Maximum Lifetime Scheduling in Wireless Sensor Networks

Dhawan, Akshaye

doi:10.5772/48575

Cited by 6 publications

(8 citation statements)

References 46 publications

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“…For maximizing the lifetime of sensor networks, many algorithms have been presented in recent years [7,[10][11][12][13][14][15][16][17][18]. Dhawan et al [10] proposed a mechanism to prolong the lifetime of the network by constructing the Lifetime dependency Graph (LG) to select a subset of sensors that can cover the target.…”

Section: Related Workmentioning

confidence: 99%

Energy-Efficient Algorithms for Path Coverage in Sensor Networks

Liu

Zhou

2023

Sensors

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Path coverage attracts many interests in some scenarios, such as object tracing in sensor networks. However, the problem of how to conserve the constrained energy of sensors is rarely considered in existing research. This paper studies two problems in the energy conservation of sensor networks that have not been addressed before. The first problem is called the least movement of nodes on path coverage. It first proves the problem as NP-hard, and then uses curve disjunction to separate each path into some discrete points, and ultimately moves nodes to new positions under some heuristic regulations. The utilized curve disjunction technique makes the proposed mechanism unrestricted by the linear path. The second problem is called the largest lifetime on path coverage. It first separates all nodes into independent partitions by utilizing the method of largest weighted bipartite matching, and then schedules these partitions to cover all paths in the network by turns. We eventually analyze the energy cost of the two proposed mechanisms, and evaluate the effects of some parameters on performance through extensive experiments, respectively.

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Section: Related Workmentioning

confidence: 99%

Energy-Efficient Algorithms for Path Coverage in Sensor Networks

Liu

Zhou

2023

Sensors

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“…In order to extend the lifetime of a sensor network while maintaining coverage, a minimal subset of the deployed sensors is kept active while the other sensors can sleep. Then, the problem is to determine how long to use a given subset of sensors and which subset is to be used next in a scheduling approach [4]. This minimal subset of sensors could be noted as cover according to the following definition.…”

Section: Definition 1 the Wsns Lifetimementioning

confidence: 99%

NDSC based methods for maximizing the lifespan of randomly deployed wireless sensor networks for infrastructures monitoring

Ahmed

Adjallah

Stock

et al. 2018

Computers & Industrial Engineering

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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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“…The non-cluster based protocols use adjusting sensing range and load balancing techniques. They include LBP [6,[7][8][9]], deterministic energy efficient protocol (DEEPS) [8,9], ALBPS [10,11], deterministic energy efficient protocol with adjustable sensing range (ADEEPS) protocol [10,11]. Other protocols such as hybrid energy efficient distributed (HEED) protocol [17] use both the approaches that have been used in cluster based and non-cluster based protocols.…”

Section: Related Workmentioning

confidence: 99%

“…To the best of our knowledge, no protocol from the noncluster-based class uses the heterogeneous WSN. In this paper, we propose a heterogeneous model for the WSNs and simulate the ALBP [10,11] protocol for estimating the lifetime of a WSN. From the simulation results, it is found that the lifetime of a WSN prolongs as compared to the ALBP protocol.…”

Section: Related Workmentioning

confidence: 99%

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3-Level Heterogeneity Model for Wireless Sensor Networks

Chand¹,

Singh²,

Kumar³

2013

IJCNIS

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-In this paper, we propose a network model with energy heterogeneity. This model is general enough in the sense that it can describe 1-level, 2-level, and 3-level heterogeneity. The proposed model is characterized by a parameter whose lower and upper bounds are determined. For 1-level heterogeneity, the value of parameter is zero and, for 2-level heterogeneity, its value is √. For 3-level of heterogeneity, the value of parameter varies between its lower bound and upper bound. The lower bound is determined from the energy levels of different node types, whereas the upper bound is given by √ . As value of parameter decreases from upper bound towards the lower bound, the network lifetime increases. Furthermore, as the level of heterogeneity increases, the network lifetime increases.

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Maximum Lifetime Scheduling in Wireless Sensor Networks

Cited by 6 publications

References 46 publications

Energy-Efficient Algorithms for Path Coverage in Sensor Networks

Energy-Efficient Algorithms for Path Coverage in Sensor Networks

NDSC based methods for maximizing the lifespan of randomly deployed wireless sensor networks for infrastructures monitoring

3-Level Heterogeneity Model for Wireless Sensor Networks

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