QoS-Aware Matchmaking for Adaptative Microservice-based Applications

Applications that make use of Internet of Things (IoT) capture an enormous amount of raw data from sensors and actuators, which is frequently transmitted to cloud data centres for processing and analysis. However, due to varying and unpredictable data generation rates and network latency, this can lead to a performance bottleneck. With the emergence of Fog and Edge computing hosted microservices, data processing could be moved towards the network edge. We propose a new method for continuous deployment and adaptation of multi-tier applications along edge, fog and cloud tiers by considering Quality of Service (QoS)-aware and optimal resource and non-functional requirements (e.g. operational cost, response time and latency etc.) matchmaking of application and Edge-Fog-Cloud infrastructure based on subgraph pattern matching (P-Match). The results show that the present approach improves resource utilisation and overall application Quality of Service. The approach can also be integrated into software engineering workbenches for the creation and deployment of cloud-native applications, enabling partitioning of an application across the multiple infrastructure tiers outlined above