Planning rendezvous using the Halin graph in wireless sensor networks

Chang, Ruay-Shiung; Wang, Shuo-Hung; Tsai, Shih-Yu; Yang, Wude

doi:10.1049/iet-wss.2011.0138

Cited by 5 publications

(7 citation statements)

References 26 publications

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“…In [16], to have better WSN energy saving, the authors plan rendezvous points for a mobile sink to travel by mapping sensors in a plane to a point on a Halin graph. They focus on balancing energy depletion to extend network lifetime with the use of mobile sinks and a proper travel plan.…”

Section: Related Workmentioning

confidence: 99%

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%

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

2018

KSII TIIS

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“…For improving network coverage for large heterogeneous network, mobile sink (MS) based routing (data collection) have attained much attention in recent times [34], [35], [36], and [37]. Here, MS will move through the WSN area to gather sensory information from SN.…”

Section: Introductionmentioning

confidence: 99%

“…As a result, mobile sink path is very restricted. In [36], [37] presented an unconstrained method where MS can move freely within region of WSN's. In [4], mapped SN to region on a Halin graph (HG) for choosing rendezvous point considering given to the residual energy availability status of the SNs.…”

Section: Introductionmentioning

confidence: 99%

Energy Efficient Mobile Sink Based Routing Model For Maximizing Lifetime of Wireless Sensor Network

Ghorpade¹,

Vijayakarthik.²

2019

GJCST

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Recently, wide adoption of wireless sensor networks (WSNs) has been seen for provision real-time and non-real-time application services. Provisioning these application service requires energy efficient routing design for WSN. Clustering technique is an efficient mechanism that plays a major role in minimizing energy dissipation of WSN. However, the existing model are designed considering minimizing energy consumption of sensor device considering homogenous. However, it incurs energy overhead among cluster head. Further, maximizing coverage time is not considered by exiting clustering approach considering heterogeneous network affecting lifetime performance. For overcoming issues of routing data packets in WSN, mobile sink has been used. Here, the sensor device will transmit packet in multihop fashion to the rendezvous and the mobile sink will move towards rendezvous points (RPs) to collect data, as opposed to all nodes. However, the exiting model designed so far incurs packet delay (latency) and energy (storage) overhead among sensor device. For overcoming research challenges, this work present energy efficient mobile sink based routing model for maximizing lifetime of wireless sensor network. Experiment are conducted to evaluate the performance of proposed model shows significant performance in terms of communication, routing overhead and lifetime of sensor network.

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“…In [7], to have better energy saving of WSN, the authors plan rendezvous points for a mobile sink to travel by mapping sensors in a plane to a point on a Halin graph. They focus on balancing energy depletion to extend network lifetime with the use of mobile sinks and a proper travel plan.…”

Section: Introduction and Related Workmentioning

confidence: 99%

A Rendezvous Node Selection Algorithm for Mobile Sink Path Planning in Wireless Sensor Networks

2016

Proceedings of 2016 the 6th International Workshop on Computer Science and Engineering

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Recent research shows that significant energy hole problem can be solved in wireless sensor network (WSN) by using mobile sink capable of carrying data. In order to plan an optimal moving tour for mobile sink without long distance travel, we develop the rendezvous node selection algorithm (RNSA) to find rendezvous nodes (RN) for the sink to visit. The RNSA can select the set of RNs to act as store points for the mobile sink, and several factors would be considered to find suitable RNs from sensor nodes, the other sensor nodes would forward data via multi hopping to the nearest RN, such that the energy consumption of sensor nodes is minimized and uniform to avoid the problem of energy holes while ensuring sensed data are collected on time. Our scheme is then validated through extensive simulations.

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Planning rendezvous using the Halin graph in wireless sensor networks

Cited by 5 publications

References 26 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

Energy Efficient Mobile Sink Based Routing Model For Maximizing Lifetime of Wireless Sensor Network

A Rendezvous Node Selection Algorithm for Mobile Sink Path Planning in Wireless Sensor Networks

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