DocumentCode :
31495
Title :
A Survey on Biologically Inspired Algorithms for Computer Networking
Author :
Chenyu Zheng ; Sicker, D.C.
Author_Institution :
Dept. of Comput. Sci., Univ. of Colorado at Boulder, Boulder, CO, USA
Volume :
15
Issue :
3
fYear :
2013
fDate :
Third Quarter 2013
Firstpage :
1160
Lastpage :
1191
Abstract :
Biologically Inspired Algorithms (BIAs), processes that mimic how organisms solve problems, offer a number of attributes well suited to addressing challenges presented by future computer networking scenarios. Such future networks will require more scalable, adaptive and robust designs to address the dynamic changes and potential failures caused by high heterogeneity and large scale networks. A variety of biological algorithms demonstrate characteristics desirable to network design, and significant effort has been placed on analyzing and developing the corresponding BIAs and applying them to computer networking applications. This paper provides a comprehensive survey of BIAs for the computer networking field, in which different BIAs are organized and explored based on their: (1) biological source; (2) mathematical model; (3) major application; (4) advantages to corresponding "classic" approach; (5) limitations and border conditions; and (6) potential directions for future applications. The paper also compares performance amongst each type of BIA, and compares BIAs that are inspired by different biological sources but are applicable to similar networking applications. The paper concludes by offering a framework for understanding the application of BIAs to problems in the computer networking space.
Keywords :
bio-inspired materials; computer networks; biologically inspired algorithms; computer networking; dynamic changes; large scale networks; Algorithm design and analysis; Biological system modeling; Computer security; Routing; artificial immune systems; biological symbiosis; biologically inspired algorithms; cellular signaling networks; chemotaxis and morphogenesis; computer networking; corpse clustering and brood sorting; division of labor; foraging; homeostasis; information epidemics; pattern formation; predator-prey relationship; pulse-coupled oscillator; self-organization;
fLanguage :
English
Journal_Title :
Communications Surveys & Tutorials, IEEE
Publisher :
ieee
ISSN :
1553-877X
Type :
jour
DOI :
10.1109/SURV.2013.010413.00175
Filename :
6422291
Link To Document :
بازگشت