Energy consumption and lifetime analysis in clustered multi-hop wireless sensor networks using the probabilistic cluster-head selection method

Choi, Jinchul; Lee, Chae-Woo

doi:10.1186/1687-1499-2011-156

Cited by 16 publications

(5 citation statements)

References 14 publications

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“…A probabilistic cluster energy model is proposed to estimate the energy consumption of multihop [44], [46] .wireless sensor networks. Each sensor node selects itself as a cluster head with a certain probability; it does not communicate any information with other nodes.…”

Section: Energy Consumption and Lifetime Analysis In Clustered Multi-...mentioning

confidence: 99%

Untitled

2024

EJCSIT

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Low-powered wirelessly connected devices create a system that is self-contained and called Wireless sensor network (WSN), this system has a number of practical applications in the modern world. Nodes in WSN are spread out spatially and have wireless communication with other nodes in the network, these nodes are primarily dedicated to sensing the vicinity and recording the physical properties of the area, including collect observations pertaining to humidity, noise, load, temperature Sensors and other factors at a central station. From there, the end user analyzes the information. After distribution, a cluster is formed between nodes, called a cluster. One of the nodes is selected as the cluster's head, which is used to migrate the data across the network. Clustering is essential in addressing many issues in WSN, particularly in regards to their lifetime, energy savings, and interoperability. Many approaches exist for clustering WSN, the difference between them is in the choice of CH, the number of clusters, the structure of clusters, the policy for data aggregation, the efficiency of communication between clusters, and the choice of communication between internal and external clusters. This article provides a comprehensive comparison of various methods of clustering and their advantages and disadvantages in WSNs. It also describes the principles of CH selection and how it works within each category. This helps the end user to choose the most suitable one protocol for their needs, and also will assist researchers in addressing the problems revealed in the process of clustering WSN.

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Section: Energy Consumption and Lifetime Analysis In Clustered Multi-...mentioning

confidence: 99%

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2024

EJCSIT

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“…The authors in [34] proposed a distributed clustering algorithm that builds clusters of different sizes in every step depending on the load of the network. The volume of data that is required to be sent to the BS is to be measured in every step.…”

Section: Distributed Clustering With Load Balancing (Dclb) Protocolmentioning

confidence: 99%

Clustering Algorithms of Wireless Sensor Networks: A Survey

Riaz¹

2018

IJWMT

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In the recent few years the research on Wireless Sensor Networks (WSN) and its variants have risen enormously. The researchers all across the globe are trying to develop a routing protocol that is energy efficient and provides adequate security level in data communication. One of the techniques the researchers use is Clustering of the sensor network. This technique inherently consumes less energy during data communication as the nodes have assigned a dedicated task to perform. A total of 35 clustering algorithms / protocols have been surveyed and comparison of these protocols based on the metrics like heterogeneity, clustering method, size of the cluster etc. have been presented. 42Clustering Algorithms of Wireless Sensor Networks: A Survey Clustering Algorithms' & Protocols For WSNThe WSN algorithms and protocols can be categorized in several different ways. In this paper we have categorized the clustering algorithms / protocols of WSN on the basis of probabilistic and non-probabilistic protocols and are described below: A. Probabilistic ProtocolsIn probability based clustered routing protocols each sensor node at the time of deployment is assigned with probability that how often that sensor node will likely to be selected as CH during the CH election process. The assigned probability of the senor node serves as the basic criterion for CH selection.The WSN algorithms and protocols are described below: Low Energy Adaptive Cluster Hierarchical (LEACH) ProtocolThe authors in [8] proposed a well-known cluster centered routing protocol known as Low Energy Adaptive Cluster Hierarchical (LEACH) routing protocol. In LEACH after every round the energy level of the current Cluster Head (CH) is checked and if its energy is drained and below the threshold value then based on the probabilistic theory new CH will be selected. The responsibilities of the CH are to be rotated or shared among the sensor nodes of the network. This rotation of CH responsibility stabilizes the consumption of energy of network nodes such that no node will be overwhelmed. Stable Election Protocol (SEP)Temporary-DEEC Clustering Algorithms of Wireless Sensor Networks: A Survey 45 The authors in [21] developed a protocol that is multilevel clustering protocol explicitly designed for heterogeneous WSNs. In this protocol, a procedure for the selection of CH is established on the ratio of remaining energy of the sensor node which is being evaluated for the role of CH with that of the average network energy. In this protocol the authors have initially considered two levels of energy and three levels i.e. the nodes distributed in the sensor network are of two / three energy levels or possess different amounts of energy. Later on, a generic solution for multi-level energy level solution was figured out. Each node of the network must have knowledge of energy levels of all the nodes present in sensor network. For CH select the average network energy is required that is inherently more energy consuming. This protocol forms the varying number of clusters after...

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“…An analytical study of the deployment of trafficaware relay nodes is presented in [10]. In [11], an energy model for clustered multi-hop WSNs is derived and optimized with respect to the cluster-head selection process, hereby using a probabilistic method. A cluster-head is a node which collects data from other nodes and transfers it to the sink.…”

Section: Related Studymentioning

confidence: 99%

Concept and framework of a self-regulating symbiotic network

David

Joseph

Poorter

et al. 2012

J Wireless Com Network

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The concept and framework of a self-regulating symbiotic network planner is introduced as a way to improve the use of available resources and infrastructure and the overall performance of co-located wireless networks. A framework for physical-layer optimization is proposed, based on an advanced and reliable network planner. Besides an optimal network planning including the adjustment of transmit powers, also a symbiotic optimization over different networks and network layers is implemented, a new concept in network cooperation based on shared and variable incentives. In this article, specifically, it is assumed that the co-located networks share the incentive of a lower global power consumption and the newly created symbiotic network is optimized accordingly. Feedback about the signal quality parameters allows optimizing path loss models, finetuning device transmit powers, coping with a changing propagation environment, and improving network reliability. The concept is applied to and experimentally validated with a real-life wireless test environment and a power consumption reduction of 79.5% is obtained, by consecutively enabling energy-saving features of the network planner: intelligent cognitive network planning, symbiotic network cooperation, and transmit power adjustments.

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Energy consumption and lifetime analysis in clustered multi-hop wireless sensor networks using the probabilistic cluster-head selection method

Cited by 16 publications

References 14 publications

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Clustering Algorithms of Wireless Sensor Networks: A Survey

Concept and framework of a self-regulating symbiotic network

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