Serverless edge computing adopts an event-based paradigm that provides back-end services on an as-used basis, resulting in efficient resource utilization. To improve the end-to-end latency and revenue, service providers need to optimize the number and placement of serverless containers while considering the system cost incurred by the provisioning. The particular reason for this circumstance is that frequently creating and destroying containers not only increases the system cost but also degrades the time responsiveness due to the cold-start process. Function caching is a common approach to mitigate the coldstart issue. However, function caching requires extra hardware resources and hence incurs extra system costs. Furthermore, the dynamic and bursty nature of serverless invocations remains an under-explored area. Hence, it is vitally important for service providers to conduct a context-aware request distribution and container caching policy for serverless edge computing. In this paper, we study the request distribution and container caching problem in serverless edge computing. We prove the proposed problem is NP-hard and hence difficult to find a global optimal solution. We jointly consider the distributed and resource constrained nature of edge computing and propose an optimized request distribution algorithm that adapts to the dynamics of serverless invocations with a theoretical performance guarantee. Also, we propose a context-aware probabilistic caching policy that incorporates a number of characteristics of serverless invocations. Via simulation and implementation results, we demonstrate the superiority of the proposed algorithm by outperforming existing caching policies in terms of the overall system cost and cold-start frequency by up to 62.1% and 69.1%, respectively.

翻译：无服务边缘计算采用基于事件的范式，按需提供后端服务，从而实现高效的资源利用。为改善端到端延迟和收益，服务提供商需在考虑置备所引发系统成本的前提下，优化无服务容器的数量与部署位置。其特殊原因在于：频繁创建和销毁容器不仅增加系统成本，还会因冷启动过程降低时间响应性。函数缓存是缓解冷启动问题的常见方法，但函数缓存需要额外硬件资源，因而产生额外系统成本。此外，无服务调用的动态性与突发性特征仍是研究不足的领域。因此，服务提供商制定上下文感知的请求分发与容器缓存策略对于无服务边缘计算至关重要。本文研究了无服务边缘计算中的请求分发与容器缓存问题。我们证明所提问题属于NP难问题，难以找到全局最优解。我们联合考虑边缘计算的分布式与资源受限特性，提出了一种具有理论性能保证的优化请求分发算法，该算法能自适应无服务调用的动态变化。同时，我们提出了一种上下文感知的概率缓存策略，该策略整合了无服务调用的多种特征。通过仿真与实现结果，我们展示了所提算法在整体系统成本和冷启动频率方面的优越性，分别比现有缓存策略降低了高达62.1%和69.1%。