On calculating connected dominating set for efficient routing in ad hoc wireless networks
DIALM '99 Proceedings of the 3rd international workshop on Discrete algorithms and methods for mobile computing and communications
Capacity of Ad Hoc wireless networks
Proceedings of the 7th annual international conference on Mobile computing and networking
Approximating minimum size weakly-connected dominating sets for clustering mobile ad hoc networks
Proceedings of the 3rd ACM international symposium on Mobile ad hoc networking & computing
Optimizing the Placement of Internet TAPs in Wireless Neighborhood Networks
ICNP '04 Proceedings of the 12th IEEE International Conference on Network Protocols
Gateway Placement for Latency and Energy Efficient Data Aggregation
LCN '04 Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks
Efficient integration of multihop wireless and wired networks with QoS constraints
IEEE/ACM Transactions on Networking (TON)
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A wireless mesh network (WMN) composed of multiple access-points (APs) that communicate mutually using radio transmissions, and all the traffics to/from the Internet are aggregated and go through the limited number of gateway APs. The meshed topology provides good reliability, market coverage, and scalability, as well as low upfront investment. However, due to the nature of routing algorithm the traffic load for a access point may be extremely heavy during particular periods while the other access points are in very light load. Consequently, the overall performance of the network are poor even the total traffic load is far below the system capacity. The performance can be improved dramatically by Traffic Balancing. Strategically placing and connecting the gateways to the wired backbone is critical to the management and efficient operation of a WMN. In this paper, we address the problem of gateway access-points placement, consisting in placing a minimum number of gateways such that quality-of-service (QoS) requirements are satisfied. We propose a genetic algorithm that consistently preserves QoS requirements. We evaluate the performance of our algorithm using both analysis and simulation, and show that it outperforms other alternative schemes by comparing the number of gateways placed in different scenarios.