A Particle Swarm Optimization Approach for Energy Efficient Clustering in Wireless Sensor Networks

Singh, Santar Pal; Sharma, S. C.

doi:10.5815/ijisa.2017.06.07

Cited by 19 publications

(10 citation statements)

References 27 publications

(23 reference statements)

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“…In the proposed method the following features were added: Drawback: Energy consumption is one of the most important concerns in the implementation of ad-hoc networks [16][17][18][19]. In this scheme, path selection based on the shortest path in view of shorter battery life is not conducted.…”

Section: Enhancement To Improve Performancementioning

confidence: 99%

An Energy Constraint Approach to Improve Lifetime and Reduce Routing Overhead in Heterogeneous MANET

2019

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Heterogeneous Mobile Ad-hoc Networks (H-MANET) contain different configuration nodes, each of which communicates over a wireless channel and is capable of movement. Heterogeneous wireless networking has attracted lot of interest from consumers in the previous few years for its applications in mobile and personal communications. One of the main constraints in MANET is the high probability of failure due to energy-exhausted nodes. So if the path selected for communication has low battery life then the path breaks prematurely and the re-discovery phase starts, which costs more overhead in the network. Therefore, there is unequal consumption of node energy, which must be prevented. The energy expenditure of the nodes should be balanced in order to minimize path breakage. This can be done by finding the communication path that is the most energy-efficient among alternative disjoint paths. This approach reduces path breakage and routing overhead caused by nodes with low battery life dying in the communication path, thus increasing the network's lifetime.

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Section: Enhancement To Improve Performancementioning

confidence: 99%

An Energy Constraint Approach to Improve Lifetime and Reduce Routing Overhead in Heterogeneous MANET

2019

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“…He also stated that, in order to meet the dynamic on-demand cluster head selection, artificial intelligence can be used. Santa Pal Singh et al [13], proposed a methodology based on Particle Swarm Optimization (PSO).The cluster head is selected by PSO on basis of its maximum power of nodes. The algorithm is a combination of proficient particle encoding method and fitness function.…”

Section: Literature Reviewmentioning

confidence: 99%

Pil-Leach Model for Increasing Energy Efficiency in Wireless Sensor Network

Ponnada¹

2018

ijarcs

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Wireless Sensor Networks (WSN) play a vital role in the modern arena. WSN is deployed in the various vital areas such as military operations, health care, surveillance, home application and environmental applications. WSN mainly works on battery power, whose capacity is limited. Energy efficiency is one of the main issues in wireless sensor networks. Various routing techniques are developed to achieve maximum reliability, network lifetime and scalability. Leach is one of the clustering convention used in wireless sensor networks. Even, after its existence of more than 17 years, Leach protocol grabs attention and interest of research community. Our research area is confined to power management. This paper proposes a technique called as Improved Lifetime -Leach with Particle Swarm Optimization (PIL-LEACH) to smoothen the associated information transmission inside the group and, to control the problems such as correlated data, cluster head selection and large distance transmission of the packet in Leach. Particle Swarm Optimization (PSO) algorithm selects the cluster head based on various parameters of sensor nodes such as residual energy, distance from base sink etc. This approach admits that we know the area of the sensor hubs. It uses the two-tier architecture of clusters heads which are far away from the sink in order to mitigate the energy losses.

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“…As in recent years, there is a tendency to create a large scale DCS, which are intended to serve a big number of users, the resource control in such systems require the development of new methods and tools. For the scalable DCS is important to apply the decentralized approach to resource control [3,4,5].…”

Section: Introductionmentioning

confidence: 99%

Distributed Computer System Resources Control Mechanism Based on Network-Centric Approach

Hu¹,

Mukhin²,

Kornaga³

et al. 2017

IJISA

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In this paper, we present the development of a decentralized mechanism for the resources control in a distributed computer system based on a network-centric approach. Intially, the network-centric approach was proposed for the military purposes, and now its principles are successfully introduced in the other applications of the complex systems control. Due to the features of control systems based on the network-centric approach, namely adding the horizontal links between components of the same level, adding the general knowledge control in the system, etc., there are new properties and characteristics. The concept of implementing of resource control module for a distributed computer system based on a network-centric approach is proposed in this study. We, basing on this concept, realized the resource control module and perform the analysis of its operation parameters in compare with resource control modules implemented on the hierarchical approach and on the decentralized approach with the creation of the communities of the computing resources. The experiments showed the advantages of the proposed mechanism for resources control in compare with the control mechanisms based on the hierarchical and decentralized approaches.One of the main components of resource control system (RCS) of DCS is a scheduler which coordinates the solution of the tasks that arrive for processing to the distributed system by placing them on available computing resources [7]. It is important to meet the requirements of the user and to avoid the idles for the computational resources [8]. In [7] there are identified the following key characteristics of the DCS scheduler: the run time of the task, DCS performance and the response time of the system.In recent years, there was devoted much attention to the study of decentralized resource control techniques for the distributed computer systems to improve the performance of the DCS in the context of its scalability and reliability [9]. In [9] are described the comparative analysis of the existing decentralized distributed computer systems and the mechanisms that are used for resource control. This study contains a comparative analysis of mechanisms of resource control of DCS in different contexts.Additionally, [10,11,12] presents more recent developments of DCS resources control systems, that are implemented on a decentralized basis.The development in [11] uses the exchanges of network messages between DCS compute nodes for the organization of distributed computing. The messages of several types come, each of which provides a specific functions of the algorithm for the resources allocation. This planning framework supports several heuristic algorithms and it also provides the load balancing for the DCS nodes.In [12] there is considered the DCS, which consists of heterogeneous computing elements (CE), which are interconnected by a computer network. In addition to CE, the system has passive nodes, the so-called "Bulletin boards", which are used to allocate users tasks and to collect some service in...

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A Particle Swarm Optimization Approach for Energy Efficient Clustering in Wireless Sensor Networks

Cited by 19 publications

References 27 publications

An Energy Constraint Approach to Improve Lifetime and Reduce Routing Overhead in Heterogeneous MANET

An Energy Constraint Approach to Improve Lifetime and Reduce Routing Overhead in Heterogeneous MANET

Pil-Leach Model for Increasing Energy Efficiency in Wireless Sensor Network

Distributed Computer System Resources Control Mechanism Based on Network-Centric Approach

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