a set of paths. Fuzzy membership function is used for designing the edge weight function. Simulation results obtained under a variety of network scenarios show that the proposed multipath scheme is able to achieve better lifetime results than those obtained by its predecessor singlepath fuzzy routing scheme as well as by another wellknown online routing scheme, namely the Online Maximum Lifetime heuristic.
Ear: An energy and activity aware routing protocol for wireless sensor networks in smart environments. The Computer Journal
, 2012
"... Sensor network, unlike traditional communication network, is deeply embedded in physical environments and its operation is mainly driven by the event activities in the environment. In longterm operations, the event activities usually show certain patterns which can be learned and exploited to optim ..."
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Sensor network, unlike traditional communication network, is deeply embedded in physical environments and its operation is mainly driven by the event activities in the environment. In longterm operations, the event activities usually show certain patterns which can be learned and exploited to optimize network design. However, this has been underexplored in the literature. One work related to this is using ATPG for radio duty cycling ([1]). In this paper we present a novel Energy and Activity aware Routing (EAR) protocol for sensor networks. As a case study, we have evaluated EAR with the data trace of real Smart Environments. In EAR an Activity Transition Probability Graph (ATPG) is learned and built from the event activity patterns. EAR is an online routing protocol, which chooses the nexthop relay node by utilizing: activity pattern information in the ATPG graph and a novel index of energy balance in the network. EAR extends network lifetime by maintaining an energy balance across the nodes in the network, while meeting application performance with desired throughput and low data delivery latency. We theoretically prove that: (a) the network throughput with EAR achieves
Maximal Lifetime Power and Rate Allocation for Wireless Sensor Systems with Data Distortion Constraints
 IEEE Trans. Signal Proc
"... Abstract—We address a lifetime maximization problem for a singlehop wireless sensor system (also known as a Gaussian sensor network) where multiple sensors encode and communicate their measurements of a Gaussian random source to a fusion center (FC). The FC is required to reconstruct the source wit ..."
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Abstract—We address a lifetime maximization problem for a singlehop wireless sensor system (also known as a Gaussian sensor network) where multiple sensors encode and communicate their measurements of a Gaussian random source to a fusion center (FC). The FC is required to reconstruct the source within a prescribed distortion threshold. The lifetime optimization problem is formulated as a joint power, rate, and timeslot [for timedivision multiple access (TDMA)] allocation problem under the constraints of the wellknown rate distortion constraints for the Gaussian CEO problem, the capacity constraints of the wireless links, the energy constraints of the sensor nodes and the strict delay constraint within which the encoded sensor data must arrive at the FC. We study the performances of TDMA and an interference limited nonorthogonal multiple access (NOMA) (with singleuser decoding)based protocols and compare them against
Lifetime and distortion optimization with joint source/channel rate adaptation and network codingbased error control in wireless video sensor networks." Vehicular Technology
 IEEE Transactions on
, 2011
"... Abstract—In this paper, we study joint performance optimization on network lifetime and video distortion for an energyconstrained wireless video sensor network (WVSN). To seek an appropriate tradeoff between maximum network lifetime and minimum video distortion, a framework for joint source/channe ..."
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Abstract—In this paper, we study joint performance optimization on network lifetime and video distortion for an energyconstrained wireless video sensor network (WVSN). To seek an appropriate tradeoff between maximum network lifetime and minimum video distortion, a framework for joint source/channel rate adaptation is proposed, where the video encoding rate, link rate, and power consumption are jointly considered, formulating a weighted convex optimization problem. In the context of lossy wireless channels, an efficient error control scheme that couples network coding and multipath routing is explored. Moreover, an integrated power consumption model, including power dissipation on video compression, error control, and data communication, is specifically developed for the video sensor node. By primal decomposition, the original problem is decomposed into a twolevel optimization procedure, with the highlevel procedure for source adaptation (source rate optimization) and the lowlevel procedure for channel adaptation (network resource allocation). Finally, a fully decentralized iterative algorithm is developed to resolve the target optimization problem. Extensive simulation results evaluate the convergence performance of the proposed algorithm and demonstrate the best tradeoff performance. Index Terms—Lifetime, power–rate–distortion (PRD), resource allocation, wireless video sensor networks (WVSNs).
Networks Based on Grid
, 2016
"... All intext references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately. ..."
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All intext references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.