Energy optimal data propagation in wireless sensor networks

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

doi:10.1016/j.jpdc.2006.10.007

Cited by 97 publications

(64 citation statements)

References 12 publications

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“…In fact, in systems of robotic sensors, the determination of one's neighbours is done by sensing capabilities (e.g., vision): any sensor in the sensing radius is detected even if inactive, and thus no other mechanisms are needed. On the other hand, in traditional wireless sensor networks, determination of the neighbours is achieved by radio communication; since an inactive sensor does not participate in any communication, the simple activity of determining one's neighbours, to be completed, requires the use of randomization or the presence of sophisticated synchronization and scheduling mechanisms (e.g., [63,69,74]). …”

Section: Mobile Robotic Sensorsmentioning

confidence: 99%

Computing by Mobile Robotic Sensors

Flocchini

Prencipe

Santoro

2010

Monographs in Theoretical Computer Science. An EATCS Series

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The research areas of mobile robotic sensors lie in the intersection of two major fields of investigations carried out by quite distinct communities of researchers: autonomous robots and mobile sensor networks. Robotic sensors are micro-robots capable of locomotion and sensing. Like the sensors in wireless sensor networks, they are myopic: their sensing range is limited. Unlike the sensors in wireless sensor networks, robotic sensors are silent: they have no direct communication capabilities. This means that synchronization, interaction, and communication of information among the robotic sensors can be achieved solely by means of their sensing capability, usually called vision. In this Chapter, we review the results of the investigations on the computability and complexity aspects of systems formed by these myopic and silent mobile sensors.

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Section: Mobile Robotic Sensorsmentioning

confidence: 99%

Computing by Mobile Robotic Sensors

Flocchini

Prencipe

Santoro

2010

Monographs in Theoretical Computer Science. An EATCS Series

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“…Because of the limited energy of sensor nodes, route optimization design not only considers the length of the data transmission path, but also considers saving energy and network energy balance and other issues. WSN route optimization not only concerned about the path length, are more concerned about saving energy and balance energy consumption of the whole network [6] [7].…”

Section: Introductionmentioning

confidence: 99%

Wireless Sensor Network Route Optimization Based on Improved Ant Colony-Genetic

Liu¹,

Cui²,

Zhao³

2015

Int. J. Onl. Eng.

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Abstract-The objective of this paper is focuses on route optimization, for a given wireless sensor network. We detail the significance of route optimization problem and the corresponding mathematical model. After analyzing the complex multi-objective optimization problem, Ant Colony Optimization (ACO) algorithm was introduced to search the best route. Inspired by Genetic Algorithm (GA), we embed two operations into ACO to refine it. First, every ant after achieving sink will be regarded as an individual such as that in GA. The crossover operation will be applied and then, the generated new ants will replace the weaker parents. Second, we designed a mutation operation for ants selecting next nodes to visit. Experimental results demonstrate that the proposed combination algorithm has significant enhancements than both GA and ACO. The lifetime of WSN can be extended and the coverage speed can be accelerated.

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“…We have extended this line of research by establishing formally the conditions ensuring that such energy-balance strategy is realistic in [34]. By establishing the formal link between the lifetime of the network and energy-balance mechanism, we provide a formal definition of optimal routing strategies in [34].…”

Section: Introduction Our Contribution and Related Workmentioning

confidence: 99%

“…By establishing the formal link between the lifetime of the network and energy-balance mechanism, we provide a formal definition of optimal routing strategies in [34]. Moreover, we provide a decentralized algorithm to compute the probabilities with minimal assumptions and we establish formally that energy-balance mechanisms are efficient.…”

Section: Introduction Our Contribution and Related Workmentioning

confidence: 99%

“…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. In [34], we propose and we validate numerically an inter-slice spreading mechanism to overcome the impact of these irregularities to the energy consumption. Our present work generalizes these results.…”

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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Energy optimal data propagation in wireless sensor networks

Cited by 97 publications

References 12 publications

Computing by Mobile Robotic Sensors

Computing by Mobile Robotic Sensors

Wireless Sensor Network Route Optimization Based on Improved Ant Colony-Genetic

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

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