Dynamic service placement and replication framework to enhance service availability using team formation algorithm

The motivation of this work is to reduce the complexity in managing and administering services in the ever growing distributed environment via automated service placement and replication with team formation algorithm. The team formation algorithm is designed in a way that it would continuously search for resources with better performance and pool resources together to achieve better availability. The main intention of this work is not to replace the human administrators but to provide a better alternative in managing services in dynamic distributed environment. Instructions from the administrators are still required but at a different level. Administrators are freed from making low level decisions such as to decide the actual placement of the services and design the failover capabilities for each of the services. The evaluation results showed that the framework is capable of managing resources according to the requirements given by administrator, even during in the event of multiple consecutive resources failure. The proposed solution had the probability of 72.1% of its services that are still available after 83.3% of the available resources were shut down while conventional failover solution using three redundant units had only the probability of 40.8% of services that are still available.

► Enhance service availability via automated service placement and replication.
► A team formation algorithm and a resource evaluation technique that uses a combination of Fuzzy Logic and ANFIS (Adaptive Network Based Fuzzy Inference System) are proposed.
► ANFIS is compared against multilayer perception neural network to strengthen the design of our resource evaluation technique.
► We evaluated the framework and it shows that the automated service placement and replication can enhance service availability with minimal human intervention.