论文标题
基于公用事业的资源分配和定价用于无服务器计算
Utility-based Resource Allocation and Pricing for Serverless Computing
论文作者
论文摘要
当前的无服务器计算平台依赖于静态的基本定价方案，并且不反映客户反馈。从总效用的角度来看，这导致了明显的效率低下。作为增长最快的云服务之一，无服务器计算通过纳入基于市场的定价和资源分配策略为用户和提供商提供了一个机会。借助实用程序功能来建模客户的延迟敏感性，我们建议一个新颖的调度程序，以分配资源以用于无服务器计算。从最大化系统中所有用户的总实用性，从而最大程度地提高社会福利的意义上，最佳的资源分配方案是最佳的。我们的方法产生了一种自然动态定价方案，该方案是通过以双重形式解决优化问题获得的。我们进一步开发了反馈机制，即使用户的实用程序是私人的并且服务提供商未知，云提供商也可以收敛到最佳资源分配。模拟表明，与现有计划相比，我们的方法可以跟踪市场需求并获得更高的社会福利（或等效地节省成本）。
Serverless computing platforms currently rely on basic pricing schemes that are static and do not reflect customer feedback. This leads to significant inefficiencies from a total utility perspective. As one of the fastest-growing cloud services, serverless computing provides an opportunity to better serve both users and providers through the incorporation of market-based strategies for pricing and resource allocation. With the help of utility functions to model the delay-sensitivity of customers, we propose a novel scheduler to allocate resources for serverless computing. The resulting resource allocation scheme is optimal in the sense that it maximizes the aggregate utility of all users across the system, thus maximizing social welfare. Our approach gives rise to a natural dynamic pricing scheme that is obtained by solving an optimization problem in its dual form. We further develop feedback mechanisms that allow the cloud provider to converge to optimal resource allocation, even when the users' utilities are private and unknown to the service provider. Simulations show that our approach can track market demand and achieve significantly higher social welfare (or, equivalently, cost savings for customers) compared to existing schemes.
