Scheduled System Maintenance:
Some services will be unavailable Sunday, March 29th through Monday, March 30th. We apologize for the inconvenience.
By Topic

Modeling and Performance Evaluation of Reconfiguration Decision Making in Heterogeneous Radio Network Environments

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.

The purchase and pricing options are temporarily unavailable. Please try again later.
3 Author(s)
Patouni, E. ; Dept. of Inf. & Telecommun., Univ. of Athens, Athens, Greece ; Alonistioti, N. ; Merakos, L.

In heterogeneous radio network environments, the incorporation of dynamic adaptation capabilities in the protocol stack of mobile devices is an important challenge. In this direction, an appropriate model of the network decision-making process for mobile device adaptation is presented. Two main adaptation alternatives are assumed: (1) handover and (2) protocol reconfiguration. We consider two classes of mobile devices, i.e., reconfigurable and autonomous; the difference between them lies on the degree by which they support the decision-making functionality. An algorithmic framework for the management of the decision-making requests for reconfiguration or handovers is proposed. This work is based on the introduced metric of user satisfaction, which is based on the network response time for serving the decision-making requests. Such a framework is important for guiding the relocation of mobile terminals to achieve offloading. Furthermore, an analytical model for the computation of the user satisfaction is introduced, based on the work by Litoiu The analysis uses multiclass queuing networks to model the requests to the network as transactions among the system entities and compute the user satisfaction and the required parameters, e.g., network response time bounds. The obtained results show how the global bounds on the asymptotic network response time and throughput per class are affected by the number and frequency of reconfiguration decision requests. The analysis quantifies how the increase in the autonomicity level of mobile devices affects the network load and how to maximize the percentage of requests handled by the network, compared with the percentage of dropped requests. Moreover, our work reveals the degree of performance deterioration caused by increasing the autonomicity level in the management of requests.

Published in:

Vehicular Technology, IEEE Transactions on  (Volume:59 ,  Issue: 4 )