Transmission Scheduling in Wireless Networked Control for Industrial IoT

Wireless networked control systems (WNCS) consist of spatially distributed sensors, actuators, and controllers communicating through wireless networks. WNCS has recently emerged as a fundamental infrastructure technology to enable reliable control for mission-critical Industrial Internet of Things (IIoT) applications such as factory automation, intelligent transportation systems, telemedicine and smart grids. The design of WNCS requires the joint design of communications, computing and control. WNCS faces challenges such as unreliable transmission and latency in transmitting control and sensing information due to channel impairment in wireless communications for large scale deployment. This can have a significant impact on the stability and performance of WNCS. Most existing works have mainly focused on the design of WNCS from a control perspective rather than communications or have considered an ideal or simplified wireless model. How to reliably control WNCS in practical wireless channels and design wireless communication scheduling policy to optimize control performance is a challenging task. This thesis presents the design of practical communication protocols of a general discrete linear time-invariant (LTI) dynamic system in WNCS. We address the transmission scheduling problems in WNCS in three scenarios, which require the development of different strategies. Firstly, to minimize the long-term average remote estimation mean-squared-error (MSE), a hybrid automatic repeat request (HAQR)-based real-time estimation framework is proposed. Secondly, a downlink-uplink transmission scheduling policy is developed for a half-duplex (FD) controller to optimize the system performance. Finally, a novel controller with adaptive packet length is studied, and a variable-length packet-transmission policy is proposed to balance the delay-reliability tradeoff in WNCS optimally. Numerical results show that our dynamic scheduling policies can significantly improve the performance of WNCS in terms of estimation and control costs while maintaining the stability of the system

Hierarchical Agent-based Adaptation for Self-Aware Embedded Computing Systems

Siirretty Doriast

Energy-efficient diversity combining for different access schemes in a multi-path dispersive channel

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e ComputadoresThe forthcoming generation of mobile communications, 5G, will settle a new standard for a larger bandwidth and better Quality of Service (QoS). With the exploding growth rate of user generated data, wireless standards must cope with this growth and at the same time be energy efficient to avoid depleting the batteries of wireless devices. Besides these issues, in a broadband wireless setting QoS can be severely affected from a multipath dispersive channel and therefore be energy demanding. Cross-layered architectures are a good choice to enhance the overall performance of a wireless system. Examples of cross-layered Physical (PHY) - Medium Access Control (MAC) architectures are type-II Diversity Combining (DC) Hybrid-ARQ (H-ARQ) and Multi-user Detection (MUD) schemes. Cross-layered type-II DC H-ARQ schemes reuse failed packet transmissions to enhance data reception on posterior retransmissions; MUD schemes reuse data information from previously collided packets on posterior retransmissions to enhance data reception. For a multipath dispersive channel, a PHY layer analytical model is proposed for Single-Carrier with Frequency Domain Equalization (SC-FDE) that supports DC H-ARQ and MUD. Based on this analytical model, three PHY-MAC protocols are proposed. A crosslayered Time Division Multiple Access (TDMA) scheme that uses DC H-ARQ is modeled and its performance is studied in this document; the performance analysis shows that the scheme performs better with DC and achieves a better energy efficiency at the cost of a higher delay. A novel cross-layered prefix-assisted Direct-Sequence Code Division Multiple Access (DS-CDMA) scheme is proposed and modeled in this document, it uses principles of DC and MUD. This protocol performs better by means of additional retransmissions, achieving better energy efficiency, at the cost of higher redundancy from a code spreading gain. Finally, a novel cross-layered protocol H-ARQ Network Division Multiple Access (H-NDMA) is proposed and modeled, where the combination of DC H-ARQ and MUD is used with the intent of maximizing the system capacity with a lower delay; system results show that the proposed scheme achieves better energy efficiency and a better performance at the cost of a higher number of retransmissions. A comparison of the three cross-layered protocols is made, using the PHY analytical model, under normalized conditions using the same amount of maximum redundancy. Results show that the H-NDMA protocol, in general, obtains the best results, achieving a good performance and a good energy efficiency for a high channel load and low Signal-to-Noise Ratio (SNR). TDMA with DC H-ARQ achieves the best energy efficiency, although presenting the worst delay. Prefix-assisted DS-CDMA in the other hand shows good delay results but presents the worst throughput and energy efficiency

Optimization based energy-efficient control inmobile communication networks

In this work we consider how best to control mobility and transmission for the purpose of datatransfer and aggregation in a network of mobile autonomous agents. In particular we considernetworks containing unmanned aerial vehicles (UAVs). We first consider a single link betweena mobile transmitter-receiver pair, and show that the total amount of transmittable data isbounded. For certain special, but not overly restrictive cases, we can determine closed-formexpressions for this bound, as a function of relevant mobility and communication parameters.We then use nonlinear model predictive control (NMPC) to jointly optimize mobility and trans-mission schemes of all networked nodes for the purpose of minimizing the energy expenditureof the network. This yields a novel nonlinear optimal control problem for arbitrary networksof autonomous agents, which we solve with state-of-the-art nonlinear solvers. Numerical re-sults demonstrate increased network capacity and significant communication energy savingscompared to more na ̈ıve policies. All energy expenditure of an autonomous agent is due tocommunication, computation, or mobility and the actual computation of the NMPC solutionmay be a significant cost in both time and computational resources. Furthermore, frequentbroadcasting of control policies throughout the network can require significant transmit andreceive energies. Motivated by this, we develop an event-triggering scheme which accounts forthe accuracy of the optimal control solution, and provides guarantees of the minimum timebetween successive control updates. Solution accuracy should be accounted for in any triggeredNMPC scheme where the system may be run in open loop for extended times based on pos-sibly inaccurate state predictions. We use this analysis to trade-off the cost of updating ourtransmission and locomotion policies, with the frequency by which they must be updated. Thisgives a method to trade-off the computation, communication and mobility related energies ofthe mobile autonomous network.Open Acces

Reliable load-balancing routing for resource-constrained wireless sensor networks

Wireless sensor networks (WSNs) are energy and resource constrained. Energy limitations make it advantageous to balance radio transmissions across multiple sensor nodes. Thus, load balanced routing is highly desirable and has motivated a significant volume of research. Multihop sensor network architecture can also provide greater coverage, but requires a highly reliable and adaptive routing scheme to accommodate frequent topology changes. Current reliability-oriented protocols degrade energy efficiency and increase network latency. This thesis develops and evaluates a novel solution to provide energy-efficient routing while enhancing packet delivery reliability. This solution, a reliable load-balancing routing (RLBR), makes four contributions in the area of reliability, resiliency and load balancing in support of the primary objective of network lifetime maximisation. The results are captured using real world testbeds as well as simulations. The first contribution uses sensor node emulation, at the instruction cycle level, to characterise the additional processing and computation overhead required by the routing scheme. The second contribution is based on real world testbeds which comprises two different TinyOS-enabled senor platforms under different scenarios. The third contribution extends and evaluates RLBR using large-scale simulations. It is shown that RLBR consumes less energy while reducing topology repair latency and supports various aggregation weights by redistributing packet relaying loads. It also shows a balanced energy usage and a significant lifetime gain. Finally, the forth contribution is a novel variable transmission power control scheme which is created based on the experience gained from prior practical and simulated studies. This power control scheme operates at the data link layer to dynamically reduce unnecessarily high transmission power while maintaining acceptable link reliability

COOPERATIVE NETWORKING AND RELATED ISSUES: STABILITY, ENERGY HARVESTING, AND NEIGHBOR DISCOVERY

This dissertation deals with various newly emerging topics in the context of cooperative networking. The first part is about the cognitive radio. To guarantee the performance of high priority users, it is important to know the activity of the high priority communication system but the knowledge is usually imperfect due to randomness in the observed signal. In such a context, the stability property of cognitive radio systems in the presence of sensing errors is studied. General guidelines on controlling the operating point of the sensing device over its receiver operating characteristics are also given. We then consider the hybrid of different modes of operation for cognitive radio systems with time-varying connectivity. The random connectivity gives additional chances that can be utilized by the low priority communication system. The second part of this dissertation is about the random access. We are specifically interested in the scenario when the nodes are harvesting energy from the environment. For such a system, we accurately assess the effect of limited, but renewable, energy availability on the stability region. The effect of finite capacity batteries is also studied. We next consider the exploitation of diversity amongst users under random access framework. That is, each user adapts its transmission probability based on the local channel state information in a decentralized manner. The impact of imperfect channel state information on the stability region is investigated. Furthermore, it is compared to the class of stationary scheduling policies that make centralized decisions based on the channel state feedback. The backpressure policy for cross-layer control of wireless multi-hop networks is known to be throughput-optimal for i.i.d. arrivals. The third part of this dissertation is about the backpressure-based control for networks with time-correlated arrivals that may exhibit long-range dependency. It is shown that the original backpressure policy is still throughput-optimal but with increased average network delay. The case when the arrival rate vector is possibly outside the stability region is also studied by augmenting the backpressure policy with the flow control mechanism. Lastly, the problem of neighbor discovery in a wireless sensor network is dealt. We first introduce the realistic effect of physical layer considerations in the evaluation of the performance of logical discovery algorithms by incorporating physical layer parameters. Secondly, given the lack of knowledge of the number of neighbors along with the lack of knowledge of the individual signal parameters, we adopt the viewpoint of random set theory to the problem of detecting the transmitting neighbors. Random set theory is a generalization of standard probability theory by assigning sets, rather than values, to random outcomes and it has been applied to multi-user detection problem when the set of transmitters are unknown and dynamically changing