Edge-Cloud Computing for Internet of Things Data Analytics

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The number of connected devices is growing at an unprecedented rate, creating an explosion of Internet of Things (IoT) data that are moving among devices, storage, and processing locations. Data from sensors are typically transferred to the cloud for storage and analysis and then delivered to various software applications. For example, data from a smart home are transferred to a data centre possibly thousands of miles away and then back again for display on devices within the home. With data centre traffic already measured in zettabytes, attempting to transfer all IoT data to the cloud will strain communication networks and increase cost. Moreover, real-time systems, which are common in safety critical applications, cannot tolerate latencies caused by transfer to the cloud.*******To address these IoT challenges, the proposed research program will combine edge and cloud computing. Whereas cloud computing transfers data to the computing location, edge computing brings computation closer to the network edge where data are generated. Here, the term edge encompasses measuring devices (e.g., sensors, smart phones) and fog nodes, the resources close to data sources (e.g., gateways, local servers). Edge-cloud approaches will decrease network traffic and latencies, improve user experience, enable off-line operation, and reduce exposure to cloud-related security risks.*******The long term objective of this research program is to advance the field of IoT data analytics by extending it to edge computing. The short-term objectives include:****1. Enabling Edge-Cloud IoT Data Analytics for Smart Cities will initiate work on edge-cloud analytics by adopting edge computing for specific smart city use cases such as energy management and sustainable buildings.****2. Designing Resource Management Models to allocate and manage computation across diverse nodes of the edge-cloud environment to minimize response time and/or network traffic.****3. Enabling IoT Interoperability to integrate data from diverse IoT devices and non-IoT data in support of novel data analytics methods and new software applications through edge computing.****4. Designing IoT Edge-Cloud Data Management Methods that will distribute data storage over edge and cloud nodes to reduce network traffic and response time by storing or replicating data close to where they are produced (edge) or consumed (edge or cloud).*******The proposed research will enable new IoT applications and services that are currently not possible due to latencies or costs associated with data transfer to the cloud. Software applications will benefit through improved quality of service, ability to offload computation to nearby devices, and increased location awareness. Companies using IoT analytics will benefit through process optimization, insights discovery, and improved decision-making. This research program will contribute to Canadian leadership in this rapidly growing field.***