Efficient Service Task Assignment in Grid Computing Environments

Efficient Service Task Assignment in Grid Computing Environments

Angelos Michalas (Technological Educational Institute of Western Macedonia, Kastoria, Greece) and Malamati Louta (Harokopio University of Athens, Greece)
DOI: 10.4018/978-1-61520-611-7.ch104
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The availability of powerful computers and highspeed network technologies is changing the way computers are used. These technology enhancements led to the possibility of using distributed computers as a single, unified computing resource, leading to what is popularly known as Grid computing (Foster, 2001). The term Grid is adopted from the power Grid which supplies transparent access to electric power regardless of its source. Cloud computing, scalable computing, global computing, internet computing, and more recently peer-to-peer computing are well known names describing the Grid technology in distributed systems.
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Most studies in the field of resource allocation schemes aim at efficiently utillising the resources spread throughout a network. In most cases the problem is reduced to load balancing among specific nodes. Basic service task assignment strategies comprise the following (Balasubramanian, 2004): First, Round Robin, according to which the tasks are allocated to nodes by simply iterating through the nodes list. Second, Random, where the nodes to be assigned with the tasks are selected randomly. Third, Least Loaded in accordance with which the tasks are assigned to a specific node until a pre-specified threshold is reached. Thereafter, all subsequent requests are transferred to the node with the lowest load and the aforementioned steps are repeated. Fourth, Load Minimum, where the average load of the system is calculated. In case the load of a node is higher than the average node and of the least loaded node by a certain amount, all subsequent requests are transferred to the least loaded location.

Key Terms in this Chapter

Grid Computing: A distributed network of high performance computers, storage elements, sensors and collaboration environments accessed transparently by users. Access to resources is conditional based on factors like authorization, trust, negotiation and resource-based policies.

Job Scheduling: An optimization problem in computer science specifying which jobs should be assigned to specific resources at particular times.

Ant Colony Algorithm: Ant colony algorithms follow the behavioural pattern of real ants in nature which travel across various paths marking them with pheromone while seeking for food. These kinds of algorithms are used to solve many NP-hard problems including routing, assignment, and scheduling.

Generalized Assignment Problem: In this problem a set of tasks has to be assigned to a set of resources . Each resource has a limited capacity . Each task assigned to resource consumes a quantity of the resource’s capacity. Also the cost of assigning a task to resource is given. The objective is to find a task assignment pattern which has minimum cost. Care should be taken to assign tasks to resources with enough spare capacity. In case there is no resource with enough spare capacity, the task is assigned to any resource, producing in this way an infeasible assignment.

Load Balancing: A technique to spread work between two or more computers, network links, CPUs, hard drives, or other resources in order to get optimal resource utilization, maximize throughput, and minimize response time.

Service Task Allocation: The way tasks are chosen, coordinated and assigned to resources.

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