An adaptive communication model for mobile agents in highly dynamic networks based on forming flexible regions via swarming behabiour

Im letzten Jahrzehnt gilt die mobile Agententechnologie als eines der wichtigsten Forschungsgebiete der Informatik. Mobile Agenten sind Software, die Aufträge im Namen ihrer Besitzer erfüllen können (ZK02). Mobile Agenten können selbstbestimmend von Server zu Server migrieren, sie können ihren Arbeitsstand speichern und dann ihre Arbeit am neuen Aufenthaltsort fortsetzen. Ihre wichtigsten Merkmale sind: autonom, reaktiv, opportunistisch und zielgerichtet. Diese genannten Merkmale sind für verteilte Anwendungen geeignet, z. B: Ressourcenverteilung (TYI99), Netzwerkmanagement (MT99), E-Commerce (BGP05), Fernüberwachung CMCV02), Gesundheitssysteme (Mor06), um nur einige zu nennen. Es ist die Mobilität der Agenten, die mobile Agenten zu einer guten Computing Technologie macht (Pau02). Kommunikation ist wesentlich in verteilten Systemen, und dies gilt auch für mobile Agentensysteme (LHL02). Neben den eher technischen Aspekten mobiler Agententechnologien, wie Migration (Bra03) und Kontrollmechanismen (Bau00), wurde die Kommunikation zwischen den Agenten als eine der wichtigsten Komponenten in der mobilen Agententechnologie identifiziert (FLP98). Es ist diskutiert worden, ob Agentenkommunikation ausschließlich lokal sein sollte, angesichts der Tatsache, dass mobile Agenten erfunden wurden, weil man die Verarbeitung zu den Daten tragen möchte, anstatt umgekehrt (SS97). Allerdings hat es sich gezeigt, dass es in vielen Fällen lohnt, wenn die mobilen Agenten kommunizieren anstatt migrieren (BHR+97),(FLP98),(ea02). Kommunikation hilft mobilen Agenten, eine bessere Leistung zu erreichen (Erf04). Kommunikation ist daher aus unserer Sicht die Basis mobiler Agentensysteme. An der Friedrich-Schiller-Universität Jena ist das interdisziplinäre Projekt SpeedUp seit April 2009 durchgeführt worden (FSU11). Das Projekt entwickelt ein Unterstützungssystem für Rettungs- und Einsatzkräfte bei einem Massenanfall von Verletzten (MANV). Im Projekt ist das Konzept mobiler Agenten als eine der Basistechnologien ausgesucht worden. Die hohe Netzwerkdynamik stellt neue Herausforderungen für mobile Agentensysteme dar, die in MANV Rettungsszenarien arbeiten. Es wird erwartet, dass die Kommunikation sich an die dynamische Umgebung zur Ausführungszeit anpassen kann. Dazu fehlen heute tragfähige Konzepte. In dieser Arbeit wird daher ein Ansatz zur adaptiven Kommunikation mobiler Agenten in hochdynamischen Netzwerken des SpeedUp-Typs vorgestellt. Nach unserer Beurteilung sollte die Kommunikation zwischen den mobilen Agenten nicht nur Interoperabilität und Standortunabhängigkeit, sondern auch Anpassungsfähigkeit aufweisen. Wir schlagen ein Kommunikationsmodell vor, das sich auf den koordinierenden Aspekt und das Zusammenspiel der Agenten konzentriert, sowie die Zuverlässigkeit und die Fehlertoleranz unterstützt. Um die Netzwerkdynamik zu managen, planen wir einen selbstorganisierten Mechanismus zu verwenden, der sich ”honey bee” inspiriertes Verfahren nennt. Wir werden dazu eine Software für ein adaptives Kommunikationsmodell mobiler Agenten, basierend auf das mobile Agentensystem Ellipsis gestalten, implementieren, und evaluieren.In the last decade, mobile agent technology has been considered as one of the most active research fields in computer science. Mobile agents are software agents which run on behalf of their owner to fulfil jobs that have been ordered (ZK02). They have the ability to migrate from location to location in the network, they can temporarily save their work state at the time of migrating and then restore their tasks when arriving at the new location. Their outstanding characteristics are to be autonomous, reactive, opportunistic, and goal-oriented. Those characteristics are suitable for distributed applications, such as resource allocation (TYI99), network management (MT99), remote supervision (CMCV02), e-commerce (BGP05), health care systems (Mor06), to name but a few. It is the mobility of mobile agents that makes them to be a powerful computing technique, especially for pervasive computing (Pau02). Communication is an essential component of distributed systems and this is no exception for multiagent systems (LHL02). Besides technical aspects of mobile agent technology, such as migrations (Bra03) and control mechanisms (Bau00), communication between mobile agents has been identified as an important issue in mobile agent technology (FLP98). It has been argued whether agent communication should be remote or restricted to local, considering that the main reason for the birth of mobile agents was to move computation to the data instead of moving the data to the computation. Therefore, remote communication could be avoided completely (SS97). However, it has been shown that in many cases mobile agent systems can benefit from performing communication instead of sending agents to remote platforms (BHR+97),(FLP98),(ea02). The communication between agents helps to increase the chance that an agent attains its objectives (Erf04). Communication is one of the bases of multi-agent systems; it is difficult, if not impossible for a group of agents to solve tasks without communication (Hel03). At Friedrich Schiller University Jena, an interdisciplinary project, named SpeedUp, for the support of handling mass casualty incidents (MCI) has been in development since April 2009 (FSU11). In the project the mobile agent concept has been selected as one of the main technologies on the communication infrastructure level. The dynamic nature of MCI networks poses new challenges to mobile systems working in a rescue scenario. For mobile agent systems working in highly dynamic networks, communication between mobile agents is expected to adapt easily to environmental stimuli which occur at execution time. Much research has been done into the design of an appropriate, highly flexible model for mobile agent communication in dynamic networks. However, to the best of our knowledge none of the suggested solutions has been able to achieve the necessary performance and quality attributes to count as a practical solution. In most cases, these existing approaches seem to neglect the inherent dynamics of modern networks. In this dissertation, we present our approach for an adaptive communication model for mobile agent systems in highly dynamic networks of the SpeedUp type. In our opinion, communication in mobile agent systems should deal not only with interoperability and location-transparency, but also with adaptability. To achieve industrial strength, we propose a model for agent communication that focuses on the cooperation aspect of agent interaction and supports reliability and fault tolerance as the key qualities, while keeping up an acceptable overall performance at the same time. For the management of highly dynamic communication domains we use a self-organizing mechanism, a so-called honey bee inspired algorithm. In order to ensure message delivery, we propose a resilient mechanism for the management of a mobile agent’s location. Based on this thesis, we will design, implement and evaluate a software prototype for an adaptive model for mobile agent communication based on the Ellipsis mobile agent system

The English and Vietnamese of Vietnamese immigrants in the US

This study focuses on the Vietnamese community in Texas, aiming to explore the characteristics of English and Vietnamese languages among Vietnamese Americans in the United States when the two languages are in contact. The research investigates cross-linguistic interactions, particularly in vowel production and question formation, with a focus on generational differences within the community. The findings contribute to our understanding of language contact outcomes in immigrant diasporic communities, shedding light on linguistic and social factors influencing language varieties. The study's insights can enhance cultural understanding and integration efforts for Vietnamese immigrants in the U.S. The study conducted within the Vietnamese community in Texas reveals positive indicators for the future maintenance of the Vietnamese heritage language (HL) within the community. While there are variations in perspectives across generations due to different social and linguistic exposures, the overall attitude within this Vietnamese American com-munity is optimistic about using and preserving the Vietnamese HL in the U.S. Participants express pride in speaking the language and a strong desire to maintain it in their host country. Key factors identified for HL maintenance include its role as a communicative tool, facilitating connections with older generations in the family and community, and its identity value. Effective HL maintenance strategies identified in the study involve speaking the heritage language at home and enrolling children in HL classes. Cross-linguistic interac-tions were found to impact oral language production, with differences between the first language (L1) and second language (L2) and language proficiency being significant driv-ing factors. While participants tended to select standard question structures in both English and Vietnamese when assessing different sets of structures, spontaneous speech revealed a tendency to use more non-standard features than perceived. The study also presents characteristics of English and Vietnamese questions among Vietnamese Americans across generations. In English, first-generation speakers commonly exhibited non-standard features such as Subject- Auxiliary inversion, verb conjugation is-sues, and plural noun problems. Vietnamese questions by Vietnamese Americans often involved non-standard features related to verb conjugation, interrogative words/phrases, and word choice, with second-generation speakers facing challenges in using copula verbs and interrogative word placement.Includes bibliographical references

Directional Dense-Trajectory-based Patterns for Dynamic Texture Recognition

International audienceRepresentation of dynamic textures (DTs), well-known as a sequence of moving textures, is a challenging problem in video analysis due to disorientation of motion features. Analyzing DTs to make them "under-standable" plays an important role in different applications of computer vision. In this paper, an efficient approach for DT description is proposed by addressing the following novel concepts. First, beneficial properties of dense trajectories are exploited for the first time to efficiently describe DTs instead of the whole video. Second, two substantial extensions of Local Vector Pattern operator are introduced to form a completed model which is based on complemented components to enhance its performance in encoding directional features of motion points in a trajectory. Finally, we present a new framework, called Directional Dense Trajectory Patterns , which takes advantage of directional beams of dense trajectories along with spatio-temporal features of their motion points in order to construct dense-trajectory-based descriptors with more robustness. Evaluations of DT recognition on different benchmark datasets (i.e., UCLA, DynTex, and DynTex++) have verified the interest of our proposal

Improving Texture Categorization with Biologically Inspired Filtering

Within the domain of texture classification, a lot of effort has been spent on local descriptors, leading to many powerful algorithms. However, preprocessing techniques have received much less attention despite their important potential for improving the overall classification performance. We address this question by proposing a novel, simple, yet very powerful biologically-inspired filtering (BF) which simulates the performance of human retina. In the proposed approach, given a texture image, after applying a DoG filter to detect the "edges", we first split the filtered image into two "maps" alongside the sides of its edges. The feature extraction step is then carried out on the two "maps" instead of the input image. Our algorithm has several advantages such as simplicity, robustness to illumination and noise, and discriminative power. Experimental results on three large texture databases show that with an extremely low computational cost, the proposed method improves significantly the performance of many texture classification systems, notably in noisy environments. The source codes of the proposed algorithm can be downloaded from https://sites.google.com/site/nsonvu/code.Comment: 11 page

Development of a Planning and Analysis Tool for Wireless Mesh Network

The aim of this project, "Development of Wireless Mesh Network Planning and Analysis Tool", is to create a GUI-oriented modeler for wireless mesh network planning and analysis. The main purpose of network planning is to provide a costeffective solution in term of two objectives which are coverage and capacity. Network planning covers a wide range of issues from coverage (base station or access point) to core network system. It will develop a tool, using Java programming language, which provides functions to help users do planning setting up a desired wireless mesh network and also techniques to analyze the system

Ellipse detection through decomposition of circular arcs and line segments

International audienceIn this work we propose an efficient and original method for ellipse detection which relies on a recent contour representation based on arcs and line segments \cite{NguyenD11a}. The first step of such a detection is to locate ellipse candidate with a grouping process exploiting geometric properties of adjacent arcs and lines. Then, for each ellipse candidate we extract a compact and significant representation defined from the segment and arc extremities together with the arc middle points. This representation allows then a fast ellipse detection by using a simple least square technique. Finally some first comparisons with other robust approaches are proposed

Noise Tolerant Descriptor for Texture Classification

International audienceAmong many texture descriptors, the LBP-based representation emerged as an attractive approach thanks to its low complexity and effectiveness. Many variants have been proposed to deal with several limitations of the basic approach like the small spatial support or the noise sensitivity. This paper presents a new method to construct an effective texture descriptor addressing those limitations by combining three features: (1) a circular average filter is applied before calculating the Complemented Local Binary Pattern (CLBP), (2) the histogram of CLBPs is calculated by weighting the contribution of every local pattern according to the gradient magnitude, and (3) the image features are calculated at different scales using a pyramidal framework. An efficient calculation of the pyramid using integral images, together with a simple construction of the multi-scale histogram based on concatenation, make the proposed approach both fast and memory efficient. Experimental results on different texture classification databases show the good results of the method, and its excellent noise robustness, compared to recent LBP-based methods