Predictable Reliability In Inter-Vehicle Communications

Predictably reliable communication in wireless networked sensing and control systems (WSC) is a basic enabler for performance guarantee. Yet current research efforts are either focus on maximizing throughput or based on inaccurate interference modelling methods, which yield unsatisfactory results in terms of communication reliability. In this dissertation, we discuss techniques that enable reliable communication in both traditional wireless sensor networks and highly mobile inter-vehicle communication networks. We focus our discussion on traditional wireless sensor networks in Chapter 2 where we discuss mechanisms that enable predictable and reliable communications with no centralized infrastructures. With the promising results in Chapter 2, we extend our methods to inter-vehicle communication networks in Chapter 3. We focus on the broadcast communication paradigm and the unique challenges in applying the PRK interference model into broadcast problems in highly mobile inter-vehicle communication networks. While Chapter 2 and Chapter 3 focus on average reliability, we switch our problem to a more challenging aspect: guaranteeing short-term per-packet reception probability in Chapter 4. Specifically, we describe the PRKS protocol in Chapter 2 which considers unicast transmission paradigm in traditional static wireless sensor networks. PRKS uses the PRK interference model as a basis for interference relation identification that captures characteristics of wireless communications. For communication reliability control, we design a controller that runs at each link receiver and is able to control the average link reliability to be no lower than an application requirement as well as minimizing reliability variation. We further evaluate PRKS with extensive ns-3 simulations. The CPS protocol described in Chapter 3 considers an one-hop broadcast problem in multi-hop inter-vehicle communication networks. We analyze the challenges of applying the PRK model in this particular setting and propose an approximated PRK model, i.e., gPRK model, that addresses the challenges. We further design principles that CPS uses to instantiate the gPRK model in inter-vehicle communications. We implement the CPS scheduling framework in an integrated platform with SUMO and ns-3 to evaluate our design. In Chapter 4, we conservatively estimate the background interference plus noise while nodes are receiving packets. In the meantime, receivers decide minimum power levels their sender should use and feedback their decisions to their senders. Senders fuse feedbacks and choose a power level that guarantees expected packet reception probability at each receivers’ side. We notice in our evaluation that guaranteeing short-term reliability causes extra concurrency loss

Predictable Reliability In Inter-Vehicle Communications

Predictably reliable communication in wireless networked sensing and control systems (WSC) is a basic enabler for performance guarantee. Yet current research efforts are either focus on maximizing throughput or based on inaccurate interference modelling methods, which yield unsatisfactory results in terms of communication reliability. In this dissertation, we discuss techniques that enable reliable communication in both traditional wireless sensor networks and highly mobile inter-vehicle communication networks. We focus our discussion on traditional wireless sensor networks in Chapter 2 where we discuss mechanisms that enable predictable and reliable communications with no centralized infrastructures. With the promising results in Chapter 2, we extend our methods to inter-vehicle communication networks in Chapter 3. We focus on the broadcast communication paradigm and the unique challenges in applying the PRK interference model into broadcast problems in highly mobile inter-vehicle communication networks. While Chapter 2 and Chapter 3 focus on average reliability, we switch our problem to a more challenging aspect: guaranteeing short-term per-packet reception probability in Chapter 4. Specifically, we describe the PRKS protocol in Chapter 2 which considers unicast transmission paradigm in traditional static wireless sensor networks. PRKS uses the PRK interference model as a basis for interference relation identification that captures characteristics of wireless communications. For communication reliability control, we design a controller that runs at each link receiver and is able to control the average link reliability to be no lower than an application requirement as well as minimizing reliability variation. We further evaluate PRKS with extensive ns-3 simulations. The CPS protocol described in Chapter 3 considers an one-hop broadcast problem in multi-hop inter-vehicle communication networks. We analyze the challenges of applying the PRK model in this particular setting and propose an approximated PRK model, i.e., gPRK model, that addresses the challenges. We further design principles that CPS uses to instantiate the gPRK model in inter-vehicle communications. We implement the CPS scheduling framework in an integrated platform with SUMO and ns-3 to evaluate our design. In Chapter 4, we conservatively estimate the background interference plus noise while nodes are receiving packets. In the meantime, receivers decide minimum power levels their sender should use and feedback their decisions to their senders. Senders fuse feedbacks and choose a power level that guarantees expected packet reception probability at each receivers’ side. We notice in our evaluation that guaranteeing short-term reliability causes extra concurrency loss

Predictable Real-Time Wireless Networking For Sensing And Control

Towards the end goal of providing predictable real-time wireless networking for sensing and control, we have developed a real-time routing protocol MTA that predictably delivers data by their deadlines, and a scheduling protocol PRKS to ensure a certain link reliability based on the Physical-ratio-K (PRK) model, which is both realistic and amenable for distributed implementation, and a greedy scheduling algorithm to deliver as many packets as possible to the sink by a deadline in lossy multi-hop wireless sensor networks. Real-time routing is a basic element of closed-loop, real-time sensing and control, but it is challenging due to dynamic, uncertain link/path delays. The probabilistic nature of link/path delays makes the basic problem of computing the probabilistic distribution of path delays NP-hard, yet quantifying probabilistic path delays is a basic element of real-time routing and may well have to be executed by resource-constrained devices in a distributed manner; the highly-varying nature of link/path delays makes it necessary to adapt to in-situ delay conditions in real-time routing, but it has been observed that delay-based routing can lead to instability, estimation error, and low data delivery performance in general. To address these challenges, we propose the Multi-Timescale Estimation (MTE) method; by accurately estimating the mean and variance of per-packet transmission time and by adapting to fast-varying queueing in an accurate, agile manner, MTE enables accurate, agile, and efficient estimation of probabilistic path delay bounds in a distributed manner. Based on MTE, we propose the Multi-Timescale Adaptation (MTA) routing protocol; MTA integrates the stability of an ETX-based directed-acyclic-graph (DAG) with the agility of spatiotemporal data flow control within the DAG to ensure real-time data delivery in the presence of dynamics and uncertainties. We also address the challenges of implementing MTE and MTA in resource-constrained devices such as TelosB motes. We evaluate the performance of MTA using the NetEye and Indriya sensor network testbeds. We find that MTA significantly outperforms existing protocols, e.g., improving deadline success ratio by 89% and reducing transmission cost by a factor of 9.7. Predictable wireless communication is another basic enabler for networked sensing and control in many cyber-physical systems, yet co-channel interference remains a major source of uncertainty in wireless communication. Integrating the protocol model\u27s locality and the physical model\u27s high fidelity, the physical-ratio-K (PRK) interference model bridges the gap between the suitability for distributed implementation and the enabled scheduling performance, and it is expected to serve as a foundation for distributed, predictable interference control. To realize the potential of the PRK model and to address the challenges of distributed PRK-based scheduling, we design protocol PRKS. PRKS uses a control-theoretic approach to instantiating the PRK model according to in-situ network and environmental conditions, and, through purely local coordination, the distributed controllers converge to a state where the desired link reliability is guaranteed. PRKS uses local signal maps to address the challenges of anisotropic, asymmetric wireless communication and large interference range, and PRKS leverages the different timescales of PRK model adaptation and data transmission to decouple protocol signaling from data transmission. Through sensor network testbed-based measurement study, we observe that, unlike existing scheduling protocols where link reliability is unpredictable and the reliability requirement satisfaction ratio can be as low as 0%, PRKS enables predictably high link reliability (e.g., 95%) in different network and environmental conditions without a priori knowledge of these conditions, and, through local distributed coordination, PRKS achieves a channel spatial reuse very close to what is enabled by the state-of-the-art centralized scheduler while ensuring the required link reliability. Ensuring the required link reliability in PRKS also reduces communication delay and improves network throughput. We study the problem of scheduling packet transmissions to maximize the expected number of packets collected at the sink by a deadline in a multi-hop wireless sensor network with lossy links. Most existing work assumes error-free transmissions when interference constraints are complied, yet links can be unreliable due to external interference, shadow- ing, and fading in harsh environments in practice. We formulate the problem as a Markov decision process, yielding an optimal solution. However, the problem is computationally in- tractable due to the curse of dimensionality. Thus, we propose the efficient and greedy Best Link First Scheduling (BLF) protocol. We prove it is optimal for the single-hop case and provide an approach for distributed implementation. Extensive simulations show it greatly enhances real-time data delivery performance, increasing deadline catch ratio by up to 50%, compared with existing scheduling protocols in a wide range of network and traffic settings

Interference Modeling And Control In Wireless Networks

With the successful commercialization of IEEE802.11 standard, wireless networks have become a tight-knit of our daily life. As wireless networks are increasingly applied to real- time and mission-critical tasks, how to ensuring real-time, reliable data delivery emerges as an important problem. However, wireless communication is subject to various dynamics and uncertainties due to the broadcast nature of wireless signal. In particular, co-channel interfer- ence not only reduces the reliability and throughput of wireless networks, it also increases the variability and uncertainty in data communication [64, 80, 77]. A basis of interference control is the interference model which \emph{predicts} whether a set of concurrent transmissions may interfere with one another. Two commonly used models, the \textit{SINR model} and the \textit{radio-K model}, are thoroughly studied in our work. To address the limitations of those models, we propose the physical-ratio-K(PRK) interference model as a reliablility-oriented instantiation of the ratio-K model, where the link-specific choice of K adapts to network and environmental conditions as well as application QoS requirements to ensure certain minimum reliability of every link. On the other hand, the interference among the transmissions, limits the number of con- current transmissions. We formulate the concept of \emph{interference budget} that, given a set of scheduled transmissions in a time slot, characterizes the additional interference power that can be tolerated by all the receivers without violating the application requirement on link reliability. We propose the scheduling algorithm \emph{iOrder} that optimizes link ordering by considering both interference budget and queue length in scheduling. Through both simulation and real-world experiments, we observe that optimizing link ordering can improve the performance of existing algorithms by a significant. Based on the strong preliminary research result on interference modeling and control, we will extend our method into distributed protocol designs. One future work will focus on imple- menting the \textit{PRK model} in a distributed protocols. We will also explore the benefits of using multiple channels in the interference control

Real-Time Guarantees For Wireless Networked Sensing And Control

Wireless networks are increasingly being explored for mission-critical sensing and control in emerging domains such as connected and automated vehicles, Industrial 4.0, and smart city. In wireless networked sensing and control (WSC) systems, reliable and real- time delivery of sensed data plays a crucial role for the control decision since out-of-date information will often be irrelevant and even leads to negative effects to the system. Since WSC differs dramatically from the traditional real-time (RT) systems due to its wireless nature, new design objective and perspective are necessary to achieve real-time guarantees. First, we proposed Optimal Node Activation Multiple Access (ONAMA) scheduling protocol that activates as many nodes as possible while ensuring transmission reliability (in terms of packets delivery ratio). We implemented and tested ONAMA on two testbeds both with 120+ sensor nodes. Second, we proposed algorithms to address the problem of clustering heterogeneous reliability requirements into a limit set of service levels. Our solutions are optimal, and they also provide guaranteed reliability, which is critical for wireless sensing and control. Third, we proposed a probabilistic real-time wireless communication framework that effectively integrates real-time scheduling theory with wireless communication. The per- packet probabilistic real-time QoS was formally modeled. By R3 mapping, the upper-layer requirement and the lower-layer link reliability are translated into the number of trans- mission opportunities needed. By optimal real-time communication scheduling as well as admission test and traffic period optimization, the system utilization is maximized while the schedulability is maintained. Finally, we further investigated the problem of how to minimize delay variation (i.e., jitter) while ensuring that packets are delivered by their deadlines

Enabling Parallel Wireless Communication in Mobile Robot Teams

Wireless inter-robot communication enables robot teams to cooperatively solve complex problems that cannot be addressed by a single robot. Applications for cooperative robot teams include search and rescue, exploration and surveillance. Communication is one of the most important components in future autonomous robot systems and is essential for core functions such as inter-robot coordination, neighbour discovery and cooperative control algorithms. In environments where communication infrastructure does not exist, decentralised multi-hop networks can be constructed using only the radios on-board each robot. These are known as wireless mesh networks (WMNs). However existing WMNs have limited capacity to support even small robot teams. There is a need for WMNs where links act like dedicated point-to-point connections such as in wired networks. Addressing this problem requires a fundamentally new approach to WMN construction and this thesis is the first comprehensive study in the multi-robot literature to address these challenges. In this thesis, we propose a new class of communication systems called zero mutual interference (ZMI) networks that are able to emulate the point-to-point properties of a wired network over a WMN implementation. We instantiate the ZMI network using a multi-radio multi-channel architecture that autonomously adapts its topology and channel allocations such that all network edges communicate at the full capacity of the radio hardware. We implement the ZMI network on a 100-radio testbed with up to 20-individual nodes and verify its theoretical properties. Mobile robot experiments also demonstrate these properties are practically achievable. The results are an encouraging indication that the ZMI network approach can facilitate the communication demands of large cooperative robot teams deployed in practical problems such as data pipe-lining, decentralised optimisation, decentralised data fusion and sensor networks

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications