Efficient Load Balancing and Extended Network Lifetime for Cluster Based Routing Wireless Sensor Networks Using Fitness Function Algorithm

2021 ◽  
Author(s):  
Harish S. V ◽  
Archana NV
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Load Balancing ◽  
Network Lifetime ◽  
Fitness Function ◽  
Wireless Sensor ◽  
Cluster Based Routing

scholarly journals Energy-Efficient QoS-Aware Intelligent Hybrid Clustered Routing Protocol for Wireless Sensor Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Parvinder Singh ◽  
Rajeshwar Singh
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Large Scale ◽  
Fitness Function ◽  
Geographical Area ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor

A wireless sensor network consists of numerous low-power microsensor devices that can be deployed in a geographical area for remote sensing, surveillance, control, and monitoring applications. The advancements of wireless devices in terms of user-friendly interface, size, and deployment cost have given rise to many smart applications of wireless sensor networks (WSNs). However, certain issues like energy efficiency, long lifetime, and communication reliability restrict their large scale utilization. In WSNs, the cluster-based routing protocols assist nodes to collect, aggregate, and forward sensed data from event regions towards the sink node through minimum cost links. A clustering method helps to improve data transmission efficiency by dividing the sensor nodes into small groups. However, improper cluster head (CH) selection may affect the network lifetime, average network energy, and other quality of service (QoS) parameters. In this paper, a multiobjective clustering strategy is proposed to optimize the energy consumption, network lifetime, network throughput, and network delay. A fitness function has been formulated for heterogenous and homogenous wireless sensor networks. This fitness function is utilized to select an optimum CH for energy minimization and load balancing of cluster heads. A new hybrid clustered routing protocol is proposed based on fitness function. The simulation results conclude that the proposed protocol achieves better efficiency in increasing the network lifetime by 63%, 26%, and 10% compared with three well-known heterogeneous protocols: DEEC, EDDEEC, and ATEER, respectively. The proposed strategy also attains better network stability than a homogenous LEACH protocol.

scholarly journals Grid-Based Hybrid Network Deployment Approach for Energy Efficient Wireless Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Haleem Farman ◽  
Huma Javed ◽  
Jamil Ahmad ◽  
Bilal Jan ◽  
Muhammad Zeeshan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Load Balancing ◽  
Network Lifetime ◽  
Sensor Nodes ◽  
Hybrid Network ◽  
Wireless Sensor ◽  
Total Energy Consumption ◽  
Grid Based ◽  
Efficient Consumption

Wireless sensor networks (WSN) empower applications for critical decision-making through collaborative computing, communications, and distributed sensing. However, they face several challenges due to their peculiar use in a wide variety of applications. One of the inherent challenges with any battery operated sensor is the efficient consumption of energy and its effect on network lifetime. In this paper, we introduce a novel grid-based hybrid network deployment (GHND) framework which ensures energy efficiency and load balancing in wireless sensor networks. This research is particularly focused on the merge and split technique to achieve even distribution of sensor nodes across the grid. Low density neighboring zones are merged together whereas high density zones are strategically split to achieve optimum balance. Extensive simulations reveal that the proposed method outperforms state-of-the-art techniques in terms of load balancing, network lifetime, and total energy consumption.

scholarly journals Load Balanced Energy Efficient Cluster-chain Based Hybrid Protocol for Wireless Sensor Networks

2019 ◽  
Vol 8 (3) ◽  
pp. 3561-3570
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Load Balancing ◽  
Network Lifetime ◽  
Outer Layer ◽  
Energy Efficient ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Load Balanced

In this paper a novel geographical multilayer protocol named Cluster-chain Based Hybrid (CCBH) Protocol is proposed for proper load balancing across the network that enhance the network lifespan and eliminate the energy holes problem. The CCBH protocol divides the network into the multilayer square structure around the sink. Each layer is divided into to the zones in such a way that the zones near to the sink are smaller in size and size of zones increases as the separation from the sink increases. In inner two layers, each zone has a cluster head (CH) and to reduce the load of CH a leader node (LN) is assigned in every zone. LN collects and aggregates the data received from neighboring nodes and sends it to the associated CH. Outer layer zones are larger in size. To reduce the clustering overhead chain strategy is introduced in outer layer zones that ensure lesser energy consumption as compared to clustering. Multi hop communiqué is used, where data is transferred from upper zone’s CH to immediate lower zone’s CH until it reaches to the sink. Simulated tests demonstrate that proposed CCBH protocol shows evident improvement in terms of the network lifetime as compare to LBCN, LEACH, TCAC, and DSBCA protocols

scholarly journals AEF: Adaptive En-Route Filtering to Extend Network Lifetime in Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 4036 ◽  
Author(s):  
Muhammad K. Shahzad ◽  
S. M. Riazul Islam ◽  
Kyung-Sup Kwak ◽  
Lewis Nkenyereye
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Fitness Function ◽  
Dynamic Network ◽  
Key Distribution ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Awareness ◽  
Energy Aware

Static sink-based wireless sensor networks (WSNs) suffer from an energy-hole problem. This incurs as the rate of energy consumption on sensor nodes around sinks and on critical paths is considerably faster. State-of-the-art en-routing filtering schemes save energy by countering false report injection attacks. In addition to their unique limitations, these schemes generally do not examine energy awareness in underlying routing. Mostly, these security methods are based on a fixed filtering capacity, unable to respond to changes in attack intensity. Therefore, these limitations cause network partition(s), exhibiting adverse effects on network lifetime. Extending network lifetime while preserving energy and security thus becomes an interesting challenge. In this article, we address the aforesaid shortcomings with the proposed adaptive en-route filtering (AEF) scheme. In energy-aware routing, the fitness function, which is used to select forwarding nodes, considers residual energy and other factors as opposed to distance only. In pre-deterministic key distribution, keys are distributed based on the consideration of having paths with a different number of verification nodes. This, consequently, permits us to have multiple paths with different security levels that can be exploited to counter different attack intensities. Taken together, the integration of the special fitness function with the new key distribution approach enables the AEF to adapt the underlying dynamic network conditions. The simulation experiments under different settings show significant improvements in network lifetime.

EAGBRP: A Gateway Based Routing Protocol for Heterogeneous Wireless Sensor Networks

2021 ◽  
Vol 13 (2) ◽  
pp. 467-481
Author(s):  
M. M. Hoque ◽  
M. G. Rashed ◽  
M. H. Kabir ◽  
A. F. M. Z. Abadin ◽  
M. I. Pramanik
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Performance Analysis ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Minimum Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Heterogeneous Wireless Sensor Networks ◽  
Cluster Based Routing

In most of the cluster-based routing protocols for wireless sensor networks (WSNs), cluster heads (CHs) are selected from the normal sensors which may expire rapidly due to fast energy diminution for such an additional workload. As a consequence, the network lifetime of such cluster-based routing protocol reduces drastically. To resolve these constraints, in this study, we proposed a gateway-based routing protocol-namely Energy-Aware Gateway Based Routing Protocol (EAGBRP) for WSNs. In our proposed protocol, the deployed sensor nodes of a WSN were divided into five logical regions based on their location in the sensing field. The base station (BS) was installed out of the sensing area, and two gateway nodes were inaugurated at two predefined regions of the sensing area. The CH in each region is independent of the other regions and selected based on a weighted election probability. We implemented our proposed routing protocol through simulations. To evaluate the performance of our EAGBRP, we simulated SEP, M-GEAR, and MGBEHA (4GW) protocols. The network lifetime, throughput, and residual energy parameters are utilized for performance analysis. It is revealed from the performance analysis results that WSNs with EAGBRP achieve maximum network lifetime and throughput over other considered protocols with minimum energy consumption.

An Energy Balancing Cross Layer Scheme for Long Lifetime Wireless Sensor Networks

2015 ◽  
Vol 764-765 ◽  
pp. 827-831
Author(s):  
Yung Fa Huang ◽  
Tan Hsu Tan ◽  
Yau Der Wang ◽  
Young Long Chen ◽  
Neng Chung Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Load Balancing ◽  
Network Lifetime ◽  
Routing Algorithm ◽  
Wireless Sensor ◽  
Cross Layer ◽  
Energy Balancing ◽  
Energy Aware

In this paper, we propose an improved routing algorithm to prolong network lifetime of wireless sensor networks (WSNs) by combining the shortest hop routing tree (SHORT) algorithm and the, turn off redundant node (TORN) MAC layer protocol to cross layer SHORTORN scheme. Moreover, to prolong the lifetime of the first node death (FND) in networks, the rate of energy consumption should be balanced for all nodes. Therefore, this paper further proposes a load balancing SHORTORN scheme by combining the weight and energy-aware, called energy-aware weight-based SHORTORN (EWSHORTORN). The proposed EWSHORTORN algorithm lets more nodes share the load of the leader and balances the opportunity of data relaying to all nodes. The proposed load balancing scheme allocates energy consumption load to be more uniformly among all nodes, thus the FNL can be prolonged evidently. Simulation results show that the proposed EWSHORTORN outperforms the SHORT scheme with double lifetime of FND.Keywords: wireless sensor networks, network lifetime, cross layer protocol, load balance.

INERTIA PARTICLE SWARM OPTIMIZATION WITH DYNAMIC VELOCITY BASED CLUSTERING TECHNIQUE IN WIRELESS SENSOR NETWORKS

2021 ◽  
Vol 10 (1) ◽  
pp. 433-442
Author(s):  
R. Sathiya Priya ◽  
K. Arutchelvan ◽  
C. T. Bhuvaneswari
Keyword(s):  
Wireless Sensor Networks ◽  
Particle Swarm Optimization ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Fitness Function ◽  
Particle Swarm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Swarm Optimization ◽  
Clustering Technique

Wireless Sensor Networks (WSN) comprises a collection of nodes commonly employed to observe the physical environment. Different sensor nodes are linked to an inbuilt power unit to carry out necessary operations and data transmission between nearby nodes. The maximization of network lifetime and minimization of energy dissipation are considered as the major design issue of WSN. Clustering is a familiar energy efficient technique and the choice of optimal cluster heads (CHs) is considered as an NP hard problem. This paper presents an Inertia Particle Swarm Optimization algorithm with dynamic velocities (IPSO-DV) algorithm based clustering technique in WSN. The aim of the IPSO-DV technique is to select the CHs in such a way to maximize network lifetime. The IPSO-DV algorithm derives a fitness function (FF) to select CHs using distance to BS and remaining energy level. The application of dynamic velocities helps to improvise the effectiveness of the conventional PSO algorithm. To assure the performance of the presented IPSO-DV algorithm, a series of experiments were carried out and the results are investigated under several aspects. The experimentation outcome ensured the effective performance of the IPSO-DV algorithm over the compared clustering techniques.

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