Resource Management for Latency-Sensitive IoT Applications With Satisfiability

Abstract

Satisfying the software requirements of emerging service-based Internet of Things (IoT) applications has become challenging for cloud-centric architectures, as applications demand fast response times and availability of computational resources closer to end-users. Meeting application demands must occur at runtime, facing uncertainty and in a decentralized manner, something that must be reflected in system deployment. We propose a decentralized resource management technique and accompanying technical framework for the deployment of service-based IoT applications at the edge. Faithful to services engineering, applications we consider are composed of interdependent tasks, which in the IoT setting may be concretized as containerized microservices or serverless functions. A deployment for an arbitrary application is found at runtime through satisfiability; the mapping produced is compliant with tasks' individual resource requirements and latency constraints by construction. Our approach ensures seamless deployment at runtime, assuming no design-time knowledge of device resources or the current network topology. We evaluate the applicability and realizability of our technique over single-board computers as edge devices, particularly in the absence of cloud resources.