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Divisible load theory is a methodology involving the linear and continuous modeling of partitionable computation and communication loads for parallel processing. It adequately represents an important class of problems with applications in parallel and distributed system scheduling, various types of data processing, scientific and engineering computation,(More)
Data replication has been widely used as a mean of increasing the data availability of large-scale cloud storage systems where failures are normal. Aiming to provide cost-effective availability, and improve performance and load-balancing of cloud storage, this paper presents a cost-effective dynamic replication management scheme referred to as CDRM. A novel(More)
Large-scale distributed applications are subject to frequent disruptions due to resource contention and failure. Such disruptions are inherently unpredictable and, therefore, robustness is a desirable property for the distributed operating environment. In this work, we describe and evaluate a robust topology for applications that operate on a spanning tree(More)
The problem of distributing and processing a divisible load in a heterogeneous linear network of processors with arbitrary processors release times is considered. A divisible load is very large in size and has computationally intensive CPU requirements. Further, it has the property that the load can be partitioned arbitrarily into any number of portions and(More)
ÐOptimal distribution of divisible loads in bus networks is considered in this paper. The problem of minimizing the processing time is investigated by including all the overhead components that could penalize the performance of the system, in addition to the inherent communication and computation delays. These overheads are considered to be constant(More)
In this paper, we address several issues that are imperative to grid environments such as handling resource heterogeneity and sharing, communication latency, job migration from one site to other, and load balancing. We address these issues by proposing two job migration algorithms, which are MELISA (modified ELISA) and LBA (load balancing on arrival). The(More)
In this paper, we present two heuristic energy-aware scheduling algorithms (EGMS and EGMSIV) for scheduling task precedence graphs in an embedded multiprocessor system having processing elements with dynamic voltage scaling capabilities. Unlike most energy-aware scheduling algorithms that consider task ordering and voltage scaling separately from task(More)
Shrinking transistor geometries, aggressive voltage scaling and higher operating frequencies have negatively impacted the lifetime reliability of embedded multi-core systems. In this paper, a convex optimization-based task-mapping technique is proposed to extend the lifetime of a multiprocessor systems-on-chip (MPSoCs). The proposed technique generates(More)