Long-term IaaS Cloud Selection using Performance Discovery

Sheik Mohammad Mostakim Fattah and Athman Bouguettaya.

Our objective is to design a novel framework that selects and composes IaaS cloud services for a long-term period. IaaS providers usually reveal limited information about their performance which makes the optimal selection and composition very challenging. The proposed framework introduces novel performance discovery approaches to select and compose IaaS cloud services considering a consumer’s long-term performance requirements.

Publications

– Conferences:

1. IaaS Signature Change Detection with Performance Noise. Sheik Mohammad Mostakim Fattah, and Athman Bouguettaya. ICSOC 2021, Virtual.
2. Event-based Detection of Changes in IaaS Performance Signatures. Sheik Mohammad Mostakim Fattah, and Athman Bouguettaya. SCC 2020, Beijing, China.
3. Signature-based Selection of IaaS Cloud Services. Sheik Mohammad Mostakim Fattah, Athman Bouguettaya, and Sajib Mistry. ICWS 2020, Beijing, China.
4. Long-Term IaaS Provider Selection Using Short-Term Trial Experience. Sheik Mohammad Mostakim Fattah, Athman Bouguettaya, and Sajib Mistry. ICWS 2019: Milan, Italy.
5. A CP-Net Based Qualitative Composition Approach for an IaaS Provider. Sheik Mohammad Mostakim Fattah, Athman Bouguettaya, and Sajib Mistry. WISE 2018, Dubai, United Arab Emirates.

– Journals:

1. Sequential Learning-based IaaS Composition. Sajib Mistry, Sheik Mohammad Mostakim Fattah, and Athman Bouguettaya. ACM Transactions on the Web (2021).
2. Long-term IaaS Selection using Performance Discovery. Sheik Mohammad Mostakim Fattah, Athman Bouguettaya, and Sajib Mistry. IEEE Transactions on Services Computing (2020).