Reza Moraveji

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In this paper, we study CPU utilization time patterns of several MapReduce applications. After extracting running patterns of several applications, the patterns along with their statistical information are saved in a reference database to be later used to tweak system parameters to efficiently execute future unknown applications. To achieve this goal, CPU(More)
In this paper, a diverse range of routing algorithms is classified into a new family of routings called zone-ordered label-based routing algorithms. The proposed classification is based on three common steps (factors) for generating such routings, namely, graph labeling, deadlock-free zones, and zone ordering. The main goal of this classification is to(More)
Workload consolidation, sharing physical resources among multiple workloads, is a promising technique to save cost and energy in cluster computing systems. This paper highlights a number of challenges associated with workload consolidation for Hadoop; as one of the current state-of-the-art data-intensive cluster computing systems. Through a systematic(More)
Recent studies have revealed that on-chip interconnects neither is wire plentiful nor is bandwidth cheap. Based on the results of these studies, in physical design of multiprocessor system-on-chip (MPSoCs), both the wiring density constraint and routing of wires are controversial issues, and there is a trade-off between the network bandwidth and wiring(More)
Irregular topologies are desirable network structures for building scalable cluster systems and very recently they have also been employed in SoC (system-on-chip) design. Many analytical models have been proposed in the literature to evaluate the performance of networks with different topologies such as hypercube, torus, mesh, hypermesh, Cartesian product(More)
recently, businesses have started using MapReduce as a popular computation framework for processing large amount of data, such as spam detection, and different data mining tasks, in both public and private clouds. Two of the challenging questions in such environments are (1) choosing suitable values for MapReduce configuration parameters –e.g., number of(More)