Journal ArticleDOI
Two-tier particle swarm optimization protocol for clustering and routing in wireless sensor network
TLDR
The results demonstrate that the proposed protocol performs better than well-known cluster-based sensor network protocols in terms of various performance metrics such as scalability, Packet Delivery Rate (PDR) at the CHs and delivery of total data packets to the BS.About:
This article is published in Journal of Network and Computer Applications.The article was published on 2015-06-01. It has received 128 citations till now. The article focuses on the topics: Zone Routing Protocol & Wireless Routing Protocol.read more
Citations
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Journal ArticleDOI
A Survey on Underwater Acoustic Sensor Network Routing Protocols
TL;DR: This is the first paper that introduces intelligent algorithm-based UASN routing protocols, and all the routing protocols have been classified into different groups according to their characteristics and routing algorithms, such as the non-cross-layer design routing protocol, the traditional cross-layerDesign routing protocol and the intelligent algorithm based routing protocol.
Journal ArticleDOI
Genetic Algorithm-based Optimized Cluster Head selection for single and multiple data sinks in Heterogeneous Wireless Sensor Network
TL;DR: Genetic Algorithm-based Optimized Clustering (GAOC) protocol is designed for optimized CH selection by integrating the parameters of residual energy, distance to the sink and node density in its formulated fitness function and outperform the state-of-the-art protocols on the benchmark of different performance metrics.
Journal ArticleDOI
Integrated clustering and routing protocol for wireless sensor networks using Cuckoo and Harmony Search based metaheuristic techniques
Govind P. Gupta,Sonu Jha +1 more
TL;DR: An improved cuckoo search-based energy balanced node clustering protocol which uses a novel objective function for uniform distribution of cluster heads is proposed which shows significant improvement over the state-of-art protocols.
Journal ArticleDOI
Coverage protocols for wireless sensor networks: Review and future directions
TL;DR: In this paper, a taxonomy for classifying coverage protocols in WSNs is proposed and the coverage protocols are classified into three categories (i.e., coverage-aware deployment protocols, sleep scheduling protocols for flat networks, and cluster-based sleep-scheduling protocols) based on the network stage where the coverage is optimized.
Journal ArticleDOI
Optimized Clustering Algorithms for Large Wireless Sensor Networks: A Review.
TL;DR: From the analysis, it is observed that centralized clustering solutions based on the Swarm Intelligence paradigm are more adapted for applications with low energy consumption, high data delivery rate, or high scalability than algorithmsbased on the other presented paradigms.
References
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Proceedings ArticleDOI
Particle swarm optimization
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Proceedings ArticleDOI
Energy-efficient communication protocol for wireless microsensor networks
TL;DR: The Low-Energy Adaptive Clustering Hierarchy (LEACH) as mentioned in this paper is a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network.
Energy-efficient communication protocols for wireless microsensor networks
TL;DR: LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network, is proposed.
Journal ArticleDOI
An application-specific protocol architecture for wireless microsensor networks
TL;DR: This work develops and analyzes low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality.
Book
Ant Colony Optimization
TL;DR: Ant colony optimization (ACO) is a relatively new approach to problem solving that takes inspiration from the social behaviors of insects and of other animals as discussed by the authors In particular, ants have inspired a number of methods and techniques among which the most studied and the most successful is the general purpose optimization technique known as ant colony optimization.
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Energy efficient clustering and routing algorithms for wireless sensor networks: Particle swarm optimization approach
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