Ahson S.A., Ilyas M. (eds.) Cloud Computing and Software Services. Theory and Techniques

CRC Press, 2011. — 458 p.Cloud computing has gained significant traction in recent years. The proliferation of networked devices, Internet services, and simulations has resulted in large volumes of data being produced. This, in turn, has fueled the need to process and store vast amounts of data. These data volumes cannot be processed by a single computer or a small cluster of computers. Furthermore, in most cases, these data can be processed in a pleasingly parallel fashion. The result has been the aggregation of a large number of commodity hardware components in vast data centers. Among the forces that have driven the need for cloud computing are falling hardware costs and burgeoning data volumes. The ability to procure cheaper, more powerful CPUs coupled with improvements in the quality and capacity of networks have made it possible to assemble clusters at increasingly attractive prices. By facilitating access to an elastic (meaning the available resource pool that can expand or contract over time) set of resources, cloud computing has demonstrable applicability to a wide range of problems in several domains. Among the many applications that benefit from cloud computing and cloud technologies, the data/compute-intensive applications are the most important. The deluge of data and the highly compute-intensive applications found in many domains, such as particle physics, biology, chemistry, finance, and information retrieval, mandate the use of large computing infrastructures and parallel processing to achieve considerable performance gains in analyzing data. The addition of cloud technologies creates new trends in performing parallel computing. The introduction of commercial cloud infrastructure services has allowed users to provision compute clusters fairly easily and quickly by paying a monetary value for the duration of their usages of the resources. The provisioning of resources happens in minutes, as opposed to hours and days required in the case of traditional queue-based job-scheduling systems. In addition, the use of such virtualized resources allows the user to completely customize the virtual machine images and use them with administrative privileges, another feature that is hard to achieve with traditional infrastructures. Appealing features within cloud computing include access to a vast number of computational resources and inherent resilience to failures.
The latter feature arises because in cloud computing the focus of execution is not a specific, well-known resource but rather the best available one. The availability of open-source cloud infrastructure software and open-source virtualization software stacks allows organizations to build private clouds to improve the resource utilization of the available computation facilities. The possibility of dynamically provisioning additional resources by leasing from commercial cloud infrastructures makes the use of private clouds more promising. Another characteristic of a lot of programs that have been written for cloud computing is that they tend to be stateless. Thus, when failures do take place, the appropriate computations are simply relaunched with the corresponding datasets. This book provides technical information about all aspects of cloud computing, from basic concepts to research grade material including future directions. It captures the current state of cloud computing and serves as a comprehensive source of reference material on this subject. It consists of 17 chapters authored by 50 experts from around the world. The targeted audience include designers and/or planners for cloud computing systems, researchers (faculty members and graduate students), and those who would like to learn about this field.
The book is expected to have the following specific salient features:
To serve as a single comprehensive source of information and as reference material on cloud computing
To deal with an important and timely topic of emerging technology of today, tomorrow, and beyond
To present accurate, up-to-date information on a broad range of topics related to cloud computing
To present the material authored by the experts in the field
To present the information in an organized and well-structured manner
Although, technically, the book is not a textbook, it can certainly be used as a textbook for graduate courses and research-oriented courses that deal with cloud computing. Any comments from the readers will be highly appreciated.Understanding the Cloud Computing Landscape
Science Gateways: Harnessing Clouds and Software Services for Science
Enterprise Knowledge Clouds: Next Generation Knowledge Management Systems?
Real Cases and Applications of Cloud Computing
Large-Scale Data Processing
Toward a Reliable Cloud Computing Service
Abstractions for Cloud Computing with Condor
Exploiting the Cloud of Computing Environments: An Application’s Perspective
Granules: A Lightweight Runtime for Scalable Computing with Support for Map-Reduce
Dynamic and Adaptive Rule-Based Workflow Engine for Scientific Problems in Distributed Environments
Transparent Cross-Platform Access to Software Services Using GridSolve and GridRPC
High-Performance Parallel Computing with Cloud and Cloud Technologies
BioVLAB: Bioinformatics Data Analysis Using Cloud Computing and Graphical Workflow Composers
Scale-Out RDF Molecule Store for Efficient, Scalable Data Integration and Querying
Enabling XM L Capability for Hadoop and Its Applications in Healthcare
Toward a QoS-Focused SaaS Evaluation Model
Risk Evaluation-based Selection Approach for Transactional Services Composition