OddCI: on-demand distributed computing infrastructure

  • Authors:
  • Rostand Costa;Francisco Brasileiro;Guido Lemos Filho;Dênio Mariz Sousa

  • Affiliations:
  • Federal University of Campina Grande, Paraíba, Brazil and Federal University of Paraíba, João Pessoa, Paraíba, Brazil;Federal University of Campina Grande, Paraíba, Brazil;Federal University of Paraíba, João Pessoa, Paraíba, Brazil;Federal University of Paraíba, João Pessoa, Paraíba, Brazil

  • Venue:
  • Proceedings of the 2nd Workshop on Many-Task Computing on Grids and Supercomputers
  • Year:
  • 2009

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Abstract

The availability of large quantities of processors is a crucial enabler of many-task computing. Voluntary computing systems have proven that it is possible to build computing platforms with millions of nodes to support the execution of embarrassingly parallel applications. These systems, however, lack the flexibility of more traditional grid infrastructures. On the other hand, flexible infrastructures currently available can gather only dozens of thousands nodes. We propose a novel architecture for generic Distributed Computing Infrastructures (DCI) that can be instantiated on demand to be, at the same time, flexible and highly-scalable. Bringing the scalability from voluntary computing, the flexibility from grid computing and the elasticity from cloud computing in a single arrangement, our proposal allows for fast setup, fast initialization and fast dismantle of customized DCI supported by both dedicated and shared underlying infrastructures. Our approach leverages broadcast communication as an efficient mechanism to enable aggregation of geographically distributed computing resources, including millions of non-traditional processing devices such as PDA, mobile phones and Digital TV receivers, using both opportunistic and non-opportunistic models. We show the feasibility of the proposed architecture by implementing it atop a digital television system. We also assess the performance of such system and show that it can be used to execute several classes of many-tasks computing applications with very high efficiency, substantially decreasing their response time.