Scheduling Algorithm: Tasks Scheduling Algorithm for Multiple Processors with Dynamic Reassignment

Abstract

Distributed computing systems [DCSs] offer the potential for improved performance and resource sharing. To make the best use of the computational power available, it is essential to assign the tasks dynamically to that processor whose characteristics are most appropriate for the execution of the tasks in distributed processing system. We have developed a mathematical model for allocating “M” tasks of distributed program to “N” multiple processors (M>N) that minimizes the total cost of the program. Relocating the tasks from one processor to another at certain points during the course of execution of the program that contributes to the total cost of the running program has been taken into account. Phasewise execution cost [EC], intertask communication cost [ITCT], residence cost [RC] of each task on different processors, and relocation cost [REC] for each task have been considered while preparing a dynamic tasks allocation model. The present model is suitable for arbitrary number of phases and processors with random program structure.

Cost Optimization of Distributed Computing System with Dynamic Re-Allocation

“…By following the same algorithm on the remaining phases final allocation is obtained as present in Table 6 for given example. Overall results also evaluated and compared with algorithm [17] as mentioned in Fig. 3.…”

“…A dynamic task allocation method is used here to solve task allocation problem and it allocates the tasks to optimize overall task allocation cost. Some of the other related task allocation methods have been reported in literature such asTask Assignment [1, 10,19], task scheduling [2, 3], Distributed Processing Environment [4], Task Allocation [5,7,9,11,13], data communication in Mobile Computing [6], Dynamic Task Allocation [8], Dynamic Tasks Scheduling [12,16,20,22], Dynamic Optimization Algorithm [14], dynamic programming [15], Dynamic Reassignment [17], Dynamic Load Balancing [18] and Dynamic Task Assignment [21].This research solve here a task allocation problem dynamically in DCS by allocating available processors in such a way that overall load should be balanced so system overloading can be avoided by using the proper utilization of processors.…”

“…Communication cost between executing and non-executing task, reallocation cost of task are also added to evaluate final optimal cost of each phase. Phase wise results are generated in MLATLAB for presented algorithm and algorithm [17], results are compared for both algorithms, on comparing phase wise execution cost and total execution cost, it is found presented model shows the better results as mentioned in Table 7. Overall Optimal Cost 118 120…”

A Heuristic Model for Tasks Scheduling in Heterogeneous Distributed Real Time System under Fuzzy Environment

“…Many approaches have been reported for solving the Static tasks assignment problem in a DRTS [1][2][3][4][5][6][7]. While in dynamic allocation a module can be reassigned during program execution [8][9][10][11]. Donight et al [12] has determined the level of reliability of components with expending low cost.…”

A Tasks Allocation Model with Fuzzy Execution and Fuzzy Inter-Tasks Communication Times in a Distributed Computing System

“…Also it is shown that an optimal dynamic assignment corresponds to a "dynamic" partition imposed by a minimum weight cut in an extended graph. Yadav et al [11] in 2008 developed a mathematical model for multiple processors with dynamic re-assignment. Nagarajan et al [12] in 2010, has developed a model for solving a fuzzy assignment problem using Robust's ranking method.…”