Keynote 2: Resource Management in Edge Computing: Opportunities and Open Issues Recent technological trends such asIndustry 4.0 introduced new challenges that push the limit of current com puter and networking architectures. It demands the connection of thousands, if not millions, of sensors and mobile devices coupled with optimized operations to automate various operations inside factories. This led to the new era of Internet of Things (IoTs) where lightweight (possibly mobile) devices are envisaged to send vital information to cloud data centres (mobile and fixed infras tructure) for further processing and decision making. Current cloud computing systems, however, are not able to efficiently digest and process collected information from IoT devices with strict response requests for two main reasons: (1) the round trip delay between IoT devices to the processing engines of cloud could exceed an applicationxe2x80x99s threshold, and (2) network links to cloud resources could be clogged when IoT devices flush data in an uncoordinated fashion. Fog and Edge Computing are two solutions to address both of the previous problems. Though designed to alleviate the same problem, they have fundamental differences that make adopting one more applicable than the other. This talk will overview the practical concerns of exploiting Edge Computing to realize todayxe2x80x99s IoT implementations through tackling the most important obstacles that hinder their adoption. First, production of applicable network (fixed and mobile) latency models to capture all elements of IoT platforms. Second, building a holistic Edge ecosystem to orchestrate various interrelated layers of IoT platforms, including connectivity, bigdata analytics, and workload optimization. Third, proposing viable solutions that can be actually implemented in IoTbased applications. More details will be provided about the above issues during the talk.

Edge Computing Platform Management: Design for F2C and F2F for Small Businesses to Reduce Costs With a focus on edge computing and the cloud, IoT and connected devices require both edge computing platform management for realtime decisions and cloud computing for optimization. From a businessu0027s perspective, this requires further investments in keeping devices updated. Big players in edge computing have proposed new devices and concepts for industries, resulting in the likelihood of increasingly expensive devices going forward. However, small businesses and factories cannot afford such investments. Thus, this paper proposes a simple and lowcost implementation of an edge computing platform for small businesses to automate their business in real time. Furthermore, having the perspective of historical performance enables realtime optimization of the entire business process.