IoTm: A Lightweight Framework for Fine-Grained Measurements of IoT Performance Metrics

Abstract

Most Internet of Things (IoT) applications require unique guarantees on various performance metrics (such as latency, CPU availability, power fairness, etc.) from the IoT infrastructure. A small deterioration in these performance metrics can cause serious violations of service level agreements. To ensure that the deployed IoT infrastructure delivers the guarantees on these metrics, the first step is to measure these metrics. We present IoTm, a framework for measuring IoT performance metrics, which include both IoT network's quality of service (QoS) metrics and IoT node's resource utilization (RU) metrics. IoTm has two key properties: 1) it is lightweight and thus amenable for implementation on resource constrained IoT nodes; and 2) it can perform measurements at fine-grained levels and not just at aggregate levels. IoTm is comprised of two components, a lightweight IoT node unit (INU), which resides in each of the IoT nodes, and a control and query unit (CQU), which resides in a logically centralized management server. The primary role of INU is to record appropriate information about the desired performance metrics in the IoT nodes. To record the information, INU leverages a generic data structure that we propose. CQU is responsible for identifying the metrics and the IoT nodes on which those metrics should be monitored to achieve a desired measurement objective. CQU also stores the copies of data structures that the INU sends to it for long term storage. Both INU and CQU further contain query processing engines, which operate on the information stored in the data structures to answer measurement queries. To demonstrate the use of our framework, we apply it to one RU metric (number of disk accesses), and one QoS metric (round trip latency), and evaluate its accuracy. We also analyze the feasibility of its implementation on IoT nodes in terms of memory requirement and computational complexity.