With the explosive growth of smart devices and the advent of many new applications, mobile traffic volume has been growing exponentially. The conventional access network architecture cannot accommodate such demands due to limited capacity and long latency on the backhaul links. Moreover, the myriad technological advances proposed for the future 5G networks still mostly focus on capacity increase, which is fundamentally constrained by the limited radio spectrum resources as well as the diminishing investment efficiency for operators and, therefore, will always lag behind the growth rate of mobile traffic. Therefore, novel distributed architectures, which bring network functions (such as computing, caching and sharing) and contents to the network edge, i.e., mobile edge computing and caching, emerges to confront the aforementioned challenges in the networks development and many emerging applications, such as AR/VR, IoT, eHealth, autonomous driving, gaming etc.
However, on the way towards efficient and intelligent network edge computing and caching architectures, there are many open problems ahead. From the computing point-of-view, how to flexibly utilize the distributed computing resources at the network edge, such as mobile computing or fog computing, to cope with the resource-intensive applications, and user mobility, is of significance. Moreover, what to be offloaded to the edge node and when to offload also call for research attentions. From the caching perspective, what, when, where and how to cache the popular content to reduce the demand for radio resources are vital. Last but not the most, how to efficiently integrate computing and caching at the edge node and utilize the synergy of computing and caching also requires a breakthrough.
The ultimate goal of this workshop is to a provide a forum where researches from these topics can meet and find synergy, leading to discovering best practices for a future intelligent wireless network. In terms of excellence, this workshop will attract submissions from a wide range of world-leading as the topic is within a hot area, and bridges several other active areas such as: information-centric networks, network optimization, big data, cloud/fog computing and IoT. Therefore, we expect to see a high volume of high quality submissions. Furthermore, the chairs and committee members have excellent academic track-records and have extensive networks that can be exploited to increase publicity of the workshop and extend its long-term impact.
Topics of Interest
This workshop aims to consolidate the timely and solid works of the current state-of-the art in terms of fundamental research ideas and network engineering geared towards exploiting intelligent caching and computing at the network edge. The topic of interest related to edge caching and computing include (but are not limited to):
- System modelling: Computation modelling, caching modelling, energy consumption modelling etc.;
- Enabling technologies: e.g., SDN, NFV, CRAN, D2D, cloud/fog computing and networking, etc.;
- Application areas: vehicular networking, IoT, smart grid etc;
- Novel network architecture: convergence of computing, communications and caching, content/information-centric network, cognitive computing and networking, big data analytic;
- Context-aware schemes: incentive mechanism for computing and caching, pricing, game theoretic approach, network economic etc, caching placement and delivery;
- Mobility management for mobile edge computing and proactive caching; Energy efficiency aspects: energy harvesting, energy storage, energy transfer, etc;
- Security and privacy issue;
- Prototyping, test-beds and field trials.
- Meixia Tao, Shanghai Jiao Tong Univeristy, Shanghai, China
- Seppo Yrjola, Nokia
Paper Submission Deadline
November 2, 2017 extended November 12, 2017
Notification of Acceptance
December 15, 2017
January 21, 2018
Shiwen Mao, Auburn University, U.S, email@example.com
Matti Latva-Aho , University of Oulu, Finland, firstname.lastname@example.org
Sheng Zhou, Tsinghua University, China, email@example.com
Zheng Chang, University of Jyvaskyla, Finland, firstname.lastname@example.org
Yu Cheng, Illinois Institute of Technology, U.S., email@example.com
Jie Gong, Sun Yat-Sen University, China, firstname.lastname@example.org
Jie Xu, University of Miami, U.S., email@example.com