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A model for communication between resource discovery and load balancing units in computing environments

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Abstract

Resource overloading causes one of the main challenges in computing environments. In this case, a new resource should be discovered to transfer the extra load. However, this results in drastic performance degradation. Thus, it is of high importance to discover the appropriate resource at first. So far, several resource discovery mechanisms have been introduced to overcome this challenge, a majority of which neglect the fact that this important decision should be made in cooperation with other units existing in a computing environment. One of the units is load balancing. In this paper, we propose a model for communication between resource discovery and load balancing units in a computing environment. Based on the model, resource discovery and load balancing decisions are made cooperatively considering the behavior of running processes and resources capacities. These considerations make decisions more precise. In addition, the model presents the loosest type of coupling between resource discovery and load balancing units, i.e., message coupling. This feature provides a better scalability in size for the model. Comparative results show that the proposed model increases scalability in size by 7 to 15 %, cuts message transmission rate by 15 % and improves hit rate by 51 %.

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References

  1. Meshkova E, Riihijärvi J, Petrova M, Mähönen P (2008) A Survey on resource discovery mechanisms, peer to peer and service discovery frameworks. J Comput Netw 24(6):2097–2128

    Article  Google Scholar 

  2. Arab MN, Mirtaheri SL, Khaneghah EM, Sharifi M, Mohammadkhani M (2011) Improving learning-based request forwarding in resource discovery through load-awareness. In: International Conference on Data Management in Grid and P2P Systems, Toulouse, pp 73–82

  3. Nitzberg B, Schopf JM, Jones JP (2004) PBS Pro: Grid computing and scheduling attributes. Kluwer Academic Publishers, Norwell

    Google Scholar 

  4. Moab Grid Suite (2012). [AAOnline]. http://www.adaptivecomputing.com/products/hpc-products/moab-hpc-basic-edition/. Accessed on Sep 2012

  5. Milojicic DS (2002) Peer to Peer Computing. Technical Report HPL-2002-57. HP Laboratories, Palo Alto

  6. Ghamri-Doudane S, Agoulmine N (2007) Enhanced DHT-based P2P architecture for effective resource discovery and management. Netw Syst Manag 19(3):335–354

    Article  Google Scholar 

  7. Iamnitchi A, Foster I, Nurmi DC (2002) A Peer-to-Peer approach to resource discovery in grid environments. In: High performance distributed computing, Edinburgh, Scotland, pp 20–28

  8. Tangpongprasit S, Katagiri T, Kise K, Honda H, Yuba T (June 2005) A time-to-live based reservation algorithm on fully decentralized resource discovery in grid computing. Parallel Comput 31(6):529–543

    Google Scholar 

  9. Schmidt C, Parashar M (2003) Flexible information discovery in decentralized distributed systems. In: 12th High Performance Distributed Computing, Seattle, pp 226–235

  10. Hasanzadeh M, Meybodi MR (2013) Grid resource discovery based on distributed learning automata. Comput J. doi:10.1007/s00607-013-0337-x, published online

  11. Deng Y, Wang F, Ciura A (2009) Ant colony optimization inspired resource discovery in P2P Grid systems. J Supercomput 49(1):4–21

    Article  Google Scholar 

  12. Mirtaheri SL, et al (2011) RNS: remote node selection for HPC clusters. In: 17th Int’l Conference on Parallel and Distributed Processing Techniques and Applications, Las Vegas, pp 23–30

  13. Khaneghah EM, Nezhad NO, Mirtaheri SL, Sharifi M, Shirpour A (2011) An efficient live process migration approach for high performance cluster computing systems. In: 1st International Conference on Innovative Computing Technology, Tehran, pp 49–55

  14. Dodonov E, de Mello RF (2010) novel approach for distributed application scheduling based on prediction of communication events. Future Gener Comput Syst 26(5):740–775

    Article  Google Scholar 

  15. Hennessy M, Merro M, Rathke J (2002) Towards a behavioural theory of access and mobility control in distributed systems. School of Cognitive and Computing Sciences, University of Sussex, pp 1350–3170

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Correspondence to Mohammad Norouzi Arab.

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Arab, M.N., Sharifi, M. A model for communication between resource discovery and load balancing units in computing environments. J Supercomput 68, 1538–1555 (2014). https://doi.org/10.1007/s11227-014-1124-y

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