A Trustworthy QoS Unicast Routing Scheme Based on Population Adaptive Based Immune Algorithm
In this paper, a trustworthy QoS unicast routing scheme based on trustworthy network is proposed. First, a cognitive network model is designed, referring to the intelligence of artificial immune system. Then, trustworthiness of each node is evaluated by deploying sliding window mechanism and analyzi...
Saved in:
| Published in: | Applied Mechanics and Materials Vol. 602-605; no. Advanced Manufacturing and Information Engineering, Intelligent Instrumentation and Industry Development; pp. 3084 - 3087 |
|---|---|
| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Zurich
Trans Tech Publications Ltd
11.08.2014
|
| Subjects: | |
| ISBN: | 9783038351948, 3038351946 |
| ISSN: | 1660-9336, 1662-7482, 1662-7482 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | In this paper, a trustworthy QoS unicast routing scheme based on trustworthy network is proposed. First, a cognitive network model is designed, referring to the intelligence of artificial immune system. Then, trustworthiness of each node is evaluated by deploying sliding window mechanism and analyzing the behavior record of each node. Finally, a population adaptive based immune of trustworthy QoS unicast routing algorithm is proposed, referring to the adaptive process of antibody identifying antigen. We verify the effectiveness of our scheme by using large-scale computer emulation experiments and compare it to existing classical algorithms. The results show that the proposed algorithm is both feasible and effective for providing users with better QoS, etc. |
|---|---|
| Bibliography: | Selected, peer reviewed papers from the 2014 2nd International Conference on Precision Mechanical Instruments and Measurement Technology (ICPMIMT 2014), May 30-31, 2014, Chongqing, China ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| ISBN: | 9783038351948 3038351946 |
| ISSN: | 1660-9336 1662-7482 1662-7482 |
| DOI: | 10.4028/www.scientific.net/AMM.602-605.3084 |

