Abstract
Problem statement: This study is for effective scheduling of grid job s based on economy for space shared resources in Bag of tasks grid. Gr id Computing aims in combining the power of heterogeneous, geographically distributed, multi-do main computational resources to provide high performance or high throughput. Approach: Space shared resources are parallel supercomputers and clusters of workstations that provides a great amou nt of computational power. These resources require jobs to be specified formally in terms of the amoun t of time (tr) and number of processors (p) needed for execution. Bag-of-Tasks (BoT) is an application consists of several uniprocessor and independent tasks that have no inter-task communications or tas k-dependencies. BoT is highly suitable for executio n in grids. It is capable of tolerating network delay s or faults and does not require formal job submiss ion. The Explicit allocation strategy assigns the formal job parameters (p, tr) to the job requests, minimi zing the overhead on the grid users to provide a formal job specification. This strategy uses adaptive heur istics to determine the parameters based on certain heuris tics, in order to improve throughput. In the propos ed system, explicit allocation strategy combined with Deadline and Budget Constraint (DBC) Cost Time optimization algorithm performs effective schedulin g of the jobs based on the user's quality of servic e (QoS) requirements such as deadline, budget and optimization strategy. Results: The cost-time optimization scheduling allocates the cheapest reso urces to ensure that the deadline can be met and computation is minimized. In case if there are two resources with the same cost, scheduling is done in any affordable resource so that the job gets execut ed as early as possible. Conclusion: The performance of this scheme against the existing system is evalu ated using cost factor (C factor ) and speed up ratio (T speedup ) and this scheme is more effective than the existi ng system.
Highlights
Grid computing is a method of computing in which very large problems are divided into small tasks that are distributed across a network for simultaneous processing
This paper proposes an effective algorithm for Bag of Tasks Grid
This study presented is an Explicit allocation strategy with Deadline and Budget Constraint (DBC) optimization, which consists of deploying an adaptive heuristic to make a smart use of space shared resources based on the economic provisions of the user, granting to grid users privileged access to an amount of resources as soon as possible, with deadline considerations
Summary
Grid computing is a method of computing in which very large problems are divided into small tasks that are distributed across a network for simultaneous processing. Due to the widespread use of grid in almost all fields, there is a need for effective utilization of the available computational power of all types of resources. Space-shared resources are parallel supercomputers and clusters of workstations with great amount of computational power. They are among the most powerful resources in a grid. BoT applications are most suitable for execution in grids as they can be preempted and recovered from failures by executing the tasks. These applications do not need specifications such as maximum number of resources, or period of time needed for job execution to be provided by the user during job submission. This paper proposes an effective algorithm for Bag of Tasks Grid
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