Tranad: Deep transformer networks for anomaly detection in multivariate time series data
Efficient anomaly detection and diagnosis in multivariate time-series data is of great
importance for modern industrial applications. However, building a system that is able to …
importance for modern industrial applications. However, building a system that is able to …
[HTML][HTML] AI augmented Edge and Fog computing: Trends and challenges
In recent years, the landscape of computing paradigms has witnessed a gradual yet
remarkable shift from monolithic computing to distributed and decentralized paradigms such …
remarkable shift from monolithic computing to distributed and decentralized paradigms such …
Management and orchestration of edge computing for IoT: A comprehensive survey
With the development of telecommunication technologies and the proliferation of network
applications in the past decades, the traditional cloud network architecture becomes unable …
applications in the past decades, the traditional cloud network architecture becomes unable …
[HTML][HTML] Causalrca: Causal inference based precise fine-grained root cause localization for microservice applications
Effectively localizing root causes of performance anomalies is crucial to enabling the rapid
recovery and loss mitigation of microservice applications in the cloud. Depending on the …
recovery and loss mitigation of microservice applications in the cloud. Depending on the …
GOSH: Task scheduling using deep surrogate models in fog computing environments
Recently, intelligent scheduling approaches using surrogate models have been proposed to
efficiently allocate volatile tasks in heterogeneous fog environments. Advances like …
efficiently allocate volatile tasks in heterogeneous fog environments. Advances like …
MCDS: AI augmented workflow scheduling in mobile edge cloud computing systems
Workflow scheduling is a long-studied problem in parallel and distributed computing (PDC),
aiming to efficiently utilize compute resources to meet user's service requirements. Recently …
aiming to efficiently utilize compute resources to meet user's service requirements. Recently …
DRAGON: Decentralized fault tolerance in edge federations
Edge Federation is a new computing paradigm that seamlessly interconnects the resources
of multiple edge service providers. A key challenge in such systems is the deployment of …
of multiple edge service providers. A key challenge in such systems is the deployment of …
Maat: Performance metric anomaly anticipation for cloud services with conditional diffusion
Ensuring the reliability and user satisfaction of cloud services necessitates prompt anomaly
detection followed by diagnosis. Existing techniques for anomaly detection focus solely on …
detection followed by diagnosis. Existing techniques for anomaly detection focus solely on …
[HTML][HTML] Load balancing for heterogeneous serverless edge computing: A performance-driven and empirical approach
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 …
(IoT) applications at the edge. However, the heterogeneity of edge computing nodes–in …
Efficient fault-tolerant consensus for collaborative services in edge computing
In many edge computing applications, edge devices are required to reach fault-tolerant
consensus in order to provide collaborative services in outdoor environments. In this paper …
consensus in order to provide collaborative services in outdoor environments. In this paper …