JMS Compliance in NaradaBrokering Shrideep Pallickara, Geoffrey Fox Community Grid Computing Laboratory Indiana University.

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Presentation transcript:

JMS Compliance in NaradaBrokering Shrideep Pallickara, Geoffrey Fox Community Grid Computing Laboratory Indiana University

Talk Outline Brief overview of NaradaBrokering JMS Compliance Objectives for achieving JMS compliance The Process of achieving compliance The Distributed JMS solution Performance Future Directions

NaradaBrokering Based on a network of cooperating broker nodes –Cluster based architecture allows system to scale to arbitrary size Based on the publish/subscribe model Also supports another model, peer-to-peer (P2P) via JXTA Incorporates algorithms for –Topic matching and calculation of destinations –Efficient routing to computed destinations Supports local broker accesses –Clients do not need to reconnect to the remote broker that it was last connected to.

JMS Compliance JMS clients are written while conforming to the messaging specification. –Vendor specific calls result in applications that are not JMS-compliant. JMS clients are vendor agnostic –One provider should be just as good as another –All that needs to be changed is the initialization sequence. JMS providers do not interoperate with each other –Interactions between clients of 2 different providers can be achieved through a client connected to the two providers.

JMS Compliance in NaradaBrokering: Rationale Providing support for JMS clients within the system. –Mature messaging specification Several existing applications –Opens NaradaBrokering to applications developed around JMS Bring NaradaBrokering functionality to JMS based systems –Distributed solution, load balancing, scaling and failure resiliency.

Providing JMS support JMS Interactions –Supported locally or mapped to corresponding NaradaBrokering calls JMS Interconnection Bridge –Operations supported locally or mapped to corresponding NaradaBrokering interactions –One bridge instance per connection –Maintains list of registered sessions –Responsible for routing events to appropriate sessions Support for –Creation of different message types e.g. ObjectMessage, BytesMessage etc. –Operations that can be invoked on these message types.

Providing JMS Support Topic –NaradaBrokering topics are created as pairs. –JMS Topics are generally “/” separated. JMS selector mechanism –We augment NaradaBrokering’s topic matching with the selector mechanism implemented by openJMS. JMS subscriptions –Mapped to corresponding NaradaBrokering subscription requests. The Narada JMS Event. –Encapsulates the entire JMS message as a payload for the event. –Matching is done based on the topic name contained in the message.

Replacing JMS providers in existing systems The Anabas Conferencing System, Anabas Inc. –Shared Display, Text, Whiteboard, audio and video conferencing –JMS provider – SonicMQ The Online Knowledge center – IU Grid Labs –JMS provider - SonicMQ

Towards a distributed JMS solution Benefits –Features in NaradaBrokering best exploited in distributed settings. –Clients of distributed solution to inherit NaradaBrokering features Routing efficiencies, load balancing, scaling etc. –Eliminate the Single point of failure model –Highly Available System

Distributed solution: Constraints Each broker should still function as a standalone JMS broker. Distributed Network should preferably be transparent to clients Existing systems should easily be replaced with distributed system –Minimal changes to clients –No change to initialization sequences No changes to the NaradaBrokering core and the protocol suite.

A simple distributed solution Set up NaradaBrokering broker network. Clients choose the broker they connect to Cons –Distributed network not transparent to clients –Clients need to keep track of un-predictabilities in distributed settings Broker up-times, network partitions Clients could use a certain known broker over and over again. –Newly added brokers, not incorporated into the solution.

Broker Locators: Distributed JMS Solution Primary Function –Discovery of brokers that clients can connect to Obviates need for client to keep track of broker states within the broker network. Keeps track of –Broker additions and removals Changes to network fabric –Published Limit on concurrent connections at a broker node Set during broker initializations –Active connections at a broker node. Individual brokers notify changes to broker locator.

Broker Locators: Features Dynamic Real time Load Balancing –Connection requests always forked to best available broker. Incorporation of new brokers into solution –A newly added broker is among the best brokers to handle a connection request. Slower clients could all be hosted on specific brokers –Eliminates broker choking resulting from servicing very slow clients.

Broker Locator: Constraints Availability –Should not constitute a bottleneck or single point of failure. Multiple broker locators per domain. Number of broker locators would be much less than number of brokers. Minimal logic –No active connections to any element of brokering system. Loss of locator should not affect the network fabric –Should not affect processing pertaining to any node in the system.

Broker Locator: Decision Metrics IP-address of requesting client Published limit on concurrent connections Number of active connections still possible Availability of broker –A simple ping test –If broker is not available, remove broker from list of available brokers. Computing capabilities at a broker –CPU speed, RAM etc.

Broker Locator: Sequence of Operations Locate valid broker Propagate broker information to client –Hostname/IP-address information –Port number on which it listens for connections –Transport protocol over which it communicates Client then uses info to establish communication channel with broker –Done transparently. Clients with multiple connections –A client could sometimes have connections to multiple brokers.

JMS Performance Data SonicMQ (version 3.0) and NaradaBrokering broker –Dual CPU (Pentium 3, 1 GHz, 256 MB RAM) machine. 100 subscribers –Over 10 different JMSTopicConnections –All hosted on a Dual CPU (Pentium 3, 866 MHz, 256 MB RAM) machine. Publisher and Measuring Subscriber –Hosted on another dual CPU (Pentium 3, 866 MHz, 256 MB RAM) machine. Operating System and Run time Environment –Linux (version ) –Java 2 JRE (Java 1.3.1, Blackdown-FCS, mixed-mode)

Performance Data:Factors Measured Transit Delay –No need for clock synchronization and accounting for clock drifts. Standard Deviation in the transit delay for the sample of messages received. System Throughput –Measured in terms of rate at which messages are received. Factors measured under varying –publish rates –message payload sizes.

Performance: Transit Delay & Standard Deviation Lower Payloads & Low Publish Rates

Performance: Transit Delay & Standard Deviation Higher Payloads & Low Publish Rates

Performance: Transit Delay & Standard Deviation Lower Payloads & High Publish Rates

Performance: System Throughput Lower Payloads & Higher Publish Rates

Conclusions JMS Compliance in NaradaBrokering Replacing existing systems with a distributed solution Support for JMS to go along with support for JXTA –Enables JXTA peers and JMS clients to interact with each other. –Provides infrastructure for building standards based peer- to-peer (P2P) grids.

JMS over UDP Server Machine –Dual CPU (1.266 GHz Pentium 3, 1024 MB RAM) –JMF server and NaradaBrokering Broker Client Machine –1.8 GHz Pentium 4, 512 MB RAM –Transmitter and Receiver Red Hat Linux 7.1, Blackdown-1.3.1, Java 2 JRE JVM H.263 video file (30 second part of a movie) –Average bit-rate of 600Kbps (Kilo bits per second) –Frame-rate of 30 frames/sec Factors Measured –Jitter J = J + (|D(i-1, i)| - J)/16 –Delay