Rendezvous points and routing path‐selection strategies for wireless sensor networks with mobile sink

Suh, Bongsue; Berber, Stevan

doi:10.1049/el.2015.2996

Cited by 24 publications

(15 citation statements)

References 6 publications

(16 reference statements)

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“…Two efficient data-forwarding strategies for wireless sensor networks with a mobile sink which visits rendezvous points (RPs) to gather data from sensor nodes are proposed in ariticle [12], which is based on WRP. With the first proposed strategy, selections of the RP nodes and the final routing paths are based on the latest information of the already selected RP nodes.…”

Section: Related Workmentioning

confidence: 99%

“…However, the above protocols in [11,12] is not suitable for the large scale sensor networks, as nodes number is larger, the complexity of RN selection optimization problem would be more difficult. Besides, in the problem of selecting RN, the WRP and proposed-II only consider small factors of distance between the alternative RN and RNs set, and the stored date number of alternative RN, but not the remaining energy and its neighbors number, which would be not comprehensive enough.…”

Section: Related Workmentioning

confidence: 99%

“…We develop a Rendezvous Node Selection and Routing Algorithm (RNSRA) to select a set of RNs and plan the sink moving tour, in which the RN can act as a store point for the mobile sink to visit. In order to search for optimal RNs, different from the above articles [11,12], 4 factors are considered in the fitness function for RN selection: the remaining energy of the alternative RN, its neighbors' number, stored delivery packet number, and its distance to other RNs. This RN selection method could balance energy consumption and avoid the energy hole problem.…”

Section: Related Workmentioning

confidence: 99%

“…How to reduce its moving distance so as to prolong lifetime is an important problem. A method proposed by several articles to address this challenge is to deploy rendezvous nodes (RN) for mobile sink to visit [10,11,12,13]. During its moving tour, the mobile sink would visit temporarily RNs to gather data [14,15].…”

Section: Introductionmentioning

confidence: 99%

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A Rendezvous Node Selection and Routing Algorithm for Mobile Wireless Sensor Network

2018

KSII TIIS

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Efficient rendezvous node selection and routing algorithm (RNSRA) for wireless sensor networks with mobile sink that visits rendezvous node to gather data from sensor nodes is proposed. In order to plan an optimal moving tour for mobile sink and avoid energy hole problem, we develop the RNSRA to find optimal rendezvous nodes (RN) for the mobile sink to visit. The RNSRA can select the set of RNs to act as store points for the mobile sink, and search for the optimal multi-hop path between source nodes and rendezvous node, so that the rendezvous node could gather information from sensor nodes periodically. Fitness function with several factors is calculated to find suitable RNs from sensor nodes, and the artificial bee colony optimization algorithm (ABC) is used to optimize the selection of optimal multi-hop path, in order to forward data to the nearest RN. Therefore the energy consumption of sensor nodes is minimized and balanced. Our method is validated by extensive simulations and illustrates the novel capability for maintaining the network robustness against sink moving problem, the results show that the RNSRA could reduce energy consumption by 6% and increase network lifetime by 5% as comparing with several existing algorithms.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Rendezvous Node Selection and Routing Algorithm for Mobile Wireless Sensor Network

2018

KSII TIIS

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“…Abo-Zahhad et al [10] proposed a new clustering protocol called mobile sink-based adaptive immune energy-efficient clustering protocol for solving the energy hole problem, which also improves the network lifetime and the stability period of the WSNs. Suh and Berber [11] proposed a new data-forwarding strategy for WSNs with a mobile sink that visits rendezvous points to gather data from sensor nodes. Selvi et al [12] proposed an energy-efficient routing algorithm for wireless sensor networks using fuzzy rules.…”

Section: Related Workmentioning

confidence: 99%

Virtual force-based intelligent clustering for energy-efficient routing in mobile wireless sensor networks

Munuswamy¹,

Saravanakumar²,

Ganapathy³

et al. 2018

Turk J Elec Eng & Comp Sci

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A mobile wireless sensor network (MWSN) consists of many sensor nodes, which can move from one position to another and gather data from the environment, and such nodes are coordinated with the support of a sink node. In recent years, the mobility behavior of sensor nodes present in wireless sensor networks is used to form effective clustering and to perform cluster-based routing. Virtual force is an important phenomenon in sensor nodes, which is used to model the mobility behavior. Production rules that use spatiotemporal constraints are able to make more accurate decisions on mobility speed, mobility area, and the required time. Routing in MWSNs under the mobility scenario will provide better performance if virtual force-based mobility modeling is used to form clusters. In this paper, an intelligent routing algorithm called virtual force-based intelligent clustering for energy-efficient routing in MWSNs has been proposed for effective and energy-efficient cluster-based routing of data packets collected by mobile sensor nodes in a MWSN. This algorithm uses attractive and repulsive forces for finding the cluster members. Moreover, spatiotemporal constraints are used in the form of rules for clustering, reclustering, and cluster head election and to perform routing through the cluster heads using intelligent rules. The main advantage of the proposed algorithm is that it increases the network lifetime and packet delivery ratio. Moreover, it reduces the delay and the energy consumption.

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A novel approach for particle swarm optimization‐based clustering with dual sink mobility in wireless sensor network

Kaur

Grewal

2020

Int J Communication

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SummaryThe proliferation in the sensing technology in wireless sensor network has left an everlasting impact to revolutionize every sector of human's lives. The limited battery of sensor nodes (SNs) has generated a tremendous challenge for the researchers to ameliorate the network's life span. To pacify this concern, in this paper, we have proposed a particle swarm optimization (PSO)‐based dual sink mobility (PSODSM) technique to reduce the energy expenditure of the SNs. PSODSM has the paramount focus on the cluster head (CH) selection based on integration of crucial factors: “ratio of remaining energy to the initial energy,” node degree, node centrality, separation factor between the SN and the sink, CH number, and energy consumption rate. As soon as the CHs are selected, two sinks placed opposite to each other are made to move towards the selected CHs for data collection. The most prominent fact is the movement of sinks which is done outside the periphery of the network to collect data rather than the reported conventional research works that employ sink mobility inside the network. Extensive simulations are performed to examine the empirical evaluation of PSODSM based on the benchmark of different performance metrics. The performance validation of PSODSM is done against the other meta‐heuristic algorithms, and findings show that the PSODSM outperforms the competitive algorithms and is also found to be scalable pertaining to real time implementation.

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Rendezvous points and routing path‐selection strategies for wireless sensor networks with mobile sink

Cited by 24 publications

References 6 publications

A Rendezvous Node Selection and Routing Algorithm for Mobile Wireless Sensor Network

A Rendezvous Node Selection and Routing Algorithm for Mobile Wireless Sensor Network

Virtual force-based intelligent clustering for energy-efficient routing in mobile wireless sensor networks

A novel approach for particle swarm optimization‐based clustering with dual sink mobility in wireless sensor network

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