Abstract
Complex problems consisting of interdependent subtasks are represented by a direct acyclic graph (DAG). Subtasks of this DAG are scheduled by the scheduler on various grid resources. Scheduling algorithms for grid strive to optimize the schedule. Nowadays a lot of grid resources are attached by P2P approach. Grid systems and P2P model both are newfangled distributed computing approaches. Combining P2P model and grid systems we get P2P grid systems. P2P grid systems require fully decentralized scheduling algorithm, which can schedule interreliant subtasks among nonuniform computational resources. Absence of central scheduler caused the need for decentralized scheduling algorithm. In this paper we have proposed scheduling algorithm which not only is fruitful in optimizing schedule but also does so in fully decentralized fashion. Hence, this unconventional approach suits well for P2P grid systems. Moreover, this algorithm takes accurate scheduling decisions depending on both computation cost and communication cost associated with DAG’s subtasks.
Highlights
Splitting a huge job into subtasks yields interdependent subtasks
In [17] we proposed fault tolerant decentralized scheduling Journal of Engineering (FTDS) algorithm for grid, which schedules independent tasks by taking into consideration the communication and computational cost associated with tasks
In this paper we propose a fully decentralized P2P grid scheduling (FDPGS) algorithm, which schedules subtasks of directed acyclic graph (DAG) based on communication and computation cost
Summary
Splitting a huge job into subtasks yields interdependent subtasks. Once predecessor subtasks return results only will the execution of successor subtask take place. We can access computational resources available on the grid and schedule our DAG based task upon them. Decentralized technique [15] (computing field scheduling) for scheduling tasks on the grid was proposed in [16] The drawback of this approach [13, 16] is that it ignores the communication cost. While scheduling interdependent subtasks of huge job, scheduling algorithm should consider both the communication and computation cost associated with subtasks of the job. Scheduling subtasks of DAG based task on the heterogeneous decentralized grid is an NP-hard problem. Researchers have used a genetic algorithm to schedule DAG based tasks on a decentralized grid [18]. In this paper we propose a fully decentralized P2P grid scheduling (FDPGS) algorithm, which schedules subtasks of DAG based on communication and computation cost.
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