Abstract
Cloud computing is the latest evolution of computing. It provides services to numerous remote users with different requests. Managing the query workload in cloud environment is a challenge to satisfy the cloud users. Improving the overall performance and response time of the query execution can lead to users’ satisfaction. In this paper, we examine the problem of the slow query response time. Sub query merging and query resource allocation approaches are proposed to minimize the query execution time.
The main aim of this paper is to exploit the shared data among the sub queries and minimize communication overhead on cloud. This paper proposes a new architecture to enhance the query execution time by applying the sub queries optimization and merging approach before implementing the query allocation approach. The results improving the query execution time as well as improving query allocation time.
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Maghawry, E.A., Ismail, R.M., Badr, N.L., Tolba, M.F. (2012). An Enhanced Resource Allocation Approach for Optimizing Sub Query on Cloud. In: Hassanien, A.E., Salem, AB.M., Ramadan, R., Kim, Th. (eds) Advanced Machine Learning Technologies and Applications. AMLTA 2012. Communications in Computer and Information Science, vol 322. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35326-0_41
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DOI: https://doi.org/10.1007/978-3-642-35326-0_41
Publisher Name: Springer, Berlin, Heidelberg
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