Quality-aware Scheduling for Key-value Data Stores [electronic resource] / by Chen Xu, Aoying Zhou.
By: Xu, Chen [author.].
Contributor(s): Zhou, Aoying [author.] | SpringerLink (Online service).
Material type:
BookSeries: SpringerBriefs in Computer Science: Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2015Description: XI, 97 p. 32 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783662473061.Subject(s): Computer science | Operating systems (Computers) | Database management | Computer Science | Database Management | Information Systems Applications (incl. Internet) | Operating SystemsAdditional physical formats: Printed edition:: No titleDDC classification: 005.74 Online resources: Click here to access online
In:
Springer eBooksSummary: Key-value stores, which are commonly used as data platform for various web applications, provide a distributed solution for cloud computing and big data management. In modern web applications, user experience satisfaction determines their success . In real application, different web queries or users produce different expectations in terms of query latency (i.e., Quality of Service (QoS)) and data freshness (i.e., Quality of Data (QoD)). Hence, the question of how to optimize QoS and QoD by scheduling queries and updates in key-value stores has become an essential research issue. This book comprehensively illustrates quality-ware scheduling in key-value stores. In addition, it provides scheduling strategies and a prototype framework for a quality-aware scheduler, as well as a demonstration of online applications. The book offers a rich blend of theory and practice, making it suitable for students, researchers and practitioners interested in distributed systems, NoSQL key-value stores and scheduling.
Key-value stores, which are commonly used as data platform for various web applications, provide a distributed solution for cloud computing and big data management. In modern web applications, user experience satisfaction determines their success . In real application, different web queries or users produce different expectations in terms of query latency (i.e., Quality of Service (QoS)) and data freshness (i.e., Quality of Data (QoD)). Hence, the question of how to optimize QoS and QoD by scheduling queries and updates in key-value stores has become an essential research issue. This book comprehensively illustrates quality-ware scheduling in key-value stores. In addition, it provides scheduling strategies and a prototype framework for a quality-aware scheduler, as well as a demonstration of online applications. The book offers a rich blend of theory and practice, making it suitable for students, researchers and practitioners interested in distributed systems, NoSQL key-value stores and scheduling.
There are no comments for this item.