Multiple QoS modeling and algorithm in computational grid

Multiple QoS modeling and algorithm in grid system is considered. Grid QoS requirements can be formulated as a utility function for each task as a weighted sum of its each dimensional QoS utility functions. Multiple QoS constraint resource scheduling optimization in computational grid is distributed to two subproblems： optimization of grid user and grid resource provider. Grid QoS scheduling can be achieved by solving sub problems via an iterative algorithm.

Improved algorithmic mechanism based on game theory in computational grids

Computational grids （CGs） aim to offer pervasive access to a diverse collection of geographically distributed resources owned by different serf-interested agents or organizations. These agents may manipulate the resource allocation algorithm in their own benefit, and their selfish behavior may lead to severe performance degradation and poor efficiency. In this paper, game theory is introduced to solve the problem of barging for resource collection in heterogeneous distributed systems. By using the Cournot model that is an important model in static and complete information games, the algorithm is optimized in order to maximize the benefit. It can be seen that the approach is more suitable to the real situation and has practical use. Validity of the solutions is shown.

Fine-grained grid computing model for Wi-Fi indoor localization in complex environments

The fingerprinting-based approach using the wireless local area network(WLAN)is widely used for indoor localization.However,the construction of the fingerprint database is quite time-consuming.Especially when the position of the access point(AP)or wall changes,updating the fingerprint database in real-time is difficult.An appropriate indoor localization approach,which has a low implementation cost,excellent real-time performance,and high localization accuracy and fully considers complex indoor environment factors,is preferred in location-based services(LBSs)applications.In this paper,we proposed a fine-grained grid computing(FGGC)model to achieve decimeter-level localization accuracy.Reference points(RPs)are generated in the grid by the FGGC model.Then,the received signal strength(RSS)values at each RP are calculated with the attenuation factors,such as the frequency band,three-dimensional propagation distance,and walls in complex environments.As a result,the fingerprint database can be established automatically without manual measurement,and the efficiency and cost that the FGGC model takes for the fingerprint database are superior to previous methods.The proposed indoor localization approach,which estimates the position step by step from the approximate grid location to the fine-grained location,can achieve higher real-time performance and localization accuracy simultaneously.The mean error of the proposed model is 0.36 m,far lower than that of previous approaches.Thus,the proposed model is feasible to improve the efficiency and accuracy of Wi-Fi indoor localization.It also shows high-accuracy performance with a fast running speed even under a large-size grid.The results indicate that the proposed method can also be suitable for precise marketing,indoor navigation,and emergency rescue.

An Improved Grid Security Infrastructure by Trusted Computing

Current delegation mechanism of grid security infrastructure （GSI） can＇t satisfy the requirement of dynamic, distributed and practical security in grid virtual organization. To improve this situation, a TC-enabled GSI is discussed in this paper. With TC-enabled GSI, a practical delegation solution is proposed in this paper through enforcing fine granularity policy over distributed platforms with the emerging trusted computing technologies. Here trusted platform module is treated as a tamper-resistance module to improve grid security infrastructure. With the implement of Project Daonity, it is demonstrated that the solution could gain dynamic and distributed security in grid environment.

Performance Predictable ServiceBSP Model for Grid Computing

This paper proposes a performance prediction model for grid computing model ServiceBSP to support developing high quality applications in grid environment. In ServiceBSP model, the agents carrying computing tasks are dispatched to the local domain of the selected computation services. By using the IP （integer program） approach, the Service Selection Agent selects the computation services with global optimized QoS （quality of service） consideration. The performance of a ServiceBSP application can be predicted according to the performance prediction model based on the QoS of the selected services. The performance prediction model can help users to analyze their applications and improve them by optimized the factors which affects the performance. The experiment shows that the Service Selection Agent can provide ServiceBSP users with satisfied QoS of applications.

Resource management and job scheduling of China earthquake grid experiment system: Construction of resource management and job dynamic scheduling model ProRMJS

Grid technique is taken as the third generation internet technology and resource management is the core of it. Aiming at the problems of resource management of CEDAGrid （China Earthquake Disaster Alleviation and Simulation Grid） in its preliminary construction, this paper presents a resource management and job scheduling model： ProRMJS to solve these problems. For platform supposed agreeably each computing node can provide computation service, ProRMJS uses ＂computation pool＂ to support scheduler, and then the scheduler allocates jobs dynamically according to computing capability and status of each node to ensure the stability of the platform. At the same time, ProRMJS monitors the status of job on each node and sets a time threshold to manage the job scheduling. By estimating the computing capability of each node, ProRMJS allocates jobs on demand to solve the problem of supposing each node can finish the job acquiescently. When calculating the computing capability of each node, ProRMJS allows for the various factors that affect the computing capability and then the efficiency of the platform is improved. Finally the validity of the model is verified by an example.

Using Hash Tree for Delegation Revocation in Grids

Grid security infrastructure （GSI） provides the security in grids by using proxy certificates to delegate the work of authentication. At present, revocation proxy certificate has two kinds of methods, one is using certificate revocation list （CRL） and the other is giving the certificate a short period of validity. However, when a lot of certifications are revoked, CRL will be the burden in the system. If the certificate has a short period of validity, entities should be often updating the certificate. In this paper, we propose a scheme for proxy certificate revocation using hash tree. Our scheme only needs hash value comparisons to achieve the purpose of certificate revocation. Previous two methods have to wait the expiration of the certificate. Therefore, our scheme is more flexible than previous methods.

Adaptive Trust Management Framework in P2P Grid Computing

In P2P Grid computing systems, the authorization decision is often tackled by two different trust management methods： policy-based approach, where authorization are built on logical rules and verifiable properties encoded in signed credentials, and reputation-based approach, based on collecting, aggregating and disseminating reputation among the peers. However, the overhead caused by proof of compliance on authorization and the absence of certifying authorities may negate the strong and objective security advantages of policy-based approach, whilst vagueness, complexity and inaccurate characterization caused by reputation evolution may eliminate the quantitative and flexible advantages of reputation-based approach. We propose an adaptive trust management framework, which combines the merit of policy proof and reputation evolution such that authorization is aware of not only the strong and objective security traits, but also the calculability and the availability security traits. Finally, the framework of system is proposed.

Call for Papers The 6^(th) International Conference on Grid and Cooperative Computing

Recent years have seen rapid advances in various grid-related technologies, middleware, and applications. The GCC conference has become one of the largest scientific events worldwide in grid and cooperative computing. The 6th international conference on grid and cooperative computing (GCC2007) Sponsored by China Computer Federation (CCF),Institute of Computing Technology, Chinese Academy of Sciences (ICT) and Xinjiang University ,and in Cooperation with IEEE Computer Soceity ,is to be held from August 16 to 18, 2007 in Urumchi, Xinjiang, China.

Spatial Data Sharing on Grid

The Internet technology has already changed the Information Society in profound ways, and will continue to do so. Nowadays many people foresee that there is a similar trajectory for the next generation of Internet - Grid Technology. As an emerging computational and networking infrastructure, Grid Computing is designed to provide pervasive, uniform and reliable access to data, computational and human resources distributed in a dynamic, heterogeneous environment. On the other hand, the development of Geographic Information System （GIS） has been highly influenced by the evolution of information technology such as the Internet, telecommunications, software and various types of computing technology. In particular, in the distributed GIS domain, the development However, due to the closed and centralized has made significant impact in the past decade. legacy of the architecture and the lack of interoperability, modularity, and flexibility, current distributed GIS still cannot fully accommodate the distributed, dynamic, heterogeneous and speedy development in network and computing environments. Hence, the development of a high performance distributed GIS system is still a challenging task. So, the development of Grid computing technology undoubtedly provides a unique opportunity for distributed GIS, and a Grid Computing based GIS paradigm becomes inevitable. This paper proposes a new computing platform based distributed GIS framework - the Grid Geographic Information System （G^2IS）.

DCCS:A General-Purpose Distributed Cryptographic Computing System

Distributed cryptographic computing system plays an important role since cryptographic computing is extremely computation sensitive. However, no general cryptographic computing system is available. Grid technology can give an efficient computational support for cryptographic applications. Therefore, a general-purpose grid-based distributed computing system called DCCS is put forward in this paper. The architecture of DCCS is simply described at first. The policy of task division adapted in DCCS is then presented. The method to manage subtask is further discussed in detail. Furthermore, the building and execution process of a computing job is revealed. Finally, the details of DCCS implementation under Globus Toolkit 4 are illustrated.

A Parallel Genetic Simulated Annealing Hybrid Algorithm for Task Scheduling

In this paper combined with the advantages of genetic algorithm and simulated annealing, brings forward a parallel genetic simulated annealing hybrid algorithm （PGSAHA） and applied to solve task scheduling problem in grid computing. It first generates a new group of individuals through genetic operation such as reproduction, crossover, mutation, etc, and than simulated anneals independently all the generated individuals respectively. When the temperature in the process of cooling no longer falls, the result is the optimal solution on the whole. From the analysis and experiment result, it is concluded that this algorithm is superior to genetic algorithm and simulated annealing.

History-based trust negotiation model

Trust negotiation （TN） is an approach to establish trust between strangers through iterative disclosure of digital credentials. Speeding up subsequent negotiations between the same negotiators is a problem worth of research. This paper introduces the concept of visiting card, and presents a history-based trust negotiation （HBTN） model. HBTN creates an account for a counterpart at the first negotiation and records valid credentials that the counterpart disclosed during each trust negotiation in his historical information base （HIB）. For the following negotiation, no more credentials need to be disclosed for both parties. HBTN speeds up subsequent negotiations between the entities that interact with each other frequently without impairing the privacy preservation.

MONTE CARLO SIMULATION ON COMPUTATIONAL FINANCE FOR GRID COMPUTING

Monte Carlo methods are a class of computational algorithms that rely on repeated random sampling to compute their results.Monte Carlo methods are often used in simulating complex systems.Because of their reliance on repeated computation of random or pseudo-random numbers,these methods are most suited to calculation by a computer and tend to be used when it is infeasible or impossible to compute an exact result with a deterministic algorithm.In finance,Monte Carlo simulation method is used to calculate the value of companies,to evaluate economic investments and financial derivatives.On the other hand,Grid Computing applies heterogeneous computer resources of many geographically disperse computers in a network in order to solve a single problem that requires a great number of computer processing cycles or access to large amounts of data.In this paper,we have developed a simulation based on Monte Carlo method which is applied on grid computing in order to predict through complex calculations the future trends in stock prices.

G-Phenomena as a Base of Scalable Distributed Computing—G-Phenomena in Moore’s Law

Today we witness the exponential growth of scientific research. This fast growth is possible thanks to the rapid development of computing systems since its first days in 1947 and the invention of transistor till the present days with high performance and scalable distributed computing systems. This fast growth of computing systems was first observed by Gordon E. Moore in 1965 and postulated as Moore’s Law. For the development of the scalable distributed computing systems, the year 2000 was a very special year. The first GHz speed processor, GB size memory and GB/s data transmission through network were achieved. Interestingly, in the same year the usable Grid computing systems emerged, which gave a strong impulse to a rapid development of distributed computing systems. This paper recognizes these facts that occurred in the year 2000, as the G-phenomena, a millennium cornerstone for the rapid development of scalable distributed systems evolved around the Grid and Cloud computing paradigms.

Multisite co-allocation scheduling algorithms for parallel jobs in computing grid environments

Cooperation of multi-domain massively parallel processor systems in computing grid environment provides new opportunities for multisite job scheduling. At the same time, in the area of co-allocation, heterogeneity, network adaptability and scalability raise the challenge for the international design of multisite job scheduling models and algorithms. It presents multisite job scheduling schema through the introduction of multisite job scheduling model and the performance model under the grid environment. It introduces two job multisite and cooperative scheduling models and algorithms with the core of the optimal and greedy-heuristic resource selection strategies. Meanwhile, compared with single and multisite cooperative scheduling models and algorithms introduced by Sabin, Yahyapour and other persons, the validity and advance of the scheduling model and the performance model herein are proved.

A Model of Grid Service Capacity

Computational grids （CGs） are large scale networks of geographically distributed aggregates of resource clusters that may be contributed by distinct organizations for the provision of computing services such as model simulation, compute cycle and data mining. Traditionally, the decision-making strategies underlying the grid management mechanisms rely on the physical view of the grid resource model. This entails the need for complex multi-dimensional search strategies and a considerable level of resource state information exchange between the grid management domains. In this paper we argue that with the adoption of service oriented grid architectures, a logical service-oriented view of the resource model provides a more appropriate level of abstraction to express the grid capacity to handle incoming service requests. In this respect, we propose a quantification model of the aggregated service capacity of the hosting environment that is updated based on the monitored state of the various environmental resources required by the hosted services. A comparative experimental validation of the model shows its performance towards enabling an adequate exploitation of provisioned services.

The extended RBAC model based on grid computing

This article proposes the extended role-based access control （RBAC） model /br solving dynamic and multidomain problems in grid computing, The formulated description of the model has been provided. The introduction of context and the mapping relations of context-to-role and context-to-permission help the model adapt to dynamic property in grid environment. The multidomain role inheritance relation by the authorization agent service realizes the multidomain authorization amongst the autonomy domain. A function has been proposed for solving the role inheritance conflict during the establishment of the multidomain role inheritance relation.

CROWN:A service grid middleware with trust management mechanism

Based on a proposed Web service-based grid architecture, a service grid middleware system called CROWN is designed in this paper. As the two kernel points of the middleware, the overlay-based distributed grid resource management mechanism is proposed, and the policy-based distributed access control mechanism with the capability of automatic negotiation of the access control policy and trust management and negotiation is also discussed in this paper. Experience of CROWN testbed deployment and application development shows that the middleware can support the typical scenarios such as computing-intensive applications, data-intensive applications and mass information processing applications.