Grid Information Service Research Articles

A Scalable Grid Information Service Framework for Engineering and Scientific Computation

A Scalable Grid Information Service Framework for Engineering and Scientific Computation

A secure information service for monitoring large scale grids

The Grid Information Service (GIS) is a core component in the Grid software infrastructure. It provides diverse information to users or other service components in Grid environments. In this paper, we propose a scalable GIS architecture for information management in a large scale Grid Virtual Organization (VO). This architecture consists of the VO layer, site layer and resource layer: at the resource layer, information agents and pluggable information sensors are deployed on each resource monitored. This information agent and sensor approach provides a flexible framework that enables specific information to be captured; at the site layer, a site information service component with caching capability aggregates and maintains up-to-date information of all the resources monitored within an administrative domain; at the VO layer, a peer-to-peer approach is used to build a virtual network of site information services for information discovery and query in a large scale Grid VO. This decentralized approach makes information management scalable and robust. Furthermore, we propose a security framework for the GIS, which provide security policies for authentication and authorization control of the GIS at both the site and the VO layers. Our GIS has been implemented based on the Globus Toolkit 4 as Web services compliant to Web Services Resource Framework (WSRF) specifications. The experimental results show that the GIS presents satisfactory scalability in handling information for large scale Grids.

An approach to grid resource selection and fault management based on ECA rules

In grid computing, resource management and fault tolerance services are important issues. Because the numbers of the application tasks and amounts of required resources are enormous and quick responses to the requirements of users are necessary in the real grid environment, real-time resource co-allocation may be large-scale. This paper proposes an Active Grid Information Server (AGIS) that is a resource manager for optimal resource selection and fault tolerant service using a database management system that supports event–condition–action (ECA) rules. Our resource manager automatically selects the set of optimal resources among idle resources that achieves optimal performance while turnaround time is chosen as metric for performance evaluation. Typically, the probability of a failure is higher in grid computing than in traditional parallel computing and the failure of resources affects job execution fatally. Therefore, a fault tolerance service is essential in computational grids. Grid services are often expected to meet some minimum levels of Quality of Service (QoS) for a desirable operation. To address this issue, we also propose a fault tolerance service that satisfies QoS requirements. The fault tolerance requires timely notification of changes, raising the need for mechanisms for monitoring and processing such changes. Event–condition–action (ECA) rules are a natural candidate to fulfill this need. We develop conservative tests for determining the termination and confluence of sets of ECA rules. We argue that the employment of ECA rules, both for resource selection and fault tolerance, leads to efficiency and to additional techniques. Furthermore, the proposed AGIS system architecture offers a number of advantages owing to the performance and scalability that can be achieved using active databases. Our preliminary performance results indicate that the ECA rule-based approach for resource matching is efficient in speed and accuracy and can keep up with high job-arrival rates — an important criterion for online resource matching systems. We describe Grid-JQA, an architecture supporting such rules in grid environments, and our current implementation of this architecture. Three heuristic approaches have been designed and compared via simulations to match tasks which take into account the QoS requested by the tasks, and at the same time, to minimize the tasks makespan as much as possible. Also, an optimum method based on the performance metric has been designed to compare the performance of the heuristics developed. Our proposed solution has at least a 45% improvement over the general method which uses a first come, first served (FCFS) strategy. The implementation and simulation results indicate that our approaches are promising in that the resource manager finds the optimal set of resources to guarantee efficient job execution, the fault manager guarantees that the submitted jobs are completed, and job execution is improved owing to job duplication even if some failures occur.

GridBench: A tool for the interactive performance exploration of Grid infrastructures

As Grids rapidly expand in size and complexity, the task of benchmarking and testing, interactive or unattended, quickly becomes unmanageable. In this article we describe the difficulties of testing/benchmarking resources in large Grid infrastructures and we present the software architecture implementation of GridBench, an extensible tool for testing, benchmarking and ranking of Grid resources. We give an overview of GridBench services and tools, which support the easy definition, invocation and management of tests and benchmarking experiments. We also show how the tool can be used in the analysis of benchmarking results and how the measurements can be used to complement the information provided by Grid Information Services and used as a basis for resource selection and user-driven resource ranking. In order to illustrate the usage of the tool, we describe scenarios for using the GridBench framework to perform test/benchmark experiments and analyze the results.

A Framework for an Integrated Co-allocator for Data Grid in Multi-Sender Environment

Data grid consists of scattered computing and storage resources located dispersedly in the grid network. These large sized data sets are replicated in more than one site for the better availability to the other nodes in a grid. Downloading the dataset from these replicated locations have practical difficulties and we find interest in a co-allocated download framework, which enables parallel download of replicated data from multiple servers. In this paper, we proposed a dynamic co-allocation scheme for parallel data transfer in grid environment, which copes up with highly inconsistent network and server performance. The model comprises of co-allocator, monitor and control mechanisms. The scheme initially obtains the bandwidth parameter from the monitor module to fix the partition size and the data transfer tasks are allocated onto the servers in duplication. In this way, the process of data transfer can neither be interrupted nor paralyzed, even when the network link is broken or server crash. We used Globus toolkit for our framework by making use of grid information and GridFTP services. We compared our scheme with the existing schemes and the results show notable improvement in overall completion time of data transfer.

S-Club: an overlay-based efficient service discovery mechanism in CROWN Grid

Information service plays a key role in grid system, handles resource discovery and management process. Employing existing information service architectures suffers from poor scalability, long search response time, and large traffic overhead. In this paper, we propose a service club mechanism, called S-Club, for efficient service discovery. In S-Club, an overlay based on existing Grid Information Service (GIS) mesh network of CROWN is built, so that GISs are organized as service clubs. Each club serves for a certain type of service while each GIS may join one or more clubs. S-Club is adopted in our CROWN Grid and the performance of S-Club is evaluated by comprehensive simulations. The results show that S-Club scheme significantly improves search performance and outperforms existing approaches.

Introducing Virtual Private Overlay Network Services in Large Scale Grid Infrastructures

The computational Grid concept is gaining great popularity as the best way to deliver access to a wide range of distributed computing and data resources. But, as Grids move from an experimental phase to real production and their deployment in the Internet significantly increases, controlling the security of a Grid application becomes imperative. The most significant Grid security issue is that the different sites composing the Grid will generally be managed by different organizations each with their own security mechanisms and policies. This makes any communication security arrangement on the entities participating to the Grid generally more difficult than if they were on the same LAN. In this paper, we propose a novel network resource abstraction for delivering dynamic on-demand Virtual Private Overlay connection services, into large-scale Grid environments. Such facility provides to Grid applications an illusion of dedicated layer-2 LAN connections that are fully comparable to a private network in performance, reliability, security and Quality of Service, but also provide topology and control plane virtualization to ensure better isolation also at the protocol and address space level. It may represent a technological breakthrough that can transform the overall connection paradigm in modern Grids, by reducing infrastructure costs, with the elimination of private circuits and long-distance direct connections, and increasing network coverage and flexibility by leveraging the Internet usage. As a proof of concept, the proposed facility has been implemented in a Grid Information Service prototype which was successfully tested on a small dedicated testbed infrastructure.

An Efficient Design and Implementation for Grid Advanced Information Service

Grid information service is an indispensable component for Grid computing, by which all types of Grid resources are virtually integrated and their information can be efficiently managed and accessed. Furthermore, the efficiency of Grid computing is dependent on the functionalities supported by Grid information service. At present, the Grid information service of Globus toolkitTM 3, an Index service, supports a few basic functions such as service data population, subscription, and lookup. In this paper, we propose an information service component of MoredreamTM which we refer to as GAIS (Grid Advanced Information Service), for providing more plentiful resource information and advanced functionalities in order to satisfy the requirements for various applications in the K*Grid computing environment characterized by both high performance and high throughput computing. In particular, GAIS includes interfaces and functionalities for dynamic VO management, peer-to-peer communication, and service categorization. In addition, our resource-monitoring tool reduces the monitoring overhead and maintains accuracy of events by detecting effective resource changes and collecting events at the kernel level, respectively. Consequently, we anticipate that our Grid information service will be broadly utilized through improved service qualities.

Fast Compositional Queries in a Relational Grid Information Service

A Grid Information service (GIS) stores information about the resources of a distributed computing environment and answers questions about it. We have developed RGIS, a GIS system that, unlike previous efforts, is based on the relational data model. RGIS users can write SQL queries that search for complex compositions of resources that meet collective requirements. Executing these queries can be very expensive, however. In response, we have introduced three query techniques, nondeterminism, scoping, and approximation, that allow the user (and RGIS) to trade off between the query’s running time and the number of results. Herein we describe RGIS, our query techniques, and their implementation. Our evaluation shows that a meaningful tradeoff between query time and results returned is achievable, and that the tradeoff can be used to keep query time largely independent of query complexity. RGIS uses our techniques to bound query execution time. This strongly supports our general case for GIS systems based on the relational data model and RDBMSes.

A Grid Architecture for Scalable e-Science and Its Prototype

This paper presents an e-Science Grid architecture called Virtual and Dynamic Hierarchical Architecture (VDHA). VDHA is a decentralized architecture with some P2P properties. It also has scalable, autonomous, exact, and full service discovery properties. We have implemented a demonstration VDHA_based Grid prototype ? VDHA_Grid, which has scalable Grid information service. VDHA_Grid is the core software for the project of the Chinese University e-Science Grid. In this paper, advantages and several protocols of the VDHA are also discussed.

Efficiency of resource brokering in grids for high-energy physics computing

This paper presents a study of the efficiency of resource brokering in a computational grid constructed for CPU and data intensive scientific analysis. Real data is extracted from the logging records of an in-use resource broker relating to the running of Monte Carlo simulation jobs, and compared to detailed modeling of job processing in a grid system. This analysis uses performance indicators relating to how efficiently the jobs are run, as well as how effectively the available computational resources are being utilized. In the case of a heavily loaded grid, the delays incurred at different stages of brokering and scheduling are studied, in order to determine where the bottlenecks appear in this process. The performance of different grid setups is tested, for instance, homogeneous and heterogeneous resource distribution, and varying numbers of resource brokers. The importance of the speed of the grid information services (IS) is also investigated.

MAAN: A Multi-Attribute Addressable Network for Grid Information Services

Recent structured peer-to-peer (P2P) systems such as distributed hash tables (DHTs) offer scalable key-based lookup for distributed resources. However, they cannot be simply applied to grid information services because grid resources need to be registered and searched using multiple attributes. We propose a multiattribute addressable network (MAAN) which extends chord to support multiattribute and range queries. MAAN addresses range queries by mapping attribute values to the chord identifier space via uniform locality preserving hashing. It uses an iterative or single attribute dominated query routing algorithm to resolve multiattribute based queries. Each node in MAAN only has O(logN) neighbors for N nodes. The number of routing hops to resolve a multiattribute range query is O(logN+N/spl times/s/sub min/), where s/sub min/ is the minimum range selectivity on all attributes. When s/sub min/=/spl epsiv/, it is logarithmic to the number of nodes, which is scalable to a large number of nodes and attributes. We also measured the performance of our MAAN implementation and the experimental results are consistent with our theoretical analysis.

Performance evaluation of a grid resource monitoring and discovery service

The Grid Information Service (GIS) is one of the Grid Common Services which make up the basic functions belonging to Grids. This service offers a resource discovery mechanism, of which an implementation is provided by the Monitoring and Discovery Service (MDS- 2) which is part of the Globus Toolkit. Grid applications are typically the users of this resource discovery mechanism; knowledge is thus obtained about the existence of appropriate resources on which to execute jobs. Since these Grid applications are likely to be influenced by dynamic middleware, it is crucial that they experience a reliable performance for the proper utilisation of resources and for accountability purposes. Consequently, the approach taken in this paper is to investigate and evaluate a level of performance obtainable from the MDS. A better understanding of the performance of the GRIS (Grid Resource Information Service) and subsequently the GIIS (Grid Index Information Service), leads to a more standard way of formalising the performance of a Grid Information Service. This is achieved by defining a number of performance metrics which are analysed against a set of different information gathering methods and GRIS back-end implementations.

An Evaluation of Alternative Designs for a Grid Information Service

Computational grids consisting of large and diverse sets of distributed resources have recently been adopted by organizations such as NASA and the NSF. One key component of a computational grid is an information services that provides information about resources, services, and applications to users and their tools. This information is required to use a computational grid and therefore should be available in a timely and reliable manner. In this work, we describe the Globus information service, describe how this service is used, analyze its current performance, and perform trace-driven simulations to evaluate alternative implementations of this grid information service. We find that the majority of the transactions with the information service are changes to the data maintained by the service. We also find that of the three servers we evaluate, one of the commercial products provides the best performance for our workload and that the response time of the information service was not improved during the single experiment we performed with data distributed across two servers.