In a distributed computing system (DCS), we need to allocate a
number of tasks to different processors for execution. The problem
of task assignment in heterogeneous computing systems has been
studied for many years with many variations and to accomplish
various objectives, such as throughput maximization, reliability
maximization, and cost minimization. There are also exists a set of
system constraints related to memory and communication link
capacity. Most of the existing approaches for task allocation deal
with a single objective only. In this project we construct the task
allocation problem as a multi-objective optimization problem to
consider system constraints. The goal programming technique is used
with pre-emptive priority structure to find the optimal allocation
that not only optimize system reliability but also optimize memory
as well as path load. The genetic algorithm is used to find the
optimal allocations. Genetic algorithm is used to find the optimal
allocations.
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