An Optimal Data Propagation Algorithm for Maximizing the Lifespan of Sensor Networks

Jarry, Aubin; Leone, Pierre; Powell, Olivier; Rolim, José D. P.

doi:10.1007/11776178_25

Cited by 71 publications

(72 citation statements)

References 13 publications

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“…This is an important generalization over previous work ( [19,23]). Interestingly, our results here imply (a) energy balanced data propagation using only two transmission levels (i.e.…”

Section: Introduction Our Contribution and Related Workmentioning

confidence: 53%

“…In other words, our result shows that edges (i, j) such that −λ i c i0 + λ i c ij + λ j c j0 > 0 are useless to increase the efficiency of the network. In a former work [23], appropriate λ i values were computed in an ad-hoc way under the specific condition that the energy consumption grows quadratically with the range of emission.…”

Section: Proposition 1 Problem 1 Is Equivalent To Problem 2 Which Mmentioning

confidence: 99%

“…Moreover, by the discussion of Section 2 this flow also maximizes the lifetime of the network. This is used in an ad-hoc way in the papers [19,23] where it is assumed that sensors can transmit data to their nearest neighbor or directly to the sink. In these papers, the energy required to send data to neighbors at distance ≤ 1 is constant and the same for all the sensors.…”

Section: A First Energy-balance Optimal Topologymentioning

confidence: 99%

“…Moreover, we provide a decentralized algorithm to compute the probabilities with minimal assumptions and we establish formally that energy-balance mechanisms are efficient. Indeed, such a strategy maximizes the flow in the network [23,26]. The numerical simulations show that the division of the network in slices is not regular and some sensors contribute more to the routing process than some others do.…”

Section: Introduction Our Contribution and Related Workmentioning

confidence: 99%

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Optimal data gathering paths and energy-balance mechanisms in wireless networks

et al. 2011

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Abstract. This paper studies the data gathering problem in wireless networks, where data generated at the nodes has to be collected at a single sink. We investigate the relationship between routing optimality and fair resource management. In particular, we prove that for energy balanced data propagation, Pareto optimal routing and flow maximization are equivalent, and also prove that flow maximization is equivalent to maximizing the network lifetime. We algebraically characterize the network structures in which energy balanced data flows are maximal. Moreover, we algebraically characterize communication links which are not used by an optimal flow. This leads to the characterization of minimal network structures supporting the maximal flows. We note that energy balance, although implying global optimality, is a local property that can be computed efficiently and in a distributed manner. We suggest online distributed algorithms for energy balance in different optimal network structures and numerically show their stability in particular setting. We remark that although the results obtained in this paper have a direct consequence in energy saving for wireless networks they do not limit themselves to this type of networks neither to energy as a resource. As a matter of fact, the results are much more general and can be used for any type of network and different types of resources. 3

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“…This is an important generalization over previous work ( [19,23]). Interestingly, our results here imply (a) energy balanced data propagation using only two transmission levels (i.e.…”

Section: Introduction Our Contribution and Related Workmentioning

confidence: 53%

Section: Proposition 1 Problem 1 Is Equivalent To Problem 2 Which Mmentioning

confidence: 99%

Section: A First Energy-balance Optimal Topologymentioning

confidence: 99%

Section: Introduction Our Contribution and Related Workmentioning

confidence: 99%

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Optimal data gathering paths and energy-balance mechanisms in wireless networks

et al. 2011

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“…In [35], a distributed algorithm is proposed. Each sensor transmits data directly to the sink or to neighbor nodes.…”

Section: Related Workmentioning

confidence: 99%

Performance Evaluation of a Topology Control Algorithm for Wireless Sensor Networks

Ababneh

2010

International Journal of Distributed Sensor Networks

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A main design challenge in the area of sensor networks is energy efficiency to prolong the network operable lifetime. Since most of the energy is spent for radio communication, an effective approach for energy conservation is scheduling sleep intervals for extraneous nodes, while the remaining nodes stay active to provide continuous service. Assuming that node position information is unavailable, we present a topology control algorithm, termed OTC, for sensor networks. It uses two-hop neighborhood information to select a subset of nodes to be active among all nodes in the neighborhood. Each node in the network selects its own set of active neighbors from among its one-hop neighbors. This set is determined such that it covers all two-hop neighbors. OTC does not assume the network graph to be a Unit Disk Graph; OTC also works well on general weighted network graphs. OTC is evaluated against two well-known algorithms from the literature, namely, Span and GAF through realistic simulations using TOSSIM. In terms of operational lifetime, load balancing and Spanner property OTC shows promising results. Apart from being symmetric and connected, the resulting graph when employing OTC shows good spanner properties.

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