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Efficient Quick Messaging Service Implementation with Fault Tolerance in Demeter/Java

This document outlines the implementation of a Quick Messaging Service (QMS) using Demeter/Java, focusing on effective communication between clients and servers while ensuring fault tolerance. The system is built in three phases: establishing a client-server database, developing a client GUI, and enabling server-to-server communication for improved resilience. Key features include instant message delivery, server failure recovery, and regular status updates among servers. Although the system demonstrates basic functionality, limitations in robustness and hidden bugs are acknowledged, emphasizing ongoing improvements.

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Efficient Quick Messaging Service Implementation with Fault Tolerance in Demeter/Java

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  1. Quick Messaging Service John Sung

  2. Objective • Use Demeter/Java to the fullest • Use COOL for coordination • Use RIDL for RMI • Ability to send messages “instantly” • Ability to handle 1 server fault at a time

  3. QMS Implementation • Implemented in 3.1 phases • Phase 1: Client/Server database with accessor traverversals and testing infrastructure • Phase 2: Client’s GUI • Phase 2.1: Client/Server communication • Phase 3: Server/Server communication for Fault-Tolerance

  4. QMS System Architecture Logon/Logoff/ Messages Notifications Server Server User Client Server Server

  5. Client’s View of System • User Logs on and off it’s server • Sends message with source and destination to the server • Server looks up in the database to find the destination client • Another server will notify if the current server is unreachable

  6. Server’s View of System • User Message Delivery • Find destination client in the database • Send the message directly to the client • Notifications to other servers in the system • Client Logon/Logoff • New Server Entering System • Server Failure Recovery

  7. Server Failure Recovery • Detection • Attempt to connect to all of the servers in the system at a regular interval • Recovery • All servers broadcast timestamp of failure detection time • Each server determines the server with the lowest timestamp to take over • Failed Clients notified of change by the winning server • All servers update their databases

  8. Fault-Tolerance • Fault-Tolerance  Robustness • Able to handle 1 server fault at a time • Possible Failing Cases • Client logon/logoff during server failure recovery • New server attempting to enter system during server failure recovery

  9. Screen Shots

  10. COOl Example selfex processServerFailureNotification; mutex {serverFailureRecoveryStart, processServerFailureNotification ,getWonServer} condition finishedRecovery = false; processServerFailureNotification { on exit { notificatoinReceived++; if (notificationExpected != -1 && notificationExpected == notificationReceived) finishedRecovery = true; } } getWonServer requires(finishedRecovery) { on exit { finishedRecovery = false; notificationExpected = -1; } }

  11. RIDL Example // the portal for the qmsServer object portal qmsServer { public void clientLogOn(ClientAddress newClientAddr) newClientAddr: copy; public void sendMessage(qmsUserMessage newMsg) newMsg: copy; public void clientLogOff(ClientAddress client) client: copy; public ServerList newServerEnterSystemRequest(ServerAddress newSrv) newSrv: copy return: copy ; public void newServerEnteredNotification(ServerAddress newSrv) newSrv: copy; public void newClientLogOnNotification(ServerAddress srvAddr, ClientAddress newClientAddress) srvAddr: copy newClientAddress: copy ; public void oldClientLogOffNotification(ServerAddress srvAddr, ClientAddress oldClientAddress) srvAddr: copy oldClientAddress: copy ; public Boolean isAlive() return: copy ; } // qmsServer

  12. Conclusion • All of the basic functionality works • Client’s GUI • Client can send messages to server • Server can deliver messages from the client • New server can enter the system • Notifications of clients and servers • Very Limited Single Fault Tolerance • There are still many bugs hidden in there!

  13. Conclusion • Found bugs in RIDL and COOL • Demeter/Java Pros • Great for accessing databases and traversing trees/graphs • Great for testing parts of the program • Demeter/Java Cons • Performance of code generator/compilation • Robustness of different features

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