A Cyber–Physical Systems Approach to Data Center Modeling and Control for Energy Efficiency

Abstract

Abstract-This paper presents data centers from a cyberphysical system (CPS) perspective. Current methods for controlling information technology (IT) and cooling technology (CT) in data centers are classified according to the degree to which they take into account both cyber and physical considerations. To evaluate the potential impact of coordinated CPS strategies at the data-center level, we introduce a control-oriented model that represents the data center as two coupled networks: a computational network representing the cyber dynamics and a thermal network representing the physical dynamics. These networks are coupled through the influence of the IT on both networks: servers affect both the quality of service (QoS) delivered by the computational network and the generation of heat in the thermal network. Using this model, three control strategies are evaluated with respect to their energy efficiency and computational performance: a baseline strategy that ignores CPS considerations, an uncoordinated strategy that manages the IT and CT independently, and a coordinated strategy that manages the IT and CT together to achieve optimal performance with respect to both QoS and energy efficiency. Simulation results show that the benefits to be realized from coordinating the control of IT and CT depend on the distribution and heterogeneity of the computational and cooling resources throughout the data center. A new cyber-physical index (CPI) is introduced as a measure of this combined distribution of cyber and physical effects in a given data center. We illustrate how the CPI indicates the potential impact of using coordinated CPS control strategies.

Holistic Virtual Machine Scheduling in Cloud Datacenters towards Minimizing Total Energy

“…For algorithms which do not consider VM migration [14], [15],  is configured as null. Total energy required to operate a datacenter is considered as the sum of computing energy Ecomputing and cooling energy Ecooling [16], [17], which are considered as energy …”

“…In other words, uncoordinated scheduling algorithms that consider minimizing computing and cooling energy usage as isolated optimization problems do not necessarily result in the minimal total datacenter energy [17], [20]. Therefore it is critical for energy-aware workload scheduling to consider computing and cooling energy as a single optimization problem to ascertain an optimal trade-off point and achieve the best energy efficiency.…”

Joint Computing and Electric Systems Optimization for Green Datacenters

“…Experimental results for a virtual datacenter demonstrate a reduction by 35% in power consumption and 15% in cooling. Authors in [27] present a control-oriented model that considers cyber and physical dynamics in datacenters to study the potential impact of coordinating the IT and cooling controls. To achieve further power savings while maintaining the QoS level, joint relationships among VMs, like load correlations, have been exploited in recent works [36,24,19].…”

Towards Middleware-Based Cooperation Topologies for the Next Generation of CPS

“…In CPS, it is necessary to simultaneously consider the computing and communication processing together with the physical system and their interactions [35]. An example of this interaction is the management of the energy consumption as described in [36]. More detailed models for describing the whole underlying infrastructure are required with algorithms to make decisions according to its current state.…”