Energy efficiency in big data complex systems: a comprehensive survey of modern energy saving techniques

Abstract

Abstract The growing need of computation and processing has led to the generation of data centers. These data centers are usually comprised of hundreds of thousands of servers and other components. This complicated arrangement of the systems lead to the adoption of complex systems. Complex systems prevail in our society as combination of lots of entities, e.g., immune system, human brain and ecosystems. The adoption and interaction of the entities is possible through nonlinear interactions. The interaction between the components of the complex system is carried out in distributed fashion. Big data which is comprised of thousands of machines is also considered to be a form of complex adaptive systems which makes use of large entities, components and nonlinear interactions with each other. The development of such a complex systems raises certain challenges. Apart from management, energy is the most concerned one which is the core discussion of this research. This paper, surveys the state of the art on modern tools, techniques, architectures and algorithms which has been proposed and deployed to achieve energy efficiency in big data over the period of 2007–2015. We group existing approaches aimed at achieving energy efficiency in the complex paradigm of big data. In this categorization, we aim to provide an easy and concise view of the underlined model adapted by each approach in the context of big data.