Communication network analysis of the enterprise grid systems

This paper addresses the problem of performance analysis based on communication modelling of largescale heterogeneous distributed systems with emphases on enterprise grid computing systems. The study of communication layers is important because the overall performance of a distributed system is often critically hinged on the effectiveness of this part. This model considers processor as well as network heterogeneity of target system. The model is validated through comprehensive simulation, which demonstrates that the proposed model exhibits a good degree of accuracy for various system sizes and under different working conditions. The proposed model is then used to investigate the performance analysis of typical systems.

An online credential management service for InterGrid computing

Grid users and their jobs need credentials to access grid resources and services. It is important to minimize the exposure of credentials to adversaries. A practical solution is needed that works with existing software and is easy to deploy, administer, and maintain. Thus, credential management services are the wave of the future for virtual organizations such as Grid computing. This paper describes architecture of a scalable, secure and reliable on-line credential management service called SafeBox for InterGrid computing platform. SafeBox provides InterGrid users with secure mechanism for storing one or multiple credentials and access them based on need at anytime from anywhere.

Autonomic system management in mobile grid environments

Mobile device integration in grid environments is a challenge for many researchers. Due to the transient nature of mobile devices, service management is a critical, but often overlooked area of research. We propose a distributed broker responsible for the autonomic management of grid services. The broker provides self discovery and negotiation, self configuration and self healing for SOA based mobile grids. In this paper the design and prototype implementation of the broker is presented and the importance of autonomic grid service management is shown.

Determining service trustworthiness in inter loud computing environments

Deployment of applications and scientific workflows that require resources from multiple distributed platforms are fuelling the federation of autonomous clouds to create cyber infrastructure environments. As the scope of federated cloud computing enlarges to ubiquitous and pervasive computing, there will be a need to assess and maintain the trustworthiness of the cloud computing entities. In this paper, we present a fully distributed framework that enable interested parties determine the trustworthiness of federated cloud computing entities.

Managing data using neighbour replication on a triangular-grid structure

Data in grid research deals with storage, replication, and management of large data sets in a distributed environment. The all-data-to-all-sites replication schemes, like Read-One Write-All (ROWA) and Tree Grid Structure (TGS), are the popular techniques in grid. However, these techniques have a weakness in data storage capacity and data access times. In this paper, we propose the all-data-to-some-sites scheme called the 'Neighbour Replication on Triangular Grid' (NRTG) technique. The proposed scheme minimises the storage capacity as well as data access time with high update availability. It also tolerates failures such as server and site failures.

An efficient approach based on trust and reputation for secured selection of grid resources

Security is a principal concern in offering an infrastructure for the formation of general-purpose computational grids. A number of grid implementations have been devised to deal with the security concerns by authenticating the users, hosts and their interactions in an appropriate fashion. Resource management systems that are sophisticated and secured are inevitable for the efficient and beneficial deployment of grid computing services. The chief factors that can be problematic in the secured selection of grid resources are the wide range of selection and the high degree of strangeness. Moreover, the lack of a higher degree of confidence relationship is likely to prevent efficient resource allocation and utilisation. In this paper, we present an efficient approach for the secured selection of grid resources, so as to achieve secure execution of the jobs. This approach utilises trust and reputation for securely selecting the grid resources. To start with, the self-protection capability and reputation weightage of all the entities are computed, and based on those values, the trust factor (TF) of all the entities are determined. The reputation weightage of an entity is the measure of both the user’s feedback and other entities’ feedback. Those entities with higher TF values are selected for the secured execution of jobs. To make the proposed approach more comprehensive, a novel method is employed for evaluating the user’s feedback on the basis of the existing feedbacks available regarding the entities. This approach is proved to be scalable for an increased number of user jobs and grid entities. The experimentation portrays that this approach offers desirable efficiency in the secured selection of grid resources.

Efficient resource selection algorithm for enterprise grid systems

This paper addresses a resource selection problem for applications that update data in enterprise grid systems. The problem is insufficiently addressed as most of the existing resource selection approaches in grid environments primarily deal with read-only job. We propose a simple yet efficient algorithm that deals with the complexity of resource selection problem in enterprise grid systems. The problem is formulated as a Multi Criteria Decision Making (MCDM) problem. Our proposed algorithm hides the complexity of resource selection process without neglecting important components that affect job response time. The difficulty on estimating job response time is captured by representing them in terms of different QoS criteria levels at each resource. Our experiments show that the proposed algorithm achieves very good results with good system performance as compared to existing algorithms.

Grid transaction management and an efficient development kit

Grid transaction management aims at guaranteeing the system consistency in face of various failures in Grid environments. In this paper, we propose a Grid transaction service (GridTS) and design coordination mechanisms for atomic, long-lived and real-time Grid transactions respectively, based on the features of Grid environments. GridTS has the following three advantages. Firstly, it separates the transaction management unit with transaction coordination algorithms so that it can coordinate the above three categories of transactions in a uniform way. Secondly, GridTS can dynamically generate compensating transactions during the long-lived transaction processing. Finally, it provides the programming interfaces similar to traditional distributed transactions. Moreover, we implement a Grid transaction development kit (GridTDK) for application programmers based on our GridTS. We evaluate the feasibility and effectiveness of GridTS by developing an application system using our GridTDK. ©2012 CRL Publishing Ltd.

An efficient scheduling method for grid systems based on a hierarchical stochastic petri net

This paper addresses the problem of resource scheduling in a grid computing environment. One of the main goals of grid computing is to share system resources among geographically dispersed users, and schedule resource requests in an efficient manner. Grid computing resources are distributed, heterogeneous, dynamic, and autonomous, which makes resource scheduling a complex problem. This paper proposes a new approach to resource scheduling in grid computing environments, the hierarchical stochastic Petri net (HSPN). The HSPN optimizes grid resource sharing, by categorizing resource requests in three layers, where each layer has special functions for receiving subtasks from, and delivering data to, the layer above or below. We compare the HSPN performance with the Min-min and Max-min resource scheduling algorithms. Our results show that the HSPN performs better than Max-min, but slightly underperforms Min-min.

Sensor grid middleware metamodeling and analysis

Sensor grid is a platform that combines wireless sensor networks and grid computing with the aim of exploiting the complementary advantages of the two systems. Proper integration of these distinct systems into effective, logically single platform is challenging. This paper presents an approach for practical sensor grid implementation and management. The proposed approach uses a metamodeling technique and performance analysis and tuning as well as a middleware infrastructure that enable practical sensor grid implementation and management. The paper presents our implementation and analysis of the sensor grid. © 2014 Srimathi Chandrasekaran et al.

Fault-tolerant dynamic job scheduling policy

In this paper, we propose a scalable and fault-tolerant job scheduling framework for grid computing. The proposed framework loosely couples a dynamic job scheduling approach with the hybrid replications approach to schedule jobs efficiently while at the same time providing fault-tolerance. The novelty of the proposed framework is that it uses passive replication approach under high system load and active replication approach under low system loads. The switch between these two replication methods is also done dynamically and transparently.

Grids vs. clouds

When it comes to grid and cloud computing, there is a lot of debate over their relations to each other. A common feature is that grids and clouds are attempts at utility computing. However, how they realize utility computing is different. The purpose of this paper is to characterize and present a side by side comparison of grid and cloud computing and present what open areas of research exist.

Guest editors' introduction : Special issue on trust, security, and privacy in parallel and distributed systems

In modern computing paradigms, most computing systems, e.g., cluster computing, grid computing, cloud computing, the Internet, telecommunication networks, Cyber- Physical Systems (CPS), and Machine-to-Machine communication networks (M2M), are parallel and distributed systems. While providing improved expandability, manageability, efficiency, and reliability, parallel and distributed systems increase their security weaknesses to an unprecedented scale. As the system devices are widely connected, their vulnerabilities are shared by the entire system. Because tasks are allocated to, and information is exchanged among the system devices that may belong to different users, trust, security, and privacy issues have yet to be resolved. This special issue of the IEEE Transactions on Parallel and Distributed Systems (TPDS) highlights recent advances in trust, security, and privacy for emerging parallel and distributed systems. This special issue was initiated by Dr. Xu Li, Dr. Patrick McDaniel, Dr. Radha Poovendran, and Dr. Guojun Wang. Due to a large number of submissions, Dr. Zhenfu Cao, Dr. Keqiu Li, and Dr. Yang Xiang were later invited to the editorial team. Dr. Xu Li was responsible for coordinating the paper review process. In response to the call for papers, we received 150 effective submissions, out of which 24 are included in this special issue after rigorous review and careful revision, presenting an acceptance ratio of 16 percent. The accepted papers are divided into three groups, covering issues related to trust, security, and privacy, respectively.

A novel time computation model based on algorithm complexity for data intensive scientific workflow design and scheduling

Scientific workflow offers a framework for cooperation between remote and shared resources on a grid computing environment (GCE) for scientific discovery. One major function of scientific workflow is to schedule a collection of computational subtasks in well-defined orders for efficient outputs by estimating task duration at runtime. In this paper, we propose a novel time computation model based on algorithm complexity (termed as TCMAC model) for high-level data intensive scientific workflow design. The proposed model schedules the subtasks based on their durations and the complexities of participant algorithms. Characterized by utilization of task duration computation function for time efficiency, the TCMAC model has three features for a full-aspect scientific workflow including both dataflow and control-flow: (1) provides flexible and reusable task duration functions in GCE;(2) facilitates better parallelism in iteration structures for providing more precise task durations;and (3) accommodates dynamic task durations for rescheduling in selective structures of control flow. We will also present theories and examples in scientific workflows to show the efficiency of the TCMAC model, especially for control-flow. Copyright©2009 John Wiley & Sons, Ltd.

Large-scale biological sequence assembly and alignment by using computing grid

Large-scale sequence assembly and alignment are fundamental parts of biological computing. However, most of the large-scale sequence assembly and alignment require intensive computing power and normally take very long time to complete. To speedup the assembly and alignment process, this paper parallelizes the Euler sequence assembly and pair-wise/multiple sequence assembly, two important sequence assembly methods, and takes advantage of Computing Grid which has a colossal computing capacity to meet the large-scale biological computing demand.