Robust Task Allocation for Dynamic Distributed Real-Time Systems Subject to Multiple Environmental Parameters

Authors:
Dazhang Gu;Frank Drews;Lonnie Welch
Affiliations:
Ohio University;Ohio University;Ohio University
Venue:
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
Year:
2005

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Abstract

Some distributed real-time systems interact with external environments that change dynamically, and it is necessary to take the external variables into account when performing task allocation. We developed an approximation algorithm for task allocation, and it finds allocations that are maximally robust against dynamic changes in multiple external variables. Such an algorithm will help to reduce expensive reallocations triggered by changes in unpredictable environments. The algorithm has a polynomial running time, and its robustness optimality is given by an approximation ratio, which equals 2.41 asymptotically, when workloads are large and workload independent utilization of tasks is insignificant.