{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T15:29:07Z","timestamp":1785511747773,"version":"3.56.0"},"publisher-location":"New York, NY, USA","reference-count":29,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,12,4]],"date-time":"2024-12-04T00:00:00Z","timestamp":1733270400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000001","name":"NSF (National Science Foundation)","doi-asserted-by":"publisher","award":["CNS-1652115"],"award-info":[{"award-number":["CNS-1652115"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"NSF (National Science Foundation)","doi-asserted-by":"publisher","award":["OAC?2029295"],"award-info":[{"award-number":["OAC?2029295"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"NSF (National Science Foundation)","doi-asserted-by":"publisher","award":["CNS-2148128"],"award-info":[{"award-number":["CNS-2148128"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"NSF (National Science Foundation)","doi-asserted-by":"publisher","award":["EEC-2133516"],"award-info":[{"award-number":["EEC-2133516"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"NSF (National Science Foundation)","doi-asserted-by":"publisher","award":["CNS?2038984"],"award-info":[{"award-number":["CNS?2038984"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000183","name":"Army Research Office","doi-asserted-by":"publisher","award":["W911NF2210031"],"award-info":[{"award-number":["W911NF2210031"]}],"id":[{"id":"10.13039\/100000183","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000183","name":"Army Research Office","doi-asserted-by":"publisher","award":["W911NF1910379"],"award-info":[{"award-number":["W911NF1910379"]}],"id":[{"id":"10.13039\/100000183","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,12,4]]},"DOI":"10.1145\/3636534.3698857","type":"proceedings-article","created":{"date-parts":[[2024,12,4]],"date-time":"2024-12-04T23:13:18Z","timestamp":1733353998000},"page":"1778-1780","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["EdgeCloudAI: Edge-Cloud Distributed Video Analytics"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0331-553X","authenticated-orcid":false,"given":"Mahshid","family":"Ghasemi","sequence":"first","affiliation":[{"name":"Electrical Engineering, Columbia University, New York City, New York, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3691-2840","authenticated-orcid":false,"given":"Zoran","family":"Kostic","sequence":"additional","affiliation":[{"name":"Columbia University, New York City, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8038-550X","authenticated-orcid":false,"given":"Javad","family":"Ghaderi","sequence":"additional","affiliation":[{"name":"Columbia University, New York City, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1845-4460","authenticated-orcid":false,"given":"Gil","family":"Zussman","sequence":"additional","affiliation":[{"name":"Columbia University, New York City, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,12,4]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Anurag Ajay, Alexander C Li, Adrien Bardes, Suzanne Petryk, Oscar Ma\u00f1as, Zhiqiu Lin, Anas Mahmoud, Bargav Jayaraman, et al.","author":"Bordes Florian","year":"2024","unstructured":"Florian Bordes, Richard Yuanzhe Pang, Anurag Ajay, Alexander C Li, Adrien Bardes, Suzanne Petryk, Oscar Ma\u00f1as, Zhiqiu Lin, Anas Mahmoud, Bargav Jayaraman, et al. 2024. An introduction to vision-language modeling. arXiv preprint arXiv:2405.17247 (2024)."},{"key":"e_1_3_2_1_2_1","volume-title":"Proc","author":"Chinchali Sandeep","unstructured":"Sandeep Chinchali, Evgenya Pergament, Manabu Nakanoya, Eyal Cidon, Edward Zhang, Dinesh Bharadia, Marco Pavone, and Sachin Katti. 2021. Sampling training data for continual learning between robots and the cloud. In Proc. Springer ISER."},{"key":"e_1_3_2_1_3_1","volume-title":"Hardware: Cameras.","author":"Project COSMOS","year":"2022","unstructured":"COSMOS Project. 2022. Hardware: Cameras. (2022). https:\/\/wiki.cosmos-lab.org\/wiki\/Hardware\/Cameras."},{"key":"e_1_3_2_1_4_1","volume-title":"Proc. MLSys.","author":"Du Kuntai","year":"2022","unstructured":"Kuntai Du, Qizheng Zhang, Anton Arapin, Haodong Wang, Zhengxu Xia, and Junchen Jiang. 2022. Accmpeg: Optimizing video encoding for accurate video analytics. In Proc. MLSys."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3662006.3662067"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(81)90024-2"},{"key":"e_1_3_2_1_7_1","volume-title":"GPT-4o: The cutting-edge advancement in multimodal LLM. Authorea Preprints","author":"Islam Raisa","year":"2024","unstructured":"Raisa Islam and Owana Marzia Moushi. 2024. GPT-4o: The cutting-edge advancement in multimodal LLM. Authorea Preprints (2024)."},{"key":"e_1_3_2_1_8_1","volume-title":"Proc. USENIX NSDI.","author":"Khani Mehrdad","year":"2023","unstructured":"Mehrdad Khani, Ganesh Ananthanarayanan, Kevin Hsieh, Junchen Jiang, Ravi Netravali, Yuanchao Shu, Mohammad Alizadeh, and Victor Bahl. 2023. RECL: Responsive resource-efficient continuous learning for video analytics. In Proc. USENIX NSDI."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3613785"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3004571"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3612585"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2005.09.031"},{"key":"e_1_3_2_1_13_1","volume-title":"Pushing large language models to the 6g edge: Vision, challenges, and opportunities. arXiv preprint arXiv:2309.16739","author":"Lin Zheng","year":"2023","unstructured":"Zheng Lin, Guanqiao Qu, Qiyuan Chen, Xianhao Chen, Zhe Chen, and Kaibin Huang. 2023. Pushing large language models to the 6g edge: Vision, challenges, and opportunities. arXiv preprint arXiv:2309.16739 (2023)."},{"key":"e_1_3_2_1_14_1","volume-title":"Visual instruction tuning. NeurIPS 36","author":"Liu Haotian","year":"2024","unstructured":"Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee. 2024. Visual instruction tuning. NeurIPS 36 (2024)."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3489517.3530474"},{"key":"e_1_3_2_1_16_1","volume-title":"Proc. IEEE ICDE.","author":"Moll Oscar","year":"2022","unstructured":"Oscar Moll, Favyen Bastani, Sam Madden, Mike Stonebraker, Vijay Gadepally, and Tim Kraska. 2022. ExSample: Efficient searches on video repositories through adaptive sampling. In Proc. IEEE ICDE."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3548249"},{"key":"e_1_3_2_1_18_1","volume-title":"Proc. IEEE\/ACM SEC.","author":"Paul Sibendu","year":"2021","unstructured":"Sibendu Paul, Utsav Drolia, Y Charlie Hu, and Srimat T Chakradhar. 2021. Aqua: Analytical quality assessment for optimizing video analytics systems. In Proc. IEEE\/ACM SEC."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3372224.3380891"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2018.05.198"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.1999.784637"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"crossref","unstructured":"Kevin Swingler and Mandy Bath. 2020. Learning spatial relations with a standard convolutional neural network. In NTCA.","DOI":"10.5220\/0010170204640470"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM41043.2020.9155524"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/DAC56929.2023.10247821"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3581791.3596870"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3613914"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00060"},{"key":"e_1_3_2_1_28_1","volume-title":"EdgeShard: Efficient LLM inference via collaborative edge computing. arXiv preprint arXiv:2405.14371","author":"Zhang Mingjin","year":"2024","unstructured":"Mingjin Zhang, Jiannong Cao, Xiaoming Shen, and Zeyang Cui. 2024. EdgeShard: Efficient LLM inference via collaborative edge computing. arXiv preprint arXiv:2405.14371 (2024)."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447993.3448628"}],"event":{"name":"ACM MobiCom '24: 30th Annual International Conference on Mobile Computing and Networking","location":"Washington D.C. DC USA","acronym":"ACM MobiCom '24","sponsor":["SIGMOBILE ACM Special Interest Group on Mobility of Systems, Users, Data and Computing"]},"container-title":["Proceedings of the 30th Annual International Conference on Mobile Computing and Networking"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3636534.3698857","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3636534.3698857","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3636534.3698857","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:10:03Z","timestamp":1750295403000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3636534.3698857"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,4]]},"references-count":29,"alternative-id":["10.1145\/3636534.3698857","10.1145\/3636534"],"URL":"https:\/\/doi.org\/10.1145\/3636534.3698857","relation":{},"subject":[],"published":{"date-parts":[[2024,12,4]]},"assertion":[{"value":"2024-12-04","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}