Reliable Communication in Wireless Networks

Wireless communication systems are increasingly being used in industries and infrastructures since they offer significant advantages such as cost effectiveness and scalability with respect to wired communication system. However, the broadcast feature and the unreliable links in the wireless communication system may cause more communication collisions and redundant transmissions. Consequently, guaranteeing reliable and efficient transmission in wireless communication systems has become a big challenging issue. In particular, analysis and evaluation of reliable transmission protocols in wireless sensor networks (WSNs) and radio frequency identification system (RFID) are strongly required. This thesis proposes to model, analyze and evaluate self-configuration algorithms in wireless communication systems. The objective is to propose innovative solutions for communication protocols in WSNs and RFID systems, aiming at optimizing the performance of the algorithms in terms of throughput, reliability and power consumption. The first activity focuses on communication protocols in WSNs, which have been investigated, evaluated and optimized, in order to ensure fast and reliable data transmission between sensor nodes. The second research topic addresses the interference problem in RFID systems. The target is to evaluate and develop precise models for accurately describing the interference among readers. Based on these models, new solutions for reducing collision in RFID systems have been investigated

Long-Term Stable Communication in Centrally Scheduled Low-Power Wireless Networks

With the emergence of the Internet of Things (IoT), more devices are connected than ever before. Most of these communicate wirelessly, forming Wireless Sensor Networks. In recent years, there has been a shift from personal networks, like Smart Home, to industrial networks. Industrial networks monitor pipelines or handle the communication between robots in factories. These new applications form the Industrial Internet of Things (IIoT). Many industrial applications have high requirements for communication, higher than the requirements of common IoT networks. Communications must stick to hard deadlines to avoid harm, and they must be highly reliable as skipping information is not a viable option when communicating critical information. Moreover, communication has to remain reliable over longer periods of time. As many sensor locations do not offer a power source, the devices have to run on battery and thus have to be power efficient. Current systems offer solutions for some of these requirements. However, they especially lack long-term stable communication that can dynamically adapt to changes in the wireless medium.In this thesis, we study the problem of stable and reliable communication in centrally scheduled low-power wireless networks. This communication ought to be stable when it can dynamically adapt to changes in the wireless medium while keeping latency at a minimum. We design and investigate approaches to solve the problem of low to high degrees of interference in the wireless medium. We propose three solutions to overcome interference: MASTER with Sliding Windows brings dynamic numbers of retransmissions to centrally scheduled low-power wireless networks, OVERTAKE allows to skip nodes affected by interference along the path, and AUTOBAHN combines opportunistic routing and synchronous transmissions with the Time-Slotted Channel Hopping (TSCH) MAC protocol to overcome local wide-band interference with the lowest possible latency. We evaluate our approaches in detail on testbed deployments and provide open-source implementations of the protocols to enable others to build their work upon them

Infective flooding in low-duty-cycle networks, properties and bounds

Flooding information is an important function in many networking applications. In some networks, as wireless sensor networks or some ad-hoc networks it is so essential as to dominate the performance of the entire system. Exploiting some recent results based on the distributed computation of the eigenvector centrality of nodes in the network graph and classical dynamic diffusion models on graphs, this paper derives a novel theoretical framework for efficient resource allocation to flood information in mesh networks with low duty-cycling without the need to build a distribution tree or any other distribution overlay. Furthermore, the method requires only local computations based on each node neighborhood. The model provides lower and upper stochastic bounds on the flooding delay averages on all possible sources with high probability. We show that the lower bound is very close to the theoretical optimum. A simulation-based implementation allows the study of specific topologies and graph models as well as scheduling heuristics and packet losses. Simulation experiments show that simple protocols based on our resource allocation strategy can easily achieve results that are very close to the theoretical minimum obtained building optimized overlays on the network

Scalable Downward Routing for Wireless Sensor Networks and Internet of Things Actuation

We present the opportunistic Source Routing (OSR), a scalable and reliable downward routing protocol for large-scale and heterogeneous wireless sensor networks (WSNs) and Internet of Things IoT. We devise a novel adaptive Bloom filter mechanism to efficiently encode the downward source route in OSR, which significantly reduces the length of the source route field in the packet header. Moreover, each node in the network stores only the set of its direct children. Thus, OSR is scalable to very large-size WSN/IoT deployments. OSR introduces opportunistic routing into traditional source routing based on the parent set of a node's upward routing in data collection, significantly addressing the drastic link dynamics in low-power and lossy networks (LLNs). Our evaluation of OSR via both simulations and real-world testbed experiments demonstrates its merits in comparison with the state-of-the-art protocols

Ambient Data Collection with Wireless Sensor Networks

One of the most important applications for wireless sensor networks (WSNs) is Data Collection, where sensing data arecollected at sensor nodes and forwarded to a central base station for further processing. Since using battery powers and wirelesscommunications, sensor nodes can be very small and easily attached at specified locations without disturbing surroundingenvironments. This makes WSN a competitive approach for data collection comparing with its wired counterpart. In this paper,we review recent advances in this research area. We first highlight the special features of data collection WSNs, by comparingwith wired data collection network and other WSN applications. With these features in mind, we then discuss issues and priorsolutions on the data gathering protocol design. Our discussion also covers different approaches for message dissemination, whichis a critical component for network control and management and greatly affects the overall performance of a data collectionWSNsystem