Tasks allocation is an important step for obtaining high performance in distributed computing system (DCS). This article attempts to develop a mathematical model for allocating the tasks to the processors in order to achieve optimal cost and optimal reliability of the system. The proposed model has been divided into two stages. Stage-I, makes the ‘n' clusters of set of ‘m' tasks by using k-means clustering technique. To use the k-means clustering techniques, the inter-task communication costs have been modified in such a way that highly communicated tasks are clustered together to minimize the communication costs between tasks. Stage-II, allocates the ‘n' clusters of tasks onto ‘n' processors to minimize the system cost. To design the mathematical model, executions costs and inter tasks communication costs have been taken in the form of matrices. To test the performance of the proposed model, many examples are considered from different research papers and results of examples have compared with some existing models.

No abstract

Distributed computing systems [DCS] offer the potential for allocating a number of tasks to different processors for execution. It is desired to assign the tasks dynamically to that processor whose characteristics are most appropriate for the execution in order to make the best use of the computational power available. This paper proposes a new mathematical model for allocating the tasks of distributed program to multiple processors in order to achieve optimal cost and optimal reliability of the system. Phase-wise execution cost, residence cost of each task on different processors, inter task communication cost and relocation cost for each task have been considered as a fuzzy number which is more realistic and general in nature. The fuzzy problem has been transformed into crisp one by using the defuzzification method. The present algorithm is formulated and applied to numerical examples to demonstrate its effectiveness. The present model is suitable for arbitrary number of phases and processors with random program structure.

Tasks allocation is an important step for obtaining high performance in distributed computing system (DCS). This article attempts to develop a mathematical model for allocating the tasks to the processors in order to achieve optimal cost and optimal reliability of the system. The proposed model has been divided into two stages. Stage-I, makes the ‘n' clusters of set of ‘m' tasks by using k-means clustering technique. To use the k-means clustering techniques, the inter-task communication costs have been modified in such a way that highly communicated tasks are clustered together to minimize the communication costs between tasks. Stage-II, allocates the ‘n' clusters of tasks onto ‘n' processors to minimize the system cost. To design the mathematical model, executions costs and inter tasks communication costs have been taken in the form of matrices. To test the performance of the proposed model, many examples are considered from different research papers and results of examples have compared with some existing models.

No abstract