Effective bandwidths with priorities
IEEE/ACM Transactions on Networking (TON)
Large deviations and the generalized processor sharing scheduling for a multiple-queue system
Queueing Systems: Theory and Applications
Large deviations analysis of the generalized processor sharing policy
Queueing Systems: Theory and Applications
A most probable path approach to queueing systems with general Gaussian input
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Advances in modeling and engineering of Longe-Range dependent traffic
Coordinated multihop scheduling: a framework for end-to-end services
IEEE/ACM Transactions on Networking (TON)
Pricing in next generation networks: a queuing model to guarantee QoS
Performance Evaluation
Optimal call admission control on a single link with a GPS scheduler
IEEE/ACM Transactions on Networking (TON)
Bandwidth Optimization for Internet Traffic in Generalized Processor Sharing Servers
IEEE Transactions on Parallel and Distributed Systems
Queueing processes in GPS and PGPS with LRD traffic inputs
IEEE/ACM Transactions on Networking (TON)
FISTE: A black box approach for end-to-end QoS management
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Capacity requirements of traffic handling schemes in multi-service networks
Computer Communications
Class-specific quality of service guarantees in multimedia communication networks
Automatica (Journal of IFAC)
| Hi-index | 754.84 |
We consider the asymptotic behavior of the queue length distribution in segregated buffers sharing a deterministic server via a class of generalized processor sharing (GPS) policies. Such policies have been proposed as a means to guarantee individual quality of service constraints to heterogeneous streams in integrated services digital networks. These results exhibit the manner in which spare capacity is shared by statistically multiplexed traffic streams. The framework corresponds to a natural relaxation of a single GPS node subject to (σ, ρ)-constrained flows where, instead of studying the worst case behavior, we consider statistical bounds on the performance of individual traffic streams