QoS enabled heterogeneous BLE mesh networks

Bluetooth Low Energy (BLE) is a widely known short-range wireless technology used for various Internet of Things (IoT) applications. Recently, with the introduction of BLE mesh networks, this short-range barrier of BLE has been overcome. However, the added advantage of an extended range can come at the cost of a lower performance of these networks in terms of latency, throughput and reliability, as the core operation of BLE mesh is based on advertising and packet flooding. Hence, efficient management of the system is required to achieve a good performance of these networks and a smoother functioning in dense scenarios. As the number of configuration points in a standard mesh network is limited, this paper describes a novel set of standard compliant Quality of Service (QoS) extensions for BLE mesh networks. The resulting QoS features enable better traffic management in the mesh network, providing sufficient redundancy to achieve reliability whilst avoiding unnecessary packet flooding to reduce collisions, as well as the prioritization of certain traffic flows and the ability to control end-to-end latencies. The QoS-based system has been implemented and validated in a small-scale BLE mesh network and compared against a setup without any QoS support. The assessment in a small-scale test setup confirms that applying our QoS features can enhance these types of non-scheduled and random access networks in a significant way

The King is Dead Long Live the King! Towards Systematic Performance Evaluation of Heterogeneous Bluetooth Mesh Networks in Real World Environments

Wireless networks based on Bluetooth mesh (BM) promise a variety of Internet of Things applications from health- care monitoring to smart buildings. BM introduces a novel network concept that supports up to 32767 devices and 127 hops. So far no readily available dataset or toolset exists to perform systematic in-depth performance analysis of this standard. In this paper, we present insights on the performance and practical usability of BM. We conduct realistic smart office experiments with heterogeneous devices distributed throughout an area of approximately 1100m2. By varying network pa- rameters and BM node features, we collect the first public available BM dataset. Based on our experience, the use of current implementations is error-prone due to the complexity of BM. To facilitate researchers to conduct further experiments, we propose a toolset to configure and systematically evaluate BM performance. Finally we discuss several pitfalls that should be avoided in designing and deploying such networks