Dynamic tuning of the IEEE 802.11 protocol to achieve a theoretical throughput limit
IEEE/ACM Transactions on Networking (TON)
Centralized channel assignment and routing algorithms for multi-channel wireless mesh networks
ACM SIGMOBILE Mobile Computing and Communications Review
CapProbe: a simple and accurate capacity estimation technique
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
Bandwidth estimation in broadband access networks
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
A measurement study of path capacity in 802.11b based wireless networks
WiTMeMo '05 Papers presented at the 2005 workshop on Wireless traffic measurements and modeling
Capacity of multi-channel wireless networks: impact of number of channels and interfaces
Proceedings of the 11th annual international conference on Mobile computing and networking
Characterizing the capacity region in multi-radio multi-channel wireless mesh networks
Proceedings of the 11th annual international conference on Mobile computing and networking
Wireless mesh networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
The capacity of wireless networks
IEEE Transactions on Information Theory
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Accurate capacity measures for a path in wireless mesh network can be useful to many applications, including routing protocol design, QoS guarantees, congestion control and other related areas. In this paper, we propose the local virtual probing analytical model. A linear programming problem of both channel assignment and packet scheduling is formulated to determine the capacity of any given path, and hence we propose a path capacity evaluating algorithm based on greedy strategy (PCEAGS) to solve it. Finally, we discuss the impact of several factors, such as hop count of path, amount of packets and numbers of available channels and radios per node, on the accuracy of PCEAGS in detail. The result shows that our algorithm can estimate path capacity accurately in lower average time complexity and also has better expansibility.