About the Workshop:

The rapid proliferation of information and communication technologies in almost every sphere of our life has led to a strong diffusion of wireless personal devices (including but not limited to, smartphones, personal computers, tablets, wearable devices, and even smart vehicles), consumer electronic devices and appliances, healthcare monitoring devices, and an unprecedented range of interconnected sensors embedded within these or similar devices, as an indispensable part of the Internet environment. These devices, also referred to as ‘things’, are designed to be largely interconnected in one form or the other and specifically maintain a seamless connectivity across the Internet thus strengthening the emerging yet promising paradigm of the Internet-of-Things (IoT), whose multibillion global market is anticipated to triple in value by the end of year 2020.

This seamless and pervasive sensing and computing generates a massive amount (terabytes, petabytes, exabytes, or even zettabytes) of structured, unstructured, and semi-structured data that requires highly efficacious decentralized approaches of both compute and storage for data accumulation, its adequate processing, in-depth analytics, and knowledge generation with a minimal possible delay. Rendering it to the remote clouds could be beneficial for compute and storage purposes, however, transmitting a considerable amount of data analytics from remote clouds is not only infeasible and uneconomical but also incurs significant delays which cannot meet the stringent latency requirements of a diverse range of critical applications. This has thus called for bringing intelligence near-to-the-edge, a notion referred to as, Edge Computing, which has the ability to ensure that the stringent Quality-of-Service and Quality-of-Experience related performance guarantees of diverse sort of networking applications and services are fully met.

Topics of Interest:

Topics of interest ranges from, but are not limited to:

• Edge computing enabled future networking architectures and models;
• Localized clouds and fog computing;
• Integrating software-defined networking and information-centric networking with edge computing and caching schemes;
• Security and privacy of edge computing and caching mechanisms;
• Autonomic self-healing networks;
• QoS provisioning and efficacious network resource management;
• 5G end-to-end latency optimization for edge-based critical applications and services;
• Edge computing for next-generation Intelligent Transportation Systems;
• Light-weight and distributed machine learning frameworks/algorithms for edge computing;
• Edge analytics; and
• Prototyping, testbeds, and field trials.

Program Committee:

• Soo Young Shin, Kumoh National Institute of Technology, South Korea
• Yang Xinghai, University of Jinan, Peoples Republic of China
• Hushairi Zen, Universiti Malaysia Sarawak, Malaysia
• Bernard Butler, Waterford Institute of Technology, Republic of Ireland
• Qiaomin Lin, Nanjing University of Posts and Telecommunications, People's Republic of China
• Zhizhong Liu, Henan Polytechnic University, People's Republic of China
• Yanjun Shu, Harbin Institute of Technology, People's Republic of China
• Hai Dong, RMIT University, Australia
• Yongrui Qin, University of Huddersfield, United Kingdom
• Amin Beheshti, Macquarie University, Australia
• Qiang He, Swinburne University of Technology, Australia
• Talal H. Noor, Taibah University, Saudi Arabia

Submission Guidelines:

Papers should be submitted in PDF format. The results described must be unpublished and must not be under review elsewhere. Submissions must conform to Springer's LNCS format and should not exceed 15 pages, including all text, figures, references and appendices. Submissions not conforming to the LNCS format, exceeding 15 pages, or obviously out of the scope of the workshop, will be rejected without review. Information about the Springer LNCS format can be found @ http://www.springer.de/comp/lncs/authors.html. Three to five keywords characterizing the paper should be indicated at the end of the abstract. The type of paper (technical/empirical evaluation/experience/exploratory paper) should be indicated in the submission.