Distributed Low-Overhead Energy-Efficient Routing for Sensory Networks via Topology Management and Path Diversity

2005 ◽  
Author(s):  
A. Boulis ◽  
M. Srivastava
Keyword(s):  
Energy Efficient ◽  
Path Diversity ◽  
Energy Efficient Routing ◽  
Topology Management ◽  
Overhead Energy

Clustering Internet of Things: A Review

2017 ◽  
Vol 3 (2) ◽  
pp. 21
Author(s):  
Sahil Sholla ◽  
Sukhkirandeep Kaur ◽  
Gh Rasool Begh ◽  
Roohie Naaz Mir ◽  
M Ahsan Chishti
Keyword(s):  
Internet Of Things ◽  
Energy Efficient ◽  
Paradigm Shift ◽  
Clustering Algorithms ◽  
Cluster Head ◽  
Smart Devices ◽  
Communication Overhead ◽  
Energy Efficient Routing ◽  
Topology Management ◽  
And Topology

Internet of Things is a paradigm shift in networking that seeks to connect virtually all things on the planet. Given the constrained nature of smart devices, energy efficient routing would play a key role in successful deployment of such networks. Clustering algorithms organize nodes of a network into groups or clusters and a specific designated node, cluster head is responsible for its cluster. Clustering algorithms have been particularly suggested in the context of Wireless Sensor Networks (WSN) but their application may also address similar challenges in Internet of Things (IoT). Clustering would facilitate energy efficient routing and topology management by delegating large chunk of communication overhead to cluster head. This paper presents a review of various clustering algorithms, analyses routing characteristics of various IoT domains and suggests appropriate clustering algorithms for each domain.

Performance Evaluation of AFOD Protocol for Energy Efficient Routing

2011 ◽  
Author(s):  
B. Smitha Shekar ◽  
M. Sudhakar Pillai ◽  
G. Narendra Kumar
Keyword(s):  
Performance Evaluation ◽  
Energy Efficient ◽  
Energy Efficient Routing

An Energy Efficient Routing Approach to Enhance Coverage for Application Specific Wireless Sensor Networks using Genetic Algorithm

2019 ◽  
Vol 13 ◽  
Author(s):  
Amandeep Kaur Sohal ◽  
Ajay Kumar Sharma ◽  
Neetu Sood
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Transmission ◽  
Energy Efficient ◽  
Search Algorithm ◽  
Cluster Formation ◽  
Green Computing ◽  
Wireless Sensor ◽  
Energy Efficient Routing

Background: An information gathering is a typical and important task in agriculture monitoring and military surveillance. In these applications, minimization of energy consumption and maximization of network lifetime have prime importance for green computing. As wireless sensor networks comprise of a large number of sensors with limited battery power and deployed at remote geographical locations for monitoring physical events, therefore it is imperative to have minimum consumption of energy during network coverage. The WSNs help in accurate monitoring of remote environment by collecting data intelligently from the individual sensors. Objective: The paper is motivated from green computing aspect of wireless sensor network and an Energy-efficient Weight-based Coverage Enhancing protocol using Genetic Algorithm (WCEGA) is presented. The WCEGA is designed to achieve continuously monitoring of remote areas for a longer time with least power consumption. Method: The cluster-based algorithm consists two phases: cluster formation and data transmission. In cluster formation, selection of cluster heads and cluster members areas based on energy and coverage efficient parameters. The governing parameters are residual energy, overlapping degree, node density and neighbor’s degree. The data transmission between CHs and sink is based on well-known evolution search algorithm i.e. Genetic Algorithm. Conclusion: The results of WCEGA are compared with other established protocols and shows significant improvement of full coverage and lifetime approximately 40% and 45% respectively.

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