MCL and ACO Based QoS Routing Algorithm for WSN Used in Power Line Monitoring

2014 ◽  
Vol 672-674 ◽  
pp. 2033-2036
Author(s):  
Li Fen Li
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Ant Colony Algorithm ◽  
Routing Algorithm ◽  
Qos Routing ◽  
Ant Colony ◽  
Link Quality ◽  
Wireless Sensor ◽  
Cross Layer ◽  
Qos Routing Algorithm

This paper presents a new cross-layer QoS routing algorithm for wireless sensor networks. Basing on the principle of cross-layer design, the algorithm adopts delay, nodes’ load and link quality as QoS metrics. The QoS routing metrics are regarded as heuristics correction factors in ant colony algorithm (ACA). The ants are divided into a number of different populations. Through the interaction of pheromone between multi populations, the routing algorithm searches for the feasible paths in parallel and updates the pheromone in time. To overcome the slow convergence of ant colony algorithm, membership cloud model (MCL) is used to control the randomness of the ants. The simulation results demonstrate that the routing algorithm can guarantee the real time, reliability and robustness of wireless sensor networks. It can also achieve the network load balancing.

scholarly journals Clustered chain founded on ant colony optimization energy efficient routing scheme for under-water wireless sensor networks

2021 ◽  
Vol 11 (6) ◽  
pp. 5197
Author(s):  
Djilali Moussaoui ◽  
Mourad Hadjila ◽  
Sidi Mohammed Hadj Irid ◽  
Sihem Souiki
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Ant Colony Optimization ◽  
Energy Efficient ◽  
Routing Algorithm ◽  
Cluster Head ◽  
Head Rotation ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Energy Efficient Routing

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.

Sign in / Sign up

Export Citation Format

Share Document