168 research outputs found

    Incremental Discovery of Process Maps

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    Protsessikaeve on meetodite kogu, analüüsimaks protsesside teostuse jooksul loodud sündmuste logisid, et saada teavet nende parandamiseks. Protsessikaeve meetodite kogu, mida nimetatakse automatiseeritud protsessi avastuseks, lubab analüütikutel leida informatsiooni äriprotsesside mudelite kohta sündmuste logidest. Automatiseeritud protsessi avastusmeetodeid kasutatakse tavaliselt ühenduseta keskkonnas, mis tähendab, et protsessi mudel avastatakse hetketõmmisena tervest sündmuste logist. Samas on olukordi, kus uued juhtumid tulevad peale sellise suure kiirusega, et ei ole mõtet salvestada tervet sündmuste logi ja pidevalt nullist taasavastada mudelit. Selliste olukordade jaoks oleks vaja võrgus olevaid protsessi avastusmeetmeid. Andes sisendiks protsessi teostuse käigus loodud sündmuste voo, võrgus oleva protsessi avastusmeetodi eesmärk on järjepidevalt uuendada protsessi mudelit, tehes seda piiratud hulga mäluga ja säilitades sama täpsust, mida suudavad meetodid ühenduseta keskkondades. Olemasolevad meetodid vajavad palju mälu, et saavutada tulemusi, mis oleks võrreldavad ühenduseta keskkonnas saadud tulemustega. Käesolev lõputöö pakub välja võrgus oleva protsessi avastusraamistiku, ühtlustades protsessi avastus probleemi vähemälu haldusega ja kasutades vähemälu asenduspoliitikaid lahendamaks antud probleemi. Loodud raamistik on kirjutatud kasutades .NET-i, integreeritud Minit protsessikaeve tööriistaga ja analüüsitud kasutades elulisi ärijuhte.Process mining is a body of methods to analyze event logs produced during the execution of business processes in order to extract insights for their improvement. A family of process mining methods, known as automated process discovery, allows analysts to extract business process models from event logs. Traditional automated process discovery methods are intended to be used in an offline setting, meaning that the process model is extracted from a snapshot of an event log stored in its entirety. In some scenarios however, events keep coming with a high arrival rate to the extent that it is impractical to store the entire event log and to continuously re-discover a process model from scratch. Such scenarios require online automated process discovery approaches. Given an event stream produced by the execution of a business process, the goal of an online automated process discovery method is to maintain a continuously updated model of the process with a bounded amount of memory while at the same time achieving similar accuracy as offline methods. Existing automated discovery approaches require relatively large amounts of memory to achieve levels of accuracy comparable to that of offline methods. This thesis proposes a online process discovery framework that addresses this limitation by mapping the problem of online process discovery to that of cache memory management, and applying well-known cache replacement policies to the problem of online process discovery. The proposed framework has been implemented in .NET, integrated with the Minit process mining tool and comparatively evaluated against an existing baseline, using real-life datasets

    QoE on media deliveriy in 5G environments

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    231 p.5G expandirá las redes móviles con un mayor ancho de banda, menor latencia y la capacidad de proveer conectividad de forma masiva y sin fallos. Los usuarios de servicios multimedia esperan una experiencia de reproducción multimedia fluida que se adapte de forma dinámica a los intereses del usuario y a su contexto de movilidad. Sin embargo, la red, adoptando una posición neutral, no ayuda a fortalecer los parámetros que inciden en la calidad de experiencia. En consecuencia, las soluciones diseñadas para realizar un envío de tráfico multimedia de forma dinámica y eficiente cobran un especial interés. Para mejorar la calidad de la experiencia de servicios multimedia en entornos 5G la investigación llevada a cabo en esta tesis ha diseñado un sistema múltiple, basado en cuatro contribuciones.El primer mecanismo, SaW, crea una granja elástica de recursos de computación que ejecutan tareas de análisis multimedia. Los resultados confirman la competitividad de este enfoque respecto a granjas de servidores. El segundo mecanismo, LAMB-DASH, elige la calidad en el reproductor multimedia con un diseño que requiere una baja complejidad de procesamiento. Las pruebas concluyen su habilidad para mejorar la estabilidad, consistencia y uniformidad de la calidad de experiencia entre los clientes que comparten una celda de red. El tercer mecanismo, MEC4FAIR, explota las capacidades 5G de analizar métricas del envío de los diferentes flujos. Los resultados muestran cómo habilita al servicio a coordinar a los diferentes clientes en la celda para mejorar la calidad del servicio. El cuarto mecanismo, CogNet, sirve para provisionar recursos de red y configurar una topología capaz de conmutar una demanda estimada y garantizar unas cotas de calidad del servicio. En este caso, los resultados arrojan una mayor precisión cuando la demanda de un servicio es mayor

    BCOOL: A novel blockchain congestion control architecture using dynamic service function chaining and machine learning for next generation vehicular networks

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    ABSTRACT: This paper presents the first, novel, dynamic, resilient, and consistent Blockchain COngestion ContrOL (BCOOL) system for vehicular networks that fills the gap of trustworthy Blockchain congestion prediction systems. BCOOL relies on the heterogeneity of Machine Learning, Software-Defined Networks and Network Function Virtualization that is customized in three hybrid cloud/edge-based On/Offchain smart contract modules and ruled by an efficient and reliable communication protocol. BCOOL’s first novel module aims at managing message and vehicle trustworthiness using a novel, dynamic and hybrid Blockchain Fogbased Distributed Trust Contract Strategy (FDTCS). The second novel module accurately and proactively predicts the occurrence of congestion, ahead of time, using a novel Hybrid On/Off-Chain Multiple Linear Regression Software-defined Contract Strategy (HOMLRCS). This module presents a virtualization facility layer to the third novel K-means/Random Forest-based On/Off-Chain Dynamic Service Function Chaining Contract Strategy (KRF-ODSFCS) that dynamically, securely and proactively predicts VNF placements and their chaining order in the context of SFCs w.r.t users’ dynamic QoS priority demands. BCOOL exhibits a linear complexity and a strong resilience to failures. Simulation results show that BCOOL outperforms the next best comparable strategies by 80% and 100% reliability and efficiency gains in challenging data congestion environments. This yields to fast, reliable and accurate congestion prediction decisions, ahead of time, and optimizes transaction validation processing time. Globally, the Byzantine resilience, complexity and attack mitigation strategies along with simulation results prove that BCOOL securely predicts the congestion and provides real-time monitoring, fast and accurate SFC deployment decisions while lowering both capital and operational expenditures (CAPEX/OPEX) costs

    Ecocinema Theory and Practice 2

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    This second volume builds on the initial groundwork laid by Ecocinema Theory and Practice by examining the ways in which ecocritical cinema studies have matured and proliferated over the last decade, opening whole new areas of study and research. Featuring fourteen new essays organized into three sections around the themes of cinematic materialities, discourses, and communities, the volume explores a variety of topics within ecocinema studies from examining specific national and indigenous film contexts to discussing ecojustice, environmental production studies, film festivals, and political ecology. The breadth of the contributions exemplifies how ecocinema scholars worldwide have sought to overcome the historical legacy of binary thinking and intellectual norms and are working to champion new ecocritical, intersectional, decolonial, queer, feminist, Indigenous, vitalist, and other emergent theories and cinematic practices. The collection also demonstrates the unique ways that cinema studies scholarship is actively addressing environmental injustice and the climate crisis. This book is an invaluable resource for students and scholars of ecocritical film and media studies, production studies, cultural studies, and environmental studies
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