A Novel Deployment Scheme for Green Internet of Things Jun Huang, Member, IEEE, Yu Meng, Xuehong Gong, Yanbing Liu, and Qiang Duan, Member, IEEE Abstract—The Internet of Things (IoT) has been realized as one of the most promising networking paradigms that bridge the gap between the cyber and physical world. Developing green deploy- ment schemes for IoT is a challenging issue since IoT achieves a larger scale and becomes more complex so that most of the current schemes for deploying wireless sensor networks (WSNs) cannot be transplanted directly in IoT. This paper addresses this challenging issue by proposing a deployment scheme to achieve green net- worked IoT. The contributions made in this paper include: 1) a hierarchical system framework for a general IoT deployment, 2) an optimization model on the basis of proposed system framework to realize green IoT, and 3) a minimal energy consumption algorithm for solving the presented optimization model. The numerical results on minimal energy consumption and network lifetime of the system indicate that the deployment scheme proposed in this paper is more flexible and energy efficient compared to typical WSN deployment scheme; thus is applicable to the green IoT deployment. Index Terms—Deployment, energy efficient, green, Internet of Things (IoT). I. INTRODUCTION T HE INTERNET OF THINGS (IoT) has been envisioned as one of the most promising networking paradigms that bridge the gap between the cyber and physical world. The prevalence of IoT leads toward a new digital context for config- uring novel applications and services. IoT consists of a variety of things or objects such as Radio Frequency Identification (RFID) tags, sensors, actuators, mobile phones, etc., which are inter- connected through both wired and wireless networks to the Internet. Objects in IoT can sense the environment, transfer the data, and communicate with each other. They become powerful tools to understand physical world and to respond to emergent events and irregularities promptly. Thus, the IoT is seen by many as the ultimate solution for getting insights about real-world physical processes in real-time. In parallel, the advancement of IoT brings some challenges to its implementation. Different from traditional wireless sensor networks (WSNs), IoT achieves a larger scale and becomes more complex [1]. This turns out that the schemes for deploying WSNs may not be transplanted in the IoT directly. On the other hand, since IoT consists of more objects that consume higher power, green issues should also be taken into consideration. Green networking plays a vital role in deploying IoT: they can reduce emission and pollution, exploit environmental conservation and surveillance, and minimize operational costs and power con- sumption [2]–[5]. Therefore, how to cost-effectively realize green deployment for IoT is a crucial issue, which is the research focus of this paper. Although much exciting progress has been made in deploying energy-efficient WSNs, such as exact [6]–[8], ad hoc [9]–[11], hierarchy [12]–[14], and hybrid [13]–[15] schemes, these studies have not sufficiently investigated the deployment issue with green networking consideration in order to build a scalable and sustainable IoT. In response, we investigate how to cost- effectively arrange objects to form a green networked IoT in this paper and propose a novel deployment scheme. Specifically, we first give a hierarchical system framework for IoT deployment. The framework captures the scale feature of IoT and thus making it extensible. Then, we present an optimization model on the basis of the presented framework, where the model is constrained in terms of energy consumption, link flow balance, and system budget, which facilitate the IoT toward green. Finally, we devise a minimal energy consumption algorithm (MECA) by leverag- ing the clustering principle and a well-known Steiner tree algo- rithm to solve the optimization problem. We show that the proposed scheme can work more flexibly and energy-efficiently compared to typical WSN deployment scheme; thus is applicable to the green IoT deployment. The contributions of this paper are summarized as follows. 1) We present a hierarchical framework for placing network elements, i.e., objects/things in IoT. The framework cap- tures the scale feature of IoT thus enables its extension. By allowing direct communications among relay nodes and not allowing communications among sensing nodes, the framework can migrate the traffic load from sensing nodes to relay nodes, thus prolonging the network lifetime. 2) Based on the presented framework, we model a green IoT by considering energy consumption, link flow balance, and system budget as an optimization problem. We then pro- pose an MECA, which leverages the clustering principle and the Steiner tree algorithm to solve the optimization Manuscript received September 27, 2013; revised December 18, 2013; accepted January 10, 2014. Date of publication January 21, 2014; date of current version May 14, 2014. This work was supported in part by NCET, NSFC (Grants 61272400, 61309031), in part by Program for Innovation Team Building at Institutions of Higher Education in Chongqing (Grant KJTD201310), in part by Natural Science Foundation of Chongqing (Grant cstc2013jcyjA40026), in part by Scientific and Technological Research Program of Chongqing Municipal Education Commission (Grant KJ130523), and in part by CQUPT Research Fund for Young Scholars (Grant A2012-79). J. Huang is with the Department of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China (e-mail: xiaoniuadmin@gmail.com). Y. Meng, X. Gong, and Y. Liu are with the Department of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China (e-mail: liuyb@cqupt.edu.cn). Q. Duan is with the Department of Information Science and Technology, The Pennsylvania State University, Abington, PA 19001 USA (e-mail: qduan@psu.edu). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/JIOT.2014.2301819 196 IEEE INTERNET OF THINGS JOURNAL, VOL. 1, NO. 2, APRIL 2014 2327-4662 © 2014 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.