Internet of Things (IoT) refers to the interconnection of uniquely identifiable smart devices which enables them to participate more actively in everyday life. Among large-scale applications, machine-type communications (MTC) supported by cellular networks will be one of the most important enablers for the success of IoT. The existing cellular infrastructure has been optimized for serving a small number of long-lived human-oriented communications (HoC) sessions, originated from smartphones whose batteries are charged in a daily basis. As a consequence, serving a massive number of non-rechargeable machine-type devices demanding a long battery lifetime is a big challenge for cellular networks. The present work is devoted to energy consumption modeling, battery lifetime analysis, and lifetime-aware network design for massive MTC services over cellular networks. At first, we present a realistic model for energy consumption of machine devices in cellular connectivity, which is employed subsequently in deriving the key performance indicator, i.e. network battery lifetime. Then, we develop an efficient mathematical foundation and algorithmic framework for lifetime-aware clustering design for serving a massive number of machine devices. Also, by extending the developed framework to non-clustered MTC, lifetime-aware uplink scheduling and power control solutions are derived. Finally, by investigating the delay, energy consumption, spectral efficiency, and battery lifetime tradeoffs in serving coexistence of HoC and MTC traffic, we explore the ways in which energy saving for the access network and quality of service for HoC traffic can be traded to prolong battery lifetime for machine devices. The numerical and simulation results show that the proposed solutions can provide substantial network lifetime improvement and network maintenance cost reduction in comparison with the existing approaches. / <p>QC 20161103</p>