Computing Reviews
Today's Issue Hot Topics Search Browse Recommended My Account Log In
Review Help
Search
Self-aware computing systems
Kounev S., Kephart J., Milenkoski A., Zhu X., Springer International Publishing, New York, NY, 2017. 722 pp. Type: Book (978-3-319474-72-4)
Date Reviewed: Sep 14 2017

Self-aware computing systems are covered in this book, which is an expanded collection of papers (each chapter by a group of authors). Organized under five parts, the book is an attempt to bring together researchers in the topic across various application domains. Each part is organized as a set of chapters, and each chapter is an attempt to tie together the multiple perspectives on the issues considered. The five parts are: “Introduction,” “System Architectures,” “Methods and Algorithms,” “Applications and Case Studies,” and “Outlook.”

Part 1 consists of four chapters that collate multiple perspectives to formally define self-aware computing systems and establish a taxonomy. The formal definition is expressed in terms of the ability of the system to learn and reason. Reading this part, its similarity to the early attempts of defining multiagent systems is uncanny! The authors in chapter 2 define multiagent systems (MAS) and the differences between self-aware computing systems and MAS. Similarly, they also discuss comparisons with autonomic computing, a topic similar to the preceding one in a different domain, as well as other areas such as service-based computing, self-organized systems, and so on. However, these differences could have been better elaborated and articulated rather than appear like a short literature survey chapter. An example to illustrate the subtle differences could have been useful to all readers. The rest of the chapters in this part address several related topics on self-awareness as it applies to humans and machines with an attempt to define a conceptual framework for self-awareness. Further, they also put forth three key dimensions of self-awareness: goal complexity, goal alignment, and heterogeneity. They also offer three scenarios to demonstrate self-awareness: adaptive sorting, data center resource management, and multiple entities with conflicting goals.

In Part 2, organized as four chapters, the authors present some architectures for self-aware computing systems. Chapter 5 introduces some notations, contexts, and terminologies based on unified modeling language (UML) for modeling self-aware computing systems. Chapter 6 discusses architectures for isolated self-aware systems. Chapter 7 deals with interactions among multiple self-aware systems, and the final chapter (chapter 8) deals with the current state of reference architectures, frameworks, and languages. The authors also present some open challenges in the field.

Part 3 deals with methods and algorithms and contains seven chapters. Chapters 9 through 11 deal with issues of self-modeling, retrofitting non-self-aware systems, and the synthesis and verification of self-aware computing systems. Chapters 12 and 13 address interplay among multiple self-aware systems and resulting emergent behaviors and consequences. Chapters 14 and 15 discuss metrics, benchmarks, and assessment.

In Part 4, applications and case studies across multiple domains are presented. These include cloud computing, including topics of data center performance management (chapters 16 and 17), workload forecasting (chapter 18), virtualization (chapters 19 and 20), self-protection (chapter 21), intrusion detection systems (chapter 22), networking (chapter 23), cyber-physical systems (chapter 24), and autonomous spacecraft (chapter 25).

Part 5 contains one chapter that discusses open challenges and future research in self-aware computing systems.

In summary, the book is, as designed, an assimilation of related topics on self-aware computing systems (nicely expanded from a focused conference in the area) and could be a quick and useful reference for someone starting out research in the field. However, it is not suitable for regular undergraduate student audiences because it is quite conceptual and requires a holistic understanding of several related topics in computing.

Reviewer:  Srini Ramaswamy Review #: CR145539 (1711-0712)
Bookmark and Share
  Featured Reviewer  
 
Applications And Expert Systems (I.2.1 )
 
 
General (D.2.0 )
 
 
Performance of Systems (C.4 )
 
Would you recommend this review?
yes
no
Other reviews under "Applications And Expert Systems": Date
Institutionalizing expert systems: a handbook for managers
Liebowitz J. (ed), Prentice-Hall, Inc., Upper Saddle River, NJ, 1991. Type: Book (9780134720777)
Nov 1 1991
Verifying and validating personal computer-based expert systems
Bahill A., Prentice-Hall, Inc., Upper Saddle River, NJ, 1991. Type: Book (9780139574573)
Jun 1 1992
Knowledge-based systems: a manager’s perspective
Tuthill G., Levy S., TAB Books, Blue Ridge Summit, PA, 1991. Type: Book (9780830634798)
Dec 1 1991
more...

E-Mail This Printer-Friendly
Send Your Comments
Contact Us
Reproduction in whole or in part without permission is prohibited.   Copyright 1999-2024 ThinkLoud®
Terms of Use
| Privacy Policy