Cloud Computing: Data-Intensive Computing and Scheduling by Frederic Magoules, Jie Pan, Fei Teng

By Frederic Magoules, Jie Pan, Fei Teng

As increasingly more info is generated at a faster-than-ever fee, processing huge volumes of information is changing into a problem for facts research software program. Addressing functionality concerns, Cloud Computing: Data-Intensive Computing and Scheduling explores the evolution of classical options and describes thoroughly new tools and leading edge algorithms. The ebook delineates many techniques, versions, equipment, algorithms, and software program utilized in cloud computing.

After a common creation to the sector, the textual content covers source administration, together with scheduling algorithms for real-time initiatives and functional algorithms for person bidding and auctioneer pricing. It subsequent explains techniques to info analytical question processing, together with pre-computing, facts indexing, and knowledge partitioning. functions of MapReduce, a brand new parallel programming version, are then offered. The authors additionally talk about how one can optimize a number of group-by question processing and introduce a MapReduce real-time scheduling algorithm.

A precious reference for learning and utilizing MapReduce and cloud computing systems, this ebook offers a variety of applied sciences that exhibit how cloud computing can meet company specifications and function the infrastructure of multidimensional facts research purposes.

Show description

Read or Download Cloud Computing: Data-Intensive Computing and Scheduling PDF

Similar number systems books

Numerical Integration on Advanced Computer Systems

This monograph is a entire remedy of the theoretical and computational elements of numerical integration. The authors supply a different review of the subject by way of bringing into line many fresh learn effects now not but offered coherently; the wide bibliography lists 268 goods. specific emphasis is given to the capability parallelism of numerical integration difficulties and to using it through dynamic load distribution ideas.

Higher-Order Finite Element Methods

The finite point technique has continuously been a mainstay for fixing engineering difficulties numerically. the newest advancements within the box sincerely point out that its destiny lies in higher-order equipment, quite in higher-order hp-adaptive schemes. those recommendations reply good to the expanding complexity of engineering simulations and fulfill the general development of simultaneous solution of phenomena with a number of scales.

Additional info for Cloud Computing: Data-Intensive Computing and Scheduling

Example text

Stanford Peers [Stanford University, 2011] is a peer-to-peer data trading framework, in which both auction and bartering models are applied. A local site wishing to replicate its collection holds an auction to solicit bids from remote sites by Àrst announcing its request for storage space. Each interested remote site then returns a bid, and the site with the lowest bid for maximum beneÀt is selected by the local site. Besides that, a bartering system supports a cooperative trading environment for producer and consumer participants, so that sites exchange free storage spaces to beneÀt both themselves and others.

Overview of cloud computing 5 Through pre-deÀned APIs, users can access, conÀgure and program cloud services. Qualitative aspects. Qualitative characteristics refer to qualities or properties of cloud computing, rather than speciÀc technological requirements. One qualitative feature can be realized in multiple ways depending on different providers. • Elasticity. Elasticity means that the provision of services is elastic and adaptable, which allows the users to request the service near real-time without engineering for peak loads.

Tasks belonging to different users are no longer distinguished one from another. The scheduling problem in such a context is match- 28 Cloud Computing: Data-Intensive Computing and Scheduling ing multi tasks to multi machines. As mentioned in the previous section, the optimal matching is an optimization problem, generally with NP-complete complexity. Heuristics are often applied as a sub-optimal algorithm to obtain relatively good solutions. This section intensively researches two types of strategies, static and dynamic heuristics.

Download PDF sample

Rated 4.59 of 5 – based on 48 votes

About the Author

admin