scholarly journals Cluster-based Routing Protocols for Energy-Efficiency in Wireless Sensor Networks

10.5772/13274 ◽  
2010 ◽  
Author(s):  
Moufida Maimour ◽  
Houda Zeghilet ◽  
Francis Lepage
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocols ◽  
Wireless Sensor ◽  
Cluster Based Routing

Performance Analysis of TBC-ACO Routing Protocol with Existing Routing Protocols of Wireless Sensor Networks

2017 ◽  
Vol 7 (8) ◽  
pp. 169
Author(s):  
A. Radhika ◽  
D. Haritha
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Congestion Aware

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.

scholarly journals A Survey on the Taxonomy of Cluster-Based Routing Protocols for Homogeneous Wireless Sensor Networks

Sensors ◽  
2012 ◽  
Vol 12 (6) ◽  
pp. 7350-7409 ◽  
Author(s):  
Soroush Naeimi ◽  
Hamidreza Ghafghazi ◽  
Chee-Onn Chow ◽  
Hiroshi Ishii
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocols ◽  
Wireless Sensor ◽  
Cluster Based Routing

scholarly journals Distributed Energy Efficient Clustering Routing Protocol for Wireless Sensor Networks Using Affinity Propagation And Fuzzy Logic

2021 ◽  
Author(s):  
Chu-hang Wang ◽  
Huang-shui Hu ◽  
Zhi-gang Zhang ◽  
Yu-xin Guo ◽  
Jin-feng Zhang
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Fuzzy Logic ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Residual Energy ◽  
Affinity Propagation ◽  
Wireless Sensor ◽  
Distributed Clustering

Abstract Organizing nodes into clusters and forwarding data to the Base Station (BS) in clustering routing protocols have been widely utilized to improve the energy efficiency, scalability and stability of Wireless Sensor Networks (WSN). Making decisions on how many clusters are formed, which nodes are selected as Cluster Heads (CHs) and who become the relay nodes significantly impact the network performance. Therefore, a Distributed clustering routing protocol combined Affinity Propagation (AP) with Fuzzy Logic called DAPFL is proposed in this paper, which considers not only energy efficiency but also energy balance to extend the network lifetime. In DAPFL, AP is firstly used to determine the number of clusters and select the best CHs simultaneously based on residual energy, distance between nodes. Then the optimal next-hop CHs are chosen by using fuzzy logic system with residual energy, data length and distance to BS as descriptors. Simulations in different scenarios are carried out to verify the effectiveness of DAPFL, and the results show that DAPFL exhibits the promising performance in terms of network energy consumption, standard deviation of residual energy, network throughput and lifetime, compared with the up-to-date distributed clustering routing protocols EEFUC, EEFRP, LEACH-AP and APSA.

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