On the design of clustering-based scheduling algorithms for realistic machine models

While the NP-complete problem of scheduling weighted arbitrary directed acyclic graphs under the delay model has been studied extensively, comparatively little work exists for this problem under more realistic models such as the LogP model. Recently, a number of LogP-based scheduling heuristics and related works have appeared in the literature, including a task clustering algorithm design methodology which identifies four crucial design issues (Boeres et al., 1997). Through the use of five task replication-based scheduling heuristics based on this design methodology, this paper investigates the effect of various implementations of these design issues on the schedules produced for the allocation of arbitrary task graphs to fully connected networks of processors under a LogP-type model. The quality of the schedules produced by these algorithms are also compared with good, well-known delay model-based algorithms and an existing LogP strategy