An Energy-Efficient Mobile Sink-Based Unequal Clustering Mechanism for WSNs

Gharaei, Niayesh; Bakar, Kamalrulnizam Abu; Hashim, Siti Zaiton Mohd; Pourasl, Ali Hosseingholi; Siraj, Mohammad; Darwish, Tasneem

doi:10.3390/s17081858

Cited by 27 publications

(18 citation statements)

References 40 publications

(52 reference statements)

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“…To investigate the performance of SMACP we designed WSNs using the NS2 simulator with varying number of sensor nodes, for example, 200 to 700 with aggregate of 60 mobile specialists to perform the tasks of data collection and aggregation to achieve the load balancing and energy efficiency in network. The SMACP performance is compared with MAPA [16] and CM2SV2 [17]. The network parameters presented in table 1 used to configure the WSNs.…”

Section: Simulation Resultsmentioning

confidence: 99%

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Secure Mobile Agents Based Clustering Protocol using Modified PSO Algorithm

Auti,

Verma,

Sarkar

2020

IJEAT

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As per the studies on Wireless Sensor Network (WSN), the major concern of WSN is network lifespan and Quality of Service (QoS) improvement as the sensor nodes are having limited processing and battery capabilities. The clustering based methods delivered improved performance compared to non-clustering methods, but cluster heads (CHs) suffered from the excessive load which leads more energy consumption of sensor nodes that becomes the CH in each interval. The mobile agent’s technology solves such problems. But using mobile agent’s leads problems of data security and unreliable communications in WSN. In this paper, we proposed novel mobile specialists based clustering protocol utilizing the adjusted particle swarm optimization (PSO) algorithm called Secure Mobile Agent based Clustering using modified PSO (SMACP). To optimize the clustering performance we design modified PSO based in CH selection and cluster formation performed efficiently. To secure data communications using the mobile agents, we applied the trust evaluation scheme to evaluate each mobile agents and sensors using parameters such as residual energy, distance, and packet forwarding probability. The simulation results computed for different WSNs in terms of energy efficiency, average throughput, packet delivery ratio (PDR), also, start to finish delay. The exhibition demonstrates that SMACP outperformed the previous methods effectively.

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Section: Simulation Resultsmentioning

confidence: 99%

“…In [17], author proposed mobile sink as the mobile specialist for the energy productivity execution change for WSN. They planned the round Movement of Mobile-Sink with Varied Velocity Algorithm (CM2SV2) to modify the energy use degree of cluster heads (CH).…”

Section: Related Workmentioning

confidence: 99%

Secure Mobile Agents Based Clustering Protocol using Modified PSO Algorithm

Auti,

Verma,

Sarkar

2020

IJEAT

View full text Add to dashboard Cite

show abstract

“…Although the lifetime of network is improved, the unbalanced load problem still exists. With the help of multiple mobile Sinks, Gharaei et al proposed a two-stage greedy algorithm to obtain the upper bound of an optimal cluster size interval [ 30 ]. Then, by designing the circular motion of the mobile sinks with varied velocity, the energy consumption of CHs in different coronas achieves balance.…”

Section: Related Workmentioning

confidence: 99%

A Type of Annulus-Based Energy Balanced Data Collection Method in Wireless Rechargeable Sensor Networks

Sha

Liu

Song

et al. 2018

Sensors

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With the increasing number of ubiquitous terminals and the continuous expansion of network scale, the problem of unbalanced energy consumption in sensor networks has become increasingly prominent in recent years. However, a node scheduling strategy or an energy consumption optimization algorithm may be not enough to meet the requirements of large-scale application. To address this problem a type of Annulus-based Energy Balanced Data Collection (AEBDC) method is proposed in this paper. The circular network is divided into several annular sectors of different sizes. Nodes in the same annulus-sector form a cluster. Based on this model, a multi-hop data forwarding strategy with the help of the candidate cluster headers is proposed to balance energy consumption during transmission and to avoid buffer overflow. Meanwhile, in each annulus, there is a Wireless Charging Vehicle (WCV) that is responsible for periodically recharging the cluster headers as well as the candidate cluster headers. By minimizing the recharging cost, the energy efficiency is enhanced. Simulation results show that AEBDC can not only alleviate the “energy hole problem” in sensor networks, but also effectively prolong the network lifetime.

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“…By simulating the process of evolution in the natural system, the GA can be considered as an adaptive heuristic search algorithm that is very suitable for providing a robust, near optimal solution for many real world NP-hard problems, and it is also widely applied for the performance optimization of WSNs, such as in network coverage control for WSNs [ 31 , 32 , 33 ], the scheduling problem [ 34 , 35 ], the optimal sensor deployment problem [ 36 , 37 ], and topology control [ 38 ]. This bio-inspired algorithm imitates the natural evolution of biological organisms to provide a robust, near-optimal solution for various problems.…”

Section: Optimization Algorithmsmentioning

confidence: 99%

Joint Power Charging and Routing in Wireless Rechargeable Sensor Networks

Jia

Chen

Deng

et al. 2017

Sensors

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The development of wireless power transfer (WPT) technology has inspired the transition from traditional battery-based wireless sensor networks (WSNs) towards wireless rechargeable sensor networks (WRSNs). While extensive efforts have been made to improve charging efficiency, little has been done for routing optimization. In this work, we present a joint optimization model to maximize both charging efficiency and routing structure. By analyzing the structure of the optimization model, we first decompose the problem and propose a heuristic algorithm to find the optimal charging efficiency for the predefined routing tree. Furthermore, by coding the many-to-one communication topology as an individual, we further propose to apply a genetic algorithm (GA) for the joint optimization of both routing and charging. The genetic operations, including tree-based recombination and mutation, are proposed to obtain a fast convergence. Our simulation results show that the heuristic algorithm reduces the number of resident locations and the total moving distance. We also show that our proposed algorithm achieves a higher charging efficiency compared with existing algorithms.

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An Energy-Efficient Mobile Sink-Based Unequal Clustering Mechanism for WSNs

Cited by 27 publications

References 40 publications

Secure Mobile Agents Based Clustering Protocol using Modified PSO Algorithm

Secure Mobile Agents Based Clustering Protocol using Modified PSO Algorithm

A Type of Annulus-Based Energy Balanced Data Collection Method in Wireless Rechargeable Sensor Networks

Joint Power Charging and Routing in Wireless Rechargeable Sensor Networks

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