AL-Naday, Mays and Thomos, Nikolaos and Hu, Jiejun and Volckaert, Bruno and de Turck, Filip and Reed, Martin J (2022) Service-based, Multi-Provider, Fog Ecosystem with Joint Optimization of Request Mapping and Response Routing. IEEE Transactions on Services Computing, 16 (3). pp. 1-15. DOI https://doi.org/10.1109/tsc.2022.3211739
AL-Naday, Mays and Thomos, Nikolaos and Hu, Jiejun and Volckaert, Bruno and de Turck, Filip and Reed, Martin J (2022) Service-based, Multi-Provider, Fog Ecosystem with Joint Optimization of Request Mapping and Response Routing. IEEE Transactions on Services Computing, 16 (3). pp. 1-15. DOI https://doi.org/10.1109/tsc.2022.3211739
AL-Naday, Mays and Thomos, Nikolaos and Hu, Jiejun and Volckaert, Bruno and de Turck, Filip and Reed, Martin J (2022) Service-based, Multi-Provider, Fog Ecosystem with Joint Optimization of Request Mapping and Response Routing. IEEE Transactions on Services Computing, 16 (3). pp. 1-15. DOI https://doi.org/10.1109/tsc.2022.3211739
Abstract
Digital transformation is increasingly reliant on service -based operations in fog networks. The latter is a geo-dispersed form of the cloud, extending resources closer to end-users for improved privacy and reduced latency. The dispersion leverages diversity of compute-network capacities and energy prices, while promotes the coexistence of multiple providers. This drives variation in operational cost, coupled with limited information sharing across providers. Consequently, there is a critical need for an orchestration solution that preserves autonomy and optimizes operational cost across domains, while meeting service requirements. This paper proposes a novel service-based fog management and network orchestrator (sbMANO), which utilizes service metadata in enabling multi-provider resource management. The sbMANO is empowered with a novel optimization algorithm for service-based joint request mapping and response routing. The algorithm acts on partial information and preserves the edge for delay-critical services. The performance of the algorithm is evaluated analytically for delay-aware and delay-agnostic variants. The results show that both achieve near-optimal performance in maximizing user satisfaction with minimum operational cost. Furthermore, the delay-aware variant outperforms the agnostic counterpart, with higher user satisfaction and lower operational cost.
Item Type: | Article |
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Uncontrolled Keywords: | Fog computing networks; service-based networking; joint optimization; request mapping; response routing; service management |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 06 Dec 2022 11:19 |
Last Modified: | 30 Oct 2024 19:15 |
URI: | http://repository.essex.ac.uk/id/eprint/33660 |
Available files
Filename: service_based_fog-1.pdf