Simplifying Internet of Things (IoT) Data Processing Work ow Composition and Orchestration in Edge and Cloud Datacenters

Abstract

Internet of Things (IoT) allows the creation of virtually in nite connections into a global array of distributed intelligence. Identifying a suitable con guration of devices, software and infrastructures in the context of user requirements are fundamental to the success of delivering IoT applications. However, the design, development, and deployment of IoT applications are complex and complicated due to various unwarranted challenges. For instance, addressing the IoT application users' subjective and objective opinions with IoT work ow instances remains a challenge for the design of a more holistic approach. Moreover, the complexity of IoT applications increased exponentially due to the heterogeneous nature of the Edge/Cloud services, utilised to lower latency in data transformation and increase reusability. To address the composition and orchestration of IoT applications in the cloud and edge environments, this thesis presents IoT-CANE (Context Aware Recommendation System) as a high-level uni ed IoT resource con guration recommendation system which embodies a uni ed conceptual model capturing con guration, constraint and infrastructure features of Edge/Cloud together with IoT devices. Second, I present an IoT work ow composition system (IoTWC) to allow IoT users to pipeline their work ows with proposed IoT work ow activity abstract patterns. IoTWC leverages the analytic hierarchy process (AHP) to compose the multi-level IoT work ow that satis es the requirements of any IoT application. Besides, the users are be tted with recommended IoT work ow con gurations using an AHP based multi-level composition framework. The proposed IoTWC is validated on a user case study to evaluate the coverage of IoT work ow activity abstract patterns and a real-world scenario for smart buildings. Last, I propose a fault-tolerant automation deployment IoT framework which captures the IoT work ow plan from IoTWC to deploy in multi-cloud edge environment with a fault-tolerance mechanism. The e ciency and e ectiveness of the proposed fault-tolerant system are evaluated in a real-time water ooding data monitoring and management application