Resource Optimisation in IoT Cloud Systems by Using Matchmaking and Self-management Principles

Abstract

IoT Cloud systems provide scalable capacity and dynamic behaviour control of virtual infrastructures for running applications, services and processes. Key aspects in this type of complex systems are the resource optimisation and the performance of dynamic management based on distributed user data metrics and/or IoT application data demands and/or resource utilisation metrics. In this paper we particularly focus on Cloud management perspective – integrating IoT Cloud service data management - based on annotated data of monitored Cloud performance and user profiles (matchmaking) and enabling management systems to use shared infrastructures and resources to enable efficient deployment of IoT services and applications. We illustrate a Cloud service management approach based on matchmaking operations and self-management principles which enable improved distribution and management of IoT services across different Cloud vendors and use the results from the analysis as mechanism to control applications and services deployment in Cloud systems. For our IoT Cloud data management solution we utilize performance metrics expressed with linked data in order to integrate monitored performance data and end user profile information (via linked data relations).