Autonomous Distributed Congestion Control Scheme in WCDMA Network

Hafiz Farooq AHMAD
Muhammad Qaisar CHOUDHARY
Muhammad Umer KHAN

IEICE TRANSACTIONS on Information and Systems   Vol.E91-D    No.9    pp.2267-2275
Publication Date: 2008/09/01
Online ISSN: 1745-1361
DOI: 10.1093/ietisy/e91-d.9.2267
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (IEICE/IEEE Joint Special Section on Autonomous Decentralized Systems Theories and Application Deployments)
case based reasoning,  congestion control,  high assurance,  radio resource management,  service level agreement,  intelligent agents,  

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Wireless technology has become widely popular and an important means of communication. A key issue in delivering wireless services is the problem of congestion which has an adverse impact on the Quality of Service (QoS), especially timeliness. Although a lot of work has been done in the context of RRM (Radio Resource Management), the deliverance of quality service to the end user still remains a challenge. Therefore there is need for a system that provides real-time services to the users through high assurance. We propose an intelligent agent-based approach to guarantee a predefined Service Level Agreement (SLA) with heterogeneous user requirements for appropriate bandwidth allocation in QoS sensitive cellular networks. The proposed system architecture exploits Case Based Reasoning (CBR) technique to handle RRM process of congestion management. The system accomplishes predefined SLA through the use of Retrieval and Adaptation Algorithm based on CBR case library. The proposed intelligent agent architecture gives autonomy to Radio Network Controller (RNC) or Base Station (BS) in accepting, rejecting or buffering a connection request to manage system bandwidth. Instead of simply blocking the connection request as congestion hits the system, different buffering durations are allocated to diverse classes of users based on their SLA. This increases the opportunity of connection establishment and reduces the call blocking rate extensively in changing environment. We carry out simulation of the proposed system that verifies efficient performance for congestion handling. The results also show built-in dynamism of our system to cater for variety of SLA requirements.