Data networks
Intelligent congestion control for ABR service in ATM networks
ACM SIGCOMM Computer Communication Review
The ERICA switch algorithm for ABR traffic management in ATM networks
IEEE/ACM Transactions on Networking (TON)
An efficient rate allocation algorithm for ATM networks providing max-min fairness
Proceedings of the IFIP Sixth International Conference on High Performance Networking VI
Minimum Rate Guarantee without Per-Flow Information
ICNP '99 Proceedings of the Seventh Annual International Conference on Network Protocols
The rate-based flow control framework for the available bit rate ATM service
IEEE Network: The Magazine of Global Internetworking
A decentralized resource allocation policy in minigrid
Future Generation Computer Systems
Bandwidth Management for Supporting Differentiated Service Aware Traffic Engineering
IEEE Transactions on Parallel and Distributed Systems
Steady and fair rate allocation for rechargeable sensors in perpetual sensor networks
Proceedings of the 6th ACM conference on Embedded network sensor systems
Perpetual and fair data collection for environmental energy harvesting sensor networks
IEEE/ACM Transactions on Networking (TON)
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Abstract--This paper considers the fundamental problem of bandwidth allocation among flows in a packet-switched network. The classical max-min rate allocation has been widely regarded as a fair rate allocation policy. But, for a flow with a minimum rate requirement and a peak rate constraint, the classical max-min policy no longer suffices to determine rate allocation since it is not capable of supporting either the minimum rate or the peak rate constraint from a flow. In this paper, we generalize the theory of the classical max-min rate allocation with the support of both the minimum rate and peak rate constraints for each flow. Additionally, to achieve generalized max-min rate allocation in a fully distributed packet network, we present a distributed algorithm that uses a feedback-based flow control mechanism. Our design not only offers a fresh perspective on flow marking technique, but also advances the state-of-the-art flow marking technique favored by other researchers. We provide proof that such a distributed algorithm, through asynchronous iterations, will always converge to the generalized max-min rate allocation under any network configuration and any set of link distances. We use simulation results to demonstrate the fast convergence property of the distributed algorithm.