Capacity of Ad Hoc wireless networks
Proceedings of the 7th annual international conference on Mobile computing and networking
Introduction to Algorithms
Ad hoc QoS on-demand routing (AQOR) in mobile ad hoc networks
Journal of Parallel and Distributed Computing - Special issue on Routing in mobile and wireless ad hoc networks
Impact of interference on multi-hop wireless network performance
Proceedings of the 9th annual international conference on Mobile computing and networking
Routing in multi-radio, multi-hop wireless mesh networks
Proceedings of the 10th annual international conference on Mobile computing and networking
Optimizing the Placement of Internet TAPs in Wireless Neighborhood Networks
ICNP '04 Proceedings of the 12th IEEE International Conference on Network Protocols
Efficient integration of multihop wireless and wired networks with QoS constraints
IEEE/ACM Transactions on Networking (TON)
Gateway Placement Optimization in Wireless Mesh Networks With QoS Constraints
IEEE Journal on Selected Areas in Communications
Diffusion based distributed internet gateway load balancing in a wireless mesh network
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Genetic algorithms for wireless mesh network planning
Proceedings of the 13th ACM international conference on Modeling, analysis, and simulation of wireless and mobile systems
Zero-Degree algorithm for Internet GateWay placement in backbone wireless mesh networks
Journal of Network and Computer Applications
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In a Wireless Mesh Network (WMN), Mesh Routers (MRs) are interconnected by wireless links and constitute a wireless backbone to provide ubiquitous high-speed Internet connectivity for mobile clients (MCs). The wireless backbone is tightly integrated with the Internet by some selected nodes called as Internet Gateways (IGWs). An IGW has more capabilities than a simple MR and is more expensive. In this paper, we address the IGW deployment problem which is shown to be NP-hard. We first formulate it as a linear program (LP) issue, then develop two heuristic algorithms: Degree based Greedy Dominating Tree Set Partitioning (Degree based GDTSP) and Weight based Greedy Dominating Tree Set Partitioning (Weight based GDTSP), for the purpose of cost-effective IGW deployment. We evaluate the effectiveness of these two algorithms by extensive simulations and comparisons with two major approaches.