REMUS: A Rerouting and Multiplexing System for Grid Connectivity Across Firewalls

The Grid provides unique opportunities for high-performance computing through distributed applications that execute over multiple remote resources. Participating institutions can form a virtual organization to maximize the utilization of collective resources as well as to facilitate collaborative projects. However, there are two design aspects in distributed environments like the Grid that can easily clash: security and resource sharing. It may be that resources are secure but are not entirely conducive to resource sharing, or networks are wide open for resource sharing but sacrifice security as a result. We developed REMUS, a rerouting and multiplexing system that provides a compromise through connection rerouting and wrappers. REMUS reroutes connections using proxies, ports and protocols that are already authorized across firewalls, avoiding the need to make new openings through the firewalls. We also encapsulate applications within wrappers, transparently rerouting the connections among Grid applications without modifying their programs. In this paper, we describe REMUS and the tests we conducted across firewalls using two Grid middleware case studies: Globus Toolkit 2.4 and Nimrod/G 3.0.     

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.     

Optimal grids for five-axis machining

This paper presents a new grid generation method for tool path planning for five-axis machining based on minimization of the kinematics error. First, the procedure constructs a space-filling curve so that the scallops between the resulting tracks of the tool do not exceed a prescribed tolerance. At the second stage (which is the subject of this paper) a one-dimensional grid along the space-filling curve is generated using direct minimization of the kinematics error. A closed form representation of the kinematics error as a function of locations cutter contact points is derived from the inverse kinematics transformations associated with a particular five-axis machine and obtained through automatic symbolic calculations. The grid of cutter location points is generated so that it minimizes the kinematics error. Numerical and cutting experiments demonstrate that the proposed procedure outperforms distribution of points based on the equi-arc-length principle. Finally, we show that our optimization routine requires less points than that based on sequential point insertion and numerical evaluation of the cost function, such as bisection.     

Scheduling Task Parallel Applications for Rapid Turnaround on Enterprise Desktop Grids

Desktop Grids are popular platforms for high throughput applications, but due to their inherent resource volatility it is difficult to exploit them for applications that require rapid turnaround. Efficient desktop Grid execution of short-lived applications is an attractive proposition and we claim that it is achievable via intelligent resource selection. We propose three general techniques for resource selection: resource prioritization, resource exclusion, and task duplication. We use these techniques to instantiate several scheduling heuristics. We evaluate these heuristics through trace-driven simulations of four representative desktop Grid configurations. We find that ranking desktop resources according to their clock rates, without taking into account their availability history, is surprisingly effective in practice. Our main result is that a heuristic that uses the appropriate combination of resource prioritization, resource exclusion, and task replication can achieve performance within a factor of 1.7 of optimal in practice.     

医用诊断X线机“限、集、屏”装置防护效果评价

本文评述了用“限、集、屏”装置改装的10台50mA、6台200mAX 线机的防护效果。改装前在透视防护区测试平面位置上的空气照射量率没有1台符合 X 线机的卫生防护规定,改装后全部达到了规定的防护要求。     

PaGrid: A Mesh Partitioner for Computational Grids

Computational Grids are emerging as a new infrastructure for high performance computing. Since the resources in a Grid can be heterogeneous and distributed, mesh-based applications require a mesh partitioner that considers both processor and network heterogeneity. We have developed a heterogeneous mesh partitioner, called PaGrid. PaGrid uses a multilevel graph partitioning approach, augmented by execution time load balancing in the final uncoarsening phase. We show that minimization of total communication cost (e.g., as used by JOSTLE) can lead to significant load being placed on processors connected by slow links, which results in higher application execution times. Therefore, PaGrid balances the estimated execution time of the application across processors. PaGrid performance is compared with two existing mesh partitioners, METIS 4.0 and JOSTLE 3.0, for mapping several application meshes to two models of heterogeneous computational Grids. PaGrid is found to produce significantly better partitions than JOSTLE and slightly better partitions than METIS in most cases, in terms of estimated application execution time averaged over a large number of runs with different random number seeds.     

Enhancing Computational Grids with Peer-to-Peer Technology for Large Scale Service Discovery

Within computational Grids, some services (typically software components, e.g., linear algebra libraries) are made available by some servers to some clients. In spite of the growing popularity of such Grids, the service discovery, although efficient in many cases, does not reach several requirements. Among them, the flexibility of the discovery and its efficiency on wide-area dynamic platforms are two major issues. Therefore, it becomes crucial to propose new tools coping with such platforms. Emerging peer-to-peer technologies provide algorithms allowing the distribution and the retrieval of data items while addressing the dynamicity of the underlying network. Whereas merging peer-to-peer technology and Grid infrastructures has been widely suggested, very few implementations are available. The contribution of this paper is twofold. First, we present the design, the implementation and the experimentation of the first architecture, to our knowledge, extending traditional Network-Enabled Servers (NES) systems with an unstructured peer-to-peer network. This extension allows to dynamically connect distributed agents thus providing to clients an entry point to servers geographically distributed. Our implementation is based on the Diet middleware and the JXTA toolbox and experimentation have been conducted on a high speed network. Then, we study the service discovery in a pure peer-to-peer environment. We describe a new trie-based approach for the peer-to-peer service discovery service, supporting range queries while providing fault-tolerance and taking into account the topology of the underlying network. We validate this approach both by analysis and simulation. This work has been supported in part by the ANR project LEGO (ANR-05-CIGC-11).     

新型智能接地网接地电阻测量装置的研究

接地电阻值是发电厂、变电站接地系统的重要技术指标。本文回顾了传统的接地电阻测量方法，介绍了变电站接地网接地电阻智能测量装置的组成、工作原理和特点。该装置可以缩短测量引线的长度，而且测量所需电流小，大大提高了测量的准确性与便捷性。