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Filterfresh Fault-tolerant Java Servers Through Active Replication Arash Baratloo www.cs.nyu.edu/phd_students/baratloo
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Investigation of failure models in distributed Java applications Provide transparent fault-masking (to users and to programmers) Support highly available services in presence of failures Remove single-points of failure Filterfresh
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Remote Method Invocation (RMI) 100% Java, hot, new, easy-to-use and Reliable Object Services (ROS) Interest in Providing: –support active-active replication –support Java objects Motivating Factors
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Roadmap Motivation –RMI Registry & crash failures –RMI Server Architecture & crash failures –A Unified Solution -- process group approach –Fault-tolerant Registry –Fault-tolerant RMI –Conclusion
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RMI in a Nutshell Servers register with the local registry Clients looks up a server at a well known registry Given a remote reference, client performs a remote method invocation
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Limitations of RMI Registry The “well known registry” requirement too restrictive for failure recovery Single point of failure Can not support replicated servers, thus, highly available servers
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FT Registry requires... Distribute and replicate registry servers Replication strategy to maintain a consistent state Failure detection and removal of failed registry servers Failed objects must be restarted automatically Dynamic addition of registry servers
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RMI Architecture RRL assumes a stream-oriented transport Transport layer implemented on TCP/IP
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Architecture (cont…)
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Transparent FT system implies RRL or below
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FT Servers Require... Distribute and replicate servers Replication strategy to maintain a consistent state Failure detection and removal of failed registry servers Dynamic addition of registry servers Object reference must remain valid after the associated object has failed
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A Unified Solution... Process Group Approach where all non-faulty objects –form a group –consistent view of the group –interact through reliable group primitives -- all or nothing –total order on group primitives
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Fortunately Process Group Membership is –well understood problem and protocols –well tested (ISIS, Transis, Amoeba, etc.) –basis for virtual synchrony Equivalent Problems* (implement one, get all) –Group Membership –Reliable Failure Detectors –Reliable and ordered multicast * Chandra and Toueg. Unreliable failure detectors for Reliable Distributed Systems. JACM, March 96.
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Unfortunately Process Group Membership is –as hard as distributed consensus –impossible in purely asynchronous systems with crash failures* Our solution –the standard “timeout” assumption –variation of protocol used in Amoeba OS** * Chandra, Toueg, Hadzilacos and Charron-Bost. Impossibility of Group Membership in Asynchronous Systems. ** Oey, Langendoen and Bal. Comparing Kernel-level and User-level Communication protocols on Amoeba. ICDCS 95.
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What We Provide... A Group Manager Class –100% Java –build on top of UDP/IP Implements –group creation –join operation (with state transfer) –leave operation –failure detection and recovery –reliable multicast All events are atomic and totally ordered
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Multicast Performance Pentium Pro 200, Linux RedHat 4.0, Fast Ethernet hub
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FT Registry Architecture registry on each host/domain group managers ensure reliable ordered events support dynamic joins w/state transfer
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FT Registry Architecture (cont…) lookup becomes a local operation detect and remove failed objects consistent global state
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FT Registry Performance Pentium Pro 200, Linux RedHat 4.0, Fast Ethernet, Ethernet hub
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RMI & FT Registry support multiple servers register with a same name can now support recovery from server failure
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What if... In the event of server failure...
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Failure Recovery The old connection is patched with a connection to a non-faulty server Illusion of a valid object reference Transparent! A “reverse” lookup returns a name given a wire connection
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Failure Recovery Performance ? Working but measurements have not been made
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FT Server Architecture Client has the illusion of a single server In reality, we have active replicated servers Highly available?
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Highly Available Servers Group managers ensure reliable ordering of events across all servers Guarantees servers have a consistent state Failure detection and removal of failed servers Dynamic addition of servers w/state transfer Illusion of a valid server reference even after the associated object has failed
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Conclusions
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