PPT-CSE 486/586 Distributed Systems

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. Security --- 2. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Three . types of functions. Cryptographic hash, symmetric key crypto, asymmetric key . crypto. Cryptographic hash. Concurrency Control --- 3. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Strict execution of transactions?. Delay . both their read and write operations . on an . object until . Google Chubby Lock Service. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Paxos. is a consensus algorithm.. Proposers?. Acceptors?. Learners?. 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.. Graph Processing. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Byzantine generals problem. They must decide on a common plan of action.. But. , . some of the generals can be traitors. 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 there’s only a single copy.. 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. 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. Gossiping. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Consistency models. Linearizability. Sequential consistency. Causal consistency. Eventual consistency. Depending on application scenarios, one consistency model makes more sense that others.. Reliable Multicast --- 2. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap: Multicast. How do a group of processes communicate?. Multicast. One-to-many: “Local” broadcast within a group . 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 . Mutual Exclusion --- 2. & Leader Election --- 1. Steve Ko. Computer Sciences and Engineering. University at Buffalo. 4. . Maekawa’s. Algorithm. Observation: . no need to have all peers reply. Only need to have . Web Content Distribution-. --3. Case Study: Facebook f4. Steve Ko. Computer Sciences and Engineering. University at Buffalo. Recap. Engineering principle. Make the common case fast, and rare cases correct. 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,.