Security implications of typical Grid Computing usage scenarios

The Internet of Things (IoT) is defined as interconnected digital and mechanical devices with intelligent and interactive data transmission features over a defined network. The ability of the IoT to collect, analyze and mine data into information and knowledge motivates the integration of IoT with grid and cloud computing. New job scheduling techniques are crucial for the effective integration and management of IoT with grid computing as they provide optimal computational solutions. The computational grid is a modern technology that enables distributed computing to take advantage of a organization’s resources in order to handle complex computational problems. However, the scheduling process is considered an NP-hard problem due to the heterogeneity of resources and management systems in the IoT grid. This paper proposed a Greedy Firefly Algorithm (GFA) for jobs scheduling in the grid environment. In the proposed greedy firefly algorithm, a greedy method is utilized as a local search mechanism to enhance the rate of convergence and efficiency of schedules produced by the standard firefly algorithm. Several experiments were conducted using the GridSim toolkit to evaluate the proposed greedy firefly algorithm’s performance. The study measured several sizes of real grid computing workload traces, starting with lightweight traces with only 500 jobs, then typical with 3000 to 7000 jobs, and finally heavy load containing 8000 to 10,000 jobs. The experiment results revealed that the greedy firefly algorithm could insignificantly reduce the makespan makespan and execution times of the IoT grid scheduling process as compared to other evaluated scheduling methods. Furthermore, the proposed greedy firefly algorithm converges on large search spacefaster , making it suitable for large-scale IoT grid environments.

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.

A distributed multiple dimensional QoS constrained resource scheduling optimization policy in computational grid

In traditional distributed computing systems a few user types are found having rather ``flat profiles, mainly due to the same administrative domain the users belong to. This is quite different in Computational Grids (CGs) in which several user types should co-exist and make use of resources according to hierarchical nature and the presence of the multiple administrative domains. One implication of the existence of different hierarchical levels in CGs is that it imposes different access and usage policies on resources. In this paper we firstly highlight the most common Grid users types and their relationships and access scenarios in CGs corresponded to old (e.g. performance) and new (e.g security) requirements. Then, we identify and analyze new features arising in users' behavior in Grid scheduling, such as dynamic, selfish, cooperative, trustful, symmetric and asymmetric behaviors. We discuss also how computational economy-based approaches, such as market mechanisms, and computational paradigms, such as Neural Networks, can be used to model user requirements and predict users' behaviors in CGs. As a result of this study we have provided a comprehensive analysis of Grid user scenarios than can serve as a basis for application designers in CGs.

In 1998, Ian Foster and Carl Kesselman, together with thirty distinguished experts in high-performance computing and networking, laid the foundations of a new computing model called GRID. Their vision was introduced in the book, The GRID: Blueprint for a New Computing Infrastructure (see review, SCPE Vol. 3, No. 3 ). The editors wrote: … A computational grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities… allowing new classes of applications to emerge… as yet, we have only a preliminary understanding of what these new applications will look like. Over the next five years, Grid computing became the hottest R&D field. Academia and national labs built experimental infrastructures, new startups were established to develop Grid technologies, and the HPC giant vendors joined the party. Each one pushed in a different direction based on what and how he believed Grid computing should look. It was only a matter of time until people started to ask what the Grid is all about. A survey of ten Grid experts produced ten different answers. The question remains without a clear answer, leaving many people confused. Ian Foster picked up the gloves. In his article, What is the GRID? A three point checklist (GRIDtoday, July 22, 2002: Vol. 1, No. 6), he redefines the Grid model to reflect the trades and changes in the field during the past five years. According to Foster, a Grid is a system that: Coordinates resources that are not subject to centralized control. Uses standard, open, general-purpose protocols and interfaces. Delivers a nontrivial quality of service. But Foster's new definition could not encompass all of the Grid's approaches. Moreover, Foster explained by example what the Grid is not: A cluster management system such as Sun's Sun Grid Engine, Platform's Load Sharing Facility, or Viridian's Portable Batch System can, when installed on a parallel computer or local area network, deliver quality of service guarantees and thus constitutes a powerful Grid resource. However, such a system is not a Grid itself, due to its centralized control of the hosts that it manages Within a week the responses started to come in. The first one was from Wolfgang Gentzsch, Director of Grid computing at Sun Microsystems (GRIDtoday, August 5, 2002: Vol. 1, No. 8). Gentzsch wrote: I very much like Ian's two earlier definitions. Combined, they may provide a very generic Grid definition. The new checklist, however, reduces the potential of a wide and rich variety of Grids, with different architectures, operational models, and applications, and may miss the chance to becoming widely accepted as a standard definition of the Grid. Why do we need a definition for the Grid? Can the Grid be defined? Is a definition is necessary to the Grid's development? The Grid is an open vision and thus cannot be defined. An attempt to define the Grid can only reach the foreseen technology horizon, and this horizon is only one to two years ahead. Grid computing is a paradigm in shift. New architectures and standards are changing the shape and direction of the Grid's development. In the past year one such prominent architecture was Open Grid Services Architecture (OGSA). The OGSA is the first attempt to bridge the gap between two cyberspace worlds: the Internet and the Grid. The Internet and the Grid are two different computing models. There are people who believe that the Grid is the next generation of the Internet and the World Wide Web, saying that the Great Global Grid is still many years away. Others state that the Grid will complement, not replace, the Internet as we know it. In 1998, when the Grid blueprint was published, a new Internet language appeared called eXtensible Markup Language (XML). XML is a development tool for a new Internet computing model known as Web Services. At that time, nobody understood that there is a relationship between Web Services and the Grid. Three years past before Steve Tuecke from Argonne National Laboratory started to write a spec for Grid Services. Later, people from IBM joined the mission and together they created OGSA. The OGSA specification outlines interfaces to grid computing software that comply with Web Services standards. If adopted, Grid services such as job scheduling, authentication, failure-detection, staging of applications and data, and migration of applications and data, will all be accessed through standard Web Services architecture. OGSA is basically where Grid meets Web Services and maybe the first step towards full integration of the Internet and the Grid. The Internet appeared a decade ago. In the beginning, the Net offered primitive applications: a mailing system, ftp services, and a web of home pages. Nobody asked, What is the Internet? The years passed and new emerging Internet technologies were developed. Today we can talk on the phone over the Net, chat with friends, and video conference with colleagues on the other side of the world. New computing and business models were developed: e-commerce, e-learning, e-science, and e-you-name-it. And nobody asks what the Internet is. The Grid is a super-model, a bag of networking models associated with many types of architectures, software packages, applications, and standards. Today, when people talk about the Grid they mention Data Grids, Science Grids, and Campus Grids. And at the same time they mention Farm computing, Peer-to-peer computing, and Utility computing, among others. Ten years from now many of today's technologies will disappear and new ones will be developed. I don't know how Grid computing will look a decade from now, but I know that we will have g-commerce, g-learning, g-science, and g-chat. Nobody will ask what the Grid is. It will be obvious, just as the Internet is today. Ami Marowka The Computer Aided Design Laboratory School of Engineering and Computer Science Hebrew University of Jerusalem

A survey of economic models in grid computing

With a wealth of biodiversity, a long tradition of agriculture-based industries, and an established medical and biotechnological research and development community, Thailand has become an attractive location for life sciences investment. The large amount of data generated in many areas of life sciences requires visualization, management, and analysis, principally through bioinformatics. To become successful, Thailand's research community should emphasize establishing core technologies, such as genomics and bioinformatics, to boost development of agriculture, food processing, and biomedical research. The Thai government realized the importance of this field and created a national policy to greatly increase Thailand's participation in bioinformatics and genomics, budgeting for specific development goals in research infrastructure, education, and sustainable human resources. Thailand has not lagged behind in bioinformatics research activity and recognizes the importance of bioinformatics through increased policy awareness, human resources development, and increased research activity involving genomic-scale data generation and computational analyses. Many applications of genomics and bioinformatics to biomedical research and development in Thailand have progressed substantially during the past few years, leading to successful applications in some specific local areas. However, the applications to other important areas, such as agriculture, are hampered by the limited availability of genomic sequence data and the lack of necessary biochemical/physiological information. With the advent of more and more genomic information in public databases, Thailand's research community is striving to adopt comparative genomics to obtain information of direct relevance to the country's health and industrial needs. This article highlights Thailand's contribution to genomics and bioinformatics in the following areas: (1) policy support from the Thai government, (2) capacity building through infrastructure/education/human resources, and (3) research and development in genomics and computational biology. (See Box 1 for Authors' Biographies). Box 1. Authors' Biographies Wannipha Tongsima, M.S., obtained her master's degree in Industrial Microbiology from Chulalongkorn University, Thailand. She was involved in founding the Bioinformatics research program in BIOTEC. To reinforce the research activity in this area, she also helped organize the first International Conference on Computational Biology (InCoB), held in Bangkok in 2002. Later, she was appointed to manage one of the first BIOTEC ethnic-specific human genetic variation programs, named the Thailand SNP Discovery Project. She works as a Genomic Medicine program coordinator for the Cluster and Program Management Office (CPMO) of the National Science and Technology Development Agency (NSTDA), which is an umbrella organization of four other national research centers in Thailand, including BIOTEC. Sissades Tongsima, Ph.D., received his doctoral degree in Computer Science and Engineering from the University of Notre Dame, Indiana, United States. He has worked for the National Electronics and Computer Technology Center on High Performance Computing (HPC) and Computational Grid. During 2002–2004, he cochaired the Asia-Pacific Advanced Network (APAN) Grid Working Group. In 2003, he shifted his research direction from HPC architecture to bioinformatics research, when he started working for BIOTEC, and constructed the ThaiSNP database. His main research interest is in developing algorithms and databases for analyzing various research projects on human genetic variation. He currently heads the Genome Institute biostatistics and informatics laboratory at BIOTEC. Prasit Palittapongarnpim, M.D., earned his medical degree from Mahidol University, Thailand, and his B.S. in Mathematics from Ramkumhang University, Thailand. He is a Fellow of the Royal College of Pediatricians of Thailand and also an Associate Professor in Microbiology at Mahidol University, where he has conducted research focusing on tuberculosis. While holding a Deputy Director position, he initiated the Bioinformatics research program at BIOTEC in 2002 and led the organization of the first InCoB conference in 2002. He is currently a Vice President of NSTDA.

According to the characteristics of high-performance computation and computational grid, a Grid Re- development Model ( GRM) was proposed. Regarding the combination of Remote Method Invocation ( RMI) , and SSL /TLS technology, GRM firstly provided a consistent interface to access to grid middleware; secondly, screened the complex and trivial problems for accessing grid through network; thirdly, solved the data security issues for sensitive data transferred in insecure wide-area network. Based on the grid middleware used by scientific computing grid, the GRM was implemented. The case studies and experimental results of developing user interfaces based on GRM and experimental results show that, the GRM not only provides an easy, useful and full featured development model, but also has good performance and portable features.

The distinguishing feature of a metasystem is middleware that facilitates viewing a collection of large, distributed, heterogeneous resources as a single virtual machine, where each user of the metasystem is identified by a unique metasystem-level identity.The physical resources of the metasystem can exist in multiple administrative domains, each with different local security requirements and authentication mechanisms (e.g., Kerberos, publickey).The problem this paper addresses is how to map the metasystems-level identity to an appropriate account on each local physical machine for the purposes of process creation, such that the access control and authentication policies of each local machine are not violated.This mapping must ensure the integrity of the local machines, must ensure the integrity of the metasystem user's data, and must not unnecessarily burden either the metasystem users, the metasystem system administrator, or the local machine system administrators.Specific examples are drawn from experiences gained during the deployment of the Legion metasystem.For example, Legion configurations for local sites with different access control mechanisms such as standard UNIX mechanisms and Kerberos are compared.Through analysis of these configurations, the inherent security trade-offs in each design are derived.These results have practical importance to current and future metasystem users and to sites considering any future inclusion of local resources in a global virtual computer.

In Grid computing, resource management and fault tolerance services are important issues. The availability of the selected resources for job execution is a primary factor that determines the computing performance. The failure occurrence of resources in the grid computing is higher than in a tradition parallel computing. Since the failure of resources affects job execution fatally, fault tolerance service is essential in computational grids. And grid services are often expected to meet some minimum levels of quality of service (QoS) for desirable operation. However Globus toolkit does not provide fault tolerance service that supports fault detection service and management service and satisfies QoS requirement. Thus this paper proposes fault tolerance service to satisfy QoS requirement in computational grids. In order to provide fault tolerance service and satisfy QoS requirements, we expand the definition of failure, such as process failure, processor failure, and network failure. And we propose resource scheduling service, fault detection service and fault management service and show implement and experiment results.

Computer aided drug design is progressing and playing an increasingly important role in drug discovery. Computational methods are being used to evaluate larger and larger numbers of real and virtual compounds. New methods based on molecular simulations that take protein and ligand flexibility into account also contribute to an ever increasing need for compute time. Computational grids are therefore becoming a critically important tool for modern drug discovery, but can be expensive to deploy and maintain. Here, we describe the low cost implementation of a 165 node, computational grid at Anadys Pharmaceuticals. The grid makes use of the excess computing capacity of desktop computers deployed throughout the company and of outdated desktop computers which populate a central computing grid. The performance of the grid grows automatically with the size of the company and with advances in computer technology. To ensure the uniformity of the nodes in the grid, all computers are running the Linux operating system. The desktop computers run Linux inside MS Windows using coLinux as virtualization software. HYDRA has been used to optimize computational models, for virtual screening and for lead optimization.

Recent technologies including Web services, business process modeling tools, and grid computing, are key to facilitating business agility. Web services standardize application interfaces to ease inter-application communication, and facilitate standards based business process management. Grid computing provides a way for virtualizing heterogeneous resources to collectively yield a computationally powerful IT environment with tremendous promise in improving utilization levels of individual IT resources. By leveraging Web services, a standards based grid is being envisaged in the OGSA model. In this paper, we explore the complementarities of Web services and business process management (BPM) technologies. We also lay the foundation for using Web services based BPM in solving orchestration and workflow issues in grid computing.

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.

Grid Computing refers to the combination of computer resources from multiple administrative domains to reach a common goal. Grids which are a form of distributed computing contains collection of resources that are available for an application to perform tasks. The resources in the grid are generally heterogeneous, geometrically dispersed and belong to different administrative domains. The important criterion in the grid computing is that resource sharing should be transparent, secure and better coordinated. In a typical heterogeneous user system such as in online trading, security is a major concern in terms of authentication, integrity of message and confidentiality. In the present work, secure group communication is ensured to the authenticated users by effective key distributions that are serviced by the resource. Trigon based algorithm has been used for multiple key distributions and has been demonstrated for online trading applications.

A prototype Taskspaces framework for grid computing of scientific computing problems that require intertask communication is presented. The Taskspaces framework is characterized by three major design choices: decentralization provided by an underlying tuple space concept, enhanced direct communication between tasks by means of a communication tuple space distributed over the worker hosts, and object orientation and platform independence realized by implementation in Java. Grid administration tasks, for example resetting worker nodes, are performed by mobile agent objects. We report on large-scale grid computing experiments for iterative linear algebra applications showing that our prototype framework scales well for scientific computing problems that require neighbor-neighbor intertask communication. It is shown in a computational fluid dynamics simulation using a Lattice Boltzmann method that the Taskspaces framework can be used naturally in interactive collaboration mode. The scalable Taskspaces framework runs fully transparently on heterogeneous grids while maintaining a low complexity in terms of installation, maintenance, application programming and grid operation. It thus offers a promising roadway to push scientific grid computing with intertask communication beyond the experimental research setting.