A Strategy for Tuning the Performance of Distributed Shared Memory Systems

Abstract

The increasing demands of distributed and parallel applications require sufficiently high-performance distributed shared memory algorithms capable of providing the service almost steadily. Past and recent decades witnessed the introduction of number of algorithms and strategies aim at tuning and optimizing the performance of distributed systems and at extending the scalability of the systems. This paper presents a new strategy that adjoins an intermediate level of control to the system to scale up the performance via relieving the overhead at the main server. This strategy can be implemented at both setupand run-time.