An efficient method to schedule tandem of real-time tasks in cluster computing with possible processor failures

Abstract

Each computer system in operation today is certain to experience faults in its operational lifetime. There is more than one source, which can cause faults, for example environmental factors, communication, interaction with users, or hardware and software design flaws randomly build into the system. A reliable system is the one that would continue operation albeit in a degraded mode despite the presence of faults. In this paper, we introduce an efficient method to schedule a tandem of real-time tasks in cluster computing with possible processor failures. The method is based on developing an objective function that combines different scheduling goals. This objective function is used to guide the search algorithm to find an efficient solution. The proposed algorithm consists of three terms, reliability, deadline and tasks grouping to minimize remote communication among tasks. The proposed method creates a scheduling table based on the objective function then searches this table for a feasible solution. The method is efficient because it reduces communication between different tasks by grouping them together. This grouping process reduces application de-fragmentation as well.

Grid Resource Availability Prediction-Based Scheduling and Task Replication

“…We remove all of these assumptions in our work, and utilize availability and load traces from real resources. Amin et al [2] use an objective function to maximize reliability while still meeting a real time deadline. They search a scheduling table for a set of homogenous non-dedicated processors to execute tandem real-time tasks.…”

“…2) consider forecasts about the future availability and load of resources, and -Load Adaptive techniques (Section 7.4) change their behavior based on observed system load.…”

QoS-Aware Fault-Tolerant Scheduling for Real-Time Tasks on Heterogeneous Clusters

“…Growing evidence shows that scheduling is an efficient approach to achieving high performance of applications in parallel systems like clusters. A wide variety of scheduling algorithms have been developed to provide fault tolerance for clusters supporting real-time applications in the past decade (see, for example, [11], [12]). Many QoS-based scheduling algorithms were proposed for realtime applications in distributed systems in addition to parallel systems [13], [14], [15].…”