Research Article
Resource Management in Heterogenous Wireless Networks with Overlapping Coverage
@INPROCEEDINGS{10.1109/COMSWA.2006.1665214, author={Bin Bin Chen and Mun Choon Chan}, title={Resource Management in Heterogenous Wireless Networks with Overlapping Coverage}, proceedings={1st International ICST Conference on Communication System Software and MiddleWare}, publisher={IEEE}, proceedings_a={COMSWARE}, year={2006}, month={8}, keywords={}, doi={10.1109/COMSWA.2006.1665214} }- Bin Bin Chen
Mun Choon Chan
Year: 2006
Resource Management in Heterogenous Wireless Networks with Overlapping Coverage
COMSWARE
IEEE
DOI: 10.1109/COMSWA.2006.1665214
Abstract
Development in new radio technologies and increase in user demands are driving the deployment of a wide array of wireless networks, ranging from 802.11 networks in the local area, to third generation data-only wireless networks in the wide area. With their complementary characteristics, these heterogeneous radio access technologies (RATs) are expected to be integrated together to provide mobile users "always best connections". Base stations (BS) using different RATs will coexist and have arbitrary overlapping coverage without interfering with each other, and mobile stations (MS) equipped with multi-interfaces or "software defined radio" technology can be associated with one or more BSs using different RATs. In this work, we study the common radio resource management (CRRM) problem, i.e., how should the network manager of these integrated heterogeneous wireless networks jointly allocate resources from various networks such that the scarce radio resources are used efficiently. We focus on applications with bandwidth reservation requirement, such as voice or video calls. We extend earlier works to consider the different increase in load when a single MS request is assigned to different BSs, due to independent channel condition and adaptive modulation/coding efficiency among different MS-BS pairs. We formalize CRRM problem as an online load balancing problem for temporary tasks with unrelated processors, and represent the input of problem using a weighted BS-MS graph, with a weighted BS-region graph as its compact form. We study the computational complexity for the optimal solution. We also characterize the competitive ratio for general online algorithms by exploiting combinatorial properties of the weighted BS-region graph. Cluster algorithm, which decomposes the whole area into disjoint clusters can potentially achieve a lower competitive ratio. However, its stochastic performance largely depends on the traffic distribution symmetry