Understand the challenges and potentials of serverless computing for realtime networked multimedia
Understand the challenges and potentials of serverless computing for realtime networked multimedia
批准号:
543280-2019
负责人:
Liu, Jiangchuan
金额:
$1.82万
依托单位:
依托单位国家:
加拿大
项目类别:
Engage Grants Program
财政年份:
2019
资助国家:
加拿大
项目状态:
已结题
起止时间:
2019-01-01 至 2020-12-31
中文摘要
Frozen Mountain Software是一家加拿大软件公司,总部位于不列颠哥伦比亚省萨里,为基于互联网的实时通信需求提供先进的解决方案。云计算在支持Frozen Mountain的服务方面发挥着至关重要的作用,这些服务可以处理扩展到非常大量的同时用户。受流行的基础设施即服务(IaaS)云的运营和定价模式的约束,用户不可避免地需要自行预留和管理云资源并为空闲的服务器时间付费。此外,这些重量级云服务器实例无法灵活地扩展或缩小以满足工作负载。无服务器计算作为一种新的执行模式正在兴起,以克服传统云计算模式的弱点。在这个项目中,一个由SFU和Frozen Mountain的研究人员和工程师组成的多学科团队将共同研究将无服务器计算应用于网络多媒体服务的潜力和挑战。我们将对领先的无服务器计算平台进行广泛的测量,并量化功能资源分配的影响(例如,内存大小)、功能实现方案(例如,调用外部API),分配的工作负载(例如,帧的数量)以及典型的网络化多媒体应用上的平台选择。然后,我们将开始开发新的解决方案,将无服务器计算集成到Frozen Mountain的产品中。
英文摘要
Frozen Mountain Software, a Canadian software company based on Surrey, BC, provides advanced solutions for Internet-based realtime communication needs. Cloud computing plays an essential role in supporting Frozen Moutain's services, which handle scaling to extremely large numbers of simultaneous users. Constrained by the operation and pricing model of the prevalent Infrastructure as a Service (IaaS) cloud, users inevitably need to reserve and manage cloud resources by themselves and pay for the idle server time. Further, these heavy-weight cloud server instances cannot scale up or down flexibly to meet the workloads. As a new execution model, serverless computing is emerging to overcome the weaknesses of traditional cloud computing models. It offloads the tasks of server provisioning and management from developers to platforms, and charges users at a finer-grained timescale, achieving the long-promised "pay-as-you-go" pricing strategy.In this project, a multi-disciplinary team involving researchers and engineers from both SFU and Frozen Mountain will work together to understand the potentials and challenges on applying serverless computing for networked multimedia services. We will conduct extensive measurements on leading serverless computing platforms and quantify the impact of function resource allocation (e.g., memory size), function implementation schemes (e.g., calling external APIs), allocated workload (e.g., the number of frames), and platform selection on typical networked multimedia applications. We will then start to develop novel solutions that integrate serverless computing into Frozen Mountain's products.
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会议论文
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