Grid Computing Environments Research Articles

Analysis and Design of GRB System Based on WSRF Web Service

One advantage of WSRF Web Service is to establish loosely connective system by itself. This kind of system is easier to be updated than strongly connective system, and its demand of the system is little in real implementation of Web Service. Loose connection is a favorite design pattern for a researcher in software design. GRB (Grid Resource Broker) system has to consider how the control flow flows from a service to another one and emphasize on designing the implementation of indexing service in GT5(Globus toolkits 5). GRB system centers on resource administration in computing grid environment and carries out the research surrounding numerous key technologies. The resource publication, querying resource, spending resource, file transfer service and system security problem of GRB system are analyzed and designed, and thus some exploration on the research related to grid computing and its grid application is done.

Grid High Availability and Service Security Issues with Solutions

DDoS attacks are launched through sending a large quantity of packets to a target machine, using instantaneous teamwork of multiple hosts which are distributed throughout the Grid computing environment. Today DDoS attacks on the Internet in general and especially in Grid Computing environment has become a visible issue in computer networks. DDoS attacks are easy to generate but their detection is a very difficult task and therefore, an attractive weapon for hackers. DDoS streams do not have familiar characteristics, therefore currently available IDS cannot detect these attacks perfectly. Similarly, there implementation is a challenging task. In practice, Gossip based DDoS attacks detection mechanism is used to detect such types of attacks in network, by exchanging traffic over line. Gossip based techniques results in network congestion and have overhead of extra packets. Keeping the above drawbacks in mind, we are going to propose a DDoS detection and prevention mechanism, that has the beauty of being easy to adapt and more reliable than existing counterparts. We are going to introduce entropy based detection mechanism for DDoS attack detection. Our proposed solution has no overhead of extra packets, hence resulting in good QoS. Once DDoS is detected, any prevention technique can be used to prevent DDoS in Grid environment.

An Adaptive Scheduling Mechanism for Computational Desktop Grid Using GridGain

A computational grid essentially represents a dynamic and distributed environment. Unlike, a tightlycoupled parallel computing environment, high performance computing on a grid is a complex environment because of the heterogeneous computational performance of the nodes, possible unavailability of nodes, unpredictable node behavior, and unreliable network connectivity. Therefore, in a computational grid, scheduling of jobs is an exigent proposition considering its dynamic nature. In comparison to static scheduling, an adaptive scheduling mechanism is more attractive in a grid-computing environment, owing to its capability to adjust the scheduling policy according to the dynamically changing computational environment. This paper presents an adaptive scheduling method, which can be used for parallel applications whose total workload is unknown a priori. This method can deal with the unpredictable execution conditions commonly encountered on grids. To address this scheduling problem, parameters which quantify the dynamic nature of the execution conditions had to be defined. The proposed scheduling method is based on an online algorithm which is to be adaptable to the varying execution conditions.

A Cooperative Cell Model in Computational Mobile Grid

Computation in the mobile grid nodes under the cellular network environment requires an efficient management of wireless channels along with the user mobility. Due to random movement of the mobile devices, the load over the cells in terms of initiation of new computation or carryover computation (handoff) may vary dynamically. This may result in non-availability of free channels for Inter-task communication leading in the drop of carryover computation or to initiate the new computation in the current cell. The proposed work designs a model by instigating substantive cooperation among underutilized and the overloaded cells, considering importance to the frequency reuse and assigning priority to the on-going computation in the computational mobile grid. The model seeks cooperation by grouping the cells in different sizes to reduce the blocking and dropping of the computation. Blocking of the communication is very serious in computational mobile grid environment as the drop may result in the termination of the computation. The model aims at minimizing the Call Block Probability (CBP) and Call Drop Probability (CDP) in the mobile grid by making the clusters of different sizes. A simulation experiment to evaluate the performance of the proposed model reveals the effectiveness of this model.

An Approach to Keep Credentials Secured in Grid Computing Environment for the Safety of Vital Computing Resources

Presently security attacks have aimed to vulnerabilities in repetitive-use authentication secrets like static passwords. The passwords are used by user in clients side are vulnerable, as the attackers can gain access to a user's password using different types of viruses as it is being typed. These attacks are directing many Grid sites to explore one-time password solutions for authentication in Grid deployment. We present here a novel mechanism called N-LSB where Grid security will be integrated with modified LSB based steganographic technique in order to meet the higher security demands for Grid credentials.

Sensor Data Integration With The Grid: Model and Algorithm

This paper studies the problem of sensor data integration with grid computing. We set up the mathematical models for optimal sensor resources allocation in sensor-enabled grid-computing environment. In this paper, the iterative algorithm that achieves sensor integration with the grid is proposed. The experiments are conducted to compare our proposed algorithm for sensor integration with self-optimization-based resource management and scheduling for sensor grid. In the simulations, we use several measurement metrics: response time, profit, and energy consumption.

Policy-Based Scheduling and Resource Allocation for Multimedia Communication on Grid Computing Environment

This paper discusses policy-based scheduling techniques on heterogeneous resource for multimedia services to deal with the demands of next-generation multimedia applications on grid computing environment. The proposed scheduling algorithm has the following features, which can be utilized on grid computing environment. First, the algorithm supports the resource usage constrained scheduling. A grid consists of the resources that are owned by decentralized institutions. Second, the algorithm performs the optimization-based scheduling. It provides an optimal solution to the grid resource allocation problem. Third, the algorithm assumes that a set of resources is distributed geographically and heterogeneous in nature. Fourth, the scheduling method dynamically adjusts to the grid status. It tracks the current workload of the resources. The performance of the proposed algorithm is evaluated with a set of predefined metrics. In addition to show the simulation results for the out-performance of the policy-based scheduling a set of experiment is performed on open science grid.

Adapting grid computing environments dependable with virtual machines: design, implementation, and evaluations

Due to its potential, using virtual machines in grid computing is attracting increasing attention. Most of the researches focus on how to create or destroy a virtual execution environments for different kinds of applications, while the policy of managing the virtual environments is not widely discussed. This paper proposes the design, implementation, and evaluation of an adaptive and dependable virtual execution environment for grid computing, ADVE, which focuses on the policy of managing virtual machines in grid environments. To build a dependable virtual execution environments for grid applications, ADVE provides an set of adaptive policies managing virtual machine, such as when to create and destroy a new virtual execution environment, when to migrate applications from one virtual execution environment to a new virtual execution environment. We conduct experiments over a cluster to evaluate the performance of ADVE, and the experimental results show that ADVE can improve the throughput and the reliability of grid resources with the adaptive management of virtual machines.

Security Aware Parallel and Independent Job Scheduling in Grid Computing Environments Based on Adaptive Job Replication

In grid environment, jobs may be scheduled to multiple machines across different administrative domains. However, grid security is a main hurdle to make the job scheduling decision secure, reliable and fault tolerant. A s ecurity- aware parallel and independent job s cheduling algorithm in grid computing environment based on adaptive job replications was proposed. In risky and failure-prone grids, it is robust due to its adaptive job replications and rescheduling mechanism. Simulation results generated based on the SimGrid package show that a higher scheduling success of 97% rate and higher grid resource utilization of 74% can be achieved. The performance of our algorithm is better than non-security-aware scheduling algorithms based on fixed-number job replications and it is fault tolerant and scalable.

Implementation of modern cryptanalytic methods in computational grid environments based on cluster architectures

Implementation of modern cryptanalytic methods in computational grid environments based on cluster architectures

Rescue Robot Navigation Parallel Algorithm in Grid Computing Environment

In a disaster field, to obtain the optimal path in unknown environment,a rescue robot needs to build an environment map. Sensors mounted on the robots cooperate to monitor the environment, the information of the disaster field is collected by the sonsors of different robots, all signal from sensors (mounted on all robots and signal form GPS) are sent to the bakeside parllel processors with wireless network. A grid computing environment serves as the backside parallel processors with Globus Toolkit, the grid computing processor process all the signals and construct the global map to help robot for navigation path planning.The rescue robot get control signal from the grid computing processor with wireless network,thus, the robot is not necessary to be sophisticated. New computing methods are given for parallel algorithm on grid environment.The experiments show that the method is more practical and helps the path planning problem to be solved more efficiently, the advantages of large seale computing on grid are shown.

Virtual Machine Migration through an Intelligent Mobile Agents System for a Cloud Grid

During the last years, Virtual Machine technologies have become more and more widespread. Possible Virtual Machine integration is on the Cluster Grid Computing environment. So, the implemented idea described on this paper is based on Virtual Machine computing service. For these reasons, the main purpose of this research is to validate integration functionalities and performances of a Load Balancing System into a Cloud Grid with Virtual Compute Servers. Tests have focused on the restart of a batch job after a hardware crash and on the stopping of a job or its transfer to another host for hardware maintenance. A new algorithm has been created for automatic migration of a job, from a low performance node to a higher performance node.

Rescue Robot Navigation in Grid Computing Environment

To obtain the optimal path in a unknown disaster field,a rescue robot needs to build an environment map. The information of the disaster field is collected by the sonsors of different robots, all signal from sensors (mounted on all robots and signal form GPS) are sent to the bakeside parllel processors with wireless network. A grid computing environment serves as the backside parallel processors with Globus Toolkit, the grid computing processor process all the signals and construct the global map to help robot for navigation path planning.The rescue robot get control signal from the grid computing processor with wireless network,thus, the robot is not necessary to be sophisticated. New computing methods are given for parallel algorithm on grid environment. The navigation control is implemented with the cooperation among heterogeneous agents, the advantages of large seale computing on grid are shown.

Efficient resource management for running multiple concurrent jobs in a computational grid environment

Managing resources in Grid is an intricate issue and is not possible at the application or user level. Grid provides uniform access to heterogeneous resources owned by multiple organizations. Any time a new resource can join the Grid or an existing resource can withdraw. The system loads and status of the resources also change frequently. Thus, a resource broker is an essential component in a Grid environment that can assist in the selection of a right resource provider for a job in all aspects. This paper discusses the design and implementation of resource brokering strategies within the multi-agent framework. These strategies help in finding out an optimal allocation of resources for executing multiple concurrent jobs in a Grid environment. Different stages in resource brokering and their implementation within the framework are discussed. The paper also presents results of evaluating the strategies and demonstrates their effectiveness.

Aligning block permutation methods for topology transformation on computational grids

Many traditional parallel matrix computing algorithms are performed on regular resource topologies, such as mesh. However, the grid resource topology is often irregular in practice. In this paper, we present a transformation algorithm of grid resource topology for achieving virtual meshes. And on the virtual mesh, these traditional parallel algorithms can be performed in a modern computational grid environment. The basic idea of our topology transformation is to align the basic blocks of grid computational resources through permutations in a virtual mesh. Designing a cost function of heuristic search scheme for the transformation, we use it to fully exploit the computational and communicational abilities of grid resources. The experiment results show that our aligning block permutation can significantly reduce the time complexity of search tree. They also show that the heuristic search scheme can effectively find the block permutation that makes better use of computational and communicational abilities of grid resources.

A Resource-Aware Task Scheduling Algorithm on Mobile Computational Grid

This paper proposes a Resource-Aware Task Scheduling algorithm, named RATS, on mobile computational grid environment for scheduling tasks of mobile computing applications. Based on RATS, a proper order of tasks can be found out and the tasks can be scheduled to mobile grid nodes effectively and efficiently without taking account of resources, such as bandwidth and remaining energy, the cooperated grid nodes have. Some experiments have been conducted to evaluate the performance and reliability of RATS and to make a comparison with existing approaches. The results show that the RATS is superior to the others in term of efficiency, survival rate and reliability.

Parallelization of the Scale‐Changing Technique in Grid Computing environment for the electronmagnetic simulation of multi‐scale structures

AbstractA parallel computing approach to run fast and full‐wave electromagnetic simulation of complex structures in Grid Computing environment is presented. In this study, we show how Grid Computing improves speed and/or reliability over that provided by a single computer, while typically being much more cost‐effective than single computers of comparable speed or reliability. An efficient monolithic (unique) formulation for the electromagnetic modelling of complex (multi‐scale) structures, i.e. structures that exhibit multiple metallic patterns whose sizes cover a large range of scales, is used here. This approach, named the Scale‐Changing Technique, is based on the cascade of multi‐modal Scale‐Changing Networks, each network modelling the electromagnetic coupling between two successive scale levels. These networks can be first computed separately, in an adaptive use of Grid Computing architecture nature, and then cascaded for the global electromagnetic simulation. Based on this technique, a fast computer algorithm was developed and tested in the Grid‐Computing environment. For illustration purposes, the electromagnetic analysis of multi‐scale structures, applied to phase‐shifter elements and an example of infinite passive reflectarray, was carried out. The obtained results have confirmed the effectiveness of such an approach compared with sequential computing. This approach shows very good computation performance while keeping the same accuracy. Besides, this method is very promising for optimizing circuit with multiple design parameters to handle and for the global electromagnetic simulation of multi‐scale and/or oer‐sized structures. Copyright © 2010 John Wiley & Sons, Ltd.

Visualization Of Secured Grid Model For The Distributed Applications In Grid Computing Environment

Visualization Of Secured Grid Model For The Distributed Applications In Grid Computing Environment

Task scheduling model based on resource prediction for grid computing

Resources in grid computation environments are heterogeneous and dynamic, and tasks in grid computation environments are executed by computers from different domains or clusters of virtual organization synergistically; the static task scheduling is not fit for tasks execution in grid computing environments. In the paper, a task scheduling model based on the results of resources prediction was proposed. Firstly, a method of weighted least square estimation was given to construct Autoregressive Moving Average ( ARMA) model, which would be applied in CPU load prediction of grid computer. After modeling a kind of data parallel grid tasks, the task scheduling model based on the results of resources prediction was presented. Finally the simulations on the proposed model and some other models were designed and accomplished. The simulation results demonstrate that the presented model can run both significantly faster and more stable than other models.

Evaluating Heuristics for Scheduling Dependent Jobs in Grid Computing Environments

Job scheduling plays a critical role in the utilisation of grid resources by mapping a number of jobs to grid resources. However, the heterogeneity of grid resources adds some challenges to the work of job scheduling, especially when jobs have dependencies which can be represented as Direct Acyclic Graphs (DAGs). It is widely recognised that scheduling m jobs to n resources with an objective to achieve a minimum makespan has shown to be NP-complete, requiring the development of heuristics. Although a number of heuristics are available for job scheduling optimisation, selecting the best heuristic to use in a given grid environment remains a difficult problem due to the fact that the performance of each original heuristic is usually evaluated under different assumptions. This paper evaluates 12 representative heuristics for dependent job scheduling under one set of common assumptions. The results are presented and analysed, which provides an even basis in comparison of the performance of those heuristics. To facilitate performance evaluation, a DAG simulator is implemented which provides a set of tools for DAG job configuration, execution, and monitoring. The components of the DAG simulator are also presented in this paper.