Multi objective Game Theory-based Schedule Optimization for Bags-of-Tasks on Hybrid Clouds

Scheduling multiple large-scale parallel workflow applications on heterogeneous computing systems like hybrid clouds is a fundamental NP-complete problem that is critical to meeting various types of QoS (Quality of Service) requirements. This paper addresses the scheduling problem of large-scale applications inspired from real-world, characterized by a huge number of homogeneous and concurrent bags-of-tasks that are the main sources of bottlenecks but open great potential for optimization. The scheduling problem is formulated as a new sequential cooperative game and propose a communication and storage-aware multiobjective algorithm that optimizes two user objectives (execution time and economic cost) while fulfilling two constraints (network bandwidth and storage requirements). We present comprehensive experiments using both simulation and real-world applications that demonstrate the efficiency and effectiveness of our approach in terms of algorithm complexity, makespan, cost, system-level efficiency, fairness, and other aspects compared with other related algorithms.

  • Project Category : IEEE Projects
  • Project Year : 2014-2015
  • Department
  • B.E(Computer Science) , B.E(Information Technology), B.Tech, M.E(Computer Science), M.SC(CS&M), M.SC(CS), M.SC(IT), M.SC(SOFTWARE ENGG), MCA,
  • Domain
  • Cloud Computing,
  • Technology
  • ASP.Net, C#.Net, .Net, J2EE, Java,
  • Avilable city
  • Chennai,

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