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3. 4. 5. 6. 7. (1 + δ) then Increases Pcomp (i ) by α1 up to 1 else Decreases Pcomp (i ) by α1 down to 0 endif endfor Fig. 5. Computation Pattern Pcomp (i ) of process i The computation pattern Pcomp (i ) is an element in the Comp(i, j) function. Other element is a computation time prediction CTPk+α−1 (i ) of the process i at superstep k + α − 1 (last superstep executed before process rescheduling). Analogous to PI prediction, CTP also works with the Aging concept. Supposing that CTt (i ) is the computation time of the process i during superstep t, then the prediction CTPk+α−1 (i ) is computed as follows.

Concerning this, the task of allocating processes to processors on such architecture often becomes a problem requiring considerable effort. In order to fully exploit this kind of environments, the programmer must know both the machine architecture and the application code properly. Moreover, each new application requires another analysis for process scheduling. Since both resource management and scheduling are key services for grid environments, issues like load balancing represent a common concern for most developers.

4 Potential of Migration Analysis We used the notion of force from Physics to create the Potential of Migration (PM) of each process. In Physics, force is an influence that can make an object accelerate and is represented by a vector. A vector has a size (magnitude) and a direction. Analyzing the force idea, each studied metric can be seen as a vector that acts over an object. In our case, this object is the migration of a process. Vectors Comp and Comm represent the Computation and Communication metrics, respectively.

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