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Edge computing : from hype to reality
Al-Turjman F., Springer International Publishing, New York, NY, 2019. 188 pp. Type: Book (978-3-319990-60-6)
Date Reviewed: Aug 23 2019

Edge computing is a hot topic that deserves a lot of attention, especially in the context of the Internet of Things (IoT) and mobile and autonomous computing. Moreover, the connection between edge computing and cloud computing can lead to interesting new architectures and applications, driven by key requirements like low latency, cost-effective resource management, and energy savings. Edge computing: from hype to reality, edited by Fadi Al-Turjman, has the ambitious goal of providing the necessary knowledge for implementing edge computing. The book is a collection of papers, organized in ten chapters, with not much fluidity among them.

The first chapter has an appealing title: “The Era of the Personal Cloud.” It introduces readers to the individual benefits of using cloud services. The concept of “the personal cloud” deserves more discussion, though, as the authors quickly move on to issues faced by cloud providers, for example, pricing their services.

The second chapter discusses optimization in edge computing. You would expect to see models of edge computing that include mobility and cloud cooperation. Also, edge servers are heterogeneous, but they can still cooperate in supporting applications. Instead, the chapter considers a grid architectural model, server deployment, and resource allocation optimization strategies. The scope and information delivered are disappointing.

Another disappointment is the next chapter, which claims to be “a comprehensive survey on architecture for big data.” The only significant element is its clarification of mobile edge computing. Personally, I would have liked to see an analysis of big data generation patterns, the appropriate selection of computing resources for processing, and so on. Instead, readers will find deep learning applied to different processes such as mobile sensing and the detection of security threats.

Chapter 4 sticks to its aim of presenting data reduction methods, after giving an introduction very similar to that of the previous chapter (for example, mobile edge computing). Why not take an area such as a smart city and discuss big data produced by crowd sensing? The practical aspects are missing and an application area would focus the presentation.

The next chapter reviews IoT applications, from industrial ones to healthcare. Although it presents an architectural diagram that includes edge and cloud computing, no analysis or comments are included.

Chapter 6 makes the case for software-defined networks (SDN) used to manage big data in smart cities. This more research-oriented section of the book considers traffic management. More sophisticated writing and a comprehensive analysis of the traffic SDN system would increase its value.

An interesting chapter 7 covers the importance and challenges of edge computing in Africa. It gives more definitions of edge, fog, mobile edge, mist, and dew computing, followed by a discussion of information and communications technology (ICT) development challenges in Africa. Overall, it is an interesting read.

Chapter 8 presents a device that can be used for bowel activity monitoring. Although interesting, it doesn’t mention IoT and edge computing at all. It is difficult to understand its place in this book.

The next chapter covers IoT and cloud computing for improving the supply chain process. It will be interesting and helpful to those working in this area.

The last chapter, on security and privacy, is a systematic review of edge features and security and privacy threats.

In summary, this book can be recommended to undergraduates who are interested in learning more about edge computing and IoT, or as a text on these topics for the general public. It has much less value for graduates and researchers.

Reviewer:  D. Grigoras Review #: CR146670 (1911-0380)
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