Swarm Intelligence Based Self-organizing QoS Framework for Ever-changing Future Networks

Cited 1 time in webofscience Cited 0 time in scopus
  • Hit : 335
  • Download : 3
We consider a new QoS framework for a wide range of multimedia services in ever-changing networks where traffic is dynamic and network topologies frequently change. In this paper, for such networks, we propose a new self-organizing QoS framework called AntQoS, which is inspired by recent works on ant colony optimization. Compared with previous QoS frameworks, AntQoS provides two quite promising capabilities: 1) the self-organized network QoS (not pre-defined QoS), which autonomously reconfigures itself by promptly adapting to changing network environments such as sudden arrivals of highly bursty traffic, and 2) the self-organized network controls, which autonomously resolve the network congestion and intrinsically resist the multiple network failures. These two promising capabilities enable the proposed AntQoS framework to efficiently and reliably support a wide range of multimedia services with various quality demands. Especially, these capabilities are provided by making use of swarm intelligence of artificial ants without any supervised control. For this purpose, AntQoS employs one single artificial ant colony on an ever-changing network; a number of artificial ants in the employed colony explore network and measure or gather the status information about the networks. Based on the gathered information, AntQoS organizes and maintains a small number of virtual sub colonies named QoS colonies. The QoS colony is an intelligent virtual colony to be capable of searching the path which guarantees the given quality demands of flows. In addition, it is autonomously generated, maintained, and deleted for promptly adapting to the ever-changing network status. Simulation results demonstrate that AntQoS successfully supports various multimedia services with diverse delay requirements while increasing the network throughput by approximately 20% compared to the well-known IntServ frameworks. Simulation results also show that AntQoS autonomously redistributes the congested traffic and resists the unexpected network failures.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2013-12
Language
English
Article Type
Article
Keywords

ANT COLONY OPTIMIZATION; PATH SELECTION ALGORITHMS; WAVELENGTH ASSIGNMENT; PERFORMANCE

Citation

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, v.31, no.12, pp.735 - 749

ISSN
0733-8716
DOI
10.1109/JSAC.2013.SUP2.1213006
URI
http://hdl.handle.net/10203/187354
Appears in Collection
EE-Journal Papers(저널논문)
Files in This Item
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 1 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0