New optimal solution to disjoint set
            <i>K</i>
            -coverage for lifetime extension in wireless sensor networks

Ashouri, Mohammadreza; Zali, Zeinab; Mousavi, Seyed Rasoul; Hashemi, Mahnaz

doi:10.1049/iet-wss.2011.0085

Cited by 29 publications

(16 citation statements)

References 15 publications

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“…We complete the proof by showing that connected hypergraphs of a particular size must have a 3-separated set of size k. From (10), the probability that the size of a saved component is at most this size is greater than 1/2. …”

Section: Lemma C3mentioning

confidence: 97%

“…In [7], the number of variables and constraints in the IP formulation of [6] was reduced, but the algorithm proposed was still heuristic. Several other heuristic algorithms without provable guarantees have been proposed in literature to solve the MLCP through the DSCP [8]- [10]. Quite recently, a √ n-approximation algorithm for the DSCP was proposed in [11] to solve the MLCP, where n is the number of targets to be monitored.…”

Section: Introductionmentioning

confidence: 99%

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Optimally Approximating the Coverage Lifetime of Wireless Sensor Networks

Pananjady

Bagaria

Vaze

2017

IEEE/ACM Trans. Networking

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Abstract-We consider the problem of maximizing the lifetime of coverage (MLCP) of targets in a wireless sensor network with battery-limited sensors. We first show that the MLCP cannot be approximated within a factor less than ln n by any polynomial time algorithm, where n is the number of targets. This provides closure to the long-standing open problem of showing optimality of previously known ln n approximation algorithms. We also derive a new ln n approximation to the MLCP by showing a ln n approximation to the maximum disjoint set cover problem (DSCP), which has many advantages over previous MLCP algorithms, including an easy extension to the k-coverage problem. We then present an improvement (in certain cases) to the ln n algorithm in terms of a newly defined quantity "expansiveness" of the network. For the special one-dimensional case, where each sensor can monitor a contiguous region of possibly different lengths, we show that the MLCP solution is equal to the DSCP solution, and can be found in polynomial time. Finally, for the special two-dimensional case, where each sensor can monitor a circular area with a given radius around itself, we combine existing results to derive a 1+ǫ approximation algorithm for solving MLCP for any ǫ > 0.

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Section: Lemma C3mentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Optimally Approximating the Coverage Lifetime of Wireless Sensor Networks

Pananjady

Bagaria

Vaze

2017

IEEE/ACM Trans. Networking

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“…One is how to judge the nature of the node according to network condition, node type and position [9], namely whether the node is a key node. The other question is how to adjust node, if the node is an ordinary node and when two or more ordinary nodes share the same electric quantity, which can prolong network lifetime [10][11][12] according to network redundancy while ensuring the quality of network coverage and saving energy.…”

Section: Network Coverage Strategymentioning

confidence: 99%

A Coverage Algorithm based on Key Node Scheduling

Zhu¹,

Fan²,

Wu³

et al. 2015

Int. J. Onl. Eng.

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Abstract-Network coverage rate is a key standard of measuring the quality of network coverage. This thesis aims at solving the differences between node energy and task, which causes coverage holes and blind spots of Wireless Sensor Network, and proposes a coverage algorithm, based on key node scheduling, divides node subsets, and adjusts the states of individual nodes according to node energy and coverage rate. This algorithm ensures network connectivity while reducing coverage holes and redundancy. Simulation results show that, the proposed algorithm can effectively reduce failure nodes, energy consumption, improve network coverage rate, and demonstrates network convergence and stability.

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“…WSN deploys sensors to acquire information and performs information fusion by embedded computing. For data transmission between the nodes, multi-hop technique and distributed information processing are usually used [3]. WSN has the advantages of low energy consumption, low cost, easy deployment, management and maintenance and flexible communications.…”

Section: Introductionmentioning

confidence: 99%

Coverage strategy for heterogeneous nodes in wireless sensor network based on temporal variability of farmland

Zhu

2017

Teh. vjesn.

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Strategija pokrivenosti za heterogene čvorove u bežičnoj mreži senzora na temelju vremenske promjenljivosti poljoprivrednog zemljišta COVERAGE STRATEGY FOR HETEROGENEOUS NODES IN WIRELESS SENSOR NETWORK BASED ON TEMPORAL VARIABILITY OF FARMLAND Huarui Wu, Li ZhuOriginal scientific paper Given temporal variability of farmland, the coverage rate of wireless sensor network (WSN) is usually low. There may arise the problems of blind spot area and congestion of hot spots. We propose a coverage strategy for heterogeneous nodes in WSN based on temporal variability of farmland, which predicts the key nodes using key node prediction model according to temporal variability of farmland environment. Through introduction of renewable energy nodes, the positions of heterogeneous nodes in the network can be determined. The task is re-allocated to the heterogeneous nodes depending on the residual energy of nodes, and the state of nodes in the network is adjusted dynamically. Simulation shows that CSHN can effectively reduce the node death rate and network energy consumption, while prolonging the survival of network and equalizing coverage and network energy consumption. Keywords: coverage rate; heterogeneous node; network energy consumption; temporal variability of farmland; Wireless Sensor Network (WSN) Strategija pokrivenosti za heterogene čvorove u bežičnoj mreži senzora na temelju vremenske promjenljivosti poljoprivrednog zemljištaIzvorni znanstveni članak Ako se razmotre različiti vremenski uvjeti na poljoprivrednom zemljištu, stopa pokrivenosti bežične mreže senzora (WSN -Wireless Sensor Network) obično je mala. Mogu se pojaviti problemi slijepih točaka i prenatrpanosti vrućim točkama. Predlažemo strategiju pokrivenosti za heterogene čvorove u WSN na temelju vremenskih promjena koje utječu na obradivost, a koja predviđa ključne čvorove primjenom modela predviđanja ključnog čvora u skladu s vremenskim promjenama na imanju. Uvođenjem obnovljivih čvorova energije, mogu se odrediti položaji heterogenih čvorova u mreži. Zadatak se ponovo prebacuje na heterogene čvorove ovisno o zaostaloj energiji čvorova te se stanje čvorova u mreži dinamički podešava. Simulacija pokazuje da CSHN može učinkovito smanjiti stopu propadanja čvora i potrošnju energije mreže i tako produžiti opstojnost mreže te ujednačiti pokrivenost i potrošnju energije mreže.Ključne riječi: bežična mreža senzora (WSN); heterogeni čvor; potrošnja energije mreže; stopa pokrivenosti; vremenska promjenljivost poljoprivrednog zemljišta

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New optimal solution to disjoint set K -coverage for lifetime extension in wireless sensor networks

Cited by 29 publications

References 15 publications

Optimally Approximating the Coverage Lifetime of Wireless Sensor Networks

Optimally Approximating the Coverage Lifetime of Wireless Sensor Networks

A Coverage Algorithm based on Key Node Scheduling

Coverage strategy for heterogeneous nodes in wireless sensor network based on temporal variability of farmland

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