Provisioning QoS-Aware and Robust Applications in Internet of Things: A Network Perspective

Abstract

The Internet-of-Things (IoT) has inspired numerous new applications ever since its invention. Nevertheless, its development and utilization have always been restricted by the limited resources in various application scenarios. In this paper, we study the problem of resource provisioning for real-time IoT applications, i.e. , applications that process concurrent data streams from data sources in the network. We investigate joint application placement and data routing to support IoT applications that have both quality-of-service and robustness requirements. We formulate four versions of the provisioning problem, spanning across two important classes of real-time applications (parallelizable and non-parallelizable), and two provisioning scenarios (single application and multiple applications). All versions are proved to be NP-hard. We propose fully polynomial-time approximation schemes for three of the four versions, and a randomized algorithm for the forth. Through simulation experiments, we analyze the impact of parallelizability and robustness on the provisioning performance, and show that our proposed algorithms can greatly improve the quality-of-service of the IoT applications.