Data networks
Optimization flow control—I: basic algorithm and convergence
IEEE/ACM Transactions on Networking (TON)
Fair end-to-end window-based congestion control
IEEE/ACM Transactions on Networking (TON)
Impact of fairness on Internet performance
Proceedings of the 2001 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Understanding TCP Vegas: a duality model
Journal of the ACM (JACM)
On achieving fairness and efficiency in high-speed shared medium access
IEEE/ACM Transactions on Networking (TON)
A Definition of General Weighted Fairness and its Support in Explicit Rate Switch Algorithms
ICNP '98 Proceedings of the Sixth International Conference on Network Protocols
End-to-end congestion control schemes: utility functions, random losses and ECN marks
IEEE/ACM Transactions on Networking (TON)
Design, analysis, and implementation of DVSR: a fair high-performance protocol for packet rings
IEEE/ACM Transactions on Networking (TON)
A packet scheduling approach to QoS support in multihop wireless networks
Mobile Networks and Applications
A comparison of complete global optimization solvers
Mathematical Programming: Series A and B
IEEE 802.17 resilient packet ring tutorial
IEEE Communications Magazine
General weighted fairness and its support in explicit rate switch algorithms
Computer Communications
A novel proposal to improve fairness in TCP Reno
International Journal of Communication Networks and Distributed Systems
Evaluation approach for efficiency: fairness tradeoff on the internet
SoftCOM'09 Proceedings of the 17th international conference on Software, Telecommunications and Computer Networks
A general branch-and-bound algorithm for fair division problems
Computers and Operations Research
| Hi-index | 0.01 |
Introducing a new concept of (@a,@b)-fairness, which allows for a bounded fairness compromise, so that a source is allocated a rate neither less than 0==1, times its fair share, this paper provides a framework to optimize efficiency (utilization, throughput or revenue) subject to fairness constraints in a general telecommunications network for an arbitrary fairness criterion and cost functions. We formulate a non-linear program (NLP) that finds the optimal bandwidth allocation by maximizing efficiency subject to (@a,@b)-fairness constraints. This leads to what we call an efficiency-fairness function, which shows the benefit in efficiency as a function of the extent to which fairness is compromised. To solve the NLP we use two algorithms. The first is a well-known branch-and-bound-based algorithm called Lipschitz Global Optimization and the second is a recently developed algorithm called Algorithm for Global Optimization Problems (AGOP). We demonstrate the applicability of the framework to a range of examples from sharing a single link to efficiency fairness issues associated with serving customers in remote communities.