Dr.-Ing. Dingwen Yuan

Millimeter-wave (mmWave) communication is a promising technology to cope with the expected exponential increase in data traffic in 5G networks. mmWave networks typically require a very dense deployment of mmWave base stations (mmBS). To reduce cost and increase flexibility, wireless backhauling is needed to connect the mmBSs. The characteristics of mmWave communication, and specifically its high directionality, imply new requirements for efficient routing and scheduling paradigms. We propose an efficient scheduling method, so-called schedule-oriented optimization, based on matching theory that optimizes QoS metrics jointly with routing. It is capable of solving any scheduling problem that can be formulated as a linear program whose variables are link times and QoS metrics. As an example of the schedule-oriented optimization, we show the optimal solution of the maximum throughput fair scheduling (MTFS). Practically, the optimal scheduling can be obtained even for networks with over 200 mmBSs. To further increase the runtime performance, we propose an efficient edge-coloring based approximation algorithm with provable performance bound. It achieves over 80% of the optimal max-min throughput and runs 5 to 100 times faster than the optimal algorithm in practice. Finally, we extend the optimal and approximation algorithms for the cases of multi-RF-chain mmBSs and integrated backhaul and access networks.

Wireless Sensor Networks (WSN) are part of the technical fundament enabling the Internet of Things (IoT), where sensing and actuator nodes instantaneously interact with the environment at large. As such they become part of everyday life and drive applications as diverse as medical monitoring, smart homes, smart environment, and smart factories, to name but a few. To acquire data, individual sensors interact with the physical environment by sensing physical phenomena in proximity. The wireless network connectivity is leveraged to collect the raw data or pre-processed events, and to disseminate code, queries or commands. Actuating capabilities facilitate instant interactions with the environment or application processes. Experience on how to operate large scale heterogeneous WSNs in (critical) real-world applications is still scarce, and operational considerations are often an afterthought to WSN deployment. A principled look into the metrics, i.e., a standard or best practice of measurement of the vital parameters in WSNs is still missing. In this article, we contribute a survey on the most important metrics to characterize the performance of WSNs. We define an abstract system model for WSNs, take a look on what the WSN community considers metrics that matter, and categorize the metrics into scopes of relevance. We discuss the properties of the metrics as well as practical aspects on how to obtain and process them. Our survey can serve as a manual for implementors and operators of WSNs in the IoT.

Monitoring and control systems have played a central role in industry and everyday life, often in a non-intrusive manner. Yet, they will become more ubiquitous, autonomous and distributed, with the rapid development of the envisioned technologies of "smart homes", "smart cities" and "industry 4.0". All these new technologies are built upon the enabling technology of WSN. Their success depends to a large extent on the communication capability of WSNs. Fast reaction and feedback is a common characteristic of these technologies, therefore, how to achieve low-latency, high-reliability and flexibility in WSN communication is a key challenge, and a decisive success factor. WSN refers to a network that connects a number of low-cost, low-power sensor nodes which have sensing and/or actuating capabilities, and can communicate with each other over short distance via a low-power radio. The predominant advantages that WSN offers are 1) distribution and fault tolerance in communication and sensing/actuation by leveraging large number of sensor nodes, 2) cost reduction by removing the cables of communication and power supply, and 3) flexibility in the deployment of tiny cableless sensor nodes. However, one main drawback of the wireless technology, in contrast to the mature wired counterpart, is the much weaker communication capability --- the combined result of stronger interference in the wireless channel, the weak signal strength of low-power radios and the complexity in the scheduling of multi-hop wireless communication. The main goal of the thesis is to facilitate the transition from wired technology to wireless technology for industrial automation. Specifically, I provide solutions for improving and guaranteeing QoS in WSN communication. I tackle the problem for two scenarios where the network topology is either known or not. When the network topology is known, I adopt an approach of reservation-based scheduling, i.e., through centralized scheduling of communication opportunities, in order to optimize various communication metrics. In the thesis, I propose a very efficient multi-channel scheduling algorithm that gives nearly optimal latency performance (within 1.22% of the optimum) for the tree-based convergecast, which is by far the predominant communication pattern, especially for monitoring applications. I also propose very efficient multi-channel scheduling algorithms that offer high schedulability and low overhead for multi-flow periodic real-time communication on an arbitrary network topology with multiple gateways. Such a communication pattern is typical of a multi-loop control system. On the other hand, if the network topology is unknown or changes very dynamically, I optimize the QoS in communication by exploiting concurrent transmission on the physical layer, which is routing-free by nature. First, I proposes a simple model for concurrent transmissions in WSN which accurately predicts the success or failure in the packet reception. Then I design the Sparkle protocol for highly reliable, low latency and energy efficient multi-flow periodic communication. Finally, it presents the Ripple protocol for high throughput, reliable and energy efficient network flooding using pipeline transmissions and forward error correction, which significantly improves the state-of-the-art. Although the thesis assumes WSN as the communication technology and industrial automation as the application scenario, it is by no means restricted to these settings since the proposed solutions can be applied to other wireless networks and other scenarios with similar communication patterns and QoS concerns.