Angela Ning Ye, Zhiming Hu, Caleb Phillips, Iqbal Mohomed
{"title":"AlertMe","authors":"Angela Ning Ye, Zhiming Hu, Caleb Phillips, Iqbal Mohomed","doi":"10.1145/3434770.3459740","DOIUrl":"https://doi.org/10.1145/3434770.3459740","url":null,"abstract":"Advances in deep learning have enabled brand new video analytics systems and applications. Existing systems research on real-time video event detection does not consider matching based on natural language; rather, it focuses on using Domain Specific Languages that define spatio-temporal operators on video streams for efficient matching. Alternatively, research in the multimodal AI community on joint understanding of video and language focuses on applications such as language-based video retrieval, where videos may have been processed offline. In this work, we propose AlertMe, a multimodal-based live video trigger system that matches incoming video streams to a set of user-defined natural language triggers. We dynamically select the optimal sliding window size to extract feature vectors from different modalities in near real time. We also describe our approach to achieve on-device deployment by introducing a profiler to select runtime-efficient feature extractors. Lastly, we show that limiting the number of trigger candidates can significantly increase event detection performance in applications such as task following in AR glasses.","PeriodicalId":389020,"journal":{"name":"Proceedings of the 4th International Workshop on Edge Systems, Analytics and Networking","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121657904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Berat Can Senel, Maxime Mouchet, Justin Cappos, Olivier Fourmaux, T. Friedman, R. McGeer
{"title":"EdgeNet","authors":"Berat Can Senel, Maxime Mouchet, Justin Cappos, Olivier Fourmaux, T. Friedman, R. McGeer","doi":"10.1145/3434770.3459737","DOIUrl":"https://doi.org/10.1145/3434770.3459737","url":null,"abstract":"EdgeNet is a public Kubernetes cluster dedicated to network and distributed systems research, supporting experiments that are deployed concurrently by independent groups. Its nodes are hosted by multiple institutions around the world. It represents a departure from the classic Kubernetes model, where the nodes that are available to a single tenant reside in a small number of well-interconnected data centers. The free open-source EdgeNet code extends Kubernetes to the edge, making three key contributions: multi-tenancy, geographical deployments, and single-command node installation. We show that establishing a public Kubernetes cluster over the internet, with multiple tenants and multiple hosting providers is viable. Preliminary results also indicate that the EdgeNet testbed that we run provides a satisfactory environment to run a variety of experiments with minimal network overhead.","PeriodicalId":389020,"journal":{"name":"Proceedings of the 4th International Workshop on Edge Systems, Analytics and Networking","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121151946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lianjie Cao, A. Merican, D. Z. Tootaghaj, Faraz Ahmed, P. Sharma, Vinay Saxena
{"title":"eCaaS","authors":"Lianjie Cao, A. Merican, D. Z. Tootaghaj, Faraz Ahmed, P. Sharma, Vinay Saxena","doi":"10.1145/3434770.3459741","DOIUrl":"https://doi.org/10.1145/3434770.3459741","url":null,"abstract":"Enterprises are containerizing their business applications and extending those applications from cloud to edge to achieve better flexibility, agility, and performance for their business workload. Unlike data centers, edge sites including infrastructure and orchestration systems are often heterogeneous and highly customized depending on the resource availability, business requirements of the use case, and technical requirements of the application. However, in many business use cases, the lack of IT professionals with proper domain expertise makes it very challenging to create, manage, and support heterogeneous containerized edge sites at a large scale. In this work, we present the eCaaS framework that provides automated lifecycle management of containerized edge sites and applications. With eCaaS, users can create customized edge sites with only high-level business intents which are analyzed and translated to deployment templates with low-level specifications. The edge site deployment templates are then automatically executed to build, deploy, and configure the containerized edge sites and applications. To support more customization options in the future, eCaaS decouples user intents, deployment rules, and deployment specifications and formulates deployment template generation as an SMT problem to achieve better scalability and extensibility. For creating an edge site with five nodes, eCaaS takes less than one second to generate the deployment template and less than ten minutes to complete the entire deployment.","PeriodicalId":389020,"journal":{"name":"Proceedings of the 4th International Workshop on Edge Systems, Analytics and Networking","volume":"221 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124390472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}