Networked Control Systems (NCS) are distributed control systems where the sensor signals to the controllers and the control data to the actuators are enclosed in messages and sent over a communication network. On the one hand, the design of an NCS requires ensuring the stability of the control system and achieving system response that is as close as possible to that of an ideal system which demands network resources. On the other hand, these resources are limited and have to be allocated efficiently to accommodate for future system extensions as well as applications other than control purpose. Furthermore the NCS design parameters for the control system messages and the message transmission over the network are interdependent. In this thesis, we propose &ldquo / Integrated NCS Design (INtERCEDE: Integrated NEtwoRked Control systEm DEsign)&rdquo / a novel algorithmic approach for the design of NCS which ensures the stability of the control system, brings system response to that of an ideal system v as close as desired and conserves network bandwidth at the same time. The core of INtERCEDE is a bargaining game approach which iteratively calculates the message parameters and network service parameters. Our experimental results demonstrate the operation of INtERCEDE and how it computes the optimal design parameters for the example NCS.

Der Trend auch für schnelle, zeitkritische Regelungsaufgaben geht zunehmend in Richtung Feldbusse und Industrial Ethernet. Dem unbestreitbaren Nutzen der Kosteneinsparung stehen Probleme gegenüber: Die unsicheren Zeitbedingungen im Netz verschlechtern die dynamischen Eigenschaften digitaler Regelungen in unvorhersehbarer Weise. Diese Arbeit stellt eine praktikable Methodik vor, um die Regelgüte solcher Systeme sicher und aufwandsarm vorherzusagen. / High dynamic, i.e. time-critical automatic feedback control systems are more and more implemented using field bus or industrial ethernet solutions. The cost-efficiency of these approaches is unchallengeable, but they also cause serious technical problems: Uncertain time behavior of data networks so far degrades the dynamic performance of digital closed-loop controls in an unpredictable manner. The research paper introduces a practicable, reliable and straightforward method to forecast the system behavior.

As institutional and professional journalism faces increasing uncertainty about its financial security and social influence, it is also being challenged by emerging forms of networked journalism that rely on open, network-based flows of information. In 2010, one of those networked groups, WikiLeaks, rose to prominence through a series of large, high-profile leaks of government information. Drawing on the concepts of paradigm repair and professional boundary work, this study examined the way numerous professional news organizations portrayed WikiLeaks as being beyond the bounds of professional journalism. Through a textual analysis of discourse about WikiLeaks from the group’s inception in 2006 through early 2011, the study found that the American professional news media depicted WikiLeaks as unreliable, unstable deviants who maliciously and indiscriminately released information rather than properly performing journalism. The discourse portrayed WikiLeaks as being outside journalism’s professional norms in four primary areas: institutionality, reporter-source relationships, original reporting, and objectivity. In doing so, professional journalists defended those domains against WikiLeaks’ networked alternative, reasserting their own social value and authority by arguing for the superiority of their professional journalistic model. Discourse from professional media criticism, conservative and liberal alternative news media, and European journalism was also examined, using the response to WikiLeaks to help form a a map of several areas of the journalistic sphere in terms of their adherence to the paradigmatic tenets of professional journalism. The WikiLeaks case provides a useful guide for evaluating future interactions between professional and networked journalism, particularly professional journalism’s evolving self-definition vis-à-vis its emerging networked counterpart. / text

Scalable system monitoring is a fundamental abstraction for large-scale networked systems. The goal of this dissertation is to design and build a scalable monitoring middleware that provides system introspection for large distributed systems and that will facilitate the design, development, and deployment of distributed monitoring applications. This middleware will enable monitoring applications to flexibly control the tradeoff between result precision and communication cost and to improve result accuracy in the face of node failures, network delays, and system reconfigurations. We present PRISM (PRecision-Integrated Scalable Monitoring), a scalable monitoring middleware that provides a global aggregate view of large-scale networked systems and that can serve as a building block for a broad range of distributed monitoring applications by coordinating views of multiple vantage points across the network. To coordinate a global view for system introspection, PRISM faces two key challenges: (1) scalability to large systems and high data volumes and (2) safeguarding accuracy in the face of node and network failures. To address these challenges, we design, implement, and evaluate PRISM, a system that defines precision as a new unified abstraction to enable scalable monitoring. PRISM quantifies (im)precision along a three-dimensional vector: arithmetic imprecision (AI) and temporal imprecision (TI) balance precision against monitoring overhead for scalability while network imprecision (NI) addresses the challenge of providing consistency guarantees despite failures. Our prototype implementation of PRISM addresses the challenge of providing these metrics while scaling to a large number of nodes and attributes by (1) leveraging Distributed Hash Tables (DHTs) to create scalable aggregation trees, (2) self-tuning AI budgets across nodes in a principled, near-optimal manner to shift precision to where it is useful, (3) pipelining TI delays across tree levels to maximize batching of updates, and (4) applying dual-tree prefix aggregation which exploits symmetry in our DHT topology to drastically reduce the cost of the active probing needed to maintain NI. Through extensive simulations and experiments on four large-scale testbeds, we observe that PRISM provides a key substrate for scalable monitoring by (1) reducing monitoring load by up to two orders of magnitude compared to existing approaches, (2) providing a flexible framework to control the tradeoff between accuracy, bandwidth cost, and response latency, (3) characterizing and improving confidence in the accuracy of results in the face of system disruptions, and (4) improving the observed accuracy by up to an order of magnitude despite churn. We have built several monitoring applications on top of PRISM including a distributed heavy hitter detection service, a distributed monitoring service for Internet-scale systems, and a detection service for monitoring distributed-denial-of-service (DDoS) attacks at the source-side in distributed networked systems. Finally, we demonstrate how the unified precision abstraction enables new monitoring applications by presenting experiences from these applications. / text

ITC/USA 2013 Conference Proceedings / The Forty-Ninth Annual International Telemetering Conference and Technical Exhibition / October 21-24, 2013 / Bally's Hotel & Convention Center, Las Vegas, NV / High speed real-time data transportation is most important for telemetry systems, especially for large-scale distributed systems. This paper introduces a STDM (Sync Time Division Multiplexing) network structure for data transportation between devices in telemetry systems. The data in these systems is transported through virtual channels between devices. In addition, a proper frame format is designed based on PCM format to meet the needs of synchronization and real-time transportation in large-scale distributed telemetry systems.

We analyze spatio-temporal routing under various constraints specific to multi-robot applications. Spatio-temporal routing requires multiple robots to visit spatial locations at specified time instants, while optimizing certain criteria like the total distance traveled, or the total energy consumed. Such a spatio-temporal concept is intuitively demonstrable through music (e.g. a musician routes multiple fingers to play a series of notes on an instrument at specified time instants). As such, we showcase much of our work on routing through this medium. Particular to robotic applications, we analyze constraints like maximum velocities that the robots cannot exceed, and information-exchange networks that must remain connected. Furthermore, we consider a notion of heterogeneity where robots and spatial locations are associated with multiple skills, and a robot can visit a location only if it has at least one skill in common with the skill set of that location. To extend the scope of our work, we analyze spatio-temporal routing in the context of a distributed framework, and a dynamic environment.

Today is an exciting time to be a political activist in sub-Saharan Africa, particularly for the technically inclined. New media technologies including the mobile phone, the Internet, and social media are proliferating rapidly and their potential as potent political tools is being realized. While 2012's Arab Spring in North Africa captivated the world, similar campaigns have been occurring south of the Sahara both before and since. But the embrace of social media for political ends raises the question of how, if at all, these new media actually perturb the political landscape. These questions have been well-studied in Western contexts, but remain virtually unexplored in developing regions where traditional media are scarcer, democracies are younger, and the effect of social media on politics has the potential to be quite distinct. This dissertation explores these questions by focusing on social media use during elections in Nigeria and Liberia in 2011. It asks how social media impacted the democratic process during these key events, and compares social media discourse to formal election monitoring operations. The findings suggest that given sufficient civil-society coordination, social media can be an effective tool for electoral scrutiny. Furthermore, for this and other reasons, it appears that social media has the potential to emerge as a key influence on public faith in electoral processes. Based on these results, it is further argued that social media's true disruptive power in developing world contexts lies in its ability to transcend the economics of scarcity that have dominated traditional media in such contexts. This observation is offered as an extension to the networked public sphere theory of Yochai Benkler that frames this work.

Networked control systems (NCSs) are feedback control systems with the feedback control loops closed via network. The origin of the term NCSs is from industrial systems where the plant and controller are often connected through networks. The applications of NCSs cover a wide range of industries, for example, manufactory automation, domestic robots, aircraft, automobiles and tele-operations. The research activities in NCSs are focused on the following three areas: control of networks, control over networks and multi-agent systems. Control of networks is mainly concerned with the problem of how to efficiently utilize the network resource by controlling and routing the network data flows. Control over networks is mainly concerned with the design of feedback control strategies of control systems in which signals are transmitted through unreliable communication links. Multi-agent systems deal with two problems: how the topology of the network connections between each component influences global control goals and how to design local control law describing the behavior of each individual to achieve the global control goal of the whole systems. The objective in this thesis is to deal with control over networks and multi-agent systems. The most challenging problem in the control over networks field is that the unreliable communication channels can degrade system performance greatly. The main unreliable properties of networks are delays and packet loss. In order to deal with this problem, a Lyapunov-based method has been used to design the sampled-data stabilization control strategy for a networked single system by choosing proper delay and packet loss dependent Lyapunov functional candidates. Linear matrix inequality techniques have been used to find the sufficient and necessary conditions for the controller design. Furthermore, the consensus formation control problem of multiple robotic vehicle systems has been investigated. The consensus-based design scheme has been applied to the formation control of multiple wheeled mobile-robot group with a virtual leader. A novel delay-dependent Lyapunov functional candidate has been constructed to investigate the convergence of the system states. The proposed control strategy is experimentally implemented for multiple wheeled mobile robots under neighbor-to-neighbor information exchange with group communication delays involved. In conclusion, through the simulation results and experimental validations, the proposed new Lyapunov-based control methods can effectively deal with the networked control systems discussed in this thesis.

No description available.

Modern industrial control systems use a multitude of spatially distributed sensors and actuators to continuously monitor and control physical processes. Information exchange among control system components is traditionally done through physical wires. The need to physically wire sensors and actuators limits flexibility, scalability and reliability, since the cabling cost is high, cable connectors are prone to wear and tear, and connector failures can be hard to isolate. By replacing some of the cables with wireless communication networks, costs and risks of connector failures can be decreased, resulting in a more cost-efficient and reliable system. Integrating wireless communication into industrial control systems is challenging, since wireless communication channels introduce imperfections such as stochastic delays and information losses. These imperfections deteriorate the closed-loop control performance, and may even cause instability. In this thesis, we aim at developing design frameworks that take these imperfections into account and improve the performance of closed-loop control systems. The thesis first considers the joint design of packet forwarding policies and controllers for wireless control loops where sensor measurements are sent to the controller over an unreliable and energy-constrained multi-hop wireless network. For a fixed sampling rate of the sensor, the co-design problem separates into two well-defined and independent subproblems: transmission scheduling for maximizing the deadline-constrained reliability and optimal control under packet losses. We develop optimal and implementable solutions for these subproblems and show that the optimally co-designed system can be obtained efficiently. The thesis continues by examining event-triggered control systems that can help to reduce the energy consumption of the network by transmitting data less frequently. To this end, we consider a stochastic system where the communication between the controller and the actuator is triggered by a threshold-based rule. The communication is performed across an unreliable link that stochastically erases transmitted packets. As a partial protection against dropped packets, the controller sends a sequence of control commands to the actuator in each packet. These commands are stored in a buffer and applied sequentially until the next control packet arrives. We derive analytical expressions that quantify the trade-off between the communication cost and the control performance for this class of event-triggered control systems. The thesis finally proposes a supervisory control structure for wireless control systems with time-varying delays. The supervisor has access to a crude indicator of the overall network state, and we assume that individual upper and lower bounds on network time-delays can be associated to each value of the indicator. Based on this information, the supervisor triggers the most appropriate controller from a multi-controller unit. The performance of such a supervisory controller allows for improving the performance over a single robust controller. As the granularity of the network state measurements increases, the performance of the supervisory controller improves at the expense of increased computational complexity. / <p>QC 20150504</p>