scholarly journals CAPNet: An Enhanced Load Balancing Clustering Algorithm for Prolonging Network Lifetime in WSNs

2014 ◽  
Vol 10 (2) ◽  
pp. 234394 ◽  
Author(s):  
Mucheol Kim ◽  
Sunhong Kim ◽  
Jiwan Seo ◽  
Kiseok Choi ◽  
Sangyong Han
Keyword(s):  
Load Balancing ◽  
Network Lifetime ◽  
Clustering Algorithm

Type 2 Fuzzy Logic based Unequal Clustering algorithm for multi-hop wireless sensor networks

2020 ◽  
pp. 33-46
Author(s):  
A. Sariga ◽  
◽  
◽  
J. Uthayakumar
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Network Lifetime ◽  
Clustering Algorithm ◽  
Hot Spot ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Clustering Protocols ◽  
Hot Spot Problem

Wireless sensor network (WSN) is an integral part of IoT and Maximizing the network lifetime is a challenging task. Clustering is the most popular energy efficient technique which leads to increased lifetime stability and reduced energy consumption. Though clustering offers several advantages, it eventually raises the burden of CHs located in proximity to the Base Station (BS) in multi-hop data transmission which makes the CHs near BS die earlier than other CHs. This issue is termed as hot spot problem and unequal clustering protocols were introduced to handle it. Presently, some of the clustering protocols are developed using Type-2 Fuzzy Logic (T2FL) but none of them addresses hot spot problem. This paper presents a Type-2 Fuzzy Logic based Unequal Clustering Algorithm (T2FLUCA) for the elimination of hot spot problem and also for lifetime maximization of WSN. The proposed algorithm uses residual energy, distance to BS and node degree as input to T2FL to determine the probability of becoming CHs (PCH) and cluster size. For experimentation, T2FLUCA is tested on three different scenarios and the obtained results are compared with LEACH, TEEN, DEEC and EAUCF in terms of network lifetime, throughput and average energy consumption. The experimental results ensure that T2FLUCA outperforms state of art methods in a significant way.

A Multi-Layer Self-Healing Algorithm for WSNs

2019 ◽  
Vol 29 (05) ◽  
pp. 2050070 ◽  
Author(s):  
Sergio Diaz ◽  
Diego Mendez ◽  
Rolf Kraemer
Keyword(s):  
Network Lifetime ◽  
Topology Control ◽  
Clustering Algorithm ◽  
Disjoint Paths ◽  
Self Healing ◽  
Spatial Clusters ◽  
Area Of Interest ◽  
Control Message ◽  
Good Coverage ◽  
Message Overhead

The implementation of Wireless Sensor Networks (WSNs) is a challenging task due to their intrinsic characteristics, e.g., energy limitations and unreliable wireless links. Considering this, we have developed the Disjoint path And Clustering Algorithm (DACA) that combines topology control and self-healing mechanisms to increase the network lifetime with minimum loss of coverage. Initially, DACA constructs a tree that includes all nodes of the network by using the Collection Tree Protocol (CTP). This tree is an initial communication backbone through which DACA centralizes the information. Then, DACA builds a set of spatial clusters using Kmeans and selects the Cluster Heads (CHs) using Particle Swarm Optimization (PSO) and a multi-objective optimization (MOO) function. Subsequently, DACA reconstructs the tree using only the CHs. In this way, DACA reduces the number of active nodes in the network and saves energy. Finally, DACA finds disjoint paths on the reconstructed tree by executing the N-to-1 multipath discovery protocol. By doing so, the network can overcome communications failures with a low control message overhead. The simulations on Castalia show that DACA considerably extends the network lifetime by having a set of inactive nodes and disjoint paths that support the communication when active nodes die. Besides, DACA still maintains a good coverage of the area of interest despite the inactive nodes. Additionally, we evaluate the shape of the tree (i.e., the average number of hops) and the risk of connection loss of the network.

An Energy-Balanced Routing Algorithm in Wireless Seismic Sensor Network

2016 ◽  
Vol 13 (10) ◽  
pp. 6823-6833
Author(s):  
Xunqian Tong ◽  
Gengfa Fang ◽  
Diep Nguyen ◽  
Jun Lin ◽  
Emerson Cabrera
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Clustering Algorithm ◽  
Hamming Distance ◽  
Hot Spot ◽  
Routing Algorithm ◽  
Residual Energy ◽  
Data Collector ◽  
Energy Balanced Routing ◽  
Candidate Set

Due to unpredictable geological outdoor environments and imbalances in energy consumption of seismometer nodes in the wireless seismic sensor networks (WSSN), some seismometer nodes fail much earlier than others due to power loss. This would cause hot spot problems, network partitions, and significantly shorten network lifetime. In this paper, we designed an energy-balanced routing algorithm (EBRA) to ensure balanced energy consumption from all seismometer nodes in the WSSN and to enhance the connectivity and lifetime of the WSSN. By aiming at minimizing the imbalance in the residual energy, we divide the routing algorithm into two parts: clustering formation and inter-cluster routing. In clustering formation, we design an energy-balanced clustering algorithm, which selects the cluster head dynamically, based on residual energy, distance between the seismometer node and data collector. The clustering algorithm mitigates hot spot problems by balancing energy consumption among seismometer nodes. In regards to inter-cluster routing, we can relate it to the pareto-candidate set. To reduce the average multi-hop delay from cluster heads to the data collector, we optimize the pareto-candidate set by Hamming distance. In the design of EBRA, we consider minute details such as energy consumed by transmitting bits and impact of average multi-hop delay. This adds to the novelty of this work compared to the existing studies. Simulation results demonstrated a reduction in the average multi-hop delay by 87.5% with network size of 200 nodes in ten different data collector locations. Our algorithm also improves the network lifetime over the others three schemes by 7.8%, 23% and 45.4%, respectively.

scholarly journals An Energy Efficient Clustering based Distributed Load Balancing Technique for Mobile Adhoc Networks

2019 ◽  
Vol 8 (9) ◽  
pp. 1869-1877
Keyword(s):  
Energy Efficiency ◽  
Load Balancing ◽  
Network Lifetime ◽  
Fault Tolerant ◽  
Mobile Nodes ◽  
Battery Lifetime ◽  
Mobile Adhoc Network ◽  
Distributed Load ◽  
Adhoc Network ◽  
Energy Efficient Clustering

In a mobile adhoc network (MANET), energy efficiency and mobility prediction are the two main challenging design issues due to the mobile nature of the nodes in any direction with limited battery lifetime, thus leads to adequate topology modifications. These two issues are mainly considered to maximize the lifetime of MANET. Load-balancing and reliable data transmission among the mobile nodes is mandatory to increase the network lifetime. To achieve this, clustering techniques can be employed to minimize the topology size and to aggregate the details related to the topology. In this paper, we introduce a new clustering based distributed load balancing (D-CALB) algorithm to maximize energy efficiency and network lifetime. Furthermore, a fault tolerant feature is included in the D-CALB algorithm, which maintains a secondary CH as a backup node in case of the failure of the present CH. The presented ZXCD- CALB algorithm has undergone an extensive set of experimentation under a varying number of nodes and speed. The detailed investigation of the experimental results verified the superior nature of the presented D-CALB algorithm over compared ones under several measures.

Sign in / Sign up

Export Citation Format

Share Document