DocumentCode :
3492447
Title :
Bio-inspired balanced tree structure dynamic network
Author :
Liu, Fengchen ; Ding, Yongsheng ; Gao, WeiXun
Author_Institution :
Coll. of Inf. Sci. & Technol., Donghua Univ., Shanghai, China
fYear :
2011
fDate :
July 31 2011-Aug. 5 2011
Firstpage :
222
Lastpage :
229
Abstract :
Bio-networks have the natural advantages of autonomy, scalability, and adaptability which are challenges for computer networks, especially P2P networks. We present a bio-inspired dynamic balanced tree structure network (called bio-block) based dynamic network. Every bio-block is a unique bio-entities collection with emergent service. This network has two parts, non-Service part (bio-entity is unit node) and in-Service part (bio-block is unit node). Useful bio-entities are dynamically transferring between these two part to keep the balance, and improve resources usage. This network inherits the balanced structure and O(nlogN) search steps with total N resources and n resources service request. It also eliminates redundancies by taking advantage of strong adaptability of bio-network which are composed of bio-entities. Any node in this balanced tree structured network can join and leave dynamically. Intensive experimental results show that the state of this network is converged when service distribution is stable. Moreover, theoretical results support an efficient search operation.
Keywords :
bio-inspired materials; computational complexity; network theory (graphs); peer-to-peer computing; resource allocation; search problems; trees (mathematics); P2P network; balanced tree structured network; bioinspired balanced tree structure dynamic network; computer network; emergent service; in-service part; nonservice part; service distribution; unique bioentities collection; Biological system modeling; Heuristic algorithms; Immune system; Redundancy; Routing; Silicon;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), The 2011 International Joint Conference on
Conference_Location :
San Jose, CA
ISSN :
2161-4393
Print_ISBN :
978-1-4244-9635-8
Type :
conf
DOI :
10.1109/IJCNN.2011.6033225
Filename :
6033225
Link To Document :
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