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We consider the problem of mapping tasks to processor nodes at
run-time (dynamic approach) in multicomputer systems. This is against
static allocation where work load allocation decisions are taken before
run time and tasks are assigned to individual processors of the system.
In a decentralized approach, the scheduling control is distributed
amongst all the nodes in the system. The scheduling strategies in such
a system should incur less overhead and identify suitable remote sites
for migrating extra work.
The decentralized algorithm proposed in
the paper [1], is a combination of neighborhood averaging and bidding
approach and it is intended for multicomputers connected by a store and
forward communication network.
The factors that characterize the performance of the system are:
• Topology used
• Stability (oscillation free or not )
• Task Trashing Level (task thrashing occurs when node spends more time in task migration than task execution)
We
intend to study the performance of the system under different
topologies like mesh, hypercube and Chordal Ring, and also comment on
the thrashing and stability of the system.
For performance
evaluation, the cost of migration and scheduling overhead is also taken
into account. For comparison, we select random scheduling strategy
which also makes use of nearest neighbor load balancing.