TOSNet : a topic-based optimal subnetwork identification in academic networks

Subnetwork identification plays a significant role in analyzing, managing, and comprehending the structure and functions in big networks. Numerous approaches have been proposed to solve the problem of subnetwork identification as well as community detection. Most of the methods focus on detecting communities by considering node attributes, edge information, or both. This study focuses on discovering subnetworks containing researchers with similar or related areas of interest or research topics. A topic- aware subnetwork identification is essential to discover potential researchers on particular research topics and provide qualitywork. Thus, we propose a topic-based optimal subnetwork identification approach (TOSNet). Based on some fundamental characteristics, this paper addresses the following problems: 1)How to discover topic-based subnetworks with a vigorous collaboration intensity? 2) How to rank the discovered subnetworks and single out one optimal subnetwork? We evaluate the performance of the proposed method against baseline methods by adopting the modularity measure, assess the accuracy based on the size of the identified subnetworks, and check the scalability for different sizes of benchmark networks. The experimental findings indicate that our approach shows excellent performance in identifying contextual subnetworks that maintain intensive collaboration amongst researchers for a particular research topic. © 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved

The Impact of Petri Nets on System-of-Systems Engineering

The successful engineering of a large-scale system-of-systems project towards deterministic behaviour depends on integrating autonomous components using international communications standards in accordance with dynamic requirements. To-date, their engineering has been unsuccessful: no combination of top-down and bottom-up engineering perspectives is adopted, and information exchange protocol and interfaces between components are not being precisely specified. Various approaches such as modelling, and architecture frameworks make positive contributions to system-of-systems specification but their successful implementation is still a problem. One of the most popular modelling notations available for specifying systems, UML, is intuitive and graphical but also ambiguous and imprecise. Supplying a range of diagrams to represent a system under development, UML lacks simulation and exhaustive verification capability. This shortfall in UML has received little attention in the context of system-of-systems and there are two major research issues: 1. Where the dynamic, behavioural diagrams of UML can and cannot be used to model and analyse system-of-systems 2. Determining how Petri nets can be used to improve the specification and analysis of the dynamic model of a system-of-systems specified using UML This thesis presents the strengths and weaknesses of Petri nets in relation to the specification of system-of-systems and shows how Petri net models can be used instead of conventional UML Activity Diagrams. The model of the system-of-systems can then be analysed and verified using Petri net theory. The Petri net formalism of behaviour is demonstrated using two case studies from the military domain. The first case study uses Petri nets to specify and analyse a close air support mission. This case study concludes by indicating the strengths, weaknesses, and shortfalls of the proposed formalism in system-of-systems specification. The second case study considers specification of a military exchange network parameters problem and the results are compared with the strengths and weaknesses identified in the first case study. Finally, the results of the research are formulated in the form of a Petri net enhancement to UML (mapping existing activity diagram elements to Petri net elements) to meet the needs of system-of-systems specification, verification and validation

Enabling Resilience in Cyber-Physical-Human Water Infrastructures

Rapid urbanization and growth in urban populations have forced community-scale infrastructures (e.g., water, power and natural gas distribution systems, and transportation networks) to operate at their limits. Aging (and failing) infrastructures around the world are becoming increasingly vulnerable to operational degradation, extreme weather, natural disasters and cyber attacks/failures. These trends have wide-ranging socioeconomic consequences and raise public safety concerns. In this thesis, we introduce the notion of cyber-physical-human infrastructures (CPHIs) - smart community-scale infrastructures that bridge technologies with physical infrastructures and people. CPHIs are highly dynamic stochastic systems characterized by complex physical models that exhibit regionwide variability and uncertainty under disruptions. Failures in these distributed settings tend to be difficult to predict and estimate, and expensive to repair. Real-time fault identification is crucial to ensure continuity of lifeline services to customers at adequate levels of quality. Emerging smart community technologies have the potential to transform our failing infrastructures into robust and resilient future CPHIs.In this thesis, we explore one such CPHI - community water infrastructures. Current urban water infrastructures, that are decades (sometimes over a 100 years) old, encompass diverse geophysical regimes. Water stress concerns include the scarcity of supply and an increase in demand due to urbanization. Deterioration and damage to the infrastructure can disrupt water service; contamination events can result in economic and public health consequences. Unfortunately, little investment has gone into modernizing this key lifeline.To enhance the resilience of water systems, we propose an integrated middleware framework for quick and accurate identification of failures in complex water networks that exhibit uncertain behavior. Our proposed approach integrates IoT-based sensing, domain-specific models and simulations with machine learning methods to identify failures (pipe breaks, contamination events). The composition of techniques results in cost-accuracy-latency tradeoffs in fault identification, inherent in CPHIs due to the constraints imposed by cyber components, physical mechanics and human operators. Three key resilience problems are addressed in this thesis; isolation of multiple faults under a small number of failures, state estimation of the water systems under extreme events such as earthquakes, and contaminant source identification in water networks using human-in-the-loop based sensing. By working with real world water agencies (WSSC, DC and LADWP, LA), we first develop an understanding of operations of water CPHI systems. We design and implement a sensor-simulation-data integration framework AquaSCALE, and apply it to localize multiple concurrent pipe failures. We use a mixture of infrastructure measurements (i.e., historical and live water pressure/flow), environmental data (i.e., weather) and human inputs (i.e., twitter feeds), combined and enhanced with the domain model and supervised learning techniques to locate multiple failures at fine levels of granularity (individual pipeline level) with detection time reduced by orders of magnitude (from hours/days to minutes). We next consider the resilience of water infrastructures under extreme events (i.e., earthquakes) - the challenge here is the lack of apriori knowledge and the increased number and severity of damages to infrastructures. We present a graphical model based approach for efficient online state estimation, where the offline graph factorization partitions a given network into disjoint subgraphs, and the belief propagation based inference is executed on-the-fly in a distributed manner on those subgraphs. Our proposed approach can isolate 80% broken pipes and 99% loss-of-service to end-users during an earthquake.Finally, we address issues of water quality - today this is a human-in-the-loop process where operators need to gather water samples for lab tests. We incorporate the necessary abstractions with event processing methods into a workflow, which iteratively selects and refines the set of potential failure points via human-driven grab sampling. Our approach utilizes Hidden Markov Model based representations for event inference, along with reinforcement learning methods for further refining event locations and reducing the cost of human efforts.The proposed techniques are integrated into a middleware architecture, which enables components to communicate/collaborate with one another. We validate our approaches through a prototype implementation with multiple real-world water networks, supply-demand patterns from water utilities and policies set by the U.S. EPA. While our focus here is on water infrastructures in a community, the developed end-to-end solution is applicable to other infrastructures and community services which operate in disruptive and resource-constrained environments

A theoretical model of the relationship between the h-index and other simple citation indicators

Of the existing theoretical formulas for the h-index, those recently suggested by Burrell (J Informetr 7: 774-783, 2013b) and by Bertoli-Barsotti and Lando (J Informetr 9(4): 762-776, 2015) have proved very effective in estimating the actual value of the h-index Hirsch (Proc Natl Acad Sci USA 102: 16569-16572, 2005), at least at the level of the individual scientist. These approaches lead (or may lead) to two slightly different formulas, being based, respectively, on a "standard'' and a "shifted'' version of the geometric distribution. In this paper, we review the genesis of these two formulas-which we shall call the "basic'' and "improved'' Lambert-W formula for the h-index-and compare their effectiveness with that of a number of instances taken from the well-known Glanzel-Schubert class of models for the h-index (based, instead, on a Paretian model) by means of an empirical study. All the formulas considered in the comparison are "ready-to-use'', i.e., functions of simple citation indicators such as: the total number of publications; the total number of citations; the total number of cited paper; the number of citations of the most cited paper. The empirical study is based on citation data obtained from two different sets of journals belonging to two different scientific fields: more specifically, 231 journals from the area of "Statistics and Mathematical Methods'' and 100 journals from the area of "Economics, Econometrics and Finance'', totaling almost 100,000 and 20,000 publications, respectively. The citation data refer to different publication/citation time windows, different types of "citable'' documents, and alternative approaches to the analysis of the citation process ("prospective'' and "retrospective''). We conclude that, especially in its improved version, the Lambert-W formula for the h-index provides a quite robust and effective ready-to-use rule that should be preferred to other known formulas if one's goal is (simply) to derive a reliable estimate of the h-index.Web of Science11131448141

Contributions to the deadlock problem in multithreaded software applications observed as Resource Allocation Systems

Desde el punto de vista de la competencia por recursos compartidos sucesivamente reutilizables, se dice que un sistema concurrente compuesto por procesos secuenciales está en situación de bloqueo si existe en él un conjunto de procesos que están indefinidamente esperando la liberación de ciertos recursos retenidos por miembros del mismo conjunto de procesos. En sistemas razonablemente complejos o distribuidos, establecer una política de asignación de recursos que sea libre de bloqueos puede ser un problema muy difícil de resolver de forma eficiente. En este sentido, los modelos formales, y particularmente las redes de Petri, se han ido afianzando como herramientas fructíferas que permiten abstraer el problema de asignación de recursos en este tipo de sistemas, con el fin de abordarlo analíticamente y proveer métodos eficientes para la correcta construcción o corrección de estos sistemas. En particular, la teoría estructural de redes de Petri se postula como un potente aliado para lidiar con el problema de la explosión de estados inherente a aquéllos. En este fértil contexto han florecido una serie de trabajos que defienden una propuesta metodológica de diseño orientada al estudio estructural y la correspondiente corrección física del problema de asignación de recursos en familias de sistemas muy significativas en determinados contextos de aplicación, como el de los Sistemas de Fabricación Flexible. Las clases de modelos de redes de Petri resultantes asumen ciertas restricciones, con significado físico en el contexto de aplicación para el que están destinadas, que alivian en buena medida la complejidad del problema. En la presente tesis, se intenta acercar ese tipo de aproximación metodológica al diseño de aplicaciones software multihilo libres de bloqueos. A tal efecto, se pone de manifiesto cómo aquellas restricciones procedentes del mundo de los Sistemas de Fabricación Flexible se muestran demasiado severas para aprehender la versatilidad inherente a los sistemas software en lo que respecta a la interacción de los procesos con los recursos compartidos. En particular, se han de resaltar dos necesidades de modelado fundamentales que obstaculizan la mera adopción de antiguas aproximaciones surgidas bajo el prisma de otros dominios: (1) la necesidad de soportar el anidamiento de bucles no desplegables en el interior de los procesos, y (2) la posible compartición de recursos no disponibles en el arranque del sistema pero que son creados o declarados por un proceso en ejecución. A resultas, se identifica una serie de requerimientos básicos para la definición de un tipo de modelos orientado al estudio de sistemas software multihilo y se presenta una clase de redes de Petri, llamada PC2R, que cumple dicha lista de requerimientos, manteniéndose a su vez respetuosa con la filosofía de diseño de anteriores subclases enfocadas a otros contextos de aplicación. Junto con la revisión e integración de anteriores resultados en el nuevo marco conceptual, se aborda el estudio de propiedades inherentes a los sistemas resultantes y su relación profunda con otros tipos de modelos, la confección de resultados y algoritmos eficientes para el análisis estructural de vivacidad en la nueva clase, así como la revisión y propuesta de métodos de resolución de los problemas de bloqueo adaptadas a las particularidades físicas del dominio de aplicación. Asimismo, se estudia la complejidad computacional de ciertas vertientes relacionadas con el problema de asignación de recursos en el nuevo contexto, así como la traslación de los resultados anteriormente mencionados sobre el dominio de la ingeniería de software multihilo, donde la nueva clase de redes permite afrontar problemas inabordables considerando el marco teórico y las herramientas suministradas para subclases anteriormente explotadas

Search-based system architecture development using a holistic modeling approach

This dissertation presents an innovative approach to system architecting where search algorithms are used to explore design trade space for good architecture alternatives. Such an approach is achieved by integrating certain model construction, alternative generation, simulation, and assessment processes into a coherent and automated framework. This framework is facilitated by a holistic modeling approach that combines the capabilities of Object Process Methodology (OPM), Colored Petri Net (CPN), and feature model. The resultant holistic model can not only capture the structural, behavioral, and dynamic aspects of a system, allowing simulation and strong analysis methods to be applied, it can also specify the architectural design space. Both object-oriented analysis and design (OOA/D) and domain engineering were exploited to capture design variables and their domains and define architecture generation operations. A fully realized framework (with genetic algorithms as the search algorithm) was developed. Both the proposed framework and its suggested implementation, including the proposed holistic modeling approach and architecture alternative generation operations, are generic. They are targeted at systems that can be specified using object-oriented or process-oriented paradigm. The broad applicability of the proposed approach is demonstrated on two examples. One is the configuration of reconfigurable manufacturing systems (RMSs) under multi-objective optimization and the other is the architecture design of a manned lunar landing system for the Apollo program. The test results show that the proposed approach can cover a huge number of architecture alternatives and support the assessment of several performance measures. A set of quality results was obtained after running the optimization algorithm following the proposed framework --Abstract, page iii

Model-based provisioning and management of adaptive distributed communication in mobile cooperative systems

Adaptation of communication is required to maintain the reliable connection and to ensure the minimum quality in collaborative activities. Within the framework of wireless environment, how can host entities be handled in the event of a sudden unexpected change in communication and reliable sources? This challenging issue is addressed in the context of Emergency rescue system carried out by mobile devices and robots during calamities or disaster. For this kind of scenario, this book proposes an adaptive middleware to support reconfigurable, reliable group communications. Here, the system structure has been viewed at two different states, a control center with high processing power and uninterrupted energy level is responsible for global task and entities like autonomous robots and firemen owning smart devices act locally in the mission. Adaptation at control center is handled by semantic modeling whereas at local entities, it is managed by a software module called communication agent (CA). Modeling follows the well-known SWRL instructions which establish the degree of importance of each communication link or component. Providing generic and scalable solutions for automated self-configuration is driven by rule-based reconfiguration policies. To perform dynamically in changing environment, a trigger mechanism should force this model to take an adaptive action in order to accomplish a certain task, for example, the group chosen in the beginning of a mission need not be the same one during the whole mission. Local entity adaptive mechanisms are handled by CA that manages internal service APIs to configure, set up, and monitors communication services and manages the internal resources to satisfy telecom service requirements

Energy-Efficient Neural Network Architectures

Emerging systems for artificial intelligence (AI) are expected to rely on deep neural networks (DNNs) to achieve high accuracy for a broad variety of applications, including computer vision, robotics, and speech recognition. Due to the rapid growth of network size and depth, however, DNNs typically result in high computational costs and introduce considerable power and performance overheads. Dedicated chip architectures that implement DNNs with high energy efficiency are essential for adding intelligence to interactive edge devices, enabling them to complete increasingly sophisticated tasks by extending battery lie. They are also vital for improving performance in cloud servers that support demanding AI computations. This dissertation focuses on architectures and circuit technologies for designing energy-efficient neural network accelerators. First, a deep-learning processor is presented for achieving ultra-low power operation. Using a heterogeneous architecture that includes a low-power always-on front-end and a selectively-enabled high-performance back-end, the processor dynamically adjusts computational resources at runtime to support conditional execution in neural networks and meet performance targets with increased energy efficiency. Featuring a reconfigurable datapath and a memory architecture optimized for energy efficiency, the processor supports multilevel dynamic activation of neural network segments, performing object detection tasks with 5.3x lower energy consumption in comparison with a static execution baseline. Fabricated in 40nm CMOS, the processor test-chip dissipates 0.23mW at 5.3 fps. It demonstrates energy scalability up to 28.6 TOPS/W and can be configured to run a variety of workloads, including severely power-constrained ones such as always-on monitoring in mobile applications. To further improve the energy efficiency of the proposed heterogeneous architecture, a new charge-recovery logic family, called zero-short-circuit current (ZSCC) logic, is proposed to decrease the power consumption of the always-on front-end. By relying on dedicated circuit topologies and a four-phase clocking scheme, ZSCC operates with significantly reduced short-circuit currents, realizing order-of-magnitude power savings at relatively low clock frequencies (in the order of a few MHz). The efficiency and applicability of ZSCC is demonstrated through an ANSI S1.11 1/3 octave filter bank chip for binaural hearing aids with two microphones per ear. Fabricated in a 65nm CMOS process, this charge-recovery chip consumes 13.8µW with a 1.75MHz clock frequency, achieving 9.7x power reduction per input in comparison with a 40nm monophonic single-input chip that represents the published state of the art. The ability of ZSCC to further increase the energy efficiency of the heterogeneous neural network architecture is demonstrated through the design and evaluation of a ZSCC-based front-end. Simulation results show 17x power reduction compared with a conventional static CMOS implementation of the same architecture.PHDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147614/1/hsiwu_1.pd

Protecting Networked Systems from Malware Threats

Currently, networks and networked systems are essential media for us to communicate with other people, access resources, and share information. Reading (or sending) emails, navigating web sites, and uploading pictures to social medias are common behaviors using networks. Besides these, networks and networked systems are used to store or access sensitive or private information. In addition, major economic activities, such as buying food and selling used cars, can also be operated with networks. Likewise, we live with networks and networked systems. As network usages are increasing and popular, people face the problems of net- work attacks. Attackers on the networks can steal people’s private information, mislead people to pay money for fake products, and threaten people, who operate online commercial sites, by bothering their services. There are much more diverse types of network attacks that torture many people using networks, and the situation is still serious. The proposal in this dissertation starts from the following two research questions: (i) what kind of network attack is prevalent and how we can investigate it and (ii) how we can protect our networks and networked systems from these attacks. Therefore, this dissertation spans two main areas to provide answers for each question. First, we analyze the behaviors and characteristics of large-scale bot infected hosts, and it provides us new findings of network malware and new insights that are useful to detect (or defeat) recent network threats. To do this, we investigate the characteristics of victims infected by recent popular botnet - Conficker, MegaD, and Srizbi. In addition, we propose a method to detect these bots by correlating network and host features. Second, we suggest new frameworks to make our networks secure based on the new network technology of Software Defined Networking (SDN). Currently, SDN technology is considered as a future major network trend, and it can dynamically program networks as we want. Our suggested frameworks for SDN can be used to devise network security applications easily, and we also provide an approach to make SDN technology secure