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

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

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

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

Multi-Cell, Multi-Channel Scheduling with Probabilistic Per-Packet Real-Time Guarantee

For mission-critical sensing and control applications such as those to be enabled by 5G Ultra-Reliable, Low-Latency Communications (URLLC), it is critical to ensure the communication quality of individual packets. Prior studies have considered Probabilistic Per-packet Real-time Communications (PPRC) guarantees for single-cell, single-channel networks with implicit deadline constraints, but they have not considered real-world complexities such as inter-cell interference and multiple communication channels. Towards ensuring PPRC in multi-cell, multi-channel wireless networks, we propose a real-time scheduling algorithm based on \emph{local-deadline-partition (LDP)}. The LDP algorithm is suitable for distributed implementation, and it ensures probabilistic per-packet real-time guarantee for multi-cell, multi-channel networks with general deadline constraints. We also address the associated challenge of the schedulability test of PPRC traffic. In particular, we propose the concept of \emph{feasible set} and identify a closed-form sufficient condition for the schedulability of PPRC traffic. We propose a distributed algorithm for the schedulability test, and the algorithm includes a procedure for finding the minimum sum work density of feasible sets which is of interest by itself. We also identify a necessary condition for the schedulability of PPRC traffic, and use numerical studies to understand a lower bound on the approximation ratio of the LDP algorithm. We experimentally study the properties of the LDP algorithm and observe that the PPRC traffic supportable by the LDP algorithm is significantly higher than that of a state-of-the-art algorithm

Power control for predictable communication reliability in wireless cyber-physical systems

Wireless networks are being applied in various cyber-physical systems and posed to support mission-critical cyber-physical systems applications. When those applications require reliable and low-latency wireless communication, ensuring predictable per-packet communication reliability is a basis. Due to co-channel interference and wireless channel dynamics (e.g. multi-path fading), however, wireless communication is inherently dynamic and subject to complex uncertainties. Power control and MAC-layer scheduling are two enablers. In this dissertation, cross-layer optimization of joint power control and scheduling for ensuring predictable reliability has been studied. With an emphasis on distributed approaches, we propose a general framework and additionally a distributed algorithm in static networks to address small channel variations and satisfy the requirements on receiver-side signal-to-interference-plus-noise-ratio (SINR). Moreover, toward addressing reliability in the settings of large-scale channel dynamics, we conduct an analysis of the strategy of joint scheduling and power control and demonstrate the challenges. First, a general framework for distributed power control is considered. Given a set of links subject to co-channel interference and channel dynamics, the goal is to adjust each link\u27s transmission power on-the-fly so that all the links\u27 instantaneous packet delivery ratio requirements can be satised. By adopting the SINR high-delity model, this problem can be formulated as a Linear Programming problem. Furthermore, Perron-Frobenius theory indicates the characteristic of infeasibility, which means that not all links can nd a transmission power to meet all the SINR requirements. This nding provides a theoretical foundation for the Physical-Ratio-K (PRK) model. We build our framework based on the PRK model and NAMA scheduling. In the proposed framework, we dene the optimal K as a measurement for feasibility. Transmission power and scheduling will be adjusted by K and achieve near-optimal performance in terms of reliability and concurrency. Second, we propose a distributed power control and scheduling algorithm for mission-critical Internet-of-Things (IoT) communications. Existing solutions are mostly based on heuristic algorithms or asymptotic analysis of network performance, and there lack eld-deployable algorithms for ensuring predictable communication reliability. When IoT systems are mostly static or low mobility, we model the wireless channel with small channel variations. For this setting, our approach adopts the framework mentioned above and employs feedback control for online K adaptation and transmission power update. At each time instant, each sender will run NAMA scheduling to determine if it can obtain channel access or not. When each sender gets the channel access and sends a packet, its receiver will measure the current SINR and calculate the scheduling K and transmission power for the next time slot according to current K, transmission power and SINR. This adaptive distributed approach has demonstrated a signicant improvement compared to state-of-the-art technique. The proposed algorithm is expected to serve as a foundation for distributed scheduling and power control as the penetration of IoT applications expands to levels at which both the network capacity and communication reliability become critical. Finally, we address the challenges of power control and scheduling in the presence of large-scale channel dynamics. Distributed approaches generally require time to converge, and this becomes a major issue in large-scale dynamics where channel may change faster than the convergence time of algorithms. We dene the cumulative interference factor as a measurement of impact of a single link\u27s interference. We examine the characteristic of the interference matrix and propose that scheduling with close-by links silent will be still an ecient way of constructing a set of links whose required reliability is feasible with proper transmission power control even in the situation of large-scale channel dynamics. Given that scheduling alone is unable to ensure predictable communication reliability while ensuring high throughput and addressing fast-varying channel dynamics, we demonstrate how power control can help improve both reliability at each time instant and throughput in the long-term. Collectively, these ndings provide insight into the cross-layer design of joint scheduling and power control for ensuring predictable per-packet reliability in the presence of wireless network dynamics and uncertainties

The Alive-in-Range Medium Access Control Protocol to Optimize Queue Performance in Underwater Wireless Sensor Networks, Journal of Telecommunications and Information Technology, 2017, nr 4

Time synchronization between sensor nodes to reduce the end-to-end delay for critical and real time data monitoring can be achieved by cautiously monitoring the mobility of the mobile sink node in underwater wireless sensor networks. The Alive-in-Range Medium Access Control (ARMAC) protocol monitors the delay of sensitive, critical and real-time data. The idea evolves as it involves reduction in duty cycle, precise time scheduling of active/sleep cycles of the sensors, monitoring the mobility of the sink node with the selection of appropriate queues and schedulers. The model for the path loss due to attenuation of electromagnetic wave propagation in the sea water is explained. The three-path reflection model evaluating reflection loss from the air-water and watersand interfaces as a function of distance between sensors and water depth is introduced. The algorithms for effective path determination and optimum throughput path determination are elaborated. The results verify that implementation of the Alive-in-Range MAC protocol has reduced the total number of packets dropped, the average queue length, the longest time in queue, the peak queue length and the average time in queue significantly, making it relevant for critical and real-time data monitoring