Complex Systems and Clouds

A Self-Organization and Self-Management Perspective

Dan C. Marinescu

• Publisher: Elsevier
• Year: 2016
• Print ISBN: 9780128040416
• eBook ISBN: 9780128040942
• Topic: Computer Science
• Subtopic: Computer Networking
• Index: Computer Science

Complex Systems and Clouds: A Self-Organization and Self-Management Perspective provides insights into the intricate world of self-organizing systems. Large scale distributed computer systems have evolved into very complex systems and are at the point where they need to borrow self-adapting organizing concepts from nature.The book explores complexity in big distributed systems and in the natural processes in physics and chemistry, building a platform for understanding how self-organization in big distributed systems can be achieved. It goes beyond the theoretical description of self-organization to present principles for designing self-organizing systems, and concludes by showing the need for a paradigm shift in the development of large-scale systems from strictly deterministic to non-deterministic and adaptive.- Analyzes the effect of self-organization applied to computer clouds- Furthers research on principles of self-organization of computing and communication systems inspired by a wealth of self-organizing processes and phenomena in nature and society- Presents a unique analysis of the field, with solutions and case studies

Chapter 1

Complex Systems

Abstract

After a brief review of the evolution of thinking about systems, consisting of an ensemble of components, the chapter analyzes the nondeterminism, nonlinearity, and phase transitions in complex systems. A range of topics pertinent to complexity, such as self-organization, self-organized criticality, power law distributions, computational irreducibility, and quantitative characterization of complexity are then covered. Cybernetics and the interdisciplinary nature of complexity conclude the chapter.

Keywords

Complexity; Emergence; Phase transitions; Open systems; Nondeterminism; Self-similarity; Fractal geometry; Power Law distribution

Informally, we say that a system or a phenomenon is complex if its behavior cannot be easily described and understood [121]. Biological systems shaped by evolution, physical phenomena such as turbulence, the mixture of biology and social components involved in spreading of infectious diseases, and man-made systems such as the Large Hadron Collider (LHC) exhibit elements of complexity.

Complex systems are difficult to model, thus it is difficult to study them and understand the laws governing their evolution. A complex system is characterized by intricate interactions among its components and the emergence of novel properties that cannot be inferred from the study of the individual system components. The behavior of a complex system is subject to statistical laws which affect the individual system components, as well as the interactions among them.

We review philosophical concepts related to the nature and scope of knowledge and the defining attributes of complexity, including nondeterminism, self-similarity, emergence, nonlinearity, and phase transitions. We analyze the interactions of a complex system with the environment. In this chapter, we discuss fractal geometry, Power Law distributions, self-organized criticality, and quantitative characterization of complexity. We conclude with a discussion of the interdisciplinary nature of complexity studies.

1.1 The Thinking on Complex Systems Through the Centuries

Abstract questions about systems consisting of an ensemble of components have preoccupied the minds of humans since antiquity. Plato, a student of Socrates, and Aristotle’s mentor, laid the very foundations of Western philosophy and science. He founded one of the earliest known schools in Athens, the Academy. In The Republic, Plato introduces the concept of “level of knowledge,” ranging from total ignorance to total knowledge. Plato was influenced by Pythagoras in believing that abstract thinking represents the basis for philosophical thinking and sound theses in science, as well as morals. In A History of Western Philosophy, Bertrand Russel argues that Pythagoras should be considered the most influential Western philosopher.

Aristotle, in Metaphysics, Book H states “…the totality is not, as it were, a mere heap, but the whole is something besides the parts …,” i.e., the whole is other than the sum of the parts. Zino of Eleea, a Greek philosopher living in the 5th century BC, is famous for his paradoxes. One of his paradoxes was that a distance of any length could be divided into an infinite number of shorter segments, therefore covering the distance required traversing an infinite number of shorter segments taking an infinite amount of time; we obviously do cross distances in finite time! Aristotle’s answer was that a length was first and foremost a whole.

The philosophy of science has always been that the world can be understood by discovering the properties of its simple building blocks. The traditional scientific method, based on analysis, isolation, and the gathering of complete information about a phenomenon, is a reflection of the reductionist principle. The Greek philosopher Leucippus of Miletus thought the material world is composed of tiny indivisible particles called atoms.¹ Democritus (c.460–371 BC), a disciple of Leucippus, was inspired by his mentor’s book, The Greater World System and he refined and extended the concept.

The atomic theory of Democritus states that matter is composed of atoms separated by empty space through which the atoms move and that atoms are solid, homogeneous, indivisible, and unchangeable. Some 2500 years later, we are still struggling to better understand the properties of the visible physical matter which accounts for only 4% of the universe. We know even less about the dark matter and the dark energy, which represent 23% and 73%, respectively, of the universe.

Classical mechanics, formulated by Newton and further developed by Laplace and others, was accepted as the foundation for all scientific disciplines until the beginning of the 20th century. Epistemology is a branch of philosophy concerned with the nature and scope of knowledge. Newtonian epistemology is based on the principle of analysis formulated by the French mathematician and philosopher Descartes, who laid the foundation of 17th century rationalism. According to this principle, also called reductionism, to understand a complex phenomenon one has to identify its components and understand their properties and if these components are also complex, the reduction process should be applied recursively until reaching the simplest, or atomic, components with well understood properties.

Newtonian epistemology is based on a reflection-correspondence view of knowledge and on sound philosophical monisms including materialism, reductionism, and determinism. Newtonian epistemology had a pervasive influence on scientific thinking for several centuries, not only because its basic paradigm is compelling by its simplicity, coherence, and apparent completen...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• Dedication
• Preface
• Chapter 1: Complex Systems
• Chapter 2: Nature-Inspired Algorithms and Systems
• Chapter 3: Managing Complexity of Large-Scale Cyber-Physical Systems
• Chapter 4: Computer Clouds
• Chapter 5: Cloud Self-Organization and Big Data Applications
• Bibliography
• Index