Autonomic Resource Contention‐aware Scheduling

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Prof. Varsha Apte, Associate Professor, IIT Bombay

8. An Overhead and Resource Contention Aware Analytical Model of Overloaded Web Servers , Vipul Mathur and Varsha Apte, in Proceedings of Workshop on Software Performance '07, Buenos Aires, Argentina, February 2007. 9. A Methodology and Tool for Performance Analysis of …

Self-Aware Synchronization Mechanisms and Decision Making

hierarchy, and task scheduling and mapping help in sustaining that moving threads with high contention on the same core can lead to a reduction of the tasks execution time. To put this design into practice, the following contributions were made: a monitoring infrastructure able to quantify the lock contention among threads was im-plemented;

A Contention Aware Hybrid Evaluator for Schedulers of Big

network (QN) models to assess resource contention at the cluster nodes. The implemented scheduler takes as input a synthetic or a real trace of jobs of various types (in terms of resource usage) and schedules (not necessarily as dictated by the trace) them on “servers,” which are modeled by analytical QNs. This allows the user to examine how

A Contention-Aware Hybrid Evaluator for Schedulers of Big

configuring autonomic job scheduling [16]. We do not discuss autonomic aspects of dynamic scheduling in any detail in this paper. Hadoop was originally designed to run large batch jobs infrequently. The out-of-the-box FIFO scheduler packaged with Hadoop was sufficient for that purpose. There was really no need to worry about resource utilization to com-

Awais Khan - lass.sogang.ac.kr

To improve information and resource sharing for joint scienti c work ows, simulation and analysis between the HPC data centers, we designed and developed SciSpace, Scienti c Collaboration Workspace for collab-orative data centers. It o ers a global view of information shared from multiple geo-distributed HPC data centers under a single

Workshop on Computer Modeling and Design

Energy-EfficientContention-AwareChannelSelectionin CognitiveRadioAd-Hoc Networks Agapi Mesodiakaki (UPC, Spain); FerranAdelantado (Universitat Obertade Catalunya, Spain); LuisAlonso(Universidad Politecnica deCatalunya,Spain); ChristosVerikoukis (TelecommunicationsTechnological CentreofCatalonia, Spain) pp. 46-50