Cloud Ready Applications Composed via HTN Planning

Ilche Georgievski, Faris Nizamic, Alexander Lazovik, Marco Aiello
2017 2017 IEEE 10th Conference on Service-Oriented Computing and Applications (SOCA)  
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
more » ... e 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. Proposed solution As a necessary direction to automate the composition of Cloud applications ready for deployment, it appears natural to resort to automated planning [5] . Planning provides powerful methods for searching in large and complex Cloud infrastructures to find "good" compositions of Cloud ready applications. Applications are composed dynamically, thus services need not to be fixed in advance in scripts and always available (the same holds for the servers of the Cloud). Additionally,
doi:10.1109/soca.2017.19 dblp:conf/soca/GeorgievskiNL017 fatcat:2bbaqrlycnhr3nwqzmbfrxgotq