ViBES: virtual backbone for energy saving in wireless sensor networks

Basagni, Stefano; Elia, Mimmo; Ghosh, Rabindranath

doi:10.1109/milcom.2004.1495121

Cited by 15 publications

(19 citation statements)

References 12 publications

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“…Constraint (4) induces a unit of flow from the origin to some node α ∈ S, while constraint (5) causes the destination to absorb a unit of flow coming from some node k ∈ S. Constraint (6) forces flow conservation at all sites k ∈ S, thus ensuring the generation of a route. Constraint (7) ensures that the sites k ∈ S on the generated route are sites at which the sink sojourns (k|y k = 1). To elaborate, if y k in constraint (7) equals 1, then the sink sojourns at site k, and therefore there must be one and only one arc on the sink's movement route reaching site k. On the other hand, if y k equals 0, then there will not be any incoming arc to that site.…”

Section: Milp Formulationmentioning

confidence: 99%

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Controlled sink mobility for prolonging wireless sensor networks lifetime

et al. 2007

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This paper demonstrates the advantages of using controlled mobility in wireless sensor networks (WSNs) for increasing their lifetime, i.e., the period of time the network is able to provide its intended functionalities. More specifically, for WSNs that comprise a large number of statically placed sensor nodes transmitting data to a collection point (the sink), we show that by controlling the sink movements we can obtain remarkable lifetime improvements. In order to determine sink movements, we first define a Mixed Integer Linear Programming (MILP) analytical model whose solution determines those sink routes that maximize network lifetime. Our contribution expands further by defining the first heuristics for controlled sink movements that are fully distributed and localized. Our Greedy Maximum Residual Energy (GMRE) heuristic moves the sink from its current location to a new site as if drawn toward the area where nodes have the highest residual energy. We also introduce a simple distributed mobility scheme (Random Movement or RM) according to which the sink moves uncontrolled and randomly throughout the network. The different mobility schemes are compared through extensive ns2-based simulations in networks with different nodes deployment, data routing protocols, and constraints on the sink movements. In all considered scenarios, we observe that moving the sink always increases network lifetime. In particular, our experiments show that controlling the mobility of the sink leads to remarkable improvements, which are as high as sixfold compared to having the sink statically (and optimally) placed, and as high as twofold compared to uncontrolled mobility

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Section: Milp Formulationmentioning

confidence: 99%

“…Sink sites are arranged into a 4 × 4, 6 × 6, 8 × 8 grid. Data are delivered to the sink according to the routing protocol presented in [7]. The route construction process is sink initiated.…”

Section: Simulation Scenarios and Parametersmentioning

confidence: 99%

Controlled sink mobility for prolonging wireless sensor networks lifetime

et al. 2007

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“…The main drawback of these solutions is the usually large overhead induced by the transmission of multiple copies of a single packet. Other solutions consider hop count (HC) routing [2,7,[30][31][32][33], where the geographical information is substituted by an integer number representing the number of transmissions needed to reach the sink on the shortest path. In [2] the authors present directed diffusion, where the sink queries sensor nodes by disseminating an interest, i.e., a list of attribute-value pairs for the desired data.…”

Section: Related Workmentioning

confidence: 99%

“…Also, throughout the paper and without loss of generality we consider normalized costs in [0, 1]. For every node i ∈ N we define its hop count (HC(i)) as the minimum number of transmissions needed to get to the sink [2,7,[30][31][32][33]. The interested reader is referred to the above references for more details on how HC fields can be created and maintained.…”

Section: Network Modelmentioning

confidence: 99%

Statistically assisted routing algorithms (SARA) for hop count based forwarding in wireless sensor networks

2006

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The main goal of this paper is to provide routing-table-free online algorithms for wireless sensor networks (WSNs) to select cost (e.g., node residual energies) and delay efficient paths. As basic information to drive the routing process, both node costs and hop count distances are considered. Particular emphasis is given to greedy routing schemes, due to their suitability for resource constrained and highly dynamic networks. For what concerns greedy forwarding, we present the Statistically Assisted Routing Algorithm (SARA), where forwarding decisions are driven by statistical information on the costs of the nodes within coverage and in the second order neighborhood. By analysis, we prove that an optimal online policy exists, we derive its form and we exploit it as the core of SARA. Besides greedy techniques, sub-optimal algorithms where node costs can be partially propagated through the network are also presented. These techniques are based on real time learning LRTA algorithms which, through an initial exploratory phase, converge to quasi globally optimal paths. All the proposed schemes are then compared by simulation against globally optimal solutions, discussing the involved trade-offs and possible performance gains. The results show that the exploitation of second order cost information in SARA substantially increases the goodness of the selected paths with respect to fully localized greedy routing. Finally, the path quality can be further increased by LRTA schemes, whose convergence can be considerably enhanced by properly setting real time search parameters. However, these solutions fail in highly dynamic scenarios as they are unable to adapt the search process to time varying costs

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“…Depending on the application scenario, these backbone nodes can be wired or wireless [4]- [7] with different routing/dissemination protocols [8]- [10]. While backbone-assisted routing can significantly improve end-toend transmission reliability, adding resourceful gateways to a WSN is a costly proposition.…”

Section: Introductionmentioning

confidence: 99%

On the reliability of backbone-assisted end-to-end transmissions in WSNs

Tufail

Khayam

Ali

et al. 2009

2009 First International Conference on Ubiquitous and Future Networks

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Many anticipated deployment scenarios, in particular military, healthcare, and disaster-recovery applications, of Wireless Sensor Networks (WSNs) require reliable source to sink communication. Since transmission range of sensors is quite limited, to achieve higher end-to-end transmission reliability, WSNs generally employ intermediate backbone links (wired or wireless) that can deliver packets at larger distances. In this paper, we evaluate the reliability of backbone-assisted routing and dissemination in WSNs. In particular, we use reliability theory to investigate two important problems: a) if sensor node to backbone/gateway node ratio is fixed in a unit area, what is the maximum achievable reliability? b) How many wired hops or gateway nodes are required to achieve a given reliability? Finally we analyze the cost and benefit incurred by adding gateway nodes to a backbone-assisted WSN and observe that after a certain threshold adding more backbone nodes to the WSN provides negligible improvement in the overall end-to-end reliability.

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ViBES: virtual backbone for energy saving in wireless sensor networks

Cited by 15 publications

References 12 publications

Controlled sink mobility for prolonging wireless sensor networks lifetime

Controlled sink mobility for prolonging wireless sensor networks lifetime

Statistically assisted routing algorithms (SARA) for hop count based forwarding in wireless sensor networks

On the reliability of backbone-assisted end-to-end transmissions in WSNs

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