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21
Extending Network Lifetime for PrecisionConstrained Data Aggregation
 in Wireless Sensor Networks,” Proc. IEEE INFOCOM
, 2006
"... Abstract — This paper exploits the tradeoff between data quality and energy consumption to extend the lifetime of wireless sensor networks. We consider the applications that require some aggregate form of sensed data with precision guarantees. Our key idea is to differentiate the precisions of data ..."
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Cited by 28 (8 self)
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Abstract — This paper exploits the tradeoff between data quality and energy consumption to extend the lifetime of wireless sensor networks. We consider the applications that require some aggregate form of sensed data with precision guarantees. Our key idea is to differentiate the precisions of data collected from different sensor nodes to balance their energy consumption. This is achieved by partitioning the precision constraint of data aggregation and allocating error bounds to individual sensor nodes in a coordinated fashion. Three factors affecting the lifetime of sensor nodes are identified: (1) the changing pattern of sensor readings; (2) the residual energy of sensor nodes; and (3) the communication cost between the sensor nodes and the base station. We analyze the optimal precision allocation in terms of network lifetime and propose an adaptive precision allocation scheme that dynamically adjusts the error bounds of sensor nodes. Experimental results using real data traces show that the proposed scheme significantly improves network lifetime compared to existing methods. I.
Optimizing Lifetime for Continuous Data Aggregation with Precision Guarantees
 IEEE/ACM Trans. Networking
, 2008
"... Abstract—This paper exploits the tradeoff between data quality and energy consumption to extend the lifetime of wireless sensor networks. To obtain an aggregate form of sensor data with precision guarantees, the precision constraint is partitioned and allocated to individual sensor nodes in a coordi ..."
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Cited by 4 (2 self)
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Abstract—This paper exploits the tradeoff between data quality and energy consumption to extend the lifetime of wireless sensor networks. To obtain an aggregate form of sensor data with precision guarantees, the precision constraint is partitioned and allocated to individual sensor nodes in a coordinated fashion. Our key idea is to differentiate the precisions of data collected from different sensor nodes to balance their energy consumption. Three factors affecting the lifetime of sensor nodes are identified: 1) the changing pattern of sensor readings; 2) the residual energy of sensor nodes; and 3) the communication cost between the sensor nodes and the base station. We analyze the optimal precision allocation in terms of network lifetime and propose an adaptive scheme that dynamically adjusts the precision constraints at the sensor nodes. The adaptive scheme also takes into consideration the topological relations among sensor nodes and the effect of innetwork aggregation. Experimental results using real data traces show that the proposed scheme significantly improves network lifetime compared to existing methods. Index Terms—Data accuracy, data aggregation, energy efficiency, network lifetime, sensor network. I.
“How long is the lifetime of a wireless sensor network?”
"... Wireless sensor networks (WSNs) are known to be highly energyconstrained and each network’s lifetime has a strong dependence on the nodes ’ battery capacity. As such, the network lifetime has been a critical concern in WSN research. While numerous energyefficient protocols have been proposed to pr ..."
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Cited by 2 (0 self)
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Wireless sensor networks (WSNs) are known to be highly energyconstrained and each network’s lifetime has a strong dependence on the nodes ’ battery capacity. As such, the network lifetime has been a critical concern in WSN research. While numerous energyefficient protocols have been proposed to prolong the network lifetime, various definitions of network lifetime have also been used for the different scenarios and protocols. The lifetime of a sensor network is most commonly defined as the time to the first sensor node failure – seemingly overpessimistic in many envisaged deployment scenarios. While other definitions exist, there has not been any consensus on which quantitative lifetime definition is most useful. In this paper, we aim to provide as objectively as possible, a comparative study of WSN protocols based on various network lifetime definitions. We also discuss the implications of these metrics and their applicability in evaluating the effectiveness of WSN data delivery schemes.
Distributed Algorithms for Lifetime Maximization in Sensor Networks via MinMax Spanning Subgraphs
, 2008
"... We consider the problem of static transmissionpower assignment for lifetime maximization of a wireless sensor network with stationary nodes operating in a datagathering scenario. Using a graphtheoretic approach, we propose two distributed algorithms, MLS and BSPAN, that construct spanning trees w ..."
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We consider the problem of static transmissionpower assignment for lifetime maximization of a wireless sensor network with stationary nodes operating in a datagathering scenario. Using a graphtheoretic approach, we propose two distributed algorithms, MLS and BSPAN, that construct spanning trees with minimum maximum (minmax) edge cost. MLS is based on computation of minmaxcost paths from a reference node, while BSPAN performs a binary search over the range of power levels and exploits the wireless broadcast advantage. We also present a simple distributed method for pruning a graph to its Relative Neighborhood Graph, which reduces the worstcase message complexity of MLS under natural assumptions on the pathloss. In our network simulations both MLS and BSPAN significantly outperform the recently proposed Distributed MinMax Tree algorithm in terms of number of messages required.
V.: Updating Directed Minimum Cost Spanning Trees
 In: Proceedings of the 5th Workshop on Experimental Algorithms (WEA), Springer, LNCS
, 2006
"... Abstract. We consider the problem of updating a directed minimum cost spanning tree (DMST), when edges are deleted from or inserted to a weighted directed graph. This problem apart from being a classic for directed graphs, is to the best of our knowledge a wide open aspect for the field of dynamic g ..."
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Abstract. We consider the problem of updating a directed minimum cost spanning tree (DMST), when edges are deleted from or inserted to a weighted directed graph. This problem apart from being a classic for directed graphs, is to the best of our knowledge a wide open aspect for the field of dynamic graph algorithms. Our contributions include results on the hardness of updates, a dynamic algorithm for updating a DMST, and detailed experimental analysis of the proposed algorithm exhibiting a speedup factor of at least 2 in comparison with the static practice.
Distributed computation of maximum lifetime spanning subgraphs in sensor networks
 IN: PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON MOBILE ADHOC AND SENSOR NETWORKS (MSN
, 2007
"... We present a simple and efficient distributed method for determining the transmission power assignment that maximises the lifetime of a datagathering wireless sensor network with stationary nodes and static power assignments. Our algorithm determines the transmission power level inducing the maximu ..."
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We present a simple and efficient distributed method for determining the transmission power assignment that maximises the lifetime of a datagathering wireless sensor network with stationary nodes and static power assignments. Our algorithm determines the transmission power level inducing the maximumlifetime spanning subgraph of a network by means of a distributed breadthfirst search for minmaxpower communication paths, i.e. paths that connect a given reference node to each of the other nodes so that the maximum transmission power required on any link of the path is minimised. The performance of the resulting Maximum Lifetime Spanner (MLS) protocol is validated in a number of simulated networking scenarios. In particular, we study the performance of the protocol in terms of the number of required control messages, and compare it to the performance of a recently proposed Distributed MinMax Tree (DMMT) algorithm. For all network scenarios we consider, MLS outperforms DMMT significantly. We also discuss bringing down the message complexity of our algorithm by initialising it with the Relative Neighbourhood Graph (RNG) of a transmission graph rather than the full graph, and present an efficient distributed method for reducing a given transmission graph to its RNG.
Lifetime Maximization in Wireless Sensor Networks by Distributed Binary Search
"... Abstract. We consider the problem of determining the transmission power assignment that maximizes the lifetime of a datagathering wireless sensor network with stationary nodes and static transmission power levels. We present a simple and efficient distributed algorithm for this task that works by e ..."
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Abstract. We consider the problem of determining the transmission power assignment that maximizes the lifetime of a datagathering wireless sensor network with stationary nodes and static transmission power levels. We present a simple and efficient distributed algorithm for this task that works by establishing the minimum power level at which the network stays connected. The algorithm is based on a binary search over the range of feasible transmission power levels and does not require prior knowledge of network topology. We study the performance of the resulting BSpan protocol by network simulations and compare the number of control messages required by BSpan to two other recently proposed methods, the Distributed MinMax Tree (DMMT) andMaximumLifetime Spanner (MLS) algorithms. We find that BSpan outperforms both DMMT and MLS significantly. 1
UFlood: HighThroughput Flooding over Wireless Mesh Networks
"... Abstract—This paper proposes UFlood, a flooding protocol for wireless mesh networks. UFlood targets situations such as software updates where all nodes need to receive the same large file of data, and where limited radio range requires forwarding. UFlood’s goals are high throughput and low airtime, ..."
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Abstract—This paper proposes UFlood, a flooding protocol for wireless mesh networks. UFlood targets situations such as software updates where all nodes need to receive the same large file of data, and where limited radio range requires forwarding. UFlood’s goals are high throughput and low airtime, defined respectively as rate of completion of a flood to the slowest receiving node and total time spent transmitting. The key to achieving these goals is good choice of sender for each transmission opportunity. The best choice evolves as a flood proceeds in ways that are difficult to predict. UFlood’s core new idea is a distributed heuristic to dynamically choose the senders likely to lead to all nodes receiving the flooded data in the least time. The mechanism takes into account which data nearby receivers already have as well as internode channel quality. The mechanism includes a novel bitrate selection algorithm that trades off the speed of high bitrates against the larger number of nodes likely to receive low bitrates. Unusually, UFlood uses both random network coding to increase the usefulness of each transmission and detailed feedback about what data each receiver already has; the feedback is critical in deciding which node’s coded transmission will have the most benefit to receivers. The required feedback is potentially voluminous, but UFlood includes novel techniques to reduce its cost. The paper presents an evaluation on a 25node 802.11 testbed. UFlood achieves 150 % higher throughput than MORE, a highthroughput flooding protocol, using 65 % less airtime. UFlood uses 54 % less airtime than MNP, an existing efficient protocol, and achieves 300 % higher throughput. I.
SelfManaging EnergyEfficient Multicast Support in MANETs under EndtoEnd Reliability Constraints
 COMPUTER NETWORKS
, 2009
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Throughput and Energy Efficiency in Wireless Ad Hoc Networks With Gaussian Channels
, 2012
"... This paper studies the bottleneck link capacity under the Gaussian channel model in strongly connected random wireless ad hoc networks, with nodes independently and uniformly distributed in a unit square. We assume that each node is equipped with two transceivers (one for transmission and one for re ..."
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This paper studies the bottleneck link capacity under the Gaussian channel model in strongly connected random wireless ad hoc networks, with nodes independently and uniformly distributed in a unit square. We assume that each node is equipped with two transceivers (one for transmission and one for reception) and allow all nodes to transmit simultaneously. We draw lower and upper bounds, in terms of bottleneck link capacity, for homogeneous networks (all nodes have the same transmission power level) and propose an energyefficient power assignment algorithm (CBPA) for heterogeneous networks (nodes may have different power levels), with a provable bottleneck link capacity guarantee of, where is the channel bandwidth. In addition, we develop a distributed implementation of CBPA with message complexity and provide extensive simulation results.