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作者： Negin Fathollahnejad Asl Chalmers University of Technology

学位级别：博士

Vehicle-to-vehicle communication technologies support diverse cooperative applications for intelligent transportation systems to increase safety and fuel efficiency of road vehicles. Vehicles participating in a co- operative application are expected to make coordinated and mutually consistent decisions. To ensure consistency, it is often essential that the participating vehicles reach agreement on the data they use as a basis for these decisions. This thesis deals with the fundamental problem of reaching agreement on a value, or a set of values, in a distributed sys- tem in the presence of unrestricted communication failures. It is known from the literature that this problem is impossible to solve perfectly, i. e., no matter what algorithm we use there is always a non-zero probability of disagreement. Hence, our aim is to design algorithms that minimize the probability of disagreement. We propose and analyse several agree- ment algorithms to solve three fundamental consensus problems. These algorithms are distinguished by their decision criterion, which determine whether a computer should decide on a value or decide to abort. Our analyses show that the probability of disagreement depends strongly on the number of computers in the system, the number of rounds of mes- sage exchange, the choice of decision criterion, as well as the probability of message loss. We identify two types of disagreement, safe and unsafe disagreement, and show that unsafe disagreement can be avoided if all computers know the number of computers in the system.

关键词： agreement algorithms Probabilistic Analysis Consensus Vehicular Ad-Hoc Networks Communication Failure Intelligent Transportation Systems

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Towards an Extended Evolutionary Game Theory with Survival Analysis and agreement algorithms for Modeling Uncertainty, Vulnerability, and Deception

Towards an Extended Evolutionary Game Theory with Survival A...

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International Conference on Artificial Intelligence and Computational Intelligence

作者： Ma, Zhanshan (Sam) Univ Idaho IBEST Initiat Bioinformat & Evolutionary Studies Moscow ID 83843 USA

ISBN: (纸本)9783642052521

Competition, cooperation and communication are the three fundamental relationships upon which natural selection acts in the evolution of life. Evolutionary game theory (EGT) is a 'marriage' between game theory and Darwin's evolution theory;it gains additional modeling power and flexibility by adopting population dynamics theory. In EGT, natural selection acts as optimization agents and produces inherent strategies, which eliminates some essential assumptions in traditional game theory such as rationality and allows more realistic modeling of many problems. Prisoner's Dilemma (PD) and Sir Philip Sidney (SPS) games are two well-known examples of EGT, which are formulated to study cooperation and communication, respectively. Despite its huge success, EGT exposes a certain degree of weakness in dealing with time-, space- and covariate-dependent (i.e., dynamic) uncertainty, vulnerability and deception. In this paper. I propose to extend EGT in two ways to overcome the weakness. First. I introduce survival analysis modeling to describe the lifetime or fitness of game players. This extension allows more flexible and powerful modeling of the dynamic uncertainty and vulnerability (collectively equivalent to the dynamic frailty in survival analysis). Secondly, I introduce agreement algorithms, which can be the agreement algorithms in distributed computing, (e.g., Byzantine Generals Problem [6][8], Dynamic Hybrid Fault Models [12]) or any algorithms that set and enforce the rules for players to determine their consensus. The second extension is particularly useful for modeling dynamic deception (e.g., asymmetric faults in fault tolerance and deception in animal communication). From a computational perspective, the extended evolutionary game theory (EEGT) modeling, when implemented in simulation, is equivalent to an optimization methodology that is similar to evolutionary computing approaches such as Genetic algorithms with dynamic populations [15][17].

关键词： Evolutionary Game Theory Extended Evolutionary Game Theory Survival Analysis agreement algorithms Frailty Deception Dynamic Hybrid Fault Models UUUR (Uncertain, latent, Unobservable or Unobserved Risks) Strategic Information Warfare Reliability Security Survivability

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Dynamic Hybrid Fault Modeling and Extended Evolutionary Game Theory for Reliability, Survivability and Fault Tolerance Analyses

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IEEE TRANSACTIONS ON RELIABILITY 2011年第1期60卷 180-196页

作者： Ma, Zhanshan Sam Krings, Axel W. Chinese Acad Sci Lab Computat Biol & Bioinformat Kunming Inst Zool Beijing 100864 Peoples R China Univ Idaho Dept Computat Sci Moscow ID 83843 USA Univ Idaho Inst Bioinformat & Evolutionary STudies Moscow ID 83843 USA

We introduce a new layered modeling architecture consisting of dynamic hybrid fault modeling and extended evolutionary game theory for reliability, survivability, and fault tolerance analyses. The architecture extends traditional hybrid fault models and their relevant constraints in the agreement algorithms with survival analysis, and evolutionary game theory. The dynamic hybrid fault modeling (i) transforms hybrid fault models into time- and covariate-dependent models;(ii) makes real-time prediction of reliability more realistic, and allows for real-time prediction of fault-tolerance;(iii) sets the foundation for integrating hybrid fault models with reliability and survivability analyses by integrating them with evolutionary game modeling;and (iv) extends evolutionary game theory by stochastically modeling the survival (or fitness) and behavior of 'game players.' To analyse survivability, we extend dynamic hybrid fault modeling with a third-layer, operational level modeling, to develop the three-layer survivability analysis approach (dynamic hybrid fault modeling constitutes the tactical and strategic levels). From the perspective of evolutionary game modeling, the two mathematical fields, i. e., survival analysis and agreement algorithms, which we applied for developing dynamic hybrid fault modeling, can also be utilized to extend the power of evolutionary game theory in modeling complex engineering, biological (ecological), and social systems. Indeed, a common property of the areas where our extensions to evolutionary game theory can be advantageous is that the risk analysis and management are a core issue. Survival analysis (including competing risks analysis, and multivariate survival analysis) offers powerful modeling tools to analyse time-, space-, and/or covariate-dependent uncertainty, vulnerability, and/or frailty which 'game players' may experience. The agreement algorithms, which are not limited to the agreement algorithms from distributed computing, whe

关键词： agreement algorithms Byzantine generals problem dynamic hybrid fault models extended evolutionary game theory modeling fault tolerance reliability survivability survival analysis wireless sensor networks

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Dynamic Hybrid Fault Models and the Applications to Wireless Sensor Networks (WSNs)

Dynamic Hybrid Fault Models and the Applications to Wireless...

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11th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

作者： Ma, Zhanshan (Sam) Krings, Axel W. Univ Idaho Dept Comp Sci Moscow ID 83843 USA

ISBN: (纸本)9781605582351

In this paper, we introduce a new concept termed dynamic hybrid fault models together with the mathematic models and approaches for applying the new concept to reliability and fault tolerance analyses. It extends the traditional hybrid fault models and their relevant constraints in agreement algorithms with survival analysis and evolutionary game theory. The new dynamic hybrid fault models (i) transform hybrid fault models into time and covariate dependent models;(ii) make real-time prediction of reliability more realistic and allows for real-time prediction of fault-tolerance;(iii) set the foundations for integrating hybrid fault models with reliability and survivability analyses by introducing evolutionary game modeling;(iv) extend evolutionary game theory in its modeling of the survivals of game players. The application domain is wireless sensor network (WSN), but the large part of the modeling architecture also applies to general engineering reliability and network survivability.

关键词： Dynamic Hybrid Fault Models Hybrid Fault Models Wireless Sensor Networks agreement algorithms Reliability Survivability Evolutionary Game Theory Survival Analysis

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Approaches to asynchronous decentralized decision making

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COMPUTERS & CHEMICAL ENGINEERING 1999年第3期23卷 341-355页

作者： Androulakis, IP Reklaitis, GV Purdue Univ Sch Chem Engn W Lafayette IN 47907 USA

Motivated by the ideas of asynchronous relaxation algorithms this paper investigates optimal decision-making problems that exhibit decentralized characteristics. Such problems consist of a collection of interacting sub-systems, each one described by local properties and dynamics, joined together by the need to accomplish a common task which achieves overall optimal performance. Special properties of such systems that make them ideally suited for the framework of asynchronous computing are (a) the lack of a single overall objective describing the collective performance, and (b) the asynchronism in implementing topologically optimal decisions based on information which is local in space and time. A methodology for decentralized decision making is developed based on the solution of a series of sub-problems in which each minimizes a local objective while maximizing a common Lagrangian function, by generating independent approximations of an ascent direction in the space of the dual variables. The concepts are illustrated by means of motivating examples. (C) 1999 Elsevier Science Ltd. All rights reserved.

关键词： asynchronous distributed computing decision making agreement algorithms decentralized operations

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