Energy and Security Awareness in Evolutionary-Driven Grid Scheduling

Ensuring the energy efficiency, thermal safety, and security-awareness in today’s large-scale distributed computing systems is one of the key research issues that leads to the improvement of the system scalability and requires researchers to harness an understanding of the interactions between the system external users and the internal service and resource providers. Modeling these interactions can be computationally challenging especially in the infrastructures with different local access and management policies such as computational grids and clouds. In this chapter, we approach the independent batch scheduling in Computational Grid (CG) as a three-objective minimization problem with Makespan, Flowtime and energy consumption in risky and security scenarios. Each physical resource in the system is equipped with Dynamic Voltage Scaling (DVS) module for optimizing the cumulative power energy utilized by the system. The effectiveness of six genetic-based singleand multi-population grid schedulers has been justified in comprehensive empirical analysis. Joanna Kołodziej Institute of Computer Science, Cracow University of Technology, ul. Warszawska 24, 31-155 Cracow,Poland e-mail: [email protected] Samee U. Khan Department of Electrical and Computer Engineering, North Dakota State University, ND 58108, USA; e-mail: [email protected] Lizhe Wang Center for Earth Observation and Digital Earth; Chinese Academy of Sciences; Beijing; China e-mail: [email protected] Dan Chen China University of Geosciences Wuhan, China; e-mail: [email protected] Albert Y. Zomaya School of Information Technologies, University of Sydney, Sydney, NSW 2006, Australia; e-mail: [email protected]