Evolution of Planning for Wireless Communication Systems
HICSS '03 Proceedings of the 36th Annual Hawaii International Conference on System Sciences (HICSS'03) - Track 9 - Volume 9
Tighter Bounds for Graph Steiner Tree Approximation
SIAM Journal on Discrete Mathematics
Mobile backbone networks --: construction and maintenance
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
Minimum-cost coverage of point sets by disks
Proceedings of the twenty-second annual symposium on Computational geometry
Relay Node Placement in Wireless Sensor Networks
IEEE Transactions on Computers
Mono- and multiobjective formulations for the indoor wireless LAN planning problem
Computers and Operations Research
Additive approximation for bounded degree survivable network design
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Assessment of urban-scale wireless networks with a small number of measurements
Proceedings of the 14th ACM international conference on Mobile computing and networking
Optimization models for the radio planning of wireless mesh networks
NETWORKING'07 Proceedings of the 6th international IFIP-TC6 conference on Ad Hoc and sensor networks, wireless networks, next generation internet
DTN support for news dissemination in an urban area
NETWORKING'11 Proceedings of the 10th international IFIP TC 6 conference on Networking - Volume Part I
DTN support for news dissemination in an urban area
Computer Networks: The International Journal of Computer and Telecommunications Networking
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Wireless mesh networks are popular as a cost-effective means to provide broadband connectivity to large user populations. A mesh network placement provides coverage, such that each target client location has a link to a deployed mesh node, and connectivity, such that each mesh node wirelessly connects directly to a gateway or via intermediate mesh nodes. Prior work on placement assumes wireless propagation to be uniform in all directions, i.e., an unrealistic assumption of circular communication regions. In this paper, we present approximation algorithms to solve the NP-hard mesh node placement problem for non-uniform propagation settings. The first key challenge is incorporating non-uniform propagation, which we address by formulating the problem input as a connectivity graph consisting of discrete target coverage locations and potential mesh node locations. This graph incorporates non-uniform propagation by specifying the estimated signal quality per link. Secondly, our algorithms are the first to minimize the number of deployed mesh nodes with constant-factor approximation ratio in the non-uniform propagation setting. To achieve this, we formulate the Degree-Constrained Terminal Steiner tree problem and present approximation algorithms which leverage prior results on the Steiner tree problem. Third, it is impractical to measure all possible potential mesh links, and therefore deployment planning must rely on estimations. To address this challenge, we extend our algorithm to iteratively measure the links in the solution Steiner tree, refining the graph input on a per-link basis in order to ensure the deployed network is not disconnected. Finally, we use propagation measurements at 35,000 locations in the deployed GoogleWiFi network to investigate placement in a realistic, non-uniform propagation environment. Under this measured propagation setting, our algorithms result in up to 80% fewer mesh nodes than current algorithms and only require an average of 3 measurements per deployed mesh node to ensure backhaul connectivity.