A Quality of Service Anycast Routing Algorithm Based on Improved Ant Colony Optimization

2013 ◽  
Vol 8 (4) ◽  
Author(s):  
Yongsheng Li
Keyword(s):  
Quality Of Service ◽  
Ant Colony Optimization ◽  
Routing Algorithm ◽  
Ant Colony ◽  
Anycast Routing

scholarly journals A Quality of Service Routing Algorithm in Wireless Sensor Networks

2017 ◽  
Vol 13 (07) ◽  
pp. 47
Author(s):  
Xiaoqing Yang
Keyword(s):  
Wireless Sensor Networks ◽  
Quality Of Service ◽  
Sensor Networks ◽  
Ant Colony Optimization ◽  
Routing Algorithm ◽  
Secure Routing ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Font Size

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">An Quality of Service(QOS) secure routing algorithm based on ant colony optimization is put forward to solve a variety of security problems in wireless sensor networks. The algorithm combines the ant colony optimization algorithm with the cr</span><span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-ansi-language: EN-US; mso-fareast-font-family: 'Times New Roman'; mso-fareast-language: DE; mso-bidi-language: AR-SA;" lang="EN-US">edit evaluation mechanism, and introduces the node 's credit as the control factor to obtain better security performance. The algorithm first cuts the network topology according to the QOS requirements, kicks out the nodes that do not meet the QOS requirements, and then quickly converges the route to the optimal route according to the ant colony optimization method. Finally, the security analysis of the algorithm is carried out from various aspects of network layer attack.</span><span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US"> The experimental results show that the algorithm has very good performance in wireless sensor networks. As a result, it is concluded that it can be widely applied in wireless sensor networks.</span>

An Adapted Ant-Inspired Algorithm for Enhancing Web Service Composition

2017 ◽  
Vol 13 (4) ◽  
pp. 181-197 ◽  
Author(s):  
Fadl Dahan ◽  
Khalil El Hindi ◽  
Ahmed Ghoneim
Keyword(s):  
Quality Of Service ◽  
Web Service ◽  
Ant Colony Optimization ◽  
Service Composition ◽  
Web Service Composition ◽  
Ant Colony ◽  
User Requirements ◽  
Diverse Population ◽  
Flexible Framework

Web Service Composition (WSC) provides a flexible framework for integrating independent web services to satisfy complex user requirements. WSC aims to choose the best web service from a set of candidates. The candidates have the same functionality and different non-functional criteria such as Quality of Service (QoS). In this work, the authors propose an ant-inspired algorithm for such problem. They named it Flying Ant Colony Optimization (FACO). Flying ants inject pheromone not only on the nodes on their paths but also on neighboring nodes increasing their chances of being explored in future iterations. The amount of pheromone deposited on these neighboring nodes is inversely proportional to the distance between them and the nodes on the path. The authors believe that by depositing pheromone on neighboring nodes, FACO may consider a more diverse population of solutions, which may avoid stagnation. The empirical experiments show that FACO outperform Ant Colony Optimization (ACO) for the WSC problem, in terms of the quality of solutions but it requires slightly more execution time.

An Adapted Ant-Inspired Algorithm for Enhancing Web Service Composition

Web Services ◽  
2019 ◽  
pp. 904-921
Author(s):  
Fadl Dahan ◽  
Khalil El Hindi ◽  
Ahmed Ghoneim
Keyword(s):  
Quality Of Service ◽  
Web Service ◽  
Ant Colony Optimization ◽  
Service Composition ◽  
Execution Time ◽  
Web Service Composition ◽  
Ant Colony ◽  
Diverse Population ◽  
Flexible Framework

Web Service Composition (WSC) provides a flexible framework for integrating independent web services to satisfy complex user requirements. WSC aims to choose the best web service from a set of candidates. The candidates have the same functionality and different non-functional criteria such as Quality of Service (QoS). In this work, the authors propose an ant-inspired algorithm for such problem. They named it Flying Ant Colony Optimization (FACO). Flying ants inject pheromone not only on the nodes on their paths but also on neighboring nodes increasing their chances of being explored in future iterations. The amount of pheromone deposited on these neighboring nodes is inversely proportional to the distance between them and the nodes on the path. The authors believe that by depositing pheromone on neighboring nodes, FACO may consider a more diverse population of solutions, which may avoid stagnation. The empirical experiments show that FACO outperform Ant Colony Optimization (ACO) for the WSC problem, in terms of the quality of solutions but it requires slightly more execution time.

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