Distributed Serverless Computing in Cloud-Edge Environments

云边缘环境中的分布式无服务器计算

• 批准号: 2606813
• 金额: --
• 依托单位: Queen's University Belfast
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2606813
• 关键词: Distributed; Serverless; Computing; Cloud; Edge

Considered as the next evolution in Cloud computing, the 'Serverless' computing paradigm facilitates on-demand computation without an end-user provisioning a server. The 'Serverless' paradigm is realised using a Functions-as-a-Service (FaaS) model in which Cloud providers monetise usage by charging per function invocation or function duration. FaaS differs from conventional Cloud models as end-users only pay for the resources they consume as opposed to paying for the resources they allocate (even when these resources are idle). Although 'Serverless' is known for its Cloud impact, there are numerous benefits of FaaS that could benefit the Edge. Edge Internet of Things (IoT) applications are often distributed and resource-constrained, as such, 'Serverless' function initialisation and execution of code provide a model of computation that minimises resource and energy consumption. This project has three aims and objectives that map to one year of study each with the intent to publish findings. The three objectives will form the basis for the final thesis in the third year. The first objective is to develop a 'Serverless' Edge platform that is reactive to Edge IoT application demand. In particular, it will investigate methods of providing real-time responsiveness to the varied workloads that Edge IoT deployments present. Main areas of research include trend analysis of Edge workloads, intelligent provisioning and scheduling of Edge node resources, and networking/routing capabilities of a 'Serverless' Edge platform. The second is investigating reducing latency for Edge Machine Learning inference on heterogeneous Edge nodes. This objective involves mapping 'Serverless' principles to an Edge context where inference latency should be consistent for all Edge nodes in the network. The third is developing sufficient and performative security for 'Serverless' execution on the Edge where hardware is shared and resources are constrained. The project research methodology involves continued study and review of related literature in Edge and 'Serverless' computing. Profiling and benchmarking of 'Serverless' methods including gathering quantitative data such as latency, memory and energy consumption, and volume throughput under various workloads. Analysis and identification of current challenges in existing research and use cases. Creation of computation testbeds for synthetic data generation and development of 'Serverless' Edge systems. Development of innovative systems and services for real-world domain applications. This project directly aligns with numerous EPSRC digital economy strategies such as the 'Sustainable Digital Society' research theme. 'Serverless' principles synergise with IoT device requirements by only consuming limited device resources when computation is necessary (e.g. when a sensor takes periodic readings), therefore, battery operated and energy-conscious IoT deployments benefit from lower electricity costs and extended device longevity. Another EPSRC research theme this project aligns with is enhancing individual privacy as part of the 'Beyond a Data-Driven Economy'. Edge computing brings computational ability closer to the data source, as such, sensitive information is not transported to Cloud servers. Less data is stored in centralised data centres that are more likely to be leaked from security vulnerabilities or exploited for commercial gain. This project will be carried out in collaboration with an industry partner, namely Rakuten Mobile, Japan. They will provide advice on technical aspects and on applying the proposed research to real-world use-cases. An internship with one of their labs in Tokyo is expected either remotely or in person, which is subject to when international travel is more seamless.

“无服务器”计算模式被认为是云计算的下一次演进，它促进了按需计算，而不需要最终用户配置服务器。“无服务器”模式是使用功能即服务(FAAS)模型实现的，在FAAS模型中，云提供商通过按函数调用或函数持续时间收费来实现使用货币化。FAAS与传统的云模式不同，因为终端用户只为他们消耗的资源付费，而不是为他们分配的资源付费(即使这些资源空闲)。虽然‘无服务器’以其对云的影响而闻名，但FAAS也有很多好处可以让Edge受益。边缘物联网(IoT)应用通常是分布式的和资源受限的，因此，无服务器功能的初始化和代码的执行提供了一种计算模型，可以最大限度地减少资源和能源消耗。该项目有三个目的和目的，分别对应于一年的研究，每个目的都是为了发表研究结果。这三个目标将构成第三年最后论文的基础。第一个目标是开发一个能够响应Edge IoT应用需求的无服务器边缘平台。特别是，它将研究为Edge IoT部署带来的各种工作负载提供实时响应的方法。主要研究领域包括边缘工作负载的趋势分析、边缘节点资源的智能配置和调度，以及无服务器边缘平台的网络/路由功能。二是研究了在异类边缘节点上减少边缘机器学习推理的延迟问题。这一目标涉及将无服务器原则映射到边缘环境，在该环境中，网络中的所有边缘节点的推理延迟应该一致。第三个目标是为在硬件共享且资源受限的Edge上执行“无服务器”开发足够的、可执行的安全性。该项目的研究方法包括继续研究和回顾有关Edge和‘无服务器’计算的相关文献。“无服务器”方法的评测和基准测试，包括收集各种工作负载下的延迟、内存和能源消耗以及卷吞吐量等定量数据。分析和识别现有研究和用例中的当前挑战。为合成数据生成和开发“无服务器”边缘系统创建计算试验台。为现实世界领域的应用开发创新系统和服务。该项目直接与EPSRC的众多数字经济战略保持一致，例如“可持续数字社会”研究主题。“无服务器”原则与物联网设备需求相结合，只在需要计算时(例如传感器定期读取读数时)消耗有限的设备资源，因此，电池供电和节能的物联网部署受益于更低的电力成本和更长的设备寿命。EPSRC的另一个研究主题是加强个人隐私，作为“超越数据驱动的经济”的一部分。边缘计算使计算能力更接近数据源，因此，敏感信息不会传输到云服务器。更少的数据存储在中央数据中心，这些中心更有可能因安全漏洞而泄露或被利用来谋取商业利益。该项目将与一个行业合作伙伴--日本乐天移动公司合作进行。他们将提供技术方面的建议，以及将拟议的研究应用于现实世界用例的建议。预计他们将在东京的一个实验室实习，可以远程实习，也可以面对面实习，这取决于何时可以更加无缝地出国旅行。