On Wireless Network Infrastructure Optimization for Cyber-Physical Systems in Future Smart Buildings Jia Liu 1 , Tianyou Kou 1 , Qian Chen 2 , and Hanif D. Sherali 3 1 Dept. of ECE, The Ohio State University, Columbus, OH 43210 2 Dept. of FABE, The Ohio State University, Columbus, OH 43210 3 Dept. of ISE, Virginia Tech, Blacksburg, VA 24061 Abstract. Today, most cyber-physical systems (CPS) in smart build- ings require a wireless-based network infrastructure for sensing, commu- nication, and actuation. In such CPSs, the energy expenditure and hence battery lifetime of the wireless network infrastructure depend heavily upon the placement of the base stations (BS). However, in indoor envi- ronments, BS placement is particularly challenging due to the impact of building structures and floors/walls separations. In this paper, we study the problem of jointly optimizing BS placement and power control in buildings to prolong the battery lifetime of sensors in the CPS network infrastructure. We first show that the joint BS placement and power control problem can be formulated as a mixed-integer non-convex pro- gram (MINCP), which is NP-hard and difficult to solve especially when the network size is large. To address this difficulty, we propose a novel efficient algorithm called ECPC that targets at large-sized network in- frastructures in buildings. Our theoretical analysis and numerical results show that ECPC achieves competitive solutions compared to the true optimal solutions obtained by the branch-and-bound method. 1 Introduction Today, most cyber-physical systems (CPS) in smart buildings require a wireless network infrastructure for sensing, communication, and actuation. However, stud- ies show that the poor battery lifetime performance of current wireless sensors is becoming a critical factor that affects the future prospect of these emerging CPSs in smart buildings. To prolong battery lifetime, there are two complementary ap- proaches. The first one is to increase battery capacity, which had proved to be difficult over the years. The second approach is to reduce the energy expenditure. Since a wireless sensor’s energy expenditure depends heavily on the distance from its associated base station (BS), BS placement optimization has become one of the most effective methods to address the battery lifetime issue. In the literature, BS placement optimization has been studied for various types of wireless networks (see, e.g., cellular networks [1,2], sensor networks [3–5], and references therein). However, the focus of these existing work is not on CPS in building environments. Indeed, when the unique physical features of building X. Wang et al. (Eds.): WASA 2012, LNCS 7405, pp. 607–618, 2012. c  Springer-Verlag Berlin Heidelberg 2012