Distributed Virtual System (DIVIRS) Project

As outlined in our continuation proposal 92-ISI-50R (revised) on contract NCC 2-539, we are (1) developing software, including a system manager and a job manager, that will manage available resources and that will enable programmers to program parallel applications in terms of a virtual configuration of processors, hiding the mapping to physical nodes; (2) developing communications routines that support the abstractions implemented in item one; (3) continuing the development of file and information systems based on the virtual system model; and (4) incorporating appropriate security measures to allow the mechanisms developed in items 1 through 3 to be used on an open network. The goal throughout our work is to provide a uniform model that can be applied to both parallel and distributed systems. We believe that multiprocessor systems should exist in the context of distributed systems, allowing them to be more easily shared by those that need them. Our work provides the mechanisms through which nodes on multiprocessors are allocated to jobs running within the distributed system and the mechanisms through which files needed by those jobs can be located and accessed

DIstributed VIRtual System (DIVIRS) project

As outlined in our continuation proposal 92-ISI-50R (revised) on NASA cooperative agreement NCC2-539, we are (1) developing software, including a system manager and a job manager, that will manage available resources and that will enable programmers to develop and execute parallel applications in terms of a virtual configuration of processors, hiding the mapping to physical nodes; (2) developing communications routines that support the abstractions implemented in item one; (3) continuing the development of file and information systems based on the Virtual System Model; and (4) incorporating appropriate security measures to allow the mechanisms developed in items 1 through 3 to be used on an open network. The goal throughout our work is to provide a uniform model that can be applied to both parallel and distributed systems. We believe that multiprocessor systems should exist in the context of distributed systems, allowing them to be more easily shared by those that need them. Our work provides the mechanisms through which nodes on multiprocessors are allocated to jobs running within the distributed system and the mechanisms through which files needed by those jobs can be located and accessed

Tracking Consensus of Networked Random Nonlinear Multi-agent Systems with Intermittent Communications

The paper proposes an intermittent communication mechanism for the tracking consensus of high-order nonlinear multi-agent systems (MASs) surrounded by random disturbances. Each collaborating agent is described by a class of high-order nonlinear uncertain strict-feedback dynamics which is disturbed by a wide stationary process representing the external noise. The resiliency level of this networked control system (NCS) to the failures of physical devices or unreliability of communication channels is analyzed by introducing a linear auxiliary trajectory of the system. More precisely, the unreliability of communication channels sometimes makes an agent incapable of sensing the local information or receiving it from neighboring nodes. Therefore, an intermittent communication scheme is proposed among the follower agents as a consequence of employing the linear auxiliary dynamics. The closed-loop networked system signals are proved to be noise-to-state practically stable in probability (NSpS-P). It has been justified that each agent follows the trajectory of the corresponding local auxiliary virtual system practically in probability. The simulation experiments finally quantify the effectiveness of our proposed approach in terms of providing a resilient performance against unreliability of communication channels and reaching the tracking consensus.Comment: 6 pages, 4 figure

DIstributed VIRtual System (DIVIRS) Project

The development of Prospero moved from the University of Washington to ISI and several new versions of the software were released from ISI during the contract period. Changes in the first release from ISI included bug fixes and extensions to support the needs of specific users. Among these changes was a new option to directory queries that allows attributes to be returned for all files in a directory together with the directory listing. This change greatly improves the performance of their server and reduces the number of packets sent across their trans-pacific connection to the rest of the internet. Several new access method were added to the Prospero file method. The Prospero Data Access Protocol was designed, to support secure retrieval of data from systems running Prospero

A Review of Commercial and Research Cluster Management Software

In the past decade there has been a dramatic shift from mainframe or ‘host-centric’ computing to a distributed ‘client-server’ approach. In the next few years this trend is likely to continue with further shifts towards ‘network-centric’ computing becoming apparent. All these trends were set in motion by the invention of the mass-reproducible microprocessor by Ted Hoff of Intel some twenty-odd years ago. The present generation of RISC microprocessors are now more than a match for mainframes in terms of cost and performance. The long-foreseen day when collections of RISC microprocessors assembled together as a parallel computer could outperform the vector supercomputers has finally arrived. Such high-performance parallel computers incorporate proprietary interconnection networks allowing low-latency, high bandwidth inter-processor communications. However, for certain types of applications such interconnect optimization is unnecessary and conventional LAN technology is sufficient. This has led to the realization that clusters of high-performance workstations can be realistically used for a variety of applications either to replace mainframes, vector supercomputers and parallel computers or to better manage already installed collections of workstations. Whilst it is clear that ‘cluster computers’ have limitations, many institutions and companies are exploring this option. Software to manage such clusters is at an early stage of development and this report reviews the current state-of-the-art. Cluster computing is a rapidly maturing technology that seems certain to play an important part in the ‘network-centric’ computing future

Cluster Computing Review

In the past decade there has been a dramatic shift from mainframe or ‘host−centric’ computing to a distributed ‘client−server’ approach. In the next few years this trend is likely to continue with further shifts towards ‘network−centric’ computing becoming apparent. All these trends were set in motion by the invention of the mass−reproducible microprocessor by Ted Hoff of Intel some twenty−odd years ago. The present generation of RISC microprocessors are now more than a match for mainframes in terms of cost and performance. The long−foreseen day when collections of RISC microprocessors assembled together as a parallel computer could out perform the vector supercomputers has finally arrived. Such high−performance parallel computers incorporate proprietary interconnection networks allowing low−latency, high bandwidth inter−processor communications. However, for certain types of applications such interconnect optimization is unnecessary and conventional LAN technology is sufficient. This has led to the realization that clusters of high−performance workstations can be realistically used for a variety of applications either to replace mainframes, vector supercomputers and parallel computers or to better manage already installed collections of workstations. Whilst it is clear that ‘cluster computers’ have limitations, many institutions and companies are exploring this option. Software to manage such clusters is at an early stage of development and this report reviews the current state−of−the−art. Cluster computing is a rapidly maturing technology that seems certain to play an important part in the ‘network−centric’ computing future