Reducing the energy consumption of Internet services requires knowledge about the specific traffic and energy consumption characteristics, as well as the associated end-to-end topology and the energy consumption of each network segment. Here, we propose a shift from segment-specific to service-specific end-to-end energy-efficiency modeling to align engineering with activity-based accounting principles. We use the model to assess a range of the most popular instant messaging and video play applications to emerging augmented reality and virtual reality applications. We demonstrate how measurements can be conducted and used in service-specific end-to-end energy consumption assessments. Since the energy consumption is dependent on user behavior, we then conduct a sensitivity analysis on different usage patterns and identify the root causes of service-specific energy consumption. Our main findings show that smartphones are the main energy consumers for web browsing and instant messaging applications, whereas the LTE wireless network is the main consumer for heavy data applications such as video play, video chat and virtual reality applications. By using small cell offloading and mobile edge caching, our results show that the energy consumption of popular and emerging applications could potentially be reduced by over 80%.Energies 2019, 12, 184 2 of 18 increase since 2014 [2]. Furthermore, the data centers of Akamai consumed 233,090 MWh electricity in 2016, which is an increase of around 50% since 2012 [3].The increasing number of smartphone users together with the emergence of data-heavy mobile applications such as high-definition video play, virtual reality (VR) and augmented reality (AR) are driving the growth in mobile data traffic. These applications typically require very high network bandwidth and smartphone computing resources [4][5][6]. Moreover, the instant messaging (IM) applications, such as WeChat, Twitter, etc., attract a huge number of users because they offer a variety of mobile services including text/picture/voice messages, audio/video chat, moments, etc., and also consume a lot of network resources. Existing research to reduce the overall energy consumption of the Internet, including communication networks, cloud data centers and mobile devices, has focused on segment-specific energy consumption modeling and assessment of the end-to-end delivery of mobile applications, such as power models for smartphones, BSs, and edge and core networks. For example, various power models have been developed for estimating the energy consumption of different smartphone components such as 3G/4G, WiFi, central processing unit (CPU), liquid crystal display (LCD) and global positioning system (GPS). The researches in [7][8][9][10] show that the energy consumption of smartphones is influenced by different traffic characteristics and signaling patterns of mobile applications. Various power models of a long-term evolution (LTE) BS proposed in [11][12][13][14][15] try to assess energy consumption of mobile applications by sep...

123effective guarantees on quality of service. In the process of the development of QoS technology, the Internet Engineering Task Force (IETF) has explored several QoS architectures such as IntServ [1] and Diffserv [2], but none has been successfully and globally deployed. This is partly because these QoS architectures are built on top of a distributed hop-by-hop routing architecture without a global view. Instead of IP QoS and guarantees, overlay QoS for multimedia applications may provide some level of quality of service to improve the multimedia communication on the top of the best services[3][4][5][6][7]. By using fast label switching, Multi-Protocol Label Switching (MPLS) [8] provides a reliable solution to improve QoS performance. However, it is configured statically without real-time reconfiguration ability and adaptability [19].Current QoS solutions, such as IntServ, may cost too much, or cannot provide an end to end QoS guarantee (e.g. DiffServ), or provides only soft and less efficient QoS such as application layer QoS. Software Defined Networking (SDN) [9] provides a possible way to solve these problems and paves the way for new QoS frameworks. SDN is a new approach for computer networking to manage network services with a global view and real time programmability through abstraction of lower level functionality. It separates the control plane and the forwarding plane of the traditional Abstract: Today's Internet architecture provides only "best effort" services, thus it cannot guarantee quality of service (QoS) for applications. Software Defined Network (SDN) is a new approach to computer networking that separates control plane and forwarding planes, and has the advantage of centralized control and programmability. In this paper, we propose HiQoS that provides QoS guarantees using SDN. Moreover, HiQoS makes use of multiple paths between source and destination and queuing mechanisms to guarantee QoS for different types of traffic. Experimental results show that our HiQoS scheme can reduce delay and increase throughput to guarantee QoS. Very importantly, HiQoS recovers from link failure very quickly by rerouting traffic from failed path to other available path.

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