A Clonal Selection Algorithm for Energy-Efficient Mobile Agent Itinerary Planning in Wireless Sensor Networks

2017 ◽  
Vol 23 (5) ◽  
pp. 1233-1246 ◽  
Author(s):  
Yu-Cheng Chou ◽  
Madoka Nakajima
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Mobile Agent ◽  
Energy Efficient ◽  
Clonal Selection ◽  
Wireless Sensor ◽  
Clonal Selection Algorithm ◽  
Selection Algorithm ◽  
Itinerary Planning

scholarly journals Replica Node Detection Using Enhanced Single Hop Detection with Clonal Selection Algorithm in Mobile Wireless Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
L. S. Sindhuja ◽  
G. Padmavathi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Clonal Selection ◽  
Wireless Sensor ◽  
Clonal Selection Algorithm ◽  
Selection Algorithm ◽  
Mobile Wireless ◽  
Mobile Wireless Sensor Networks ◽  
Detection Ratio ◽  
Mobile Wireless Sensor

Security of Mobile Wireless Sensor Networks is a vital challenge as the sensor nodes are deployed in unattended environment and they are prone to various attacks. One among them is the node replication attack. In this, the physically insecure nodes are acquired by the adversary to clone them by having the same identity of the captured node, and the adversary deploys an unpredictable number of replicas throughout the network. Hence replica node detection is an important challenge in Mobile Wireless Sensor Networks. Various replica node detection techniques have been proposed to detect these replica nodes. These methods incur control overheads and the detection accuracy is low when the replica is selected as a witness node. This paper proposes to solve these issues by enhancing the Single Hop Detection (SHD) method using the Clonal Selection algorithm to detect the clones by selecting the appropriate witness nodes. The advantages of the proposed method include (i) increase in the detection ratio, (ii) decrease in the control overhead, and (iii) increase in throughput. The performance of the proposed work is measured using detection ratio, false detection ratio, packet delivery ratio, average delay, control overheads, and throughput. The implementation is done using ns-2 to exhibit the actuality of the proposed work.

scholarly journals A Spawn Mobile Agent Itinerary Planning Approach for Energy-Efficient Data Gathering in Wireless Sensor Networks

Sensors ◽  
2017 ◽  
Vol 17 (6) ◽  
pp. 1280 ◽  
Author(s):  
Huthiafa Qadori ◽  
Zuriati Zulkarnain ◽  
Zurina Hanapi ◽  
Shamala Subramaniam
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Mobile Agent ◽  
Energy Efficient ◽  
Data Gathering ◽  
Wireless Sensor ◽  
Itinerary Planning ◽  
Planning Approach ◽  
Efficient Data

scholarly journals Multi-mobile agent itinerary planning algorithms for data gathering in wireless sensor networks: A review paper

2017 ◽  
Vol 13 (1) ◽  
pp. 155014771668484 ◽  
Author(s):  
Huthiafa Q Qadori ◽  
Zuriati A Zulkarnain ◽  
Zurina Mohd Hanapi ◽  
Shamala Subramaniam
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Mobile Agent ◽  
Mobile Agents ◽  
Single Agent ◽  
Data Gathering ◽  
Optimal Number ◽  
Wireless Sensor ◽  
Itinerary Planning ◽  
Multi Agent

Recently, wireless sensor networks have employed the concept of mobile agent to reduce energy consumption and obtain effective data gathering. Typically, in data gathering based on mobile agent, it is an important and essential step to find out the optimal itinerary planning for the mobile agent. However, single-agent itinerary planning suffers from two primary disadvantages: task delay and large size of mobile agent as the scale of the network is expanded. Thus, using multi-agent itinerary planning overcomes the drawbacks of single-agent itinerary planning. Despite the advantages of multi-agent itinerary planning, finding the optimal number of distributed mobile agents, source nodes grouping, and optimal itinerary of each mobile agent for simultaneous data gathering are still regarded as critical issues in wireless sensor network. Therefore, in this article, the existing algorithms that have been identified in the literature to address the above issues are reviewed. The review shows that most of the algorithms used one parameter to find the optimal number of mobile agents in multi-agent itinerary planning without utilizing other parameters. More importantly, the review showed that theses algorithms did not take into account the security of the data gathered by the mobile agent. Accordingly, we indicated the limitations of each proposed algorithm and new directions are provided for future research.

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