Performance and Cost Trade-off in Tracking Area Reconfiguration: A Pareto-optimization Approach
2012 (English)In: Computer Networks, ISSN 1389-1286, E-ISSN 1872-7069, Vol. 56, no 1, 157-168 p.Article in journal (Refereed) Published
Tracking Area (TA) design is one of the key tasks in location management of Long Term Evolution (LTE) networks. TA enables to trace and page User Equipments (UEs). As UEs distribution and mobility patterns change over time, TA design may have to undergo revisions. For revising the TA design, the cells to be reconfigured typically have to be temporary torn down. Consequently, this will result in service interruption and “cost”. There is always a trade-off between the performance in terms of the overall signaling overhead of the network and the reconfigurationcost. In this paper, we model this trade-off as a bi-objective optimization problem to which the solutions are characterized by Pareto-optimality. Solving the problem delivers a host of potential trade-offs among which the selection can be based on the preferences of a decision maker. An integer programming model has been developed and applied to the problem. Solving the integer programming model for various cost budget levels leads to an exact scheme for Pareto-optimization. In order to deliver Pareto-optimal solutions for large networks in one single run, a Genetic Algorithm (GA) embedded with Local Search (LS) is applied. Unlike many commonly adopted approaches in multi-objective optimization, our algorithm does not consider any weighted combination of the objectives. Comprehensive numerical results are presented in this study, using large-scale realistic or real-life network scenarios. The experiments demonstrate the effectiveness of the proposed approach.
Place, publisher, year, edition, pages
2012. Vol. 56, no 1, 157-168 p.
Bi-criteria optimization; Reconfiguration; Signaling overhead; Tracking Area
IdentifiersURN: urn:nbn:se:liu:diva-71335DOI: 10.1016/j.comnet.2011.08.017ISI: 000299855200012OAI: oai:DiVA.org:liu-71335DiVA: diva2:447468
funding agencies|CENIIT||Swedish Research Council||Linkoping University||2011-10-122011-10-122012-04-03