A Distributed Algorithm for Maximum Lifetime Routing in Sensor Networks with Mobile Sink

Gatzianas, Marios; Georgiadis, Leonidas

doi:10.1109/twc.2008.060727

Cited by 122 publications

(51 citation statements)

References 11 publications

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“…The assumption of delay-tolerant applications is similar to what we have made in this paper. A similar technique is proposed in [18], where information is routed to a mobile sink in a multihop fashion. A distributed algorithm is proposed for prolonging the network lifetime under energy constraints through casting it into a linear program, and solving it through a dual decomposition method.…”

Section: Related Work and Comparisonmentioning

confidence: 99%

An Energy-Balanced Heuristic for Mobile Sink Scheduling in Hybrid WSNs

Zhou¹,

Shu

et al. 2016

IEEE Trans. Ind. Inf.

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Abstract-Wireless sensor networks (WSNs) are integrated as a pillar of collaborative Internet of Things (IoT) technologies for the creation of pervasive smart environments. Generally, IoT end nodes (or WSN sensors) can be mobile or static. In this kind of hybrid WSNs, mobile sinks move to predetermined sink locations to gather data sensed by static sensors. Scheduling mobile sinks energyefficiently while prolonging the network lifetime is a challenge. To remedy this issue, we propose a three-phase energy-balanced heuristic. Specifically, the network region is first divided into grid cells with the same geo-graphical size. These grid cells are assigned to clusters through an algorithm inspired by the k-dimensional tree algorithm, such that the energy consumption of each clus-ter is similar when gathering data. These clusters are adjusted by (de)allocating grid cells contained in these clusters, while considering the energy consumption of sink movement. Consequently, the energy to be consumed in each cluster is approximately balanced considering the energy consumption of both data gathering and sink movement. Experimental evaluation shows that this technique can generate an optimal grid cell division within a limited time of iterations and prolong the network lifetime.

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Section: Related Work and Comparisonmentioning

confidence: 99%

An Energy-Balanced Heuristic for Mobile Sink Scheduling in Hybrid WSNs

Zhou¹,

Shu

et al. 2016

IEEE Trans. Ind. Inf.

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“…In the new converged WSN and MCN networks, the two protocol stacks are really converged where the data and signaling are shared between the network stacks [16]. Since the network architecture and air-interface are highly converged for WSN and MCN in the smart mobile gateway, the protocol and control signaling should also be tightly converged for a real convergence of WSN and MCN.…”

Section: System Architecture and Application Scenariomentioning

confidence: 99%

“…After a smart UE acting as mobile gateway and entering the coverage of WSN, it may cause the gateway reselection or even regrouping for sensor nodes [30]. In the conventional WSN, when the mobile UE gateway moves into the coverage area of the sensor nodes, they broadcast POLL packets to the sensor nodes, and provide the access for them [31][32][33]. However, when the serving gateway is leaving its responsible area, it will not tell the sensor nodes about its leaving.…”

Section: Access Gateway Selection/re-selectionmentioning

confidence: 99%

Smart Mobile Gateway: Technical Challenges for Converged Wireless Sensor Networks and Mobile Cellular Networks

Shan

Fang

Qiu³

et al. 2016

IJFGCN

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“…The overall network lifetime T = l∈L z l . To find the optimal network lifetime, we need to consider the routing of the traffic as well as the duration of stay by the sink at each stop [9], [2], [1], [7]. Let x (l) ij be the flow rate from node i to j while the sink is at stop l. LetN = N ∪ L. The lifetime maximization problem can be formulated as follows.…”

Section: B Mobile Sink Modelmentioning

confidence: 99%

“…Much work has been done during recent years to increase the lifetime of the WSN. Among them, in spite of the difficulties in realization, taking advantage of the mobility in the WSN has attracted much interests from researchers [1], [2], [3], [4], [5], [6], [7], [8], [9]. We can take the mobile sink as an example of mobility in the WSN.…”

Section: Introductionmentioning

confidence: 99%

Maximizing the Lifetime of Wireless Sensor Networks with Mobile Sink in Delay-Tolerant Applications

Yun

Xia

2010

IEEE Trans. on Mobile Comput.

263

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Abstract-This paper proposes a framework to maximize the lifetime the wireless sensor network (WSN) by using a mobile sink when the underlying applications tolerate delayed information delivery to the sink. Within a prescribed delay tolerance level, each node does not need to send the data immediately as they become available. Instead, the node can store the data temporarily and transmit them when the mobile sink is at the most favorable location for achieving the longest WSN lifetime. To find the best solution within the proposed framework, we formulate optimization problems that maximize the lifetime of the WSN subject to the delay bound constraints, node energy constraints and flow conservation constraints. We conduct extensive computational experiments on the optimization problems and find that the lifetime can be increased significantly as compared to not only the stationary sink model but also more traditional mobile sink models. We also show that the delay tolerance level does not affect the maximum lifetime of the WSN.

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A Distributed Algorithm for Maximum Lifetime Routing in Sensor Networks with Mobile Sink

Cited by 122 publications

References 11 publications

An Energy-Balanced Heuristic for Mobile Sink Scheduling in Hybrid WSNs

An Energy-Balanced Heuristic for Mobile Sink Scheduling in Hybrid WSNs

Smart Mobile Gateway: Technical Challenges for Converged Wireless Sensor Networks and Mobile Cellular Networks

Maximizing the Lifetime of Wireless Sensor Networks with Mobile Sink in Delay-Tolerant Applications

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