A5066451107- IoT and Edge/Fog Computing
- Caching and Content Delivery
- Cloud Computing and Resource Management
- Peer-to-Peer Network Technologies
- Context-Aware Activity Recognition Systems
- Anomaly Detection Techniques and Applications
- Distributed and Parallel Computing Systems
- IoT Networks and Protocols
- Wireless Communication Networks Research
- Age of Information Optimization
- Advanced Wireless Communication Techniques
- Cooperative Communication and Network Coding
- Energy Efficient Wireless Sensor Networks
- Opportunistic and Delay-Tolerant Networks
- Smart Grid Security and Resilience
Institut national de recherche en informatique et en automatique
2020-2022
Institut de Recherche en Informatique et Systèmes Aléatoires
2018-2022
Université de Rennes
2020-2022
Centre National de la Recherche Scientifique
2020-2022
ACTeon Environment (France)
2022
Laboratoire d'Informatique de Grenoble
2017
Verimag
2017
Université Grenoble Alpes
2017
Fog computing was designed to support the specific needs of latency-critical applications such as augmented reality, and IoT which produce massive volumes data that are impractical send faraway cloud centers for analysis. However this also created new opportunities a wider range in turn impose their own requirements on future fog platforms. This article presents study representative set 30 general-purpose platform should support.
Container orchestration engines such as Kubernetes do not take into account the geographical location of application replicas when deciding which replica should handle request. This makes them ill-suited to act a general-purpose fog computing platforms where proximity between end users and serving is essential. We present proxy-mity, proximity-aware traffic routing system for distributed platforms. It seamlessly integrates in Kubernetes, provides very simple control mechanisms allow...
Latency-sensitive fog computing applications may use replication both to scale their capacity and place application instances as close possible end users. In such geo-distributed environments, a good replica placement should maintain the tail network latency between end-user devices closest within acceptable bounds while avoiding overloaded replicas. When facing non-stationary workloads it is essential dynamically adjust number locations of application's We propose Voilà, tail-Iatency-aware...
Deciding where to handle services and tasks, as well provisioning an adequate amount of computing resources for this handling, is a main challenge edge systems. Moreover, latency-sensitive constrain the type location devices that can provide needed resources. When available are scarce there possibility some resource allocation requests denied. In work, we propose VioLinn system tackle joint problems task placement, service device provisioning. Dealing with achieved through proximity-aware...
The IEEE802.15.4e standard for low power wireless sensor networks defines a new mode called Time Slotted Channel Hopping (TSCH) as Medium Access Control (MAC). TSCH allows highly efficient deterministic time-frequency schedules that are built and maintained by the 6TiSCH operation sublayer (6top). In this paper, we propose solution to limit allocation of identical cells co-located pair nodes distributed scheduling algorithms. It consists making able overhear past cell negotiations exchanged...