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The increase in demand variability created by manufacturing enterprises presents new challenges for increasing resource usage and sharing flexibility. For this reason, it is of great importance to research manufacturing grids and their service modes. The purpose of this paper is to establish a systematic strategy and a system tool for manufacturing grid systems.

A manufacturing service oriented manufacturing grid (MSoMG) system is presented with open grid service architecture as the system architecture and GT3.9 as a development tool. A framework is proposed to support MSoMG by providing advisory tools and methods for uncertain information analysis and processing, multi-objective decision making of manufacturing grid service execution, manufacturing grid service performance prediction based on knowledge template, and flexible manufacturing grid service scheduling and solution. The methodology of the adopted rough set is discussed in detail. Finally, the design support strategies for MSoMG are investigated to guide the coordination of manufacturing activities.

Many conventional methods and models become very limited for manufacturing grid service with uncertain information. The processing of uncertain information and reasonable application flow can help to improve the completion rate and reliability of manufacturing grid services.

This research provides a solid foundation for manufacturing gird operations and can promote the use of a manufacturing grid mode.

A MSoMG system is presented. The manufacturing grid service with uncertain information is considered as well as design support strategies.

The interaction of systems through a designated control channel has improved communication, efficiency, management, storage, processing, etc. across several industries. The construction industry is an industry that thrives on a well-planned workflow rhythm; a change in the environmental dynamism will either have a positive or negative impact on the output of the project planned for execution. More so, raising the need for effective collaboration through workflow and project planning, grid application in construction facilitates the relationship between the project reality and the end users, all with the aim of improving resources and value management. However, decentralisation of close-domain control can cause uncertainty and incompleteness of data. And this can be a big factor, especially when a complex project is being executed.

Owing to the numerous part models and massive datasets used in automobile assembly design, virtual assembly software cannot simulate a whole vehicle smoothly in real time. For this reason, implementing a new virtual assembly environment for massive complex datasets would be a significant achievement. The paper aims to focus on this problem.

A new system named “Grid‐enabled collaborative virtual assembly environment” (GCVAE) is proposed in the paper, and it comprises three parts: a private grid‐based support platform running on an inner network of enterprise; a service‐based parallel rendering framework with a sort‐last structure; and a multi‐user collaborative virtual assembly environment. These components would aggregate the idle resources in an enterprise to support assembly simulation with a large complex scene of whole vehicle.

The system prototype proposed in the paper has been implemented. The following simulations show that it can support a complex scene in a real‐time mode by using existing hardware and software, and can promote the efficient usage of enterprise resources.

Using the GCVAE, it is possible to aggregate the idle resources in an enterprise to run assembly simulations of a whole automobile with massively complex scenes, thus observably reducing fault occurrence rates in future manufacturing.

The paper introduces a new grid‐enabled methodology into research on collaborative virtual assembly system which can make the best use of idle resources in the enterprise to support assembly simulations with massively complex product models. A video‐stream‐based method was used to implement the system; this enables designers to participate ubiquitously in the simulation to evaluate the assembly of the whole automobile without hardware limitations.

Grid computing is gaining more significance in the high‐performance computing world. This concept leads to the discovery of solutions for complicated problems regarding the diversity of available resources among different jobs in the grid. However, the major problem is the optimal job scheduling for heterogeneous resources, in which each job needs to be allocated to a proper grid's node with the appropriate resources. An important challenge is to solve optimally the scheduling problem, because the capability and availability of resources vary dynamically and the complexity of scheduling increases with the size of the grid. The purpose of this paper is to present a framework which combines the fuzzy C‐mean (FCM) clustering with an ant colony optimization (ACO) algorithm to improve the scheduling decision when the grid is heterogeneous.

In the proposed model, the FCM algorithm classifies the jobs into appropriate classes, and the ACO algorithm maps the jobs to the appropriate resources. The ACO is characterized by ant‐like mobile agents that cooperate and stochastically explore a network, iteratively building solutions based on their own memory and on the traces (pheromone levels) left by other agents.

The simulation is done by using historical information on jobs in a grid. The experimental results show that the proposed algorithm can allocate jobs more efficiently and more effectively than the traditional algorithms for scheduling policies.

The paper provides a scheduling model based on FCM clustering and ACO algorithm for grid scheduling. The authors compared the performance of the proposed algorithm with the performance of various job‐scheduling algorithms in the grid computing environment. The comparison results show that the proposed algorithm outperforms other algorithms and gives optimal results.

In the grid‐based simulation, the resource application needed is distributed in the grid environment as grid service, and time management is a key problem in the simulation system. Grid workflow provides convenience for grid user to management and executes grid services. But it emphasizes process and no time‐management, so a temporally constrained grid workflow model is pointed out based on grid flow with temporally constraint to schedule resources and manage time.

The temporally constrained grid workflow model is distributed model: the federate has local temporal constraints and interactive temporal constraints among federates. The problem to manage time is a temporally distributed constraint satisfaction problem given deadline time and duration time of grid services. Multi‐asynchronous weak‐commitment search (AWS) algorithm is an approach to resolve DCSP, so a practical example of a simulation project‐based grid system was presented to introduce application of Multi‐AWS algorithm.

The temporally constrained grid workflow is based temporal reasoning and grid workflow description about grid services.

The new problem about scheduling resources and managing time in the grid‐based simulation is pointed out; and the approach to resolve the problem is applied into a practical example.

Although wireless grids have been originally thought of as isolated processing clusters, the possibility of their approaching – and connecting to – a fixed network allows for a huge expansion of their processing power, due to the resources available in wired grids potentially accessible through such a network. The interoperation of mobile ad hoc grids and resources available in wired grids is, however, a problem still to be tackled in the literature. The purpose of this paper is to tackle this problem.

A prototype is developed to demonstrate the feasibility of the interoperation between wireless and wired grids, thus providing a basis for the development of novel applications that can build on this interoperation.

The outcome of the paper comprises the analysis of the necessary requirements for the interoperation between wireless and wired grids, the proposal of two different interoperation approaches, and the provision of a qualitative assessment of the implications of these approaches.

There are many points that the authors intend to address as future work. First, they are aware of the need for performing some quantitative analyses of their proxy implementations. Second, they intend to investigate the possibility of mobile ad hoc grids to process tasks coming from wired grids. Third, they are interested in allowing the submission of tasks that present interdependencies (workflows) from mobile devices in the mobile ad hoc grid.

The paper investigates the interoperation of wireless and wired grids. Such an interoperation may open new perspectives of practical use of wireless devices in scenarios such as emergency response networks and field research systems, to name a few.

The paper provides a first step into the interoperation of wireless and wired grids, thus yielding a basis for the development of novel applications that can build upon this interoperation. This is believed to be of interest to both the grid and mobile computing communities.

The purpose of this paper is to examine three different, but related, distributed computing technologies in the context of public‐funded e‐science research, and to present the author's viewpoint on future directions.

The paper takes a critical look at the state‐of‐the‐art with regard to three enabling technologies for e‐science. It forms a set of arguments to support views on the evolution of these technologies in support of the e‐science applications of the future.

Although grid computing has been embraced in public‐funded higher education institutions and research centres as an enabler for projects pertaining to e‐science, the adoption of desktop grids is low. With the advent of cloud computing and its promise of on‐demand provisioning of computing resources, it is expected that the conventional form of grid computing will gradually move towards cloud‐based computing. However, cloud computing also brings with it the “pay‐per‐use” economic model, and this may act as stimulus for organisations engaged in e‐science to harvest existing underutilised computation capacity through the deployment of organisation‐wide desktop grid infrastructures. Conventional grid computing will continue to support future e‐science applications, although its growth may remain stagnant.

The paper argues that there will be a gradual shift in the underlying distributed computing technologies that support e‐science applications of the future. While cloud computing and desktop grid computing will gain in prominence, the growth of traditional cluster‐based grid computing may remain dormant.

Grid computing is an effective environment for the execution of parallel applications that requires great computing power. This paper aims to present, based on the hierarchical architecture, an improved weighted resource discovery (WRD) algorithm to manage allocation of resources and minimize cost of communications between grid nodes.

A behavioral modeling method is addressed to prove the proposed method correctness. The behavioral model of the proposed algorithm is implemented by StarUML tool with two different model-checking mechanisms. Then, the resource discovery correctness is analyzed in terms of reachability condition, fairness condition and deadlock-free using NuSMV model checker.

The results show that WRD algorithm has better performance in requiring re-discovery process, the number of examined nodes in each request and discovering the free resources with high-bandwidth links.

To store information of resources, a new data structure called resource information table is proposed which facilitates resource finding of the algorithm. A behavioral modeling method is addressed to prove the proposed method correctness.

Grid computing has often been heralded as the next logical step after the worldwide web. Users of grids can access dynamic resources such as computer storage and use the computing resources of computers under the umbrella of a virtual organisation. Although grid computing is often compared to the worldwide web, it is vastly more complex both in organisational and technical areas. This also extends into the area of security and incident response, where established academic computer security incident response teams (CSIRTs) face new challenges arising from the use of grids. This paper aims to outline some of the organisational and technical challenges encountered by the German academic CSIRT, DFN‐CERT while extending and adapting their services to grid environments during the D‐Grid project.

Most national research and education networks (NRENs) already have computer security incident response teams to respond to security incidents involving computers connected to the networks. This paper considers how one established NREN CSIRT is dealing with the new challenges arising from grid computing.

The paper finds that D‐Grid Initiative is an ongoing project and the establishment of CSIRT services for grids is still at an early stage. The establishment of communication channels to the various grid communities as well as gaining of knowledge about grid software has required DFN‐CERT to make changes even though the basic principles of CSIRT operation remain the same.

The D‐Grid project aims to establish a common grid infrastructure that can be used by other scientific domains. The project consists of six community projects and one integration project (DGI – D‐Grid Integration). The DGI project will develop the basic infrastructure, while the community projects will build on this infrastructure and enhance it for the specific needs of their research areas. At the initial stage of the DGI project, the idea of a central CSIRT for all grids in Germany was seen as an advantage over having a CSIRT for each grid project, which would have replicated efforts and thus wasted resources. This paper gives an overview about the organisational and technical challenges and experiences DFN‐CERT has encountered while setting up a CSIRT for the D‐Grid communities.

The purpose of this paper is to characterise a number of current and future computing environments and summarises their resource discovery requirements. It then seeks to analyse, with respect to the requirements of each environment, several established service discovery protocols and some newer protocols that are still in the research domain. In addition, the key features of a new resource discovery protocol that has been developed to operate with heterogeneous computing environments are described.

A comprehensive literature survey was undertaken, highlighting the shortcomings of existing resource discovery protocols with respect to large pervasive computing environments. Given the identified gaps in existing protocols, an alternative protocol is suggested.

The main findings of this paper relate to the identified shortcomings of existing resource discovery protocols. It was also found that a hybrid resource discovery protocol capable of spanning dynamic, mobile computing environments and more stable ones was able to overcome many of the challenges presented by large‐scale pervasive computing environments.

This paper presents comprehensive literature survey of the state‐of‐the‐art in resource discovery protocols, pointing out some of the problems that are not solved. The paper describes the design of an alternative protocol, and presents an evaluation of it. The pervasive computing research community can draw upon the survey and evaluation to guide the design of future resource discovery protocols for the increasingly dynamic world in which we live.