Modern software applications are increasingly deployed and distributed on infrastructures in the Cloud, and then offered as a service. Before the deployment process happens, these applications are being manually - or with some predefined scripts - composed from various smaller interdependent components. With the increase in demand for, and complexity of applications, the composition process becomes an arduous task often associated with errors and a suboptimal use of computer resources. To alleviate such a process, we introduce an approach that uses planning to automatically and dynamically compose applications ready for Cloud deployment. The industry may benefit from using automated planning in terms of support for product variability, sophisticated search in large spaces, fault tolerance, near-optimal deployment plans, etc. Our approach is based on Hierarchical Task Network (HTN) planning as it supports rich domain knowledge, component modularity, hierarchical representation of causality, and speed of computation. We describe a deployment using a formal component model for the Cloud, and we propose a way to define and solve an HTN planning problem from the deployment one. We employ an existing HTN planner to experimentally evaluate the feasibility of our approach.
|Title of host publication||10th IEEE International Conference on Service Oriented Computing and Applications|
|Publication status||Published - 2017|
|Event|| 10th IEEE International Conference on Service-Oriented Computing and Applications (SOCA 2017) - Kanazawa, Japan|
Duration: 22-Nov-2017 → 25-Nov-2017
|Conference||10th IEEE International Conference on Service-Oriented Computing and Applications (SOCA 2017)|
|Period||22/11/2017 → 25/11/2017|