Pseudo-conservation laws in cyclic-service systems with a class of limited service policies
Annals of Operations Research - Special issue on stochastic modeling of telecommunication systems
Informed prefetching and caching
SOSP '95 Proceedings of the fifteenth ACM symposium on Operating systems principles
Application-controlled file caching and prefetching
Application-controlled file caching and prefetching
Aggressive prefetching: an idea whose time has come
HOTOS'05 Proceedings of the 10th conference on Hot Topics in Operating Systems - Volume 10
The Design of a Storage Architecture for Mobile Heterogeneous Devices
ICNS '07 Proceedings of the Third International Conference on Networking and Services
Exploring Gate-Limited Analytical Models for High Performance Network Storage Servers
ICCCN '09 Proceedings of the 2009 Proceedings of 18th International Conference on Computer Communications and Networks
Probability, Markov Chains, Queues, and Simulation: The Mathematical Basis of Performance Modeling
Probability, Markov Chains, Queues, and Simulation: The Mathematical Basis of Performance Modeling
Fundamentals of Queueing Theory
Fundamentals of Queueing Theory
Cyclic-service systems with probabilistically-limited service
IEEE Journal on Selected Areas in Communications
| Hi-index | 0.00 |
Gate-limited service is a type of service discipline found in queueing theory and can be used to describe a number of operational environments, for example, large transport systems such as buses, trains or taxis, etc. Recently, there has been the observation that such systems can also be used to describe interactive Internet Services which use a Client/Server interaction. In addition, new services of this genre are being developed for the local area. One such service is a Network Memory Server (NMS) being developed here at Middlesex University. Though there are several examples of real systems that can be modelled using gate-limited service, it is fair to say that the analytical models which have been developed for gate-limited systems have been difficult to use, requiring many iterations before practical results can be generated. In this paper, a detailed gate-limited bulk service queueing model based on Markov chains is explored and a numerical solution is demonstrated for simple scenarios. Quantitative results are presented and compared with a mathematical simulation. The analysis is used to develop an algorithm based on the concept of optimum operational points. The algorithm is then employed to build a high-performance server which is capable of balancing the need to prefetch for streaming applications while promptly satisfying demand misses. The algorithm is further tested using a systems simulation and then incorporated into an Experimental File System (EFS) which showed that the algorithm can be used in a real networking environment.