Proceedings of the 4th Workshop on Middleware for Edge Clouds & Cloudlets最新文献

Tango of edge and cloud execution for reliability Tango的边缘和云执行的可靠性

Proceedings of the 4th Workshop on Middleware for Edge Clouds & Cloudlets Pub Date : 2019-12-09 DOI: 10.1145/3366614.3368103

Shikhar Suryavansh, Chandan Bothra, M. Chiang, Chunyi Peng, S. Bagchi

{"title":"Tango of edge and cloud execution for reliability","authors":"Shikhar Suryavansh, Chandan Bothra, M. Chiang, Chunyi Peng, S. Bagchi","doi":"10.1145/3366614.3368103","DOIUrl":"https://doi.org/10.1145/3366614.3368103","url":null,"abstract":"The increasing cost of cloud services and the need for decentralization of servers has led to a rise of interest in Edge computing. Edge computing brings the servers closer to the end users which helps in reducing network latency. However, the presence of multiple edge servers adversely affects the reliability due to difficulty in maintenance of heterogeneous servers. This paper aims at evaluating the performance of various server configuration models in edge computing using EdgeCloudSim, a popular simulator for edge computing. The performance is evaluated in terms of service time and percentage of failed tasks for an Augmented Reality application. We evaluated the performance of the following edge computing models, Exclusive: Mobile only, Edge only, Cloud only; and Hybrid: Edge & Cloud hybrid with load-balancing on the Edge, and Mobile & Edge hybrid. We analyzed the impact of variation of different parameters such as WAN bandwidth, cost of cloud resources, heterogeneity of edge servers, etc., on the performance of the edge computing models. We show that due to variation in the above parameters, the exclusive models are not sufficient for computational requirements and there is a need for hybrid edge computing models.","PeriodicalId":395022,"journal":{"name":"Proceedings of the 4th Workshop on Middleware for Edge Clouds & Cloudlets","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129650519","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}

引用次数: 11

Towards distributed, fair, deadline-driven resource allocation for cloudlets 为cloudlets实现分布式、公平、截止日期驱动的资源分配

Proceedings of the 4th Workshop on Middleware for Edge Clouds & Cloudlets Pub Date : 2019-12-09 DOI: 10.1145/3366614.3368102

Stratos Dimopoulos, C. Krintz, R. Wolski

引用次数: 2

Container deployment strategy for edge networking 边缘网络的容器部署策略

Proceedings of the 4th Workshop on Middleware for Edge Clouds & Cloudlets Pub Date : 2019-12-09 DOI: 10.1145/3366614.3368101

Walter Wong, Aleksandr Zavodovski, Pengyuan Zhou, J. Kangasharju

{"title":"Container deployment strategy for edge networking","authors":"Walter Wong, Aleksandr Zavodovski, Pengyuan Zhou, J. Kangasharju","doi":"10.1145/3366614.3368101","DOIUrl":"https://doi.org/10.1145/3366614.3368101","url":null,"abstract":"Edge computing paradigm has been proposed to support latency-sensitive applications such as Augmented Reality (AR)/ Virtual Reality(VR) and online gaming, by placing computing resources close to where they are most demanded, at the edge of the network. Many solutions have proposed to deploy virtual resources as close as possible to the consumers using virtual machines and containers. However, the most popular container orchestration tools, e.g., Docker Swarm and Kubernetes, do not take into account the locality aspect during deployment, resulting in poor location choices at the edge of the network. In this paper, we propose an edge deployment strategy to tackle the lack of locality awareness of the container orchestrator. In this strategy, the orchestrator collects information about latency and the real-time resource consumption from the current container deployments, providing a bird's-eye view of the most demanded locations and the best places for deployment to cover the largest number of clients. We evaluated the proposed model using 16 AWS regions across the globe and compared to the standard deployment strategies. The experimental results show our edge strategy reduces the average latency between serving container to the clients by up to 4 times compared to the standard deployment algorithms.","PeriodicalId":395022,"journal":{"name":"Proceedings of the 4th Workshop on Middleware for Edge Clouds & Cloudlets","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124986796","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}

引用次数: 11

Proceedings of the 4th Workshop on Middleware for Edge Clouds & Cloudlets 第四届边缘云和Cloudlets中间件研讨会论文集

Proceedings of the 4th Workshop on Middleware for Edge Clouds & Cloudlets Pub Date : 1900-01-01 DOI: 10.1145/3366614

引用次数: 0