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In this paper, we have developed a heuristic for the task allocation problem on a fully connected homogeneous multiprocessor environment. Our heuristic is based on a value associated with the modules called the Computation-Communication-Load (CCLoad). This value is dependent on the computation and the communication times associated with the module. Using the concept of CCLoad, we propose a clustering algorithm of complexity O(|V| 2 (|V|+|E|)log(|V|+|E|)), and demonstrate its superiority over a generic version of Sarkar's algorithm.

In this paper, we propose a randomized scheduling algorithm on a fully connected homogeneous multiprocessor environment. This is a randomized version of our earlier algorithm in which we used priority of modules that was dependent on the computation and the communication times associated with the modules. First we propose a generalization of our earlier scheduling algorithm with restricted number of clusters to reduce the time complexity. Then we apply randomization to the generalized algorithm and demonstrate its superiority over our previous work. We show the complexity of our proposed algorithm as O(ab |V| (|V|+|E|) log (|V|+|E|)). Here a is the number of randomization steps, and b is a limit on the number of clusters formed. If we use a and b as constants, then this gives a better complexity in comparison with the complexity of our previous algorithm that was O(|V|2(|V|+|E|) log (|V|+|E|)). In comparison with our previous work we get a performance improvement of up to 6.63% and a performance improvement of up to 12.56% when compared with Sarkar's Edge Zeroing algorithm.

Performance estimation of a distributed software is a challenging problem. A distributed software runs on multiple processing nodes interconnected in some fashion. In such a situation computational load of a software is distributed onto the processing nodes of the given system. Such a system makes use of an appropriate task scheduling algorithm for obtaining a good performance. The program used in this work emulates a distributed system . An emulator gives the result like an actual system. The emulator is of a fully connected distributed system in which any two processors can directly communicate. The objective of this experiment is to identify the task scheduling algorithm that also performs well in the presence of communication fault delay occured because of network failure or computation fault delay occured because of no response from processors in a distributed system.

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