T Ask S Cheduling M Odel in H Eterogeneous D Istributed C Omputing S Ystems - a R Eview

— In the present scenario the differences amongst collecting, transporting, storing and processing information are quickly disappearing. As our ability to gather, process and distribute information grows the demand for even more sophisticated information processing system grows much faster. Distributed Computing is an optimal solution to fulfill these ever-changing demands. Distributed Computing Systems (DCS) consist of loosely coupled processors which communicate with one another only by passing messages and which do not have common memory. The DCS are increasingly drawing attention, yet have a meaning that is not understood. The term ‘Distributed Computing System’ is used to describe system with multiple processors. However, the term has different meaning to different systems because processors can be interconnected in many ways for assorted reasons. All practical real-time scheduling algorithms in distributed computing systems present a trade-off between their computational complexity and performance. In real-time systems, tasks should be performed correctly and timely. Finding minimal schedule in distributed systems with real-time constraints is shown to be NP-hard. Although some optimal algorithms have been employed in uni-processor systems, they fail when they are applied in distributed computing environment. The practical scheduling algorithms in real-time systems have not deterministic response time. Deterministic timing behavior is an important parameter for system robustness analysis. The intrinsic uncertainty in dynamic real-time systems increases the difficulties of scheduling problem. In this paper we alleviate these difficulties, and shown that there is a need to develop a scheduling approach to arrange real-time periodic and non-periodic tasks in heterogeneous distributed systems. Static and dynamic optimal scheduling algorithms fail with non-critical overload. In contrast, a balanced approach is required to be developed which may balance task loads of the processors successfully while consider starvation prevention and fairness which cause higher priority tasks to have higher running probability.)