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Timely Information Updates for the Internet of Things with Serverless Computing

The proliferation of the Internet of Things (IoT) applications has resulted in the ever-increasing research attention in recent years. In light of the sensitivity to latency in various IoT applications, the age of information (AoI) has been widely regarded as a promising performance metric to quantify the timeliness (i.e., freshness or age) of information updates from IoT devices. In addition, serverless computing (also known as function as a service (FaaS)) evolves as a highly scalable and flexible computing architecture that can facilitate timely IoT analytics. In fact, the execution of serverless functions may rely on the data collected from IoT devices, therefore the freshness of information updates of IoT devices has prompt impacts on the age of service (AoS) of serverless functions. Although existing works have been devoted to various aspects of serverless computing, the issues regarding how information updates affect the AoS of serverless functions are rarely investigated. In this paper, we address the information update delivery and acquisition (IUDA) problem for IoT with serverless computing and formulate it an integer linear program (ILP), the objective of which is to minimize a weighted sum of AoS of serverless functions. To cope with the IUDA problem, we propose an offline and an online algorithm for scheduling information updates with and without the knowledge of the arrivals of serverless functions, respectively. Our simulation results demonstrate that the proposed solutions outperform existing solutions in terms of the AoS performance and effectively provide serverless functions with timely information updates under various parameter settings.