Energy Management For Cyber-Physical Systems

With the advent of ubiquitous, low-cost computing and anytime connectivity, today's systems have evolved into a complex combination of the world's cyber-infrastructures as well as physical infrastructures. However, to date, most of these systems are comprised of components and subcomponents that are designed and developed independently. As a result, the study of systems in which the cyber and physical components are tightly integrated at all scales and levels, which are referred to as Cyber-Physical Systems (CPSs), is of paramount importance. The position paper published in the NSF workshop on CPSs gives a good overview of different aspects of CPS research.Internet Data Center (IDC) is one important emergent CPS. As the demand on In-ternet services drastically increases in recent years, the energy used by IDCs, directly related to the number of hosted servers and their workload, has been skyrocketing. A recent study estimates that the worldwide spending on enterprise and data center power and cooling to top$30 billion in year 2008 and is likely to even surpass spending on new server hardware. The trend continues with the emergence of Cloud Computing, where data and computation hosting are outsourced to IDCs, for reliability, management, and cost benefits. Therefore, the need for energy management of IDCs is becoming ever more urgent and important.Recently both industry and academia have proposed various technologies and schemes to address different aspects. Most of these energy management approaches have all been proposed as ways to reduce the energy demands of data centers. However, the ul-timate goal of IDC service providers such as Google, Microsoft etc. is to reduce the total operating cost:it does not depend on the power consumed by the IDCs, but also depend on the price (which could exhibit location and time diversity) of the energy consumed.To this end, the contribution of this thesis has twofold:●We investigate an important and novel problem of the total electricity cost for IDC service providers under a multi-electricity-market environment. Our formulation not only can help minimize the total electricity cost of IDCs, but also can guarantee the quality of service experience by end users. We approximate the mixed-integer optimization formulation with a linear programming formulation and solve it with Brenner's fast polynomial-time method. Result shows that the total electricity cost is greatly reduced for IDC locations. ●We investigate an important and novel problem of the total electricity cost for IDC service providers under a multi-electricity-market environment. Our formulation captures both center-level load balancing and server-level power management so as to achieve the goal of minimizing the total electricity cost of IDCs, while at the same time can guarantee the quality of service experience by end users. We pro-pose an efficient solution based on the extension of generalized Benders decompo-sition (GBD) to obtain the optimal load balancing and power control scheme for electricity cost minimization. Further, we evaluate the formulation and solution based on real-life electricity price data and shows that significant total electricity cost reduction can be achieved.