Development of User Interface for the Management Server of Html5 Based Mobile Agent Framework

The emergence of World Wide Web as a widely used content-sharing environment and a rich software platform has revolutionized the life style of people across the globe. The Web is an archetypal commodity used by millions of people on daily basis, for a variety of online services that range from photos, music, videos, and online games to online shopping, online banking, e-marketing, e-communication, online business, etc. A web browser is the most frequently used application to access the above-mentioned services. The appearance of HTML5 has enabled more and more applications to run in the web browsers. Latest research in the field of Web and computer networks has given a rapid upsurge in the usage of web-based services for data storage and information exchange. This has resulted in challenges to develop efficient web-based systems, which can handle huge amount of information flow. One of the solutions to these challenges is mobile agents. A mobile agent is a software program that is able to migrate from one host to another to continue its execution. This thesis presents the development of a User Interface for the management server of an HTML5-based mobile agent platform. This platform was developed in 2012 at Tampere University of Technology and its second iteration was completed in 2013 at the same campus. The management server of the framework was without a user interface and could to be managed only from the command line. In this thesis, a web-browser based User Interface for the management server of the framework is developed. The management server exposes a Web API to manage the mobile agents and the agent servers through an HTTP interface. So, the API is leveraged by using JavaScript to make Ajax calls

DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL

To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments

Context storage using NoSQL

With the ubiquity and pervasiveness of mobile computing, together with the increasing number of social networks, end-users have learned to live and share all kinds of information about themselves. As an example, Facebook reports that it has currently 500 million active users, 200 million of which access its services on mobile systems; moreover, users that access Facebook through mobile applications are twice as active as non-mobile users, and it is used by 200 mobile operators in 60 countries [1]. More specific mobile platforms such as Foursquare, which unlike Facebook only collects location information, reports 6.5 million users worldwide, and also has a mobile presence (both with a web application and iPhone / Android applications) [2]. Context- aware architectures intend to explore this increasing number of context information sources and provide richer, targeted services to end-users, while also taking into account arising privacy issues. While multiple context management platform architectures have been devised [3], this paper focuses primarily on Context- Broker-based architectures, such as the ones proposed in the projects Mobilife [4] and C-Cast [5]. More specifically, it focuses on the context management platform XCoA [6]. This platform uses XMPP for its main communication protocol, and publishes context information in a Context-Broker. This context information is provided by Context-Agents, such as mobile terminals, sensor networks and social networks. Due to the nature of the XMPP protocol, the context information is provided in XML form. This paper proposes the usage of a NoSQL storage system for the purpose of context information storage and retrieval in an XMPP broker-based context platform such as XCoA, together with a full-text searching engine. Through a comparison made through prototypes, the paper clearly demonstrates the advantages of NoSQL storage systems applied to the area of Context Management

Towards a Framework for Developing Mobile Agents for Managing Distributed Information Resources

Distributed information management tools allow users to author, disseminate, discover and manage information within large-scale networked environments, such as the Internet. Agent technology provides the flexibility and scalability necessary to develop such distributed information management applications. We present a layered organisation that is shared by the specific applications that we build. Within this organisation we describe an architecture where mobile agents can move across distributed environments, integrate with local resources and other mobile agents, and communicate their results back to the user

Machining feature-based system for supporting step-compliant milling process

STEP standards aims at setting up a standard description method for product data and providing a neutral exchanging mechanism that is independent of all the information processing systems for product information model. STEP Part 21 is the first implementation method from EXPRESS language and implemented successfully in CAD data. However, this text file consists of purely geometrical and topological data is hardly to be applied in machining process planning which requires machining features enriched data. The aim of this research is developing a new methodology to translate the EXPRESS language model of CAD STEP data into a new product data representation and enriched in machining features which is more beneficial to machining process planning. In this research, a target Database Management System (DBMS) was proposed for developing this system by using its fourth-generation tools that allow rapid development of applications through the provision of nonprocedural query language, reports generators, form generators, graphics generators, and application generators. The use of fourth-generation tools can improve productivity significantly and produce program that are easier to maintain. From this research, a new product data representation in a compact new table format is generated. Then this new product data representation has gone through a series of data enrichment process, such as normal face direction generation, edge convexity/concavity determination and machining features with transition feature recognition. Lastly, this new enriched product data representation is verified by generating to a new STEP standard data format which is according to ISO1030-224 standard format and providing an important part of solution for supporting STEP-compliant process planning and applications in milling process

MAGDA: A Mobile Agent based Grid Architecture

Mobile agents mean both a technology and a programming paradigm. They allow for a flexible approach which can alleviate a number of issues present in distributed and Grid-based systems, by means of features such as migration, cloning, messaging and other provided mechanisms. In this paper we describe an architecture (MAGDA – Mobile Agent based Grid Architecture) we have designed and we are currently developing to support programming and execution of mobile agent based application upon Grid systems