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@article{147323,
        author = {Divya dogra and Mohit Trehan},
        title = {PARALLEL CLUSTER RESOURCE AND JOB ALLOCATION USING HYBRID AHP APPROCH                                             },
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {5},
        number = {7},
        pages = {115-121},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=147323},
        abstract = {Resource availability and usability becomes critical as mass user becomes need of the hour for advanced and heterogeneous computing.  Federated cloud computing becomes building block of current environment as resources are limited and requirements are heavy. To overcome the problem deadline constraint scheduling mechanism is proposed under heterogeneous cloud computing. Reliability is a concern which is tackled in the proposed literature considering metric mean time between failures. Deadline sensitive jobs are compared against finish time of jobs which is calculated in advance and AHP is applied to determined there completion time. AHP matrix indicate  if jobs satisfy  deadline or not. Advance reservation is also used within the proposed system to handle deadline constraint jobs. Early finish time calculated in the scenario is used to preempt the resources in case resources become critically low and jobs cannot be allotted to the clusters. To resolve the faults, progress made at current machine is migrated to other machine using checkpointing approach.  The result of the proposed system shows improvement in terms Makespan and Flowtime by 10%.},
        keywords = {AHP, Deadline, federated cloud, Makespan, Flowtime},
        month = {},
        }