This research investigates two distinct issues related to a resource allocation: its robustness and the failure rate of the heuristic used to determine the allocation. The target system consists of a number of sensors feeding a set of heterogeneous applications continuously executing on a set of heterogeneous machines connected together by high-speed heterogeneous links. There are number of quality of service (QoS) constraints that must be satisfied. A heuristic failure occurs if the heuristic cannot find an allocation that allows the system to meet its QoS constraints. The system is expected to operate in an uncertain environment where the workload, i.e., the load presented by the set of sensors, is likely to change unpredictably, possibly invalidating a resource allocation that was based on the initial workload estimate. The focus of this paper is the design of a static heuristic that: (a) determines a robust resource allocation, i.e., a resource allocation that maximizes the allowable increase in workload until a run-time reallocation of resources is required to avoid a QoS violation, and (b) has a very low failure rate. This study proposes a heuristic that performs well with respect to the failure rates and robustness to unpredictable workload increases. This heuristic is, therefore, very desirable for systems where low failure rates can be a critical requirement and where unpredictable circumstances can lead to unknown increases in the system workload.
S. Ali et al., "Robust Resource Allocation for Sensor-Actuator Distributed Computing Systems," Proceedings of the International Conference on Parallel Processing, 2004, Institute of Electrical and Electronics Engineers (IEEE), Jan 2004.
The definitive version is available at https://doi.org/10.1109/ICPP.2004.1327919
International Conference on Parallel Processing, 2004
Electrical and Computer Engineering
Keywords and Phrases
QoS Constraints; Distributed Computing System; Distributed Processing; Distributed Sensors; Heterogeneous Links; Initial Workload Estimation; Quality of Service; Resource Allocation; Robust Resource Allocation; Scheduling; Static Heuristic Design
International Standard Serial Number (ISSN)
Article - Conference proceedings
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