Chapter 4

Realtime Widely Distributed

Instrumention System

Useful and robust operation of realtime distributed system requires many capability

Automated management of data stream and distributed components

Dynamic scheduling Resource reservation

This capability will be built on supporting architecture ,middleware and low level services such as

realtime cataloging

Distributed real time application

High speed data stream result from on line instrument

and imaging system

High speed network is providing the potential to collect ,organization , storage ,analysis and distribution of the large data object that result from such data stream

Health care imaging system :both high data rate and realtime cataloging

High energy physics experiments :high data rate and volume have to processed and archive in realtime

Problem Characterization and prototype

Realtime management of distributed system invlove :

distributed data collection and management

distributed data analysis and cataloging

Each of these reqiures a supporting infrastructure of middlware and of system and communication services

The required middleware services include automated cataloging (chapter 5)

Automated monitoring and management system of distributed components (chapter 14,15)

Policy based access control system to support scheduling and resource allocation (chapter 19)

Nature of the Remote Operation

Distributed instrument can be remote in space,scale,time

Remote in space is the typical circumstance of network distributed scientific collaboration

Another common circumstance is that the control function is remote in scale that direct control is not possible

Cardioangiography Key aspect of realtime data is immediate and automated

processing to organize and catalog the data Data is generated in large volume and with high throughout ,the

people generating the data are geographically seperated from the people cataloging or using the data

A realtime digital library system (WALDO) collects data from instrument and automatically processes ,catalogs ,archive each data unit together with derived data and metadata

Waldo uses an object oriented approach for capture ,catalog and management of large data object

Waldo software architecture

Data collection system High speed network based cache for providing intermediate

storage for processing and for high speed application access Processing mechanism for various sort of data Data management for automatic cataloging and metadata

generation Data access interface including application oriented interface Flexible mechanism for providing various searching strategy Transparent security that provides strong access control Transparent storage management for data component Curator interfaces for managing both the metadata and large

data object collection User access interface

Particle accelerator A detector system at high energy physics particle

accelerator .modern detector like STAR generate 20 – 40 MB/s.

data must be processed in two phase :

In phase 1 :

a detector puts out a steady state high data rate stream

In phase 2: data analysis

using DPSS (distributed parallel storage system) in this system

Electron microscopy

This example concern the remote control of electron microscopy based on the image content

In situ electron microscopy experiment requires dynamic interaction with the specimen under observations it is exited with external stimuli

Remote control via WAN do not offer realtime data and command delivery guarantes are not practical for finely tuned adjustment

Enable remote control in WAN

Human interaction can easily be performed in WAN On the other hand dynamic control operation because of

the control operation and monitored response to the control or stimuli have to be coupled by low latency communication that is not possible on WAN . dynamic remote control application usually involve automated control operation performed near

the instrument to eliminate WAN realtime delivery requirement

In this section we describe some of architectural and middleware approach in implementing high performance distributed instrument

A Model data Intensive Architecture Agent based management Policy based access control

In the previous example we demonstrate the utility of using high speed distributed cache

This cache based approach provides standard interface to large , distributed storage system

Each data source deposits its data in cache and each data consumer takes data from catch

Network based cache

DPSS provide highly distributed storage system that is usually used a cache of data

DPSS is typically used to collect data from on line instrument and supply that data to analysis application

It provides high capacity and isolate application from the tertiary storage system

It may be dynamically configured by aggregating workstation and disks from all over the network

Agent based management and monitoring

In widely distributed system ,when we observe that something has wrong , it is generally too late to react

Because the needed information is no longer accessible Because it will too long to ask and answer all of required

question

Agents not only provide standard access to comprehensive monitoring ,they can also perform task such as keeping a state history

Monitoring one successful monitoring methodology involve recording

every event with precision timestamps This monitoring is designed to facilitate performance tuning

, the characterization of distributed algorithm and the management of functioning system

When developing , high speed network based distributed services ,we often unexpectedly low network throughput /high latency. The reason for this poor performance is not obvious . A precision and comprehensive monitoring is an invaluable tool for diagnosing such problems

Agent based management of widely distributed systems Agent based management may be the key to keeping widely

distributed system running reliably Initial experimentation with such agent in DPSS indicates

several potential advantages First: Structured access to current and historical information Second :reliability not only does this system keep track of all

components within the system, but it restart any component that has crashed

Third :automatic reconfiguration .when new components are added ,the agents do not have to reconfigured

Fourth : information management Fifth: user representation , can perform actions on behalf of

user (if the data is not load in DPSS )

Policy based access control the goal for access control in such distributed system is to

reflect the general principles that have been established in society for policy based access control

The resource has multiple stakeholders and each stakeholder will impose use conditions on resource .all of the use conditions must be met simultaneously in order to satisfy the requirement for access.

An approach that addresses the general goals noted above can be based on authorization and attribute certificates

Users are permitted access to resource based on their attributes