Uneven clustering routing algorithm for Wireless Sensor Networks based on ant colony optimization

Author(s):  
Jiang Du ◽  
Liang Wang
Author(s):  
Djilali Moussaoui ◽  
Mourad Hadjila ◽  
Sidi Mohammed Hadj Irid ◽  
Sihem Souiki

One challenge in under-water wireless sensor networks (UWSN) is to find ways to improve the life duration of networks, since it is difficult to replace or recharge batteries in sensors by the solar energy. Thus, designing an energy-efficient protocol remains as a critical task. Many cluster-based routing protocols have been suggested with the goal of reducing overall energy consumption through data aggregation and balancing energy through cluster-head rotation. However, the majority of current protocols are concerned with load balancing within each cluster. In this paper we propose a clustered chain-based energy efficient routing algorithm called CCRA that can combine fuzzy c-means (FCM) and ant colony optimization (ACO) create and manage the data transmission in the network. Our analysis and results of simulations show a better energy management in the network.


Algorithms ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 250
Author(s):  
Xingxing Xiao ◽  
Haining Huang

Because of the complicated underwater environment, the efficiency of data transmission from underwater sensor nodes to a sink node (SN) is faced with great challenges. Aiming at the problem of energy consumption in underwater wireless sensor networks (UWSNs), this paper proposes an energy-efficient clustering routing algorithm based on an improved ant colony optimization (ACO) algorithm. In clustering routing algorithms, the network is divided into many clusters, and each cluster consists of one cluster head node (CHN) and several cluster member nodes (CMNs). This paper optimizes the CHN selection based on the residual energy of nodes and the distance factor. The selected CHN gathers data sent by the CMNs and transmits them to the sink node by multiple hops. Optimal multi-hop paths from the CHNs to the SN are found by an improved ACO algorithm. This paper presents the ACO algorithm through the improvement of the heuristic information, the evaporation parameter for the pheromone update mechanism, and the ant searching scope. Simulation results indicate the high effectiveness and efficiency of the proposed algorithm in reducing the energy consumption, prolonging the network lifetime, and decreasing the packet loss ratio.


2015 ◽  
Vol 713-715 ◽  
pp. 1423-1426 ◽  
Author(s):  
Dong Ya Chen ◽  
Chang Mao Zhang ◽  
Guang Ye Li ◽  
Tao Tian

Routing algorithm based on ant colony optimization for wireless sensor networks has the ant colony algorithm characteristics of self-organization, the positive feedback and the parallelism, which has good performance in constructing the optimal routing. In this paper, the distance for stimulating factor is improved, the communication distance is introduced and the pheromone update methods having the rewards and punishment mechanism are adopted, which can make better use of residual energy for wireless sensor networks nodes, prolong life of network and guarantee the effect of the optimization algorithm.


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