Fuzzy Tree Clustering Algorithm with Mobile Data Collectors in Wireless Sensor Networks

Meddah, Meriem; Haddad, Rim; Ezzedine, Tahar

doi:10.1007/s11277-020-07701-8

Cited by 5 publications

(4 citation statements)

References 20 publications

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“…The difference between setup phase and steady state phase of clustering is that the former phase focuses on cluster formation and the latter phase focuses on data transfer. While some of the previous studies like References 23,24 work on steady phase, the others like References 25,26 work on setup phase. Similar to Reference 27, the authors of this article focus on both phases.…”

Section: Related Workmentioning

confidence: 99%

“…While some of the previous works like References 5,25,26,35 deal with single‐sink mobility problem, the others like References 9,50 and 67‐69 deal with multisink mobility problem.…”

Section: Related Workmentioning

confidence: 99%

“…Increasing the efficiency and scalability are the most important benefits of distributed algorithms. The ideas proposed in References 12,15,25,26,28,29,36,41,[54][55][56][57][58][59][60] are formed based on distributed clustering algorithm. Also, ideas proposed in References 13,14 are formed based on centralized clustering algorithm.…”

Section: Clustering Approachesmentioning

confidence: 99%

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An energy‐aware and lightweight routing algorithm using clustering and mobile sinks in wireless sensor networks

Adabi

Mohammadifar

Nezhad

2022

Trans Emerging Tel Tech

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A wireless sensor network (WSN) consists of a number of small sensors which are powered by low-cost irreplaceable batteries. Therefore, one of the main issues in WSN design is to prolong the battery life of the individual sensors. Clustering and utilization of mobile sinks in collaboration with base station (BS) are two common solutions to address energy consumption challenge. Based on these solutions, a new algorithm in name "Energy-aware Routing algorithm using Clustering and Mobile Sinks (ERCMS)" is proposed in this article. The distinguishing features of ERCMS are as follows: (1) a geometric pattern is applied to divide entire network area into some parts and make cluster in each part. This pattern adjusts the cluster size based on the distance from the sink. Thus, hotspot problem is expected to be reduced, (2) computational load is distributed over sensors, (3) length of messages are controlled and each message is defined in the format with minimum required information, (4) simple mathematics approaches those impose lightweight computations are adopted, and (5) accuracy of mobile sink dispatching procedure is improved in critical conditions of the network. The simulation results show that ERCMS outperforms DFCR, MDFCR, and TEO-MCRP in terms of consumed energy, delivery ratio, delay, routing overhead, and throughput.

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Section: Related Workmentioning

confidence: 99%

“…While some of the previous works like References 5,25,26,35 deal with single‐sink mobility problem, the others like References 9,50 and 67‐69 deal with multisink mobility problem.…”

Section: Related Workmentioning

confidence: 99%

Section: Clustering Approachesmentioning

confidence: 99%

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An energy‐aware and lightweight routing algorithm using clustering and mobile sinks in wireless sensor networks

Adabi

Mohammadifar

Nezhad

2022

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…In [41], the network is split into sub-clusters based on fuzzy logic, after constructing a Minimum Spanning Tree. Then, cluster heads are chosen based on the number of hops to the root of the tree, the density, the residual energy of nodes, the number of packets to forward, and the node's centrality.…”

Section: Related Workmentioning

confidence: 99%

IPDCA: Intelligent Proficient Data Collection Approach for IoT-Enabled Wireless Sensor Networks in Smart Environments

et al. 2021

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The Internet of Things (IoT) enables the interrelation of physical things and devices that can be accessed through the internet and it simply forms a single integrated network of various things. An IoT-facilitated smart city scenario spans several sectors, such as industrial applications, public transportation, smart grid, emergency services, health care, etc. In this paper, we propose an Intelligent Proficient Data Collection Approach (IPDCA) to deliver public data in a large-scale smart city set-up. IPDCA utilizes public vehicles as the mobile data collectors (D-collectors) that read (or collect) data from multiple Access Points (APs) and send them back to the central Base Station (BS). Moreover, IPDCA adopts a modified Bat algorithm for path finding of D-collectors, where we extend the Bat algorithm to solve our discrete optimization problem. Besides, for selecting D-collectors in smart city settings, we use a multi-objective fitness function that considers the count, travelled distance, and storage of D-collectors to ensure optimal use of resources. Efficiency of the proposed mechanism is proved through simulations.

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Review on energy conservation and congestion mechanism in mobile WSN: taxonomy, software programs, challenges, and future trends

2023

Wireless Netw

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Fuzzy Tree Clustering Algorithm with Mobile Data Collectors in Wireless Sensor Networks

Cited by 5 publications

References 20 publications

An energy‐aware and lightweight routing algorithm using clustering and mobile sinks in wireless sensor networks

An energy‐aware and lightweight routing algorithm using clustering and mobile sinks in wireless sensor networks

IPDCA: Intelligent Proficient Data Collection Approach for IoT-Enabled Wireless Sensor Networks in Smart Environments

Review on energy conservation and congestion mechanism in mobile WSN: taxonomy, software programs, challenges, and future trends

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