Name
Abstract | ||
|---|---|---|
A cloud-based, highly consumable queuing service must provide extreme scalability, flexible models of consistency, and high availability in the presence of network partitions. CAP theorem states that at most two of the three properties - Consistency, Availability, and Partition Tolerance - can be achieved at the same time for any shared data system. This paper presents the design and implementation of a scalable cloud-based queuing service, named Silver Dove Queuing Service (SDQS). SDQS offers two kinds of consistency levels to applications: the first guarantees exactly-once and no-order delivery and the second exactly-once and in-order delivery. Meanwhile SDQS provides high availability and network partition tolerance. SDQS is designed and developed on top of IBM Web Sphere extreme Scale, an in-memory data grid system. Performance experiments are carried out in a cloud computing environment and the results show that Silver Dove has linear scalability with both of the consistency levels. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICEBE.2010.100 | ICEBE |
Keywords | Field | DocType |
consistency tolerance,distributed storage,partition tolerance,silver dove queuing service,queue,grid computing,consistency,sdqs,queueing theory,scalable queuing service,cap theorem,cloud computing,cloud-based queueing service,in-memory data grid,availability tolerance,system performance,availability,data grid,high availability,java,scalability,indexes,servers | Network partition,Grid computing,Computer science,CAP theorem,Data grid,Distributed data store,High availability,Distributed computing,Cloud computing,Scalability | Conference |
Volume | Issue | ISSN |
null | null | null |
ISBN | Citations | PageRank |
978-0-7695-4227-0 | 2 | 0.51 |
References | Authors | |
6 | 5 | |