Location based clustering scheme considering node mobility in wireless sensor networks

Shiokawa, Shigeki; Chen, Daqi

doi:10.1109/icufn.2014.6876770

Cited by 6 publications

(4 citation statements)

References 12 publications

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“…Kaur et al. [81] suggested to pick the cluster head through not only of the remaining potential, as well as of an approximate cluster time [82]. Rajesh et al.…”

Section: Overview Of MCC and Wsnsmentioning

confidence: 99%

“…To enhance the processing of information acquired in theWSN structured in clusters by means of a leach method, authors suggested two network topologies with adjustable paused times to allow the detection of cluster heads and information gathering for an optimised Mobile Sink route and a query of tabu and model ripple protocols was utilised [80]. Kaur et al [81] suggested to pick the cluster head through not only of the remaining potential, as well as of an approximate cluster time [82]. Rajesh et al [83] suggested optimising clusters via versatility and energy-savvy clustering techniques for power conservation, balancing of charging and lifespan development of the handheld sensor.…”

Section: Mobility Management In MCC and Wsnsmentioning

confidence: 99%

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Mobile Cloud Computing and Wireless Sensor Networks: A review, integration architecture, and future directions

et al. 2021

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In today's fast advancing world, sensors are used in various applications to provide complete data about different objects present around us. The sensor data when integrated with Mobile Cloud Computing (MCC) is used for further computation to provide useful results advanced warning, forecasting, planning, and plethora of other applications in this uncertain world. Few works have been proposed where sensor nodes are integrated with Wireless Sensor Networks (WSNs) which give a new direction in modern research for developing new technologies which help the users for fast access of sensory data over mobile devices. Herein, a systematic literature review of both MCC and WSNs are conducted and subsequently assimilated them via an architecture which is efficient and achievable within short time-span for a variety of applications. The MCC applications are reviewed from two main perspectives that are energy and information management. The communication aspect in MCC and WSNs has been discussed and the need for integration between the two has been justified in this work. The work done on mobility management in MCC and WSNs is reviewed. Also, the challenges in MCC-WSNs integration along with the comprehensive analysis and findings of the review are identified. Finally, the conclusion and specific future direction of research in this area are provided. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…Kaur et al. [81] suggested to pick the cluster head through not only of the remaining potential, as well as of an approximate cluster time [82]. Rajesh et al.…”

Section: Overview Of MCC and Wsnsmentioning

confidence: 99%

Section: Mobility Management In MCC and Wsnsmentioning

confidence: 99%

Mobile Cloud Computing and Wireless Sensor Networks: A review, integration architecture, and future directions

et al. 2021

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“…Cluster heads were selected in accordance with the residual energy, thus improving the life cycle of the network [24]. In the clustering scheme proposed by Shiokawa et al, the residual energy of the node and the time at which the node was expected to be the cluster head were considered during cluster head node selection, thus improving transmission efficiency [25]. To improve the efficiency of Quality-of-Service (QoS) aware routing, Spachos et al proposed an an angle based QoS and energy aware dynamic routing scheme designed for WMSNs, which optimized the selection of the forwarding candidate set and extended the network lifetime by using the inclination angle and the transmission distance between nodes [26].…”

Section: Related Workmentioning

confidence: 99%

A Distributed Image Compression Scheme for Energy Harvesting Wireless Multimedia Sensor Networks

Han

Zhang

et al. 2020

Sensors

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As an emerging technology, edge computing will enable traditional sensor networks to be effective and motivate a series of new applications. Meanwhile, limited battery power directly affects the performance and survival time of sensor networks. As an extension application for traditional sensor networks, the energy consumption of Wireless Multimedia Sensor Networks (WMSNs) is more prominent. For the image compression and transmission in WMSNs, consider using solar energy as the replenishment of node energy; a distributed image compression scheme based on solar energy harvesting is proposed. Two level clustering management is adopted. The camera node-normal node cluster enables camera nodes to gather and send collected raw images to the corresponding normal nodes for compression, and the normal node cluster enables the normal nodes to send the compressed images to the corresponding cluster head node. The re-clustering and dynamic adjustment methods for normal nodes are proposed to adjust adaptively the operation mode in the working chain. Simulation results show that the proposed distributed image compression scheme can effectively balance the energy consumption of the network. Compared with the existing image transmission schemes, the proposed scheme can transmit more and higher quality images and ensure the survival of the network.

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“…The locations of the moving objects are very closing for the locations of the moving objects have the geographic continuity. Therefore, the node can automatically delete the original location data through the Gossip property without costing the extra communication cost [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Based on the Forwarding Free Riding's Design and Analysis of the Location Management Method in Wireless Sensor Networks

Chen¹,

Li²,

Zeng³

2015

TOAUTOCJ

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The paper designs a forwarding Free-Riding-based location management scheme for wireless sensor networks, combining the features of the multi-points routing and the gossip-based broadcast to design the mobile data transmission methods of the objects so that the communication cost can be reduced. The mathematical model of the random Petri network is developed to analyze the behavior of the location management scheme in the WSN so that the method becomes more sophisticated. The experiments show that the forwarding Free-Riding-based location management scheme can reduce the communication cost of the WSN. © Chen et al.; Licensee Bentham Open.This is an open access articles licensed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International Public License (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/legalcode), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided that the work is properly cited.

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Location based clustering scheme considering node mobility in wireless sensor networks

Cited by 6 publications

References 12 publications

Mobile Cloud Computing and Wireless Sensor Networks: A review, integration architecture, and future directions

Mobile Cloud Computing and Wireless Sensor Networks: A review, integration architecture, and future directions

A Distributed Image Compression Scheme for Energy Harvesting Wireless Multimedia Sensor Networks

Based on the Forwarding Free Riding's Design and Analysis of the Location Management Method in Wireless Sensor Networks

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