113 research outputs found
Advancements in Adversarially-Resilient Consensus and Safety-Critical Control for Multi-Agent Networks
The capabilities of and demand for complex autonomous multi-agent systems, including networks of unmanned aerial vehicles and mobile robots, are rapidly increasing in both research and industry settings. As the size and complexity of these systems increase, dealing with faults and failures becomes a crucial element that must be accounted for when performing control design. In addition, the last decade has witnessed an ever-accelerating proliferation of adversarial attacks on cyber-physical systems across the globe. In response to these challenges, recent years have seen an increased focus on resilience of multi-agent systems to faults and adversarial attacks. Broadly speaking, resilience refers to the ability of a system to accomplish control or performance objectives despite the presence of faults or attacks. Ensuring the resilience of cyber-physical systems is an interdisciplinary endeavor that can be tackled using a variety of methodologies. This dissertation approaches the resilience of such systems from a control-theoretic viewpoint and presents several novel advancements in resilient control methodologies. First, advancements in resilient consensus techniques are presented that allow normally-behaving agents to achieve state agreement in the presence of adversarial misinformation. Second, graph theoretic tools for constructing and analyzing the resilience of multi-agent networks are derived. Third, a method for resilient broadcasting vector-valued information from a set of leaders to a set of followers in the presence of adversarial misinformation is presented, and these results are applied to the problem of propagating entire knowledge of time-varying Bezier-curve-based trajectories from leaders to followers. Finally, novel results are presented for guaranteeing safety preservation of heterogeneous control-affine multi-agent systems with sampled-data dynamics in the presence of adversarial agents.PHDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/168102/1/usevitch_1.pd
Consensus Computation in Unreliable Networks: A System Theoretic Approach
This work addresses the problem of ensuring trustworthy computation in a
linear consensus network. A solution to this problem is relevant for several
tasks in multi-agent systems including motion coordination, clock
synchronization, and cooperative estimation. In a linear consensus network, we
allow for the presence of misbehaving agents, whose behavior deviate from the
nominal consensus evolution. We model misbehaviors as unknown and unmeasurable
inputs affecting the network, and we cast the misbehavior detection and
identification problem into an unknown-input system theoretic framework. We
consider two extreme cases of misbehaving agents, namely faulty (non-colluding)
and malicious (Byzantine) agents. First, we characterize the set of inputs that
allow misbehaving agents to affect the consensus network while remaining
undetected and/or unidentified from certain observing agents. Second, we
provide worst-case bounds for the number of concurrent faulty or malicious
agents that can be detected and identified. Precisely, the consensus network
needs to be 2k+1 (resp. k+1) connected for k malicious (resp. faulty) agents to
be generically detectable and identifiable by every well behaving agent. Third,
we quantify the effect of undetectable inputs on the final consensus value.
Fourth, we design three algorithms to detect and identify misbehaving agents.
The first and the second algorithm apply fault detection techniques, and
affords complete detection and identification if global knowledge of the
network is available to each agent, at a high computational cost. The third
algorithm is designed to exploit the presence in the network of weakly
interconnected subparts, and provides local detection and identification of
misbehaving agents whose behavior deviates more than a threshold, which is
quantified in terms of the interconnection structure
Recommended from our members
Algorithm Based Fault Tolerance in Massively Parallel Systems
An A complex computer system consists of billions of transistors, miles of wires, and many interactions with an unpredictable environment. Correct results must be produced despite faults that dynamically occur in some of these components. Many techniques have been developed for fault tolerant computation. General purpose methods are independent of the application, yet incur an overhead cost which may be unacceptable for massively parallel systems. Algorithm-specific methods, which can operate at lower cost, are a developing alternative [1, 72]. This paper first reviews the general-purpose approach and then focuses on the algorithm-specific method, with an eye toward massively parallel processors. Algorithm-based fault tolerance has the attraction of low overhead; furthermore it addresses both the detection and also the correction problems. The principle is to build low-cost checking and correcting mechanism based exclusively on the redundancies inherent in the system
The interaction network : a performance measurement and evaluation tool for loosely-coupled distributed systems
Much of today's computing is done on loosely-coupled distributed systems. Performance issues for such systems usually involve interactive performance, that is, system responsiveness as perceived by the user. The goal of the work described in this thesis has been to develop and implement tools and techniques for the measurement and evaluation of interactive performance in loosely-coupled distributed systems.
The author has developed the concept of the interaction network, an acyclic directed graph designed to represent the processing performed by a distributed system in response to a user input. The definition of an interaction network is based on a general model of a loosely-coupled distributed system and a general model of user interactions. The author shows that his distributed system model is a valid abstraction for a wide range of present-day systems.
Performance monitors for traditional time-sharing systems reported performance information, such as overall resource utilisations and queue lengths, for the system as a whole. Performance problems are now much more difficult, because systems are much more complex. Recent monitors designed specifically for distributed systems have tended to present performance information for execution of a distributed program, for example the time spent in each of a program's procedures. In the work described in this thesis, performance information is reported for one or more user interactions, where a user interaction is defined to be a single user input and all of the processing performed by the system on receiving that input. A user interaction is seen as quite different from a program execution; a user interaction includes the partial or total execution of one or more programs, and a program execution performs work as part of one or more user interactions.
Several methods are then developed to show how performance information can be obtained from analysis of interaction networks. One valuable type of performance information is a decomposition of response time into times spent in each of some set of states, where each state might be defined in terms of the hardware and software resources used. Other performance information can be found from displays of interaction networks. The critical path through an interaction network is then defined as showing the set of activities such that at least one must be reduced in length if the response time of the interaction is to be reduced; the critical path is used in both response time decompositions and in displays of interaction networks.
It was thought essential to demonstrate that interaction networks could be recorded for a working operating system. INMON, a prototype monitor based on the interaction network concept, has been constructed to operate in the SunOS environment. INMON consists of data collection and data analysis components. The data collection component, for example, involved the adding of 53 probes to the SunOS operating system kernel.
To record interaction networks, a high-resolution global timebase is needed. A clock synchronisation program has been written to provide INMON with such a timebase. It is suggested that the method incorporates a number of improvements over other clock synchronisation methods.
Several experiments have been performed to show that INMON can produce very detailed performance information for both individual user interactions and groups of user interactions, with user input being made through either character-based or graphical interfaces.
The main conclusion reached in this thesis is that representing the processing component of a user interaction in an interaction network is a very valuable way of approaching the problem of measuring interactive performance in a loosely-coupled distributed system. An interaction network contains a very detailed record of the execution of an interaction and, from this record, a great deal of performance (and other) information can be derived. Construction of INMON has demonstrated that interaction networks can be identified, recorded, and analysed
Analysis of Embedded Controllers Subject to Computational Overruns
Microcontrollers have become an integral part of modern everyday embedded systems, such as smart bikes, cars, and drones. Typically, microcontrollers operate under real-time constraints, which require the timely execution of programs on the resource-constrained hardware. As embedded systems are becoming increasingly more complex, microcontrollers run the risk of violating their timing constraints, i.e., overrunning the program deadlines. Breaking these constraints can cause severe damage to both the embedded system and the humans interacting with the device. Therefore, it is crucial to analyse embedded systems properly to ensure that they do not pose any significant danger if the microcontroller overruns a few deadlines.However, there are very few tools available for assessing the safety and performance of embedded control systems when considering the implementation of the microcontroller. This thesis aims to fill this gap in the literature by presenting five papers on the analysis of embedded controllers subject to computational overruns. Details about the real-time operating system's implementation are included into the analysis, such as what happens to the controller's internal state representation when the timing constraints are violated. The contribution includes theoretical and computational tools for analysing the embedded system's stability, performance, and real-time properties.The embedded controller is analysed under three different types of timing violations: blackout events (when no control computation is completed during long periods), weakly-hard constraints (when the number of deadline overruns is constrained over a window), and stochastic overruns (when violations of timing constraints are governed by a probabilistic process). These scenarios are combined with different implementation policies to reduce the gap between the analysis and its practical applicability. The analyses are further validated with a comprehensive experimental campaign performed on both a set of physical processes and multiple simulations.In conclusion, the findings of this thesis reveal that the effect deadline overruns have on the embedded system heavily depends the implementation details and the system's dynamics. Additionally, the stability analysis of embedded controllers subject to deadline overruns is typically conservative, implying that additional insights can be gained by also analysing the system's performance
Topics in access, storage, and sensor networks
In the first part of this dissertation, Data Over Cable Service Interface Specification (DOCSIS) and IEEE 802.3ah Ethernet Passive Optical Network (ETON), two access networking standards, are studied. We study the impact of two parameters of the DOCSIS protocol and derive the probability of message collision in the 802.3ah device discovery scheme. We survey existing bandwidth allocation schemes for EPONs, derive the average grant size in one such scheme, and study the performance of the shortest-job-first heuristic.
In the second part of this dissertation, we study networks of mobile sensors. We make progress towards an architecture for disconnected collections of mobile sensors. We propose a new design abstraction called tours which facilitates the combination of mobility and communication into a single design primitive and enables the system of sensors to reorganize into desirable topologies alter failures. We also initiate a study of computation in mobile sensor networks. We study the relationship between two distributed computational models of mobile sensor networks: population protocols and self-similar functions. We define the notion of a self-similar predicate and show when it is computable by a population protocol.
Transition graphs of population protocols lead its to the consideration of graph powers. We consider the direct product of graphs and its new variant which we call the lexicographic direct product (or the clique product). We show that invariants concerning transposable walks in direct graph powers and transposable independent sets in graph families generated by the lexicographic direct product are uncomputable.
The last part of this dissertation makes contributions to the area of storage systems. We propose a sequential access detect ion and prefetching scheme and a dynamic cache sizing scheme for large storage systems. We evaluate the cache sizing scheme theoretically and through simulations. We compute the expected hit ratio of our and competing schemes and bound the expected size of our dynamic cache sufficient to obtain an optimal hit ratio. We also develop a stand-alone simulator for studying our proposed scheme and integrate it with an empirically validated disk simulator
- …