A Distributed and Heuristic Policy-based Management Architecture for Large-Scale Grids

Grid Computing provides sharing of geographically distributed resources among large scale complex applications. Due to dynamic nature of resources in grid, there is a need of highly efficient job scheduling and resource management policies in grid. In this paper, a novel Grid Resource Scheduler (GRS) is proposed to effectively utilize the available resources in Grid. Proposed GRS contributes, an optimal job scheduling algorithm on Job Rank-Backfilling policy and a resource matching algorithm based on ranking of resources with best fit allocation model. Performance of GRS is measured by considering a web based BLAST algorithm -- a bioinformatics application -- . GRS aims in reducing; Make span of the job workflow and execution time of varied size jobs. The experimental results prove that proposed job scheduling and resource matching algorithms performs better when evaluated against widely used FCFS job scheduling and biggest free resource matching strategies.

\n\t\t\t\t\tThis paper addresses the problem of resource scheduling in a grid computing environment. One of the main goals of grid computing is to share system resources among geographically dispersed users, and schedule resource requests in an efficient manner. Grid computing resources are distributed, heterogeneous, dynamic, and autonomous, which makes resource scheduling a complex problem. This paper proposes a new approach to resource scheduling in grid computing environments, the hierarchical stochastic Petri net (HSPN). The HSPN optimizes grid resource sharing, by categorizing resource requests in three layers, where each layer has special functions for receiving subtasks from, and delivering data to, the layer above or below. We compare the HSPN performance with the Min-min and Max-min resource scheduling algorithms. Our results show that the HSPN performs better than Max-min, but slightly underperforms Min-min.\n\t\t\t\t

Grid resource management and scheduling are confronted with a great challenge. This paper presented a dynamic resource price-adjusting (RPA) strategy in computational Grid. Three new concepts and two new evaluation standards are defined. On the basis of these theories, a Grid resource scheduling algorithm based on marker-driven using dynamic RPA strategy is proposed. With the help of GridSim toolkit, the simulation of resource scheduling algorithm proposed in the paper is realized, and the new algorithm is compared with GridSim DBC (deadline and budget constrained) scheduling algorithms. The experimental results show that the new algorithm improves the performance of Grid in aspect of increasing the task accomplishment ratio and solving the problem of load imbalance.

In order to resolve resource management and scheduling problem in Manufacturing Grid (MG) – an application of Grid technology, we develop a resource management and scheduling system with the interaction of Manufacturing Grid Information Service (MGIS) and the Manufacturing Grid Resource Scheduler (MGRS). The former, MGIS, provides fundamental mechanisms for remote resource encapsulating, registration, and monitoring, and the latter, MGRS, performs scheduling roles as Global Process Planning (GPP) analyzing, resource discovery, resource selection, and resource mapping.

In the research area of grid computing and workflow technology, workflow products based on Web-service technology can work as grid services in grid architecture. A new algorithm of scheduling grid resource with workflow engine is discussed in this paper. The QoS, executing time of process, cost and workload of grid resources are the key factors in grid resources scheduling. Dynamic feed back mechanism and executing time estimation are applied in this algorithm, which can keep the grid resources in a good balance and advance the whole performance of the grid application with workflow service.

A distributed multiple dimensional QoS constrained resource scheduling optimization policy in computational grid

The accelerated development in peer‐to‐peer and Grid computing has positioned them as promising next‐generation computing platforms. They enable the creation of virtual enterprises for sharing resources distributed across the world. However, resource management, application development and usage models in these environments is a complex undertaking. This is due to the geographic distribution of resources that are owned by different organizations or peers. The resource owners of each of these resources have different usage or access policies and cost models, and varying loads and availability. In order to address complex resource management issues, we have proposed a computational economy framework for resource allocation and for regulating supply and demand in Grid computing environments. This framework provides mechanisms for optimizing resource provider and consumer objective functions through trading and brokering services. In a real world market, there exist various economic models for setting the price of services based on supply‐and‐demand and their value to the user. They include commodity market, posted price, tender and auction models. In this paper, we discuss the use of these models for interaction between Grid components to decide resource service value, and the necessary infrastructure to realize each model. In addition to usual services offered by Grid computing systems, we need an infrastructure to support interaction protocols, allocation mechanisms, currency, secure banking and enforcement services. We briefly discuss existing technologies that provide some of these services and show their usage in developing the Nimrod‐G grid resource broker. Furthermore, we demonstrate the effectiveness of some of the economic models in resource trading and scheduling using the Nimrod/G resource broker, with deadline and cost constrained scheduling for two different optimization strategies, on the World‐Wide Grid testbed that has resources distributed across five continents. Copyright © 2002 John Wiley & Sons, Ltd.

Mobile grid combines mobile computing and grid computing and develops rapidly. This paper aimed at designing a general architecture of mobile grid, illustrated mobile grid architecture design principle, presented a novel architecture, analyzed the mobile grid constitutes and logical structure. After that we discussed mobile grid resource and service management and allocation mechanism from description, discovery, security, QoS and selection and assignment factors, etc. Moreover, we proposed a design application example of mobile grid based on wireless network. We make a conclusion and put forward future work finally. Result shows that the mobile grid architecture we designed and analyzed is effective and feasible and practical.

Performance evaluation of grid resource management and scheduling system is of key importance to the success of the grid. In this paper, we introduce a generalized stochastic Petri net (GSPN) model for such purpose. The model is simple with clarity and can be applied to other research issues on grid to provide them with performance evaluation capabilities.

As Grid technologies evolve quickly on Internet, research related to resource scheduling faces new opportunities and challenges. These new technologies, ideas and approaches provide a new environment for researching and developing the economy-based resource scheduling system. Aiming at the hierarchical Grid model, following utility optimization thinking, while an universal flexible utility function is provided for addressing the Grid users’ QoS requirements of deadline and budget, this paper proposes a new Grid resource scheduling algorithm, which can not only increase the utilization of resources and system throughput, but also realize cost-time optimization between resource providers and users within Grid systems. On the basis of having described the different functional parts of the proposed algorithm, two kinds of simulative experiments about completion time and cost of tasks are conducted. Finally, the experiment results show that the proposed algorithm is effective.

Clusters, Grids, and peer‐to‐peer (P2P) networks have emerged as popular paradigms for next generation parallel and distributed computing. They enable aggregation of distributed resources for solving large‐scale problems in science, engineering, and commerce. In Grid and P2P computing environments, the resources are usually geographically distributed in multiple administrative domains, managed and owned by different organizations with different policies, and interconnected by wide‐area networks or the Internet. This introduces a number of resource management and application scheduling challenges in the domain of security, resource and policy heterogeneity, fault tolerance, continuously changing resource conditions, and politics. The resource management and scheduling systems for Grid computing need to manage resources and application execution depending on either resource consumers' or owners' requirements, and continuously adapt to changes in resource availability.The management of resources and scheduling of applications in such large‐scale distributed systems is a complex undertaking. In order to prove the effectiveness of resource brokers and associated scheduling algorithms, their performance needs to be evaluated under different scenarios such as varying number of resources and users with different requirements. In a Grid environment, it is hard and even impossible to perform scheduler performance evaluation in a repeatable and controllable manner as resources and users are distributed across multiple organizations with their own policies. To overcome this limitation, we have developed a Java‐based discrete‐event Grid simulation toolkit called GridSim. The toolkit supports modeling and simulation of heterogeneous Grid resources (both time‐ and space‐shared), users and application models. It provides primitives for creation of application tasks, mapping of tasks to resources, and their management. To demonstrate suitability of the GridSim toolkit, we have simulated a Nimrod‐G like Grid resource broker and evaluated the performance of deadline and budget constrained cost‐ and time‐minimization scheduling algorithms. Copyright © 2002 John Wiley & Sons, Ltd.

The research activity accounted for in this Ph.D thesis belongs to the general field of electrical and electronic measurement. The attention is focused on the implementation of GRID services for performance assessing of digital wireless communication systems. The original contribution consists in the development of two original measurement methods, the former allows measuring the modulation quality of systems compliant with IEEE 802.16d-2004 standard by means of any hardware characterized by a enough sample rate and input band width, and the latter carries out reliability and efficiently the in-service measurements also in presence of in-channel interferences. The high computational burden experienced during the wide experimental phase by proposed methods has encouraged their implementation according to GRID Service paradigm. Respect to the classic Web Service, GRID Service provides the possibility of both sharing the proposed methods among researches and technicians who work on the same topics, and processing some proposed methods stages in parallel way on several calculus nodes, thus reducing the whole processing time. Differently from the normal GRID Service, the developed GRID Services involve the measurement instrumentation, such digital acquisition systems and waveform generator, other than the calculus nodes. Suitable strategies for discovering, accessing, setting the measurement instruments have to be provided for. To this aim, new GRID architecture has been proposed, which virtualizes the measurement instruments into new components, namely instrumentation devices, and makes use of classic mechanisms already presented in GRID architecture, such as PBS scheduler, for dealing with the instruments discovery issue. To take advantage from the proposed GRID Services, a proper web portal is also implemented. An intense experimental phase is executed for assessing the methods and GRID Services performance by applying emulated and real communication signals. Measurement results are analyzed and compared to those achievable through the application of existing methods and/or instrument available on the market. Particular attention is also made to the processing time measurement of GRID Service with respect to a sequential implementation, in order to evidence the gains provided by a parallel implementation.

The open grid services infrastructure (OGSI) defines a distributed system framework by integrating grid and Web services technologies to facilitate the sharing of various resources, which result in grid service. Grid service inherits the features from Web service, aiming at enabling interoperability among heterogeneous grid application. However, in the open grid services architecture (OGSA), grid services are isolated, it is difficult building a grid service management framework which can work across organizations. Based on BPEL4WS, this paper proposes an agent-oriented grid service modeling framework to address the difficulties in developing grid applications based on grid services.

To enable service level subscription in computing grid, the economic concept of differentiated marketing is introduced into grid resource scheduling and a novel resource-scheduling model, Differentiated Service Model (DSM), is presented. DSM uses the Strictness Factor, Greediness Factor and Credit Score to describe the characteristics of the users and resources, like service requirement and service level. A series of related strategies, including resource evaluating, job risk exposure rating, operation adjustment etc., have been developed to conduct the market players' behavior. A simulation examined DSM's performance and showed its effectiveness: With its aggregate job delivery punctuality being approximate to that of the conventional resource scheduling model, DSM delivered services to users with different quality corresponding to the subscribed service level, especially under a heavy system workload; DSM also balanced the benefit distribution among resources, avoiding the situation that some particular resources monopolize the market share.

Improving the grid resource matching performance under large-scale users and computing resources environment is an important and challenging problem. Many existing grid resource matching and scheduling algorithms need search and compare every grid computing resource node without considering characteristics of grid resource and users' behavior. At the same time, with service oriented grid development, grid system should provide personalized service in scheduling process. Therefore, this paper proposes a novel grid resource matching algorithm based improved collaborative filtering algorithm that can give user recommendation resource set by computing the best approximate resource based on user's behavior.