Wireless Networks - Special issue: mobile computing and networking: selected papers from MobiCom '96
An Introduction to GSM
Introduction to 3G Mobile Communications
Introduction to 3G Mobile Communications
Integrating heterogeneous wireless technologies: a cellular aided mobile Ad Hoc network (CAMA)
Mobile Networks and Applications
Handover Performance of Dynamic Load Balancing Schemes in Cellular Networks
ISCC '05 Proceedings of the 10th IEEE Symposium on Computers and Communications
Theory, Volume 1, Queueing Systems
Theory, Volume 1, Queueing Systems
Load-Balanced Short-Path Routing in Wireless Networks
IEEE Transactions on Parallel and Distributed Systems
Load balancing in the call admission control of heterogeneous wireless networks
Proceedings of the 2006 international conference on Wireless communications and mobile computing
802.11 Wireless Networks: The Definitive Guide, Second Edition
802.11 Wireless Networks: The Definitive Guide, Second Edition
Fairness and load balancing in wireless LANs using association control
IEEE/ACM Transactions on Networking (TON)
EURASIP Journal on Wireless Communications and Networking
WiMAX: Technology for Broadband Wireless Access
WiMAX: Technology for Broadband Wireless Access
An adaptive call admission algorithm for cellular networks
Computers and Electrical Engineering
IEEE Wireless Communications
IEEE Transactions on Wireless Communications
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In a heterogeneous wireless network (HWN), traffic is distributed primarily by grouping and channelling identical traffic through a particular access point. In this paper, we introduce an effective traffic load balancing scheme for maximising expected throughput in HWNs. Two scenarios are explored. First, we model multiple APs of a HWN as a cascade of independent M/M/1 queues. The expected number of packets in the system is formulated as a convex optimisation problem and solved using a Lagrange multiplier. A recursive approach is used in distributing the traffic to different APs. Then, we model multiple APs as a union of multiple M/M/1 and M/D/1 queues. Here, we minimise the time spent by each job in the system. We use a solver to obtain optimal rate distribution among the networks. Through extensive simulations, we show that distributing the traffic optimally outperforms existing traditional methods of grouping and channelling similar kind of traffic.