Serverless edge systems simplify the deployment of real-time AI-based Internet of Things (IoT) applications at the edge. However, the heterogeneity of edge computing nodes–in …
M Daraghmeh, A Agarwal, Y Jararweh - Simulation Modelling Practice and …, 2024 - Elsevier
In the rapidly evolving domain of serverless computing, the need for efficient and accurate predictive methods of function invocation becomes paramount. This study introduces a …
In recent years, more and more devices are connected to the network, generating an overwhelming amount of data. This term that is booming today is known as the Internet of …
J Hao, P Subedi, L Ramaswamy, IK Kim - ACM Transactions on Internet …, 2023 - dl.acm.org
The wide adoption of smart devices and Internet-of-Things (IoT) sensors has led to massive growth in data generation at the edge of the Internet over the past decade. Intelligent real …
Continuum Computing encompasses the integration of diverse infrastructures, including cloud, edge, and fog, to facilitate seamless migration of applications based on their specific …
V Kulkarni, N Reddy, T Khare, H Mohan… - 2024 IEEE 24th …, 2024 - ieeexplore.ieee.org
Functions-as-a-Service (FaaS) is a widely used serverless computing abstraction that helps developers build applications using event-driven, stateless functions that execute on the …
K Luo, T Ouyang, Z Zhou, X Chen - Journal of Systems Architecture, 2023 - Elsevier
Serverless computing has gained popularity in edge computing due to its flexible features, including the pay-per-use pricing model, auto-scaling capabilities, and multi-tenancy …
Q Yang, R Jin, N Gandhi, X Ge, HA Khouzani… - Future of Information …, 2024 - Springer
Edge computing has been developed to utilize heterogeneous computing resources from different physical locations for privacy, cost, and Quality of Service (QoS) reasons. Edge …
RD Rachmanto, Z Sukma… - … Conference on Edge …, 2024 - ieeexplore.ieee.org
Edge AI has increasingly been adopted due to the rapid development of deep learning and AI. At the same time, as AI models quickly grow in size and complexity, resource-constrained …