Grid Resource Allocation Research Articles

Modern approaches to modeling user requirements on resource and task allocation in hierarchical computational grids

Modern approaches to modeling user requirements on resource and task allocation in hierarchical computational grids Tasks scheduling and resource allocation are among crucial issues in any large scale distributed system, including Computational Grids (CGs). These issues are commonly investigated using traditional computational models and resolution methods that yield near-optimal scheduling strategies. One drawback of such approaches is that they cannot effectively tackle the complex nature of CGs. On the one hand, such systems account for many administrative domains with their own access policies, user privileges, etc. On the other, CGs have hierarchical nature and therefore any computational model should be able to effectively express the hierarchical architecture in the optimization model. Recently, researchers have been investigating the use of game theory for modeling user requirements regarding task and resource allocation in grid scheduling problems. In this paper we present two general non-cooperative game approaches, namely, the symmetric non-zero sum game and the asymmetric Stackelberg game for modeling grid user behavior defined as user requirements. In our game-theoretic approaches we are able to cast new requirements arising in allocation problems, such as asymmetric users relations, security and reliability restrictions in CGs. For solving the games, we designed and implemented GA-based hybrid schedulers for approximating the equilibrium points for both games. The proposed hybrid resolution methods are experimentally evaluated through the grid simulator under heterogeneity, and large-scale and dynamics conditions. The relative performance of the schedulers is measured in terms of the makespan and flowtime metrics. The experimental analysis showed high efficiency of meta-heuristics in solving the game-based models, especially in the case of an additional cost of secure task scheduling to be paid by the users.

Proffering Task oriented Grid Resource Discovery based on Learning Automata

challenge of existing resource discovery service is the lack of support from task oriented query. This paper puts forward a design of task-oriented grid resource discovery service based on learning automata to enable users to dynamically discover the grid resources which are suitable for their task. The core of this service is learning automata based grid resource classifier, which periodically accesses the Meta computing directory service and dynamically classifier the grid resources into task-oriented categories according to the real-time state of grid computing environment. Users can invoke this service and pass her or his task type as a parameter to discover the current most suitable grid resources. Grid resource allocation manager also can interact with this service to improve its practicability and efficiency.

An efficient resource allocation for maximizing benefit of users and resource providers in ad hoc grid environment

Ad hoc grids allow a group of individuals to accomplish a mission that involves computation and communication among the grid components, often without fixed structure. In an ad hoc grid, every node in the network can spontaneously arise as a resource consumer or a resource producer at any time when it needs a resource or it possesses an idle resource. At the same time, the node in ad hoc grid is often energy constrained. The paper proposes an efficient resource allocation scheme for grid computing marketplace where ad hoc grid users can buy usage of memory and CPU from grid resource providers. The ad hoc grid user agents purpose to obtain the optimized quality of service to accomplish their tasks on time with a given budget, and the goal of grid resource providers as profit-maximization. Combining perspectives of both ad hoc grid users and resource providers, the paper present ad hoc grid resource allocation algorithm to maximize the global utility of the ad hoc grid system which are beneficial for both grid users and grid resource providers. Simulations are conducted to compare the performance of the algorithms with related work.

Real-time Grid monitoring based on complex event processing

Monitoring systems in Grid infrastructures typically collect and aggregate data originating in distributed agents and store it in global, periodically refreshed repositories. However, in some scenarios access to real-time streams of monitoring information, rather than persistent data sets, would be beneficial. In this paper, we evaluate the Complex Event Processing (CEP) approach applied to real-time Grid monitoring and argue that CEP enables us to achieve two goals, otherwise difficult to combine: real-time access to monitoring data and advanced query capabilities. Monitoring for the purpose of dynamic allocation of Grid resources serves as a case study to demonstrate powerful real-time query capabilities provided by CEP. In addition, we show how to employ CEP for data reduction. For practical verification of our solution, a CEP-based Grid monitoring infrastructure, GEMINI2, has been developed. We have measured the overhead due to CEP-based monitoring and conclude that real-time Grid monitoring is possible without excessive intrusiveness for resources and network.

Nondominated local coteries for resource allocation in grids and clouds

The resource allocation problem is a fundamental problem in Grid and Cloud computing environments. This paper focuses on constructing nondominated ( ND) local coteries to solve the problem in a distributed way. Distributed algorithms using coteries usually incur low communication overheads and have high degrees of fault-tolerance, and ND coteries are candidates for the algorithms to achieve the highest degree of fault-tolerance. A new type of coteries, called p-coteries, is defined to aid the construction of local coteries. Theorems about the nondomination of p-coteries are then developed, and an operation, called pairwise-union ( p-union), is proposed to help generate ND p-coteries, which in turn can be used to generate ND local coteries for solving the resource allocation problem.

Development and performance analysis of grid resource allocation methods

A ‘grid’ is an infrastructure for resource sharing. A computational grid has the potential for solving large scale problems using heterogeneous and distributed resources. Resource allocation is a fundamental issue in achieving high performance on computational grids. Many methods have been developed for grid resource allocation. In this paper, we propose a new grid resource allocation method (modified least cost method) that assigns tasks to computing nodes in a way that is close to the optimum. This paper also proposes a linear programming model for grid scheduling and includes a comparative performance analysis of our proposed resource allocation method with other well known methods. To facilitate the research, a software tool has been developed which produces a comprehensive simulation of a number of grid resource allocation methods. The experimental results show that our proposed method yields improvements in terms of performance and results in a lower computational cost.

Resource allocation to conserve energy in distributed computing

Energy consumption is an issue in grid computing. There has been substantial research into grid resource allocation, but little research on energy aware resource allocation. We propose that altering the resource allocation mechanism to incorporate node power and performance data can make a substantial difference to both the time taken to execute tasks and the energy consumed by the grid. This paper examines the use of three simple economic resource allocation mechanisms through simulation. We discover that different mechanisms perform better under different circumstances, and that changing the resource allocation mechanism to incorporate the power and performance information of individual nodes can result in a substantial difference to the time taken to execute tasks, and over time can make a marked difference to the total energy consumption of the grid resource.

Device Resource Allocation in Context-Aware Mobile Grid

This paper presents device resource allocation in context-aware mobile grid. Context information in mobile grid includes device capabilities, network status and user preferences. The objective of the paper is to efficiently allocate mobile device resource under the contexts of mobile grid environment. The paper uses utility to express values for the device resource allocation. Device resource allocation was formulated by utility optimization in mobile grid. Device resource allocation algorithm (DRAA) is proposed which decomposes optimization problem into sub-problems. In the simulation, DRAA in context-aware mobile grid was compared with other related work.

Economic agent-based resource management in ad hoc grid environment

The ad hoc grid is a spontaneous organisation of cooperating heterogeneous nodes into a logical community without a fixed infrastructure and with only minimal administrative requirements. Resource management for ad hoc grids is challenging due to the participation of heterogeneous, dynamic, autonomous and ephemeral grid nodes. The paper proposes an ad hoc grid resource management system, the producers and consumers of ad hoc grid resource are modelled as the self-interested decision-makers described in microeconomic theory. All market participants in the ad hoc grid environment including grid resources and services can be represented as agents. We apply economic agents to build ad hoc grid resource management, where ad hoc grid resource consumers and providers can buy and sell ad hoc grid resource based on an underlying economic architecture. The main processes involved in ad hoc grid resource management are resource registration, discovery and resource allocation. The experiments are conducted to compare ad hoc grid resource allocation algorithm with other ad hoc grid resource allocation algorithm. Simulation results show that our proposed algorithm is more efficient than compared allocation scheme.

A Market-Based Resource Allocation Policy in Ad Hoc Grid

The paper proposes a market-based resource allocation policy in ad hoc grid environments. The objective of optimal resource allocation in ad hoc grid is to maximize the utility of the ad hoc grid system without exceeding the resource capacity constraints, expense budget and the deadline. Ad hoc grid user agents acted as the consumers pay for the ad hoc grid resources and resource providers get profits from user agents. Our grid resource allocation optimization is decomposed to two subproblems. In the simulation, the comparison experiments are conducted to test the performance of the algorithms.

A New Grid Architecture using JMF for Video-on-Demand Applications

computing was used only in scientific laboratories for many years. Only during the last few years, it is evolving into a business-innovating technology that is driving commercial adoption. In this paper, a Grid-based multimedia application for the distributed tailoring and streaming of media files is proposed. An innovative multimedia data dissemination strategy, based on the Fibonacci series, is used. To respond to the quality-of-service (QoS) requirements, soft real-time applications, a new architecture is presented. Such architecture is able to manage the Grid resource allocation effectively. Technical and practical problems encountered during the development are discussed, and a thorough performance evaluation of the developed prototype is presented. The developed application is found to be better than the existing architectures.

Research on Gird Task Scheduling Based on Ant Colony Algorithm

Combining with the advantages of ant colony algorithm to solve optimization problem, this paper designs a grid resource allocation model and task scheduling system based on ant colony algorithm. The algorithm can not only locally update for the pheromone in the allocation of grid computing resources, but also can entirely update for the pheromone after the completion of grid computing resources. Experimental results show that the ant colony algorithm can effectively achieve a reasonable task scheduling and load balancing, its application in the task scheduling in grid environment is very successful.

A Grid Resource Allocation Algorithm Based on Pricing and Trust

摘要: 该文首先对基于组合双向拍卖的网格资源分配与定价模型进行改进，提出以各类资源的单价定价的算法。然后提出一种等效价格算法，设计基于信任度的价格调整函数，将不同信任度的各节点的报价，都映射为基准信任度下的等效价格。最后基于该等效报价，以组合双向拍卖模型进行网格资源分配。仿真表明所提算法的交易率较高，能防止恶意节点参与交易，所得交易效用可激励买家提高和卖家降低其等效报价。 关键词: 网格; 资源分配; 定价; 组合双向拍卖; 信任; 效用

Market-based pricing in grids: On strategic manipulation and computational cost

Grid technologies and the related concepts of utility computing and cloud computing enable the dynamic sourcing of computer resources and services, thus allowing enterprises to cut down on hardware and software expenses and to focus on key competencies and processes. Resources are shared across administrative boundaries, e.g. between enterprises and/or business units. In this dynamic and inter-organizational setting, scheduling and pricing become key challenges. Market mechanisms show promise for enhancing resource allocation and pricing in grids. Current mechanisms, however, are not adequately able to handle large-scale settings with strategic users and providers who try to benefit from manipulating the mechanism. In this paper, a market-based heuristic for clearing large-scale grid settings is developed. The proposed heuristic and pricing schemes find an interesting match between scalability and strategic behavior.

Research on Resource Allocation Algorithm Based on MAS Cooperative Technology

With MAS(Multi Agent System)coordinated technology and market bidding game rules, a grid resource allocation model based on market economy was introduced, which could show the relation between supply and demand. The utility function of consumer was given; The results of emulation test showed that the resource allocation algorithm could be a reference to resources of consumers and the approach significantly improves resource utilization, which made the allocation of the whole network resource tend to be more reasonable.

Grid Resource Negotiation: Survey and New Directions

Since Grid computing systems involve large-scale resource sharing, resource management is central to their operations. Whereas there are more Grid resource management systems adopting auction, commodity market, and contract-net (tendering) models, this survey supplements and complements existing surveys by reviewing, comparing, and highlighting existing research initiatives on applying bargaining (negotiation) as a mechanism to Grid resource management. The contributions of this paper are: 1) discussing the motivations for considering bargaining models for Grid resource allocation; 2) discussing essential design considerations such as modeling devaluation of Grid resources, considering market dynamics, relaxing bargaining terms, and co-allocation of resources when building Grid negotiation mechanisms; 3) reviewing the strategies and protocols of state-of-the-art Grid negotiation mechanisms; 4) providing detailed comparisons and analyses on how state-of-the-art Grid negotiation mechanisms address the design considerations mentioned in 3); and 5) suggesting possible new directions.

Modelling and solving grid resource allocation problem with network resources for workflow applications

A problem of allocating resources of a grid to workflow applications is considered. The problem consists, generally, in allocating distributed grid resources to tasks of a workflow in such a way that the resource demands of each task are satisfied. Grid resources are divided into computational resources and network resources. Computational tasks and transmission tasks of a workflow are distinguished. We present a model of the problem, and an algorithm for finding feasible resource allocations. A numerical example is included, showing the importance of the resource allocation phase on a grid. Some conclusions and directions for future research are given.

An auction method for resource allocation in computational grids

A computational grid is composed of a set of resource consumers and resources providers. Usually these entities are independent and making decisions autonomously based on their policies and resource allocation in such systems is a challenging problem. In such systems using market-like techniques for this problem regulates the supply and demand for resources, provides an incentive for providers, and motivates the users to trade-off between deadline, budget, and the required level of quality of service. In this paper, we introduce a continuous double auction method (CDA) for grid resource allocation in which resources are considered as provider agents and users as consumer agents. In our proposed method these entities are allowed to participate in a grid independently and make decisions autonomously. We study this method in terms of economic efficiency and system performance. Experimental results illustrate that the proposed method is efficient in terms of successful execution rates, resource utilization rates and fair profit allocation.

Dynamic scheduling model of computing resource based on MAS cooperation mechanism

Allocation of grid resources aims at improving resource utility and grid application performance. Currently, the algorithms proposed for this purpose do not fit well the autonomic, dynamic, distributive and heterogeneous features of the grid environment. According to MAS (multi-agent system) cooperation mechanism and market bidding game rules, a model of allocating allocation of grid resources based on market economy is introduced to reveal the relationship between supply and demand. This model can make good use of the studying and negotiating ability of consumers’ agent and takes full consideration of the consumer’s behavior, thus rendering the application and allocation of resource of the consumers rational and valid. In the meantime, the utility function of consumer is given; the existence and the uniqueness of Nash equilibrium point in the resource allocation game and the Nash equilibrium solution are discussed. A dynamic game algorithm of allocating grid resources is designed. Experimental results demonstrate that this algorithm diminishes effectively the unnecessary latency, improves significantly the smoothness of response time, the ratio of throughput and resource utility, thus rendering the supply and demand of the whole grid resource reasonable and the overall grid load balanceable.

Pricing in combinatorial double auction-based grid allocation model

This article proposes a novel grid resource allocation model, in which the users and the grid service providers participate in the combinatorial double auction for the resource allocation. To obtain the detailed resource allocation status and the price information, a novel pricing algorithm is designed for the allocation model. Simulation results demonstrate that the proposed algorithm completes the resource allocation and pricing efficiently, and exhibits incentive compatible characteristic. Moreover, users with the higher average price and providers with the lower average price get compensation during the pricing process.