A novel shared key for security in grid computing

Grid computing helps us overcome heterogeneity in terms of computing elements, operating systems, policy decisions, and environments. However, security issues impede us from adopting the grid as a widespread IT virtualization solution, so we must develop solutions to address these issues.

Web 2.0 has been adopted by many as the best way for forming a collaborative framework e.g., sharing resources, experiences, information, knowledge and feedback. A collaborative framework for application to e-health is necessary to provide patients with the awareness that assists in improving their health. Moreover, collaborative framework can be used by physician to exchange experiences and discuss challenge cases. However, the use of Web 2.0 with healthcare applications is not simple as the use of Web 20 with other enterprise applications according to the privacy of healthcare applications, which requires high quality and security of data, availability of resources, maintainability of services, system security, and Quality of Services (QoS). To offer the required requirements, grid computing is proposed here. Grid computing supporting enterprise applications through offering massive resources through resources collaborative framework that is offering power computing, storage devices, and services. The use of grid computing by Web 2.0 requires robust model that is able to deploy, discover, invoke, and integrate resources in open standard format. Therefore, Service Oriented Architecture (SOA) is adopted as a model for managing the mixing between Web 2.0 and grid computing technologies. SOA for Web 2.0 and Grid Computing (SOAW2G) are used throughout this work to offer a fabric for e-health applications.

This paper presents a mathematical model to evaluate the performance of grid resources when availability of the resources is taken into account. The proposed model uses continuous time Markov chains (CTMCs) to model the failure-repair behavior of a grid resource. In grid computing environment, a resource not only may fail during task execution, but also it can cancel its membership at any time. Hence, the proposed CTMC considers the availability of a grid resource to a grid user in both failure and membership refusal situations. After modeling the availability of the resource, the mean sojourn time of grid tasks in each of the availability states is estimated. Assigning the mean sojourn times of the tasks as performance levels to each of the CTMC's states, a Markov reward model (MRM) representing the combined performance and availability measures is obtained. Computing the cumulative state probability of the CTMC and multiplying reward rates of the MRM's states to each of the corresponding state probabilities, the expected accumulated sojourn time of grid tasks in each of the grid resources is achieved. An illustrative example is presented and the results obtained from the proposed model are reported in cases where various scheduling disciplines are considered inside the grid resource to simultaneously service grid and local tasks.

In this paper, we review and summarize some of the leading computing concepts including cluster, grid, and cloud computing. These ideas relate to bringing computers together to build a more powerful computational engine that is capable of processing multiple tasks concurrently. In cluster computing, a group of computers are located close by and directly linked with extremely high speed connections in order to perform as a single computer system. In grid computing, computer resources from multiple Internet domains are combined to reach a common computational goal. Compared with clusters, grids tend to be more loosely coupled, heterogeneous, and geographically distributed. Cloud computing is an emerging technology allowing a large number of interconnected computers, hardware and/or software to be rented as a commodity like electricity. The service types of cluster, grid, and cloud have been compared. We conclude that cloud computing has the potential to meet various computing demands in a cost effective easy way provided that some crucial issues like privacy, security, migration, and management are properly addressed.

Recently, distributed computing infrastructures such as grid computing, have witnessed huge developments which have a very important impact on computationally intensive scientific, industrial and engineering problems. Collaborative computing, resources access and sharing facilitated by grid computing systems amplifies concerns about cyber attacks and misbehaviors of grid resources (resources provider). In many cases, an organization may send out jobs for remote execution on untrustworthy machines. Since resource sharing and cooperation among different administrative domains are among the central goals of grid computing, it is necessary to guarantee that, among the shared resources, there are no malicious resources interested in invalidating or corrupting the job results. In order to guarantee reliable jobs execution in grid systems, we have developed a new approach for malicious grid resources tolerance using reputation to improve the efficiency of majority voting mechanisms. The grid broker service investigates the trustworthiness of the grid resources used in the voting procedure; this investigation is based on distributed and hierarchical reputation management system which maintains a reputation value for each grid resource based on its historical behavior. The validation of the result is then decided based on the grid resources reputation level.

A 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.

Remote job submission and execution is fundamental requirement of distributed computing done using Cluster computing. However, Cluster computing limits usage within a single organization. Grid computing environment can allow use of resources for remote job execution that are available in other organizations. This paper discusses concepts of batch-job execution using LRM and using Grid. The paper discusses two ways of preparing test Grid computing environment that we use for experimental testing of concepts. This paper presents experimental testing of remote job submission and execution mechanisms through LRM specific way and Grid computing ways. Moreover, the paper also discusses various problems faced while working with Grid computing environment and discusses their trouble-shootings. The understanding and experimental testing presented in this paper would become very useful to researchers who are new to the field of job management in Grid.

Current grid computing has developed from traditional high performance, distributed and site-fixed computing to pervasive, ubiquitous and wireless computing. In practice, PKI-based solutions are introduced to solve security of grid computing. Because of limited computation power and limited memory spaces, it is difficult for wireless grid computing to gain secure solution in collaboration environment. The trusted computing (TC) technologies are introduced to offer great potential to improve this situation. In this paper, with treated trusted platform module (TPM) as a tamper-resistance module, a TC-enabled architecture is proposed to improve wireless grid security. Especially authorization protection is discussed to demonstrate how to gain enhanced and distributed security in grid environment

Computational grades have emerged as a new approach to solving large-scale problems in the fields of science, engineering, and commerce. The computing grid is a hardware and software infrastructure that provides affordable, reliable, comprehensive, and affordable access to the computational abilities of others. A computational grid is associated with a set of resources on a large scale. Computational grades have emerged as a new approach to solving large-scale problems in the fields of science, engineering, and commerce. The computing grid is a hardware and software infrastructure that provides affordable, reliable, comprehensive, and affordable access to the computational abilities of others. A computational grid is associated with a set of resources on a large scale. The purpose of this thesis is to provide a method that optimizes resource management and scheduling in at least one direction. The main focus of the research is on the time criterion, the deadline for doing things and receiving the response from the grid are parameters that can be examined. From a more general perspective, the aim of the research is to get the answer as quickly as possible from the calculation grid. The proposed algorithm improves the scheduling and resource management of the grid in the direction of improvement, and the structure and form of this problem have not yet been resolved. The proposed solution has been considered hypothesis and removed some of the definitions of grid scheduling, such as cost, quality of service, architectures, and others, but ultimately heed it and timed the grid in some ways.

Due to great advantages that Service-Oriented Architecture (SOA) offers to its adopters in almost all fields, many studies tried to leverage it in grid computing. These studies focused on enabling easy access and flexible management to underlying grid resources. However, none of them allowed access to grid resources through various technologies. Rather, most of them utilized SOA in terms of XML web services without considering its limitations. In this paper, we will introduce a high level architecture that goes beyond traditional efforts in leveraging SOA in grid computing. This architecture uses Enterprise Service Bus (ESB) model by leveraging Windows Communication Foundation (WCF) to offer a number of endpoints for published services. With these endpoints different requirements from both grid clients and executors could be easily and efficiently met. Proposed architecture does not tend to supersede other SOA-based grid computing frameworks and standards. Instead, it offers a new method for wrapping grid computing resources with a set of configurable WCF services that could be utilized by these frameworks.

Many applications involve the concepts of scheduling, such as communications, packet routing, production planning [Zhai et al., 2006], classroom arrangement [Mathaisel & Comm, 1991], aircrew scheduling [Chang, 2002], nurse scheduling [Ohki et al., 2006], food industrial [Simeonov & Simeonovova, 2002], control system [Fleming & Fonseca, 1993], resource-constrained scheduling problem [Chen, 2007] and grid computing. There are many different types of scheduling problems such as real-time, job-shop, permutation flow-shop, project scheduling and other scheduling problems have been studied intensively. However, in this work, the studied grid task scheduling problem is much more complex than above stated classic task scheduling problems. Restated, a grid application is regarded as a task scheduling problem involving tasks with inter-communication and distributed homogeneous or heterogeneous resources, and can be represented by a task interaction graph (TIG). Grid is a service for sharing computing power and data storage capacity over the Internet. The grid systems outperform simple communication between computers and aims ultimately to turn the global network of computers into one vast computational resource. Grid computing can be adopted in many applications, such as high-performance applications, large-output applications, data-intensive applications and community-centric applications. These applications major concern to efficiently schedule tasks over the available multi-processor environment provided by the grid. A grid is a collaborative environment in which one or more tasks can be submitted without knowing where the resources are or even who owns the resources [Foster et al., 2001]. The efficiency and effectiveness of grid resource management greatly depend on the scheduling algorithm [Lee et al., 2007]. Generally, in the grid environment, these resources are different over time, and such changes will affect the performance of the tasks running on the grid. In grid computing, tasks are assigned among grid system [Salman, 2002]. The purpose of task scheduling in grid is to find optimal task-processor assignment and hence minimize application completion time (total cost). Most scheduling problems in these applications are categorized into the class of NP-complete problems. This implies that it would take amount of computation time to obtain an optimal solution, especially for a large-scale scheduling problem. A variety of approaches have been applied to solve scheduling problems, such as

This paper deals with the electromagnetic modeling of large and complex electrical structures by means of extensive parallel modeling based on grid computing (GC). The numerical modeling is based on a hybrid approach which combines Transmission Line Matrix (TLM) and the mode matching methods. The former is applied to homogeneous volumes while the latter is used to describe planar structures presented within the entire simulation domain. The results prove the benefits of the combined GC and hybrid approach to solve electrically large structures.

Volunteer Computing (VC) is an approach under grid computing which prepares a platform for computer owners around the globe to donate their resources at internet based VC projects like as SETI@home, Folding@hom. Therefore, global desktop grid is a VC that includes hosts who present their resources to solve some kind of CPU, RAM or Disk space-intensive problems. At the moment, the common approach used in resource scheduling in VC is mostly based on CPU availability alone. However, we believe that RAM and disk space of the volunteering hosts also play a role in ensuring an optimized assignment of a job to a host, and hence, could lead to an improved resource scheduling performance of the VC. As an initial step to support the above proposal, a formula for normalizing the three different resource information, i.e., CPU, RAM, and disk space, into common representations is developed. In this paper, the normalization formula is presented as well as the formula for calculating the average availability of three resources. Besides, the results from applying the two formulas to a data set extracted from http://fta.inria.fr/res/ are also given. The results show a significant support to the potential of the proposed approach. Impact of this research to the organization will be execution of their tasks' project in suitable cluster of volunteers with specified weighted mean of resources.

In present era, technical problems are complex enough to be resolved by a single computer. Grid Computing is a promising field that deals with exploiting the idle CPU cycles of resources connected in a network. Job scheduling is a most demanding subject in computing grids. An effective scheduling strategy is required to utilize the resources in grid and to balance the overall load on them. This paper presents an enhanced job scheduling algorithm with budget constraint which extends existing algorithm to include economy factor into account. The main contribution of our work is dual: Firstly it tries to balance load of overall grid system and secondly it assigns tasks to resources with best computing capability which lies within the budget specified by each user. The performance of proposed algorithm is assessed by conducting simulations using GridSim. Observations prove that this algorithm achieves reduced average cost of execution for jobs to great extent so that it lies in the user's stated budget.

This paper addresses necessary modification and extensions to existing Grid Computing approaches in order to meet modern business demand. Grid Computing has been traditionally used to solve large scientific problems, focussing more on accumulative use of computing power and processing large input and output files, typical for many scientific problems. Nowadays businesses have increasing computational demands, such that Grid technologies are of interest. However, the existing business requirements introduce new constraints on the design, configuration and operation of the underlying systems, including availability of resources, performance, monitoring aspects, security and isolation issues. This paper addresses the existing Grid Computing capabilities, discussing the additional demands in detail. This results in a suggestion of problem areas that must be investigated and corresponding technologies that should be used within future Business Grid systems.KeywordsGrid SizeSoftware LandscapesApplication DataExecution CharacteristicsAutonomyService Level Agreements