@article {43337,
	title = {Opportunistic CPU sharing in Mobile Edge Computing deploying the Cloud-RAN},
	journal = {IEEE Transactions on Network and Service Management},
	year = {2023},
	publisher = { IEEE},
	keywords = {Cloud-RAN, Containers, Mobile edge computing, resource management},
	doi = {10.1109/TNSM.2023.3304067},
	author = {Andres Felipe Oca {Palacio} and Mah Rukh {Fida} and Juan Felipe Bot {Vega} and Elmokashfi, Ahmed and Bryhni, Haakon}
}
@inproceedings { SEAA2023,
	title = {Towards A Data Privacy-Aware Execution Zone Creation on Cloud/Fog Platform},
	journal = {Proceedings of the 49th Euromicro Conference Series on Software Engineering and Advanced Applications (SEAA)},
	year = {2023},
	publisher = { IEEE},
	address = {Durr{\"e}s/Albania},
	abstract = {Cloud computing is now a {\textquoteleft}go-to{\textquoteright} platform for running various types of application. A wide spectrum of users needing software and hardware resources have embraced the cloud. Following the cloud business model, one is either a cloud-based service provider or a cloud service (hardware and software) user. There is a continuous evolution in the cloud ecosystem to support the ever-changing features of user applications. The cloud ecosystem has added a new resource delegation model to accommodate such new requirements. This new resource delegation model is known as fog. Both cloud and fog platforms employ complex hardware and software to provide better run-time support for applications. This paper presents a message-based privacy-aware application execution zone management framework for the cloud/fog platform. The framework aims to create a static execution zone based on the performance of the user application and the data privacy requirements. It also enables the user to set the resource termination conditions. Here, we have prototyped the proposed framework and showed how the proposed approach works with message structure and experiments with the P4 switch. We also present how the prototype could be implemented on a cloud/fog platform.},
	keywords = {Cloud, Data, Fog, Message, Privacy, resource management},
	author = {Mazumdar, Somnath and Dreibholz, Thomas}
}
@article {23618,
	title = {Decentralized and Optimal Resource Cooperation in Geo-distributed Mobile Cloud Computing},
	journal = {IEEE Transactions on Emerging Topics in Computing},
	year = {2015},
	publisher = {IEEE Transactions on Emerging Topics in Computing},
	abstract = {Mobile cloud computing is a key enabling technology in the era of Internet-of-Things. Geo-distributed mobile cloud computing (GMCC) is a new scenario that adds geography consideration in mobile cloud computing. In GMCC, users are able to access cloud resource that are geographically close to their mobile devices. This is expected to reduce communications delay and service providers\&rsquo; cost compared to the traditional centralized approach. In this paper, we focus on resource sharing through cooperation among service providers in geo-distributed mobile cloud computing. Then, we propose two different strategies for efficient resource cooperation in geographically distributed data centers. Further, we present a coalition game theoretical approach to deal with the competition and cooperation among service providers. Utility functions have been specifically considered to incorporate the cost related to virtual machine migration and resource utilization. Illustrative results indicate that our proposed schemes are able to efficiently utilize limited resource with Quality-of-Service (QoS) consideration.},
	keywords = {cooperation, game theory, Mobile cloud computing, resource management},
	author = {Yu, R. and Ding, J. and Maharjan, Sabita and Gjessing, Stein and Zhang, Yan and Tsang, Danny}
}
