PPT-CSE 486/586 Distributed Systems

Consistency 2 Steve Ko Computer Sciences and Engineering University at Buffalo Linearizability vs Sequential Consistency Both care about giving an illusion of a single copy From the outside observer the system should almost behave as if theres only a single copy. Paxos. --- 2. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Paxos. is a consensus algorithm.. It allows multiple acceptors accepting multiple proposals.. A proposer always makes sure that,. Paxos. --- 2. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Paxos. is a consensus algorithm.. It allows multiple acceptors.. It allows multiple proposals to be accepted.. Replication --- 1. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap: Concurrency Control. Extracting more concurrency. Non-exclusive locks. Two-version locking. Reducing the lock overhead. Case Study: Amazon Dynamo. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. CAP Theorem?. Consistency, Availability, Partition Tolerance. Pick two. Eventual consistency?. Availability and partition tolerance over consistency. New Trends in Distributed Storage. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Two important components in a distributed file service?. Directory service. Flat file service. Byzantine Fault Tolerance. Steve Ko. Computer Sciences and Engineering. University at Buffalo. CSE 486/586 . Administrivia. Project 3 out. Please, please start right away!. Deadline: 4/30 (Monday) @ 11:59PM. Case Study: . Facebook Haystack. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. DNS. Hierarchical servers. Root servers, top-level domain servers, authoritative servers. CDN. Leader . Election --- 2. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Algorithm 2: Modified Ring Election . election . message tracks . all. IDs of nodes that forwarded it, not just the highest. Concurrency . Control --- 1. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap: Transactions. Transactions?. Abstraction for . grouping multiple operations into one. Transaction primitives?. Byzantine Fault Tolerance --- 1. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Spanner. Geo-distributed database. Supports a relational data model with a SQL-like language. Google Spanner. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Digital certificates. Binds a public key to its owner. Establishes a chain of trust. TLS. Provides an application-transparent way of secure communication. Paxos. --- 1. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. NFS. Caching with write-through policy at close(). Stateless server. One power efficient design: FAWN. Embedded CPUs & Flash . Gossiping. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Available copies replication?. Read and write . p. roceed with live replicas. Cannot achieve one-copy serialization itself. Global States. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Last Time. Ordering of events. Many applications need it, e.g., collaborative editing, distributed storage, etc.. Logical time.