Dynamic energy-aware cloudlet-based mobile cloud computing model for green computing Keke Gai a , Meikang Qiu a,n , Hui Zhao b , Lixin Tao a , Ziliang Zong c a Department of Computer Science, Pace University, NY, USA b Software School, Henan University, Kaifeng, Henan 475000, China c Department of Computer Science, Texas State University, TX, USA article info Available online 11 June 2015 Keywords: Mobile cloud computing Green computing Dynamic program Energy-aware Cloudlets abstract Employing mobile cloud computing (MCC) to enable mobile users to acquire benefits of cloud computing by an environmental friendly method is an efficient strategy for meeting current industrial demands. However, the restrictions of wireless bandwidth and device capacity have brought various obstacles, such as extra energy waste and latency delay, when deploying MCC. Addressing this issue, we propose a dynamic energy-aware cloudlet-based mobile cloud computing model (DECM) focusing on solving the additional energy consumptions during the wireless communications by leveraging dynamic cloudlets (DCL)-based model. In this paper, we examine our model by a simulation of practical scenario and provide solid results for the evaluations. The main contributions of this paper are twofold. First, this paper is the first exploration in solving energy waste problems within the dynamic networking environment. Second, the proposed model provides future research with a guideline and theoretical supports. & 2015 Elsevier Ltd. All rights reserved. 1. Introduction Mobile cloud computing (MCC) is an emergence of multiple Internet-based technologies development, which enables mobile users to acquire benefits of cloud computing and achieve green computing by using their mobile devices (Sabharwal et al., 2013; Bonino et al., 2013). The technology mainly derives from three hemispheres, including mobile computing, mobile Internet, and cloud computing. Combing the advantages of multiple techniques allows users to offload data processing and storage to the cloud- based servers (Huang et al., 2011; Kumar and Lu, 2010). However, behind the benefits of adopting this approach, the implementa- tions of MCC are still facing a few challenges that limit its performance, such as energy over consumptions while the wire- less communications are weak (Guan et al., 2011). Keeping searching wireless signals can dry out the power of mobile devices, which may cause unexpected energy waste (Han et al., 2011). In this paper, we propose an advanced dynamic model, dynamic energy-aware cloudlet-based mobile cloud computing model (DECM), which uses cloudlets technique to assign, manage, and optimize the cloud-based infrastructure usages and services for achieving green computing. This model uses dynamic program- ming to assist cloudlets cloud computing resources within a changing operational environment. The intention of DECM matches practical demands of mobile industry because various elements can have major influences on the cloud services quality. For example, mobile users who are using map services highly rely on the speed of wireless communications while the mobile devices are rapidly moving. Nevertheless, unstable and inefficient wireless connections usually shorten the battery life. Many researchers and scholars have done various achievements in energy-aware mobile cloud computing in previous research. The research is diverse in different perspectives (Gupta and Roy, 2013). Zhu and his team (Yang et al., 2014) developed a real-time tasks oriented virtualized cloud computing system that was designed to achieve energy-aware scheduling in their recent works. The proposed solution (Yang et al., 2014) intends to integrate various energy-aware scheduling algorithms by employing a rolling-horizon optimization policy. However, this approach did not consider mobility usage and the similar research focusing on energy-aware cloud computing systems has been accomplished by other scholars (Mezmaz et al., 2011; Beloglazovand Buyya, 2010; Berl et al., 2010). Furthermore, as one of the core techniques in cloud computing, virtual machine (VM) is considered an efficient approach for building up cloud-based datacenter to achieve green computing Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/jnca Journal of Network and Computer Applications http://dx.doi.org/10.1016/j.jnca.2015.05.016 1084-8045/& 2015 Elsevier Ltd. All rights reserved. n Corresponding author. E-mail address: mqiu@pace.edu (M. Qiu). Journal of Network and Computer Applications 59 (2016) 46–54