ZENTURIO: A Grid Service-Based Tool for Optimising Parallel and Grid Applications

ZENTURIO [R. Prodan and T. Fahringer, ZENTURIO: A Grid Middleware-based Tool for Experiment Management of Parallel and Distributed Applications, Journal of Parallel and Distributed Computing, 2003. http://authors.elsevier.com/sd/article/S0743731503001977 (to appear)] is a semi-automatic experiment management tool for performance and parameter studies of parallel and distributed applications on cluster and Grid architectures. ZENTURIO has been designed as an Open Grid Services Architecture (OGSA) – compliant Grid application built on top of standard Web and Grid services technologies. In this paper we first comparatively present various issues from our transition to an Open Grid Services Infrastructure (OGSI) – compliant prototype. Then we introduce a generic framework for solving NP-complete optimisation problems for parallel and Grid applications. We present a case study on high throughput scheduling for large sets of computational tasks on the Grid using genetic algorithms. Our algorithm has a complexity of and delivers a fivefold improvement in solution over 500 generations in a Grid with uniformly distributed computational resources. This research is supported by the Austrian Science Fund as part of the Aurora project under contract SFBF1104.     

Simultaneous Scheduling of Replication and Computation for Data-Intensive Applications on the Grid

Managing large datasets has become one major application of Grids. Life science applications usually manage large databases that should be replicated to scale applications. The growing number of users and the simple access to Internet-based application has stressed Grid middleware. Such environment are thus asked to manage data and schedule computation tasks at the same time. These two important operations have to be tightly coupled. This paper presents an algorithm (Scheduling and Replication Algorithm, SRA) that combines data management and scheduling using a steady-state approach. Using a model of the platform, the number of requests as well as their distribution, the number and size of databases, we define a linear program to satisfy all the constraints at every level of the platform in steady-state. The solution of this linear program will give us a placement for the databases on the servers as well as providing, for each kind of job, the server on which they should be executed. Our theoretical results are validated using simulation and logs from a large life science application. This work was supported in part by the ACI GRID and Grid5000 projects of the French Department of Research.     

A computational economy for grid computing and its implementation in the Nimrod-G resource broker

Computational grids that couple geographically distributed resources such as PCs, workstations, clusters, and scientific instruments, have emerged as a next generation computing platform for solving large-scale problems in science, engineering, and commerce. However, application development, resource management, and scheduling in these environments continue to be a complex undertaking. In this article, we discuss our efforts in developing a resource management system for scheduling computations on resources distributed across the world with varying quality of service (QoS). Our service-oriented grid computing system called Nimrod-G manages all operations associated with remote execution including resource discovery, trading, scheduling based on economic principles and a user-defined QoS requirement. The Nimrod-G resource broker is implemented by leveraging existing technologies such as Globus, and provides new services that are essential for constructing industrial-strength grids. We present the results of experiments using the Nimrod-G resource broker for scheduling parametric computations on the World Wide Grid (WWG) resources that span five continents.     

Achieving efficiency, quality of service and robustness in multi-organizational Grids

Scalability, flexibility, quality of service provisioning, efficiency and robustness are the desired characteristics of most computing systems. Although the emerging Grid computing paradigm is scalable and flexible, achieving both efficiency and quality of service provisioning in Grids is a challenging task but is necessary for the wide adoption of Grids. Grid middleware should also be robust to uncertainties such as those in user-estimated runtimes of Grid applications. In this paper, we present a complete middleware framework for Grids that achieves user satisfaction by providing QoS guarantees for Grid applications, cost effectiveness by efficiently utilizing resources and robustness by intelligently handling uncertain runtimes of applications.     

A system-centric scheduling policy for optimizing objectives of application and resource in grid computing

In grid computing, grid users who submit applications and resources providers who provide resources have different motivations when they join the grid. Application-centric scheduling aims to optimize the performance of individual application. Resource-centric scheduling aims to optimize the resource utilization of resources provider. Due to autonomy both in grid users and resource providers, the objectives of application-centric and resource-centric scheduling often conflict. The paper proposes a system-centric scheduling that provides a solution of joint optimization of the objectives for both the grid resource and grid application. Utility functions are used to express the objectives of grid resource and application. The system-centric scheduling policy can be formulated as joint optimization of utilities of grid applications and grid resources, which combine both application centric and resource-centric scheduling benefits. Simulations are conducted to study the performance of the system-centric scheduling algorithm. The experiment results show that the system-centric scheduling algorithm yields significantly better performance than application-centric scheduling algorithm and resource-centric scheduling algorithm.     

A Stronger Complexity Result for the Single Machine Multi-Operation Jobs Scheduling Problem to Minimize the Number of Tardy Jobs

We consider the single machine multi-operation jobs scheduling problem to minimize the number of tardy jobs. Each job consists of several operations that belong to different families. In a schedule, each family of job operations may be processed in batches with each batch incurring a setup time. A job completes when all of its operations have been processed. The objective is to minimize the number of tardy jobs. In the literature, this problem has been proved to be strongly NP-hard for arbitrary due-dates. We show in this paper that the problem remains strongly NP-hard even when the due-dates are common and all jobs have the same processing time.     

A Technique for Adaptive Scheduling of Soft Real-Time Tasks

A number of multimedia and process control applications can take advantage from the ability to adapt soft real-time load to available computational capacity. This capability is required, for example, to react to changed operating conditions as well as to ensure graceful degradation of an application under transient overloads. In this paper, we illustrate a novel adaptive scheduling technique based on rate modulation of a set of periodic tasks in a range of admissible rates. By casting constraints on rate ranges in a linear programming formulation, several adaptation policies can be considered, along with additional constraints reflecting various application requirements. The paper investigates the effectiveness of rate modulation strategies both on simulated task sets and on real experiments. Partial support for this research has been provided by MURST, Italy (PRIN project ISIDE on “Dependable reactive computing systems for industrial applications” and special project “RoboCare” funded by L. 449/97), and by ASI, Agenzia Spaziale Italiana (contract I/R/134/00). Giuseppe Beccari received the Laurea degree in Electronic Engineering in 1993, and the Ph.D. in Information Technology in 1999, both from the University of Parma, Italy. In 1995 he was visiting scholar at the Technical University of Delft, Holland, and at the Laboratoire de Robotique de Paris, France. In 1999 he was employed by CSELT (Centro Studi E Laboratori Telecomunicazioni, currently TILAB, the Telecom Italia Group research center). In 2002 he moved to a spin off company involved in the EUROSAM/FSAF (Future Surface-to-Air Family self defense missile system) project. While his current professional duties focus more on software development and team coordination, dr. Beccari still enjoys investigating real-time scheduling issues and technology. Stefano Caselli received a Laurea degree in Electronic Engineering in 1982 and the Ph.D. degree in Computer and Electronic Engineering in 1987, both from the University of Bologna, Italy. In 1989-90 he has been visiting scholar at the University of Florida. From 1990 to 1999 he has held research fellow and associate professor positions at the University of Parma, Italy. He is now professor of Computer Engineering at the University of Parma, where he is also director of the Laboratory of Robotics and Intelligent Machines (RIMLab). His current research interests include development of autonomous and remotely operated robot systems, service robotics, and real-time systems. Francesco Zanichelli received a Laurea degree in Electronic Engineering in 1987 from the University of Bologna, Italy and the Ph.D. degree in Information Technologies in 1994 from the University of Parma, Italy. Since 1996 he has been an Assistant Professor with the Department of Information Engineering of the University of Parma where he is currently teaching Operating Systems, Information Systems and Multimedia Systems courses. His current research interests include distributed multimedia architectures and protocols, real-time systems, security and Quality of Service technologies for wireless networks, as well as service-oriented Grid middleware.     

Tool support for the design and management of context models

A central task in the development of context-aware applications is the modeling and management of complex context information. In this paper, we present the NexusEditor, which can ease this task by providing a graphical user interface to design schemas for spatial and technical context models, interactively create queries, send them to a server and visualize the results. One main contribution is to show how schema awareness can improve such a tool: The NexusEditor dynamically parses the underlying data model and provides additional syntactic checks, semantic checks, and short-cuts based on the schema information. Furthermore, the tool helps to design new schema definitions based on the existing ones, which is crucial for an iterative and user-centric development of context-aware applications. Finally, it provides interfaces to existing information spaces and visualization tools for spatial data like GoogleEarth.     

A Launch-time Scheduling Heuristics for Parallel Applications on Wide Area Grids

Large and dynamic computational Grids, generally known as wide-area Grids, are characterized by a large availability, heterogene- ity on computational resources, and high vari- ability on their status during the time. Such Grid infrastructures require appropriate schedule mechanisms in order to satisfy the application performance requirements (QoS). In this paper we propose a launch-time heuristics to schedule component-based parallel applications on such kind of Grid. The goal of the proposed heuristics is threefold: to meet the minimal task computation- al requirement, to maximize the throughput between communicating tasks, and to evaluate on-the-fly the resource availability to minimize the aging effect on the resources state. We evaluate the proposed heuristics by simulations applying it to a suite of task graphs and Grid platforms randomly generated. Moreover, a further test was conducted to schedule a real application on a real Grid. Experimental results shown that the proposed solution can be a viable one.     

MediaTouch: A Native Authoring Tool for MHEG-5 Applications

MediaTouch is a visual based authoring tool for creating MHEG-5 applications. It is based on the native approach, which enables the author to operate at the level of MHEG-5 objects, in order to get the most out of the standard's features. Specialized editing functions facilitate the author's work, especially when setting properties such as the hierarchical structure of an application, dynamic behavior and appearance of objects. The paper introduces the problem of authoring multimedia applications, motivating the adoption of a standard solution, and explaining the functionality of MediaTouch, and in so doing, providing an example of use.     

Utility-based QoS optimisation strategy for multi-criteria scheduling on the grid

The paper presents quality of service (QoS) optimisation strategy for multi-criteria scheduling on the grid, based on a mathematical QoS model and a distributed iterative algorithm. Three QoS criteria are considered, namely payment, deadline and reliability, which are formulated as utility function. The optimisation problem is split into two parts: task optimisation performed on behalf of the user and resource optimisation performed on behalf of the grid. The strategy employs three types of agents: task agents responsible for task optimisation, computation resource and network resource agents responsible for resource optimisation. The agents apply economic models for optimisation purposes. Dynamic programming is used to optimise the total system utility function in terms of an iterative algorithm. The objective of multi-criteria scheduling is to maximise the global utility of the system. This paper proposes an iterative scheduling algorithm that is used to perform QoS optimisation-based multi-criteria scheduling. The proposed QoS optimisation-based multi-criteria scheduling problem solution has been practically examined by simulation experiments.     

A Taxonomy of Workflow Management Systems for Grid Computing

With the advent of Grid and application technologies, scientists and engineers are building more and more complex applications to manage and process large data sets, and execute scientific experiments on distributed resources. Such application scenarios require means for composing and executing complex workflows. Therefore, many efforts have been made towards the development of workflow management systems for Grid computing. In this paper, we propose a taxonomy that characterizes and classifies various approaches for building and executing workflows on Grids. We also survey several representative Grid workflow systems developed by various projects world-wide to demonstrate the comprehensiveness of the taxonomy. The taxonomy not only highlights the design and engineering similarities and differences of state-of-the-art in Grid workflow systems, but also identifies the areas that need further research.     

基于请求负载的网格任务模糊控制调度策略

在面向大规模复杂应用的网格环境中,网格任务的优化调度变得越来越重要.文中首先提出了一种新的网格任务-服务映射算法,即基于任务负载和优先级的网格任务模糊控制调度策略.在考虑到外部网格任务请求负载和优先级的基础上,能够减少众多网格任务的平均完成时间.使得资源利用更加合理,同时还考虑到了网格服务的价格,即在满足任务负载影响和优先级的情况下,选择价格最小的服务.最后,开发了网格任务调度中间件,并在平台上给出了算法与其他几种常见的经典调度算法进行比较的试验结果.实验表明,算法明显优于已有的经典算法,具有较好应用情景.     

A contribution-based framework for the creation of semantically-enabled web applications

We present Fortunata, a wiki-based framework designed to simplify the creation of semantically-enabled web applications. This framework facilitates the management and publication of semantic data in web-based applications, to the extent that application developers do not need to be skilled in client-side technologies, and promotes application reuse by fostering collaboration among developers by means of wiki plugins. We illustrate the use of this framework with two Fortunata-based applications named OMEMO and VPOET, and we evaluate it with two experiments performed with usability evaluators and application developers respectively. These experiments show a good balance between the usability of the applications created with this framework and the effort and skills required by developers.     

An Information Service for Grid Virtual Organization: Architecture, Implementation and Evaluation

Information Service is the heart of the entire Grid software infrastructure. It maintains various information in a Grid environment, and provides this information to users on request. We present an Information Service architecture for information capturing, aggregation, and provisioning in a Grid Virtual Organization (VO). This Information Service is a hierarchical structure which consists of VO layer, site layer and resource layer. The architecture defines downloadable and pluggable information sensors for portability and flexibility of information capturing. The meta-data mechanism is incorporated into our Information Service for information organization and management. Experiments were conducted to evaluate the performance of the Information Service, and the results show that the Information Service presents satisfactory scalability with number of users and number of information amount. Our Information Service has been implemented based on the Globus Toolkit as a Grid service compliant to the Open Grid Services Architecture (OGSA) specifications.     

A rotary chaotic PSO algorithm for trustworthy scheduling of a grid workflow

In this paper, a rotary chaotic particle swarm optimization (RCPSO) algorithm is presented to solve trustworthy scheduling of a grid workflow. In general, the grid workflow scheduling is a complex optimization problem which requires considering various scheduling criteria so as to meet a wide range of QoS requirements from users. Traditional researches into grid workflow scheduling mainly focus on the optimization constrained by time and cost. The key requirements for reliability, availability and security are not considered adequately. The main contribution of this study is to propose a new approach for trustworthy workflow scheduling in a large-scale grid with rich service resources, and present the RCPSO algorithm to optimize the scheduling performance in a multi-dimensional complex space. Experiments were done in two grid applications with at most 120 candidate services supplied to each task of various workflows. The results show better performance of the RCPSO in solving trustworthy scheduling of grid workflow problems as compared to GA, ACO and other recent variants of PSO.     

Identification of a modified Wiener-Hammerstein system and its application in electrically stimulated paralyzed skeletal muscle modeling

Electrical muscle stimulation demonstrates potential for restoring functional movement and preventing muscle atrophy after spinal cord injury (SCI). Control systems used to optimize delivery of electrical stimulation protocols depend upon mathematical models of paralyzed muscle force outputs. While accurate, the Hill-Huxley-type model is very complex, making it difficult to implement for real-time control. As an alternative, we propose a modified Wiener-Hammerstein system to model the paralyzed skeletal muscle dynamics under electrical stimulus conditions. Experimental data from the soleus muscles of individuals with SCI was used to quantify the model performance. It is shown that the proposed Wiener-Hammerstein system is at least comparable to the Hill-Huxley-type model. On the other hand, the proposed system involves a much smaller number of unknown coefficients. This has substantial advantages in identification algorithm analysis and implementation including computational complexity, convergence and also in real-time model implementation for control purposes.     

A probabilistic task scheduling method for grid environments

This paper presents a probabilistic task scheduling method to minimize the overall mean response time of the tasks submitted to the grid computing environments. Minimum mean response time of a given task can be obtained by finding a subset of appropriate computational resources to service the task. To achieve this, a discrete time Markov chain (DTMC) representing the task scheduling process within the grid environment is constructed. The connection probabilities between the nodes representing the grid managers and resources can be considered as transition probabilities of the obtained DTMC. Knowing the mean response times of the managers and resources, and finding fundamental matrix of the DTMC, the mean response time related to each of the absorbing DTMCs existing inside the overall DTMC can be computed. Minimizing the obtained mean response times and taking into account the probability constraints in each of the absorbing DTMCs, a nonlinear programming (NLP) problem is defined. Solving the NLP problem, the connection probabilities between the managers and resources are obtained. Finally, using the connection probabilities, the best scheduling path within the environment and the minimum mean response time of a particular task can be achieved. In a case in which there is only one optimal scheduling choice within the environment, the proposed method can deterministically find such scheduling by assigning zero or one to the connection probabilities. Results obtained from evaluating the proposed method on the hypothesis and real grid environments show the preference of the proposed method compared to the other methods in minimizing both the overall mean response time of the tasks and total makespan of the environment.     

一种面向TinyOS的物联网系统信息安全测评工具

近年来,随着物联网的应用范围迅速扩展,TinyOS等新技术也得到广泛应用。物联网特别是TinyOS的安全性问题越来越为人们所关注。本文介绍了当前物联网安全测评技术的发展状况,比较了几种已知物联网安全工具的特点,提出了开发面向TinyOS的物联网安全测试系统SRES的构想;给出了SRES测试系统的具体实现方案与关键技术并证实了其可行性。