Offload shaping for wearable cognitive assistanceVisa övriga samt affilieringar
2023 (Engelska)Ingår i: 2023 IEEE International Conference on Edge Computing and Communications (EDGE), IEEE, 2023Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]
Edge computing has much lower elasticity than cloud computing because cloudlets have much smaller physical and electrical footprints than a data center. This hurts the scalability of applications that involve low-latency edge offload. We show how this problem can be addressed by leveraging the growing sophistication and compute capability of recent wearable devices. We investigate four Wearable Cognitive Assistance applications on three wearable devices, and show that the technique of offload shaping can significantly reduce network utilization and cloudlet load without compromising accuracy or performance.
Ort, förlag, år, upplaga, sidor
IEEE, 2023.
Serie
IEEE International Conference on Edge Computing, E-ISSN 2767-9918
Nyckelord [en]
Computer Vision, Machine Learning, Offloading, Wearable Computing, Mobile Computing, Edge Computing, IoT, Cloudlet, Augmented Reality, 5G, Wi-Fi
Nationell ämneskategori
Kommunikationssystem
Forskningsämne
datalogi
Identifikatorer
URN: urn:nbn:se:umu:diva-214470DOI: 10.1109/EDGE60047.2023.00037ISBN: 979-8-3503-0484-8 (tryckt)ISBN: 979-8-3503-0483-1 (digital)OAI: oai:DiVA.org:umu-214470DiVA, id: diva2:1797878
Konferens
2023 IEEE International Conference on Edge Computing and Communications (EDGE), Hybrid via Chicago, IL, USA, July 2-8, 2023
Forskningsfinansiär
Wallenberg AI, Autonomous Systems and Software Program (WASP)2023-09-172023-09-172023-09-18Bibliografiskt granskad