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Cloud computing: principles, systems and applications (2nd ed.)
Antonopoulos N., Gillam L., Springer International Publishing, New York, NY, 2017. 410 pp. Type: Book (978-3-319546-44-5)
Date Reviewed: May 8 2018

In recent years, the applications and architectural specifications of cloud computing have been major streams of investigation. Besides the cloud’s technical significance at performing practical projects, it has opened a new horizon within the computing literature, including methods of classifying and utilizing the data at big and scalable dimensions. To reflect some of these properties, the book has been edited to include 14 illustrative papers that discuss different aspects of cloud computing’s architectural properties and application use cases.

Part 1, “General Principles,” includes three chapters. Chapter 1 focuses on network society components and ideas. In chapter 2, which proposes a workflow management system, the techniques of dimensioning cloud resources for high-performance computing in complex scientific applications are considered. Static and dynamic cloud dimensioning mechanisms for assigning computational resources like virtual machines (VM), memory, datasets, and so on are expressed. Chapter 3 is a fruitful paper with great references about the architectural components of cloud systems with adaptive resource management ideas. With a nice historical discussion, cloud resources and computational units are introduced, and adaptive techniques concerning high-level language VM (HLL-VM) and system VM (sys-VM) are explained. With the objective of performant processing, the responsiveness, comprehensiveness, and intricateness (RCI) taxonomy for resource management and related techniques for adaption cycles (monitoring, analysis, decision, and action) are demonstrated. The classification of VM systems is the last discussion of the paper.

Part 2, “Science Cloud,” starts with a very rich paper that is a significant review of cloud computing techniques; it has gathered nearly all the basic topics related to clouds like an encyclopedia. It contains plenty of good technical matter and covers the meaning of elasticity in detail. Definitions of elasticity, elasticity architecture, horizontal and vertical elasticity, control, and replacement task providing mechanisms are the main topics discussed. With an emphasis on reproducibility in science and its importance at validation and verification of scientific ideas and theorems, chapter 5 investigates the value and usage of cloud computing. It proposes a reference architecture for reproducibility support using clouds. Chapter 6 features a cloud-based framework for integrating genomics/healthcare data in a big data platform, which would enable users to generate meaningful insights in that domain.

Part 3 is titled “Data Cloud.” The main theme of chapter 7 is graph-based huge data management. It primarily discusses algorithms for online graph query processing and offline batch graph analysis. Large graph analysis to acquire appropriate performance benchmarks is one of its objectives. Graph theory is the basis of new huge data reservoir management systems, but its direct relevance to cloud computing is ambiguous. The MapReduce framework and its peer-to-peer architecture are explained in chapter 8.

A significant and comprehensive artifact, which features the management of integration in cloud federation, is the vanguard chapter of Part 4, “Multi-clouds.” Their interoperability is provided by provisioning cross-cloud data migration and cooperation. The platform uses a neural message bus system and integrated monitoring mechanisms. This structure affords the possibility of cooperation among heterogeneous clouds for resource leasing and trading. Consequently, a single application would be capable of utilizing multiple cloud resources, to accomplish its task with efficient data transfer among them. Chapter 10 is a survey that has collected lots of subjects, mostly about autonomic computing and its deployment in the cloud platform.

Part 5, “Performance and Efficiency,” starts with a well-written and structured paper. At first, the role of brokers in the cloud ecosystem is expressed, and then virtual cloud brokers for infrastructure as a service (IaaS) are considered. The mechanisms to provide and maintain quality of service (QoS) and profit in virtual cloud brokers are the main theme of the paper. The authors develop their ideas by formalizing a combinatorial optimization, multivariant, multiobjective Pareto problem. Offline and online scheduling policies are investigated to gain the defined goals. Chapter 12 is a perfect artifact, which discusses the involvement of data centers (DCs) with the cloud. The managing policies for heterogeneous DCs with different component capacities, central processing units (CPUs), memory, networking, and so on to host VMs are its pivotal topics. For IaaS, an efficient proactive resource allocation strategy (PRAS) mechanism via behavior predication (autoregressive moving average) and optimization enforcement mechanisms (particle swarm optimization) are discussed. Chapter 13 investigates the relationship between incoming user jobs and constituting tasks with different requirements, constraints, and available versatile resources that seem to be very complicated. Moreover, the efficiency of any scheduling policy would have a profound impact on the performance and optimum utilization of resources; with this view based on workload analysis, predictability, data center tracing, and so on, the paper proposes methods to manage jobs effectively in the cloud system. The last chapter addresses power consumption management issues in web-based applications within a software as a system (SaaS) cloud model. After a survey, it proposes the green browsing architecture, which dictates an overall system for optimum power usage based on using dynamic power management, energy-aware scheduling, and browser- and tab-level energy management policies.

The book is a collection of good articles about cloud computing. Most chapters include a brief discussion about open problems that could potentially be a useful pathway for researchers.

Reviewer:  Mohammad Sadegh Kayhani Pirdehi Review #: CR146023 (1807-0348)
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