The proliferation of Internet of Things (IoT) and the success of rich cloud services have pushed the horizon of a new computing paradigm, edge computing, which calls for processing the data at the edge of the network. Edge computing has the potential to address the concerns of response time requirement, battery life constraint, bandwidth cost saving, as well as data safety and privacy. In this paper, we introduce the definition of edge computing, followed by several case studies, ranging from cloud offloading to smart home and city, as well as collaborative edge to materialize the concept of edge computing. Finally, we present several challenges and opportunities in the field of edge computing, and hope this paper will gain attention from the community and inspire more research in this direction.

Edge Computing: Vision and Challenges

Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized mobile cloud computing toward mobile edge computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also discuss a set of issues, challenges, and future research directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.

A Survey on Mobile Edge Computing: The Communication Perspective

Mobile phones or smartphones are rapidly becoming the central computer and communication device in people's lives. Application delivery channels such as the Apple AppStore are transforming mobile phones into App Phones, capable of downloading a myriad of applications in an instant. Importantly, today's smartphones are programmable and come with a growing set of cheap powerful embedded sensors, such as an accelerometer, digital compass, gyroscope, GPS, microphone, and camera, which are enabling the emergence of personal, group, and communityscale sensing applications. We believe that sensor-equipped mobile phones will revolutionize many sectors of our economy, including business, healthcare, social networks, environmental monitoring, and transportation. In this article we survey existing mobile phone sensing algorithms, applications, and systems. We discuss the emerging sensing paradigms, and formulate an architectural framework for discussing a number of the open issues and challenges emerging in the new area of mobile phone sensing research.

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A survey of mobile phone sensing

Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized Mobile Cloud Computing towards Mobile Edge Computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also present a research outlook consisting of a set of promising directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.

Together with an explosive growth of the mobile applications and emerging of cloud computing concept, mobile cloud computing (MCC) has been introduced to be a potential technology for mobile services. MCC integrates the cloud computing into the mobile environment and overcomes obstacles related to the performance (e.g., battery life, storage, and bandwidth), environment (e.g., heterogeneity, scalability, and availability), and security (e.g., reliability and privacy) discussed in mobile computing. This paper gives a survey of MCC, which helps general readers have an overview of the MCC including the definition, architecture, and applications. The issues, existing solutions, and approaches are presented. In addition, the future research directions of MCC are discussed. Copyright © 2011 John Wiley & Sons, Ltd.

A survey of mobile cloud computing: architecture, applications, and approaches

We will demo FocusVR, a system for effectively and efficiently reducing the power consumption on Virtual Reality (VR) headset with OLED displays. FocusVR smartly dims the screen to reduce display power through the use vignette on VR displays. Our approach has shown to save up to 80% of display power with no impact to usability and task completion time on the Samsung Galaxy Gear VR, Oculus Rift and HTC Vive (paper under review). In this demo, we will demonstrate the technique on a Samsung Galaxy Gear VR with a Samsung Galaxy Note 4. During the demo, users will be able to observe the power saving technique within a virtual world in two modes: fly-through and interactive.

Demo: FocusVR: Effective & Usable VR Display Power Management

Immersive virtual reality has long been an aspiration of many. Recent advances in wearable high resolution headmounted displays (HMDs) — as embodied by Facebook’s Oculus Rift, Sony’s Morpheus, Samsung’s Gear VR, Google’s Cardboard and others — have stoked the imaginations of a new generation of VR users. For a truly immersive VR experience, three properties are essential: quality, responsiveness and mobility. By quality, we mean that realistic and life-like visual portrayals in a virtual environment heighten our sense of immersion. By responsiveness, we mean that any motion, especially of the head, must be reflected as quickly as possible in visual feedback because ocular proprioception is tightly synchronized. By mobility, we mean that we ought to be able to move untethered in physical space, free to explore our virtual world. However, HMDs face a fundamental challenge in seeking to simultaneously provide quality, responsiveness and mobility; choosing any two rules out the third. In this work, we present Irides, a stereo HMD system that simultaneously attains quality, responsiveness and mobility. Irides achieves this by offloading rendering work to a (possibly WAN) high-end GPU. The HMD client is mobile and only requires a wireless network connection, yet receives high quality and responsive visuals. Irides leverages prior work to overcome WAN latencies [2]. It employs speculative execution on the server, and compensates for misspeculation on the client. However, a straightforward application of speculative execution for stereo HMDs is prohibitive because of the 2× increase in server, client and network bandwidth costs. Therefore, we introduce two techniques to reduce these costs as shown in Figure 1. The first technique, interleaved stereo, generates a stereo video stream with only a mono video stream’s worth of work. Interleaved stereo uses image-based rendering (IBR), a way to warp a 2D image with depth information to a novel view. Synthesizing a stereo video from a mono source can introduce severe artifacts. We introduce novel “hole-filling” mechanisms that eliminate artifacts.

Demo: Irides: Attaining Quality, Responsiveness and Mobility for Virtual Reality Head-mounted Displays

Programmable consumer devices have placed computation within arm's reach at all times and in all places Unfortunately, researchers interested in investigating this phenomenon often struggle with the expense, inconvenience, and limited scale of existing experimental platforms In this paper, we introduce a new experimental platform for mobile and pervasive computing based on JellyNets, an abstraction for exposing experiments to arbitrary mobile social contexts

Eduardo Cuervo

Papers

Demo: FocusVR: Effective & Usable VR Display Power Management

Demo: Irides: Attaining Quality, Responsiveness and Mobility for Virtual Reality Head-mounted Displays

Experimenting in mobile social contexts using JellyNets