Akshay Shah on "Epidemic algorithms in replicated databases"
Details
Akshay Shah on "Epidemic algorithms in replicated databases"
ABSTRACT
Abstract 1 Introduction We present a family of epidemic algorithms for maintaining replicated data in a transactional framework. The algorithms are based on the causal delivery of log records where each record corresponds to one transaction instead of one operation. The fist algorithm in this family is a pessimistic protocol that ensures serializability and guarantees strict executions. Since we expect the epidemic algorithms to be used in environments with low probability of conflicts among transactions, we develop a variant of the pessimistic algorithm in which locks are released as soon as transactions finish their execution locally. However, this optimistic releasing of locks introduces the possibility of cascading aborts while ensuring serializable executions. The last member of thii family of epidemic algorithms is motivated from the need for asynchronous replication solutions that are being increasingly used in commercial systems. The protocol is optimistic in that transactions commit as soon as they terminate locally and inconsistencies are detected asynchronously as the effects of committed transactions propagate through the system.
https://dl.acm.org/doi/pdf/10.1145/263661.263680
Agenda:
https://docs.google.com/document/d/1p2Rx8-HbVXGscqiMQ9nFyqlUROlJEuzzYavKVRJTctc
AI summary
By Meetup
Talk on epidemic algorithms for replicated transactional databases; for distributed-systems researchers; outcome: three protocol variants and their trade-offs.
AI summary
By Meetup
Talk on epidemic algorithms for replicated transactional databases; for distributed-systems researchers; outcome: three protocol variants and their trade-offs.
