October 2018
Intermediate to advanced
368 pages
11h 53m
English
Content preview from Assured Cloud Computing
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5Scalability, Workloads, and Performance: Replication, Popularity, Modeling, and Geo-Distributed File Stores
Roy H. Campbell1, Shadi A. Noghabi1, and Cristina L. Abad2
1Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA
2Escuela Superior Politecnica del Litoral, ESPOL, Guayaquil, Ecuador
This chapter explores the problems of scalability of cloud computing systems. Scalability allows a cloud application to change in size, volume, or geographical distribution while meeting the needs of the cloud customer. A practical approach to scaling cloud applications is to improve the availability of the application by replicating the resources and files used; this includes creating multiple copies of the application across many nodes in the cloud. Replication improves availability through use of redundant resources, services, networks, file systems, and nodes, but also creates problems with respect to clients' ability to observe consistency as they are served from the multiple copies. Variability in data sizes, volumes, and the homogeneity and performance of the cloud components (disks, memory, networks, and processors) can impact scalability. Evaluating scalability is difficult, especially when there is a large degree of variability. That leads to the need to estimate how applications will scale on clouds based on probabilistic estimates of job load and performance. Scaling can have many different dimensions and properties. The emergence of low-latency ...
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