scholarly journals ENERGY EFFICIENT ROUTING IN CLUSTERED IOT WIRELESS SENSORS NETWORKS FOR QOS ENHANCEMENTS

2019 ◽  
Vol 01 (01) ◽  
pp. 1-11 ◽  
Author(s):  
Sathish P

The wireless sensor network that are randomly distributed with ability to communicate and to be communicated wirelessly appears to be vital part in the Internetwork of things to enable an autonomous communication between the visible commodities available in the tangible world. The process of the connection establishment between the WSNs and IOT for the purpose of information transmission is significant as it has to be reliable overcoming the challenges entitled in the wireless sensor networks. So the paper proposes an efficient clustering of WSN with a hierarchical proactive routing to have a transmission that affords within the limited battery availability and extended life of the network to have an improvised successful transmission rate, and diminished delay. The performance evaluation of the proposed system is conducted and compared with the previous methods to prove the energy efficiency and the QOS enhancements in terms of transmission rate and delay.

Author(s):  
Karuna Babber

Background: The advent of wireless sensor networks makes it possible to track the events even in the remotest areas that too without human intervention. But severe resource constraints, generally energy of sensor nodes push researchers worldwide to develop energy efficient protocols in order to accomplish the application objectives of these networks. Objective: However, till date there is no energy efficient routing protocol which provides uniformity with maximum resource utilization for WSNs. Methods: In this paper, a Uniform Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks (UCAEE) has been proposed. UCAEE is a base station controlled algorithm where entire sensing area is partitioned into uniform clusters. The motive of the algorithm is to split the sensing area into uniform clusters and to select cluster heads and gate-way nodes within each cluster so that the network energy can be balanced in a best possible way. Conclusion: UCAEE achieves minimum energy consumption during data transmission and reception. Results: Simulation results indicate that proposed UCAEE algorithm conserves more energy than its contemporary clustering algorithms like LEACH, PEGASIS and SECA and promises better network lifetime of wireless sensor networks.


Author(s):  
Shu Han ◽  
Xiao-ming Liu ◽  
Hong-yu Huang ◽  
Fei Wang ◽  
Yuan-hong Zhong

AbstractAs one of the basic supporting technologies of 5G system, wireless sensor networks technology is facing a new challenge to improve its transmission energy efficiency. This paper considers combining simultaneous wireless information and power transfer (SWIPT) technique and routing technique, and applying them to multi-hop clustered wireless sensor networks (MCWSN), where each node can decode information and harvest energy from a received radio-frequency signal. And the relay nodes in MCWSN can utilize the harvest energy to forward data to their next hop nodes according to the routing scheme. First, we formulate an energy-efficient routing problem of MCWSN with SWIPT. Then, a heuristic energy efficient cooperative SWIPT routing algorithm (EECSR) is presented to find a transmission path with the maximum energy efficiency. Specifically, in EECSR, the resource allocation problem in each hop of the path is transformed to some equivalent convex optimization problems, which are resolved via dual decomposition. Moreover, a distributed routing protocol based on EECSR is proposed. As far as we know, this is the first solution that considers energy efficiency optimization based on routing and SWIPT in MCWSN. Simulation results show that our EECSR algorithm has high energy efficiency and good robustness. And our distributed routing protocol has better real-time performance than traditional protocols.


Author(s):  
A. Radhika ◽  
D. Haritha

Wireless Sensor Networks, have witnessed significant amount of improvement in research across various areas like Routing, Security, Localization, Deployment and above all Energy Efficiency. Congestion is a problem of  importance in resource constrained Wireless Sensor Networks, especially for large networks, where the traffic loads exceed the available capacity of the resources . Sensor nodes are prone to failure and the misbehaviour of these faulty nodes creates further congestion. The resulting effect is a degradation in network performance, additional computation and increased energy consumption, which in turn decreases network lifetime. Hence, the data packet routing algorithm should consider congestion as one of the parameters, in addition to the role of the faulty nodes and not merely energy efficient protocols .Nowadays, the main central point of attraction is the concept of Swarm Intelligence based techniques integration in WSN.  Swarm Intelligence based Computational Swarm Intelligence Techniques have improvised WSN in terms of efficiency, Performance, robustness and scalability. The main objective of this research paper is to propose congestion aware , energy efficient, routing approach that utilizes Ant Colony Optimization, in which faulty nodes are isolated by means of the concept of trust further we compare the performance of various existing routing protocols like AODV, DSDV and DSR routing protocols, ACO Based Routing Protocol  with Trust Based Congestion aware ACO Based Routing in terms of End to End Delay, Packet Delivery Rate, Routing Overhead, Throughput and Energy Efficiency. Simulation based results and data analysis shows that overall TBC-ACO is 150% more efficient in terms of overall performance as compared to other existing routing protocols for Wireless Sensor Networks.


Author(s):  
Amandeep Kaur Sohal ◽  
Ajay Kumar Sharma ◽  
Neetu Sood

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.


Sign in / Sign up

Export Citation Format

Share Document