scholarly journals Energy-Efficient Routing Using Fuzzy Neural Network in Wireless Sensor Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Rajesh Kumar Varun ◽  
Rakesh C. Gangwar ◽  
Omprakash Kaiwartya ◽  
Geetika Aggarwal
Keyword(s):  
Neural Network ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Fuzzy Neural Network ◽  
Residual Energy ◽  
Wireless Sensor ◽  
Energy Efficient Routing ◽  
Fuzzy Neural

In wireless sensor networks, energy is a precious resource that should be utilized wisely to improve its life. Uneven distribution of load over sensor devices is also the reason for the depletion of energy that can cause interruptions in network operations as well. For the next generation’s ubiquitous sensor networks, a single artificial intelligence methodology is not able to resolve the issue of energy and load. Therefore, this paper proposes an energy-efficient routing using a fuzzy neural network (ERFN) to minimize the energy consumption while fairly equalizing energy consumption among sensors thus as to prolong the lifetime of the WSN. The algorithm utilizes fuzzy logic and neural network concepts for the intelligent selection of cluster head (CH) that will precisely consume equal energy of the sensors. In this work, fuzzy rules, sets, and membership functions are developed to make decisions regarding next-hop selection based on the total residual energy, link quality, and forward progress towards the sink. The developed algorithm ERFN proofs its efficiency as compared to the state-of-the-art algorithms concerning the number of alive nodes, percentage of dead nodes, average energy decay, and standard deviation of residual energy.

Intelligent Analogy on Wireless Communication Link Performance of Industry Wireless Sensor Networks

2011 ◽  
Vol 317-319 ◽  
pp. 366-369
Author(s):  
Guang Zhu Chen ◽  
Cheng Ming Luo
Keyword(s):  
Neural Network ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Fuzzy Neural Network ◽  
Environmental Parameters ◽  
Wireless Sensor ◽  
Neural Network Modeling ◽  
Communication Link ◽  
Key Factor ◽  
Fuzzy Neural

The received signal strength indication (RSSI) is the key factor in the communication link for industry wireless sensor networks, while it is very difficult to model the value of RSSI to the distance of two communication nodes. This paper presented a fuzzy neural network modeling method to solve the shortcoming of the theoretical modeling. After the value of RSSI and the distance value of two communication nodes are fuzzed by Gaussian membership function, a fuzzy controlling rule is also presented, and then the output value of fuzzy neural network, namely the error distance of two communication nodes can be attained. Finally, simulation results show that without correcting the environmental parameters, the estimated error value of the distance of two communication nodes through RSSI in fuzzy neural network model is less than in quadratic fit method. So, the method presented by this paper can provide precise data support for wireless sensor networks for industry environment.

scholarly journals Energy-efficient genetic algorithm variants of PEGASIS for 3D Wireless Sensor Networks

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aaqil Somauroo ◽  
Vandana Bassoo
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Residual Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Routing ◽  
Delay Performance

Due to its boundless potential applications, Wireless Sensor Networks have been subject to much research in the last two decades. WSNs are often deployed in remote environments making replacement of batteries not feasible. Low energy consumption being of prime requisite led to the development of energy-efficient routing protocols. The proposed routing algorithms seek to prolong the lifetime of sensor nodes in the relatively unexplored area of 3D WSNs. The schemes use chain-based routing technique PEGASIS as basis and employ genetic algorithm to build the chain instead of the greedy algorithm. Proposed schemes will incorporate an energy and distance aware CH selection technique to improve load balancing. Clustering of the network is also implemented to reduce number of nodes in a chain and hence reduce delay. Simulation of our proposed protocols is carried out for homogeneous networks considering separately cases for a static base-station inside and outside the network. Results indicate considerable improvement in lifetime over PEGASIS of 817% and 420% for base station inside and outside the network respectively. Residual energy and delay performance are also considered.

Distance Based Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks

2014 ◽  
Vol 626 ◽  
pp. 20-25
Author(s):  
K. Kalaiselvi ◽  
G.R. Suresh
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Base Station ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Energy Efficient Routing

In wireless sensor networks Energy-efficient routing is an important issue due to the limited battery power within the network, Energy consumption is one of the important performance factors. Specifically for the election of cluster head selection and distance between the cluster head node and base station. The main objective of this proposed system is to reduce the energy consumption and prolong the network lifetime. This paper introduces a new clustering algorithm for energy efficient routing based on a cluster head selection

scholarly journals An Energy Efficient Routing Protocol Based on Layers and Unequal Clusters in Underwater Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Fang Zhu ◽  
Junfang Wei
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Energy Efficient ◽  
High Energy ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks ◽  
Energy Efficient Routing ◽  
Unequal Cluster

Underwater Wireless Sensor Networks (UWSNs) have drawn tremendous attentions from all fields because of their wide application. Underwater wireless sensor networks are similar to terrestrial Wireless Sensor Networks (WSNs), however, due to different working environment and communication medium, UWSNs have many unique characteristics such as high bit error rate, long end-to-end delay and low bandwidth. These characteristics of UWSNs lead to many problems such as retransmission, high energy consumption and low reliability. To solve these problems, many routing protocols for UWSNs are proposed. In this paper, a localization-free routing protocol, named energy efficient routing protocol based on layers and unequal clusters (EERBLC) is proposed. EERBLC protocol consists of three phases: layer and unequal cluster formation, transmission routing, maintenance and update of clusters. In the first phase, the monitoring area under the water is divided into layers, the nodes in the same layer are clustered. For balancing energy of the whole network and avoiding the “hotspot” problem, a novel unequal clustering method based on layers for UWSNs is proposed, in which a new calculation method of unequal cluster size is presented. Meanwhile, a new cluster head selection mechanism based on energy balance and degree is given. In the transmission phase, EERBLC protocol proposes a novel next forwarder selection method based on the forwarding ratio and the residual energy. In the third phase, Intra and inter cluster updating method is presented. The simulation results show that the EERBLC can effectively balance the energy consumption, prolong the network lifetime, and increase the amount of data transmission compared with DBR and EEDBR protocols.

scholarly journals A Distributed Heuristic Algorithm for Delay Constrained Energy Efficient Routing in Wireless Sensor Networks

2017 ◽  
Author(s):  
Thua Trong Huynh ◽  
Hung Cong Tran ◽  
Vu Duc Anh Dinh
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Computational Complexity ◽  
Heuristic Algorithm ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Routing ◽  
End To End Delay

Besides energy restriction, wireless sensor networks (WSNs) should be able to provide bounded end-to-end delay when they are used to support real-time applications such as early forest fire alarm systems. In this paper, we investigate the problem of finding the least energy consumption route subject to a delay constraint with low computational complexity in such networks. Based on the distance-vector routing approach, which has less computational complexity and message overhead, we propose a distributed heuristic algorithm called Delay Constrained Energy Efficient Routing (DCEER) in order to minimize the total energy consumption while meeting the end-to-end delay requirement. DCEER only requires a moderate amount of information at each sensor node and does not suffer from the excessive running time. We prove that our proposed algorithm always finishes within a finite time and the computation complexity is only O(n), where n is a divisor of the number of sensor nodes. By mathematical proof and simulation, we verify that DCEER is suitable for large-scale WSNs because the number of messages exchanged between sensor nodes are represented by a polynomial function. Furthermore, we evaluate our proposal to compare its performance with related protocols.

scholarly journals A hybrid Meta-heuristic solution for Energy-Efficient routing in Software-Defined Wireless Sensor Network 

2021 ◽  
Author(s):  
POOJA MISHRA ◽  
NEETESH KUMAR ◽  
W WILFRED GODFREY
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Fitness Function ◽  
Life Time ◽  
Residual Energy ◽  
Wireless Sensor ◽  
Energy Efficient Routing ◽  
Nature Inspired Algorithm ◽  
Network Life Time

Abstract Software-Defined Networking (SDN) has been adopted as an emerging networking paradigm within Wireless Sensor Networks (WSNs). SDN enables WSNs with self-configuration and programmable control to dynamically and efficiently manage the network functionalities. Generally, in WSN, smart sensing devices suffer from the low battery issue and they may be deployed in such environments where frequent recharge is not possible after the deployment. Therefore, this work focuses on energy-efficient routing problem considering Software-Defined Wireless Sensor Networks (SD-WSN) architecture. In SD-WSN, Control Server (CS) assigns the tasks to selected Control Nodes (CNs) dynamically. Thus, the CNs' selection process is developed as one optimization (NP-Hard) problem to make the network functional. To solve this problem effectively, a nature-inspired algorithm i.e., Grey Wolf Optimization (GWO) is hybridized with Particle Swarm Optimization (PSO) in order to improve its convergence and overall performance. This hybrid variant of GWO is dedicated to offering a Balanced clustering (BC) based routing protocol, this variant is referred to as HGWO-BC. Further, to solve the problem effectively, a fitness function is designed that considers several parameters e.g., intracluster distance, CS to CNs distance, nodes' residual energy, and cluster size. Thus, the proposed approach performs balanced, energy-efficient, and scalable clustering and prolongs the network life-time. To verify its effectiveness, an exhaustive simulation study is done. Comparative results show that the HGWO-BC approach outperforms other state-of-the-art approaches concerning network life-time, residual energy, network throughput, and convergence rate.

scholarly journals ENHANCEMENT OF ENERGY EFFICIENT ROUTING PROTOCOL BY MINIMIZING ENERGY CONSUMPTION IN WIRELESS SENSOR NETWORKS.

2017 ◽  
Vol 5 (1) ◽  
pp. 1191-1194
Author(s):  
Mr.SharadA. Bhad. ◽  
◽  
Mr.VikramM. Chavan. ◽  
Mr.NileshS. Nalawade. ◽  
Mr.AmolP. Nagime. ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Wireless Sensor ◽  
Energy Efficient Routing
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