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

Sensor Networks ◽

Ant Colony Algorithm ◽

Routing Algorithm ◽

Qos Routing ◽

Ant Colony ◽

Link Quality ◽

Wireless Sensor ◽

Cross Layer ◽

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.

Cross-layer QoS Routing Algorithm Based on the Node Occupation Degree Control for Wireless Sensor Networks

Journal of Information and Computational Science ◽

10.12733/jics20102351 ◽

2013 ◽

Vol 10 (16) ◽

pp. 5345-5353

Author(s):

Yi Jiang

Keyword(s):

Sensor Networks ◽

Routing Algorithm ◽

Qos Routing ◽

Wireless Sensor ◽

Cross Layer ◽

Advanced Technology in Teaching - Proceedings of the 2009 3rd International Conference on Teaching and Computational Science (WTCS 2009) - Advances in Intelligent and Soft Computing ◽

Cloud Model and Ant Colony Optimization Based QoS Routing Algorithm for Wireless Sensor Networks

10.1007/978-3-642-11276-8_23 ◽

2012 ◽

pp. 179-187 ◽

Cited By ~ 2

Author(s):

Di Jian

Keyword(s):

Sensor Networks ◽

Ant Colony Optimization ◽

Cloud Model ◽

Routing Algorithm ◽

Qos Routing ◽

Ant Colony ◽

Wireless Sensor ◽

An Ant System optimization QoS routing algorithm for wireless sensor networks

Third International Workshop on Advanced Computational Intelligence ◽

10.1109/iwaci.2010.5585117 ◽

2010 ◽

Cited By ~ 1

Author(s):

Fengjun Shang ◽

Yin Wang

Keyword(s):

Sensor Networks ◽

Routing Algorithm ◽

System Optimization ◽

Qos Routing ◽

Wireless Sensor ◽

Ant System ◽

A Distributed Agents QoS Routing Algorithm to Transmit Electrical Power Measuring Information in Last Mile Access Wireless Sensor Networks

International Journal of Distributed Sensor Networks ◽

10.1155/2013/525801 ◽

2013 ◽

Vol 9 (11) ◽

pp. 525801 ◽

Cited By ~ 6

Author(s):

Ting Yang ◽

Wenping Xiang ◽

Linqi Ye

Keyword(s):

Sensor Networks ◽

Routing Algorithm ◽

Electrical Power ◽

Qos Routing ◽

Wireless Sensor ◽

Distributed Agents ◽

Last Mile ◽

A Energy-Aware QoS Routing Protocol for Wireless Sensor Networks

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.373-375.323 ◽

2013 ◽

Vol 373-375 ◽

pp. 323-328

Author(s):

Long Gao ◽

La Yuan Li

Keyword(s):

Sensor Networks ◽

Routing Protocol ◽

Routing Algorithm ◽

Residual Energy ◽

Qos Routing ◽

Wireless Sensor ◽

Energy Aware ◽

Multiple Paths ◽

As the different QoS requirements of different businesses in wireless sensor networks, we proposed a QoS routing algorithm-EAQoS. The algorithm built multiple paths to sink node by recording the minimum hops of neighbors to sink. Then data was sent by the path that satisfied its QoS requirements and had enough residual energy. According to the comparisons with the SAR routing algorithm, this algorithm has obvious advantages in providing different services and prolonging the lifetime of network.

Trust-based QoS routing algorithm for Wireless Sensor Networks

The 26th Chinese Control and Decision Conference (2014 CCDC) ◽

10.1109/ccdc.2014.6852592 ◽

2014 ◽

Cited By ~ 4

Author(s):

Junwei Wang ◽

Haifeng Wang

Keyword(s):

Sensor Networks ◽

Routing Algorithm ◽

Qos Routing ◽

Wireless Sensor ◽

Design of Trusted Security Routing in Wireless Sensor Networks Based on Quantum Ant Colony Algorithm

International Journal of Online Engineering (iJOE) ◽

10.3991/ijoe.v13i07.7273 ◽

2017 ◽

Vol 13 (07) ◽

pp. 4

Author(s):

Xiaobin Shu ◽

Caihong Liu ◽

Chunxia Jiao ◽

Qin Wang ◽

Hongfeng Yin

Keyword(s):

Energy Consumption ◽

Wireless Sensor Network ◽

Sensor Networks ◽

Large Scale ◽

Ant Colony Algorithm ◽

Routing Algorithm ◽

Ant Colony ◽

Wireless Sensor ◽

Font Size

To design an effective secure routing of trusted nodes in wireless sensor networks, quantum ant colony algorithm is applied to the design of large-scale wireless sensor network routing. The trustworthy network is used as the pheromone distribution strategy.Then, the pheromone is encoded by the quantum bit. The pheromone is updated by the quantum revolving door, and the energy consumption prediction is carried out to select the path. Finally, the trusted security routing algorithm of the wireless sensor network based on the global energy balance is realized. The quantum ant colony algorithm is superior to the traditional ant colony algorithm in algorithm convergence speed and global optimization. It can balance the energy consumption of the network node and can effectively resist the attacks such as Wormholes.It is very promising to apply the quantum ant colony algorithm to the routing algorithm of large scale wireless sensor networks.

PSO-Based Trust QoS Routing Algorithm for Wireless Sensor Networks

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.401-403.1751 ◽

2013 ◽

Vol 401-403 ◽

pp. 1751-1755

Author(s):

Jun Wei Wang ◽

Yong Tao Wei

Keyword(s):

Sensor Networks ◽

Routing Algorithm ◽

Residual Energy ◽

Qos Routing ◽

Packet Transmission ◽

Wireless Sensor ◽

Trust Value ◽

Network Utilization ◽

The existing routing algorithm of Wireless Sensor Networks (WSNs) pays more attention to the energy efficient. However, Quality of Service (QoS) supported and the validity of packet transmission unveil additional challenges. Based on the Particle Swarm Optimization (PSO), this paper presents a trust QoS routing algorithm for WSNs. Hierarchical structure is adopted and the trust value of the node is constructed with the direct trust value and the indirect trust value. In addition, delivery delay and packet loss are considered as main QoS metrics. Finally, under the optimization ability of PSO, the proposed algorithm tries to find the route with maximum residual energy and reliability in order to maximize network utilization as well as meets QoS constraints. Compared to typical routing algorithms in sensor networks, this new algorithm has better performance.