By Topic

Mobile agent-based approach for efficient network management and resource allocation: framework and applications

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Papavassiliou, S. ; Dept. of Electr. & Comput. Eng., New Jersey Inst. of Technol., Newark, NJ, USA ; Puliafito, A. ; Tomarchio, O. ; Jian Ye

Agent programming technology has emerged as a flexible and complementary way to manage resources of distributed systems due to the increased flexibility in adapting to the dynamically changing requirements of such systems. A very promising application of this technology is related to the control of forthcoming networking systems which will represent a competitive marketplace with a multitude of vendors, operators and customers. Thus, new reference models have to be investigated in order to better satisfy users' requirements in a framework where resource allocation is provided under the control of different and often competing stakeholders (users, network providers, service providers, etc.). We believe that autonomy is one of the features that will characterize the behavior of agents in such environment: autonomous choices will be taken as the result of coordination among different cooperating software entities. Following this direction, we describe the efficient integration and adoption of mobile agents and genetic algorithms in the implementation of a valuable strategy for the development of effective market based routes for brokering purposes in the future multioperator network marketplace. The proposed genetic algorithm provides a kind of stochastic algorithm searching process in order to identify optimal resource allocation strategies. The agent-based network management approach represents an underlying framework and structure for the multioperator network model, and can be used to facilitate the collection and dissemination of the required management data, as well as the efficient and distributed operation of the algorithm. We also present some numerical results to assess the performance and operation effectiveness of our approach, by applying it in some test case scenarios

Published in:

Selected Areas in Communications, IEEE Journal on  (Volume:20 ,  Issue: 4 )