Design of Scenario-based Application-optimized Data Replication Strategies through Genetic Programming
Syed Mohtashim Abbas Bokhari, Oliver Theel · 2020
A distributed system is a paradigm, which is indispensable to the current world due to countless requests with every passing second. Therefore, in distributed computing, high availability is very important. Since failures are often inevitable in a distributed paradigm, it greatly affects the availability of services. Replication plays a role in mitigating such failures by masking them to achieve a fault-tolerant distributed environment, thereby eliminating the hindrances in the availability of the data. In this regard, this research focuses on sophisticated modeling, analysis, and machine learning approaches, particularly, genetic programming to automatically identify and design new data replication strategies that are innovative. This dissertation proposes a genetic programming-based multi-objective optimization approach that offers competitive results w.r.t. the contemporary strategies as well as generating novel strategies even with a slight use of relevant genetic operators.