A Distributed Iterative Algorithm for Optimal Scheduling in Grid Computing

The paper studies a distributed iterative algorithm for optimal scheduling in grid computing. Grid user's requirements are formulated as dimensions in a quality of service problem expressed as a market game played by grid resource agents and grid task agents. User benefits resulting from taking decisions regarding each Quality of Service dimension are described by separate utility functions. The total system quality of service utility is defined as a linear combination of the discrete form utility functions. The paper presents distributed algorithms to iteratively optimize task agents and resource agents functioning as sub-problems of the grid resource QoS scheduling optimization. Such constructed resource scheduling algorithm finds a multiple quality of service solution optimal for grid users, which fulfils some specified user preferences. The proposed pricing based distributed iterative algorithm has been evaluated by studying the effect of QoS factors on benefits of grid user utility, revenue of grid resource provider and execution success ratio

Market Mechanism for Dynamic Resource Management in Computational Grid

This paper presents a market mechanism for dynamic resource allocation in computational grid. Grid market is described that consists of two economic agent types; it allows agents representing various grid resources to coordinate their resource allocation decisions without assuming a priori cooperation. The grid task agents buy resources to complete tasks. Grid resource agents charge the task agents for the amount of resource capacity allocated. Grid resource allocation problem is presented as grid user utility optimization. Given grid resource agent's pricing policy, the task agent optimization problem is to complete its job as quickly as possible when spending the least possible amount of money. This paper provides a resource allocation and pricing algorithm. Experiments are made to compare the performance of the price-directed resource allocation with conventional Round-Robin allocation

Simultaneous Optimization of Application Utility and Consumed Energy in Mobile Grid

Mobile grid computing is aimed at making grid services available and accessible anytime anywhere from mobile device; at the same time, grid users can exploit the limited resources of mobile devices. This paper proposes simultaneous optimization of application utility and consumed energy in mobile grid. The paper provides a comprehensive utility function, which optimizes both the application level satisfaction such as execution success ratio and the system level requirements such as high resource utilization. The utility function models various aspects of job, application and system. The goal of maximizing the utility is achieved by decomposing the problem into a sequence of sub-problems that are then solved using the NUM optimization framework. The proposed price-based iterative algorithms enable the sub-problems to be processed in parallel. The simulations and analysis are given to study the performance of the algorithm

A survey on probabilistic broadcast schemes for wireless ad hoc networks

Broadcast or flooding is a dissemination technique of paramount importance in wireless ad hoc networks. The broadcast scheme is widely used within routing protocols by a wide range of wireless ad hoc networks such as mobile ad hoc networks, vehicular ad hoc networks, and wireless sensor networks, and used to spread emergency messages in critical scenarios after a disaster scenario and/or an accidents. As the type broadcast scheme used plays an important role in the performance of the network, it has to be selected carefully. Though several types of broadcast schemes have been proposed, probabilistic broadcast schemes have been demonstrated to be suitable schemes for wireless ad hoc networks due to a range of benefits offered by them such as low overhead, balanced energy consumption, and robustness against failures and mobility of nodes. In the last decade, many probabilistic broadcast schemes have been proposed by researchers. In addition to reviewing the main features of the probabilistic schemes found in the literature, we also present a classification of the probabilistic schemes, an exhaustive review of the evaluation methodology including their performance metrics, types of network simulators, their comparisons, and present some examples of real implementations, in this paper

Energy Efficient Resource Management in Mobile Grid

Energy efficient computing has recently become hot research area. Many works have been carried out on conserving energy, but considering energy efficiency in grid computing is few. This paper proposes energy efficient resource management in mobile grid. The objective of energy efficient resource management in mobile grid is to maximize the utility of the mobile grid which is denoted as the sum of grid application utility. The utility function models benefits of application and system. By using nonlinear optimization theory, energy efficient resource management in mobile grid can be formulated as multi objective optimization problem. In order to derive a distributed algorithm to solve global optimization problem in mobile grid, we decompose the problem into the sub problems. The proposed energy efficient resource management algorithm decomposes the optimization problem via iterative method. To test the performance of the proposed algorithm, the simulations are conducted to compare proposed energy efficient resource management algorithm with other energy aware scheduling algorithm