Mobile agent based distributed network management : modeling, methodologies and applications

The explosive growth of the Internet and the continued dramatic increase for all wireless services are fueling the demand for increased capacity, data rates, support of multimedia services, and support for different Quality of Services (QoS) requirements for different classes of services. Furthermore future communication networks will be strongly characterized by heterogeneity. In order to meet the objectives of instant adaptability to the users\u27 requirements and of interoperability and seamless operation within the heterogeneous networking environments, flexibility in terms of network and resource management will be a key design issue. The new emerging technology of mobile agent (MA) has arisen in the distributed programming field as a potential flexible way of managing resources of a distributed system, and is a challenging opportunity for delivering more flexible services and dealing with network programmability. This dissertation mainly focuses on: a) the design of models that provide a generic framework for the evaluation and analysis of the performance and tradeoffs of the mobile agent management paradigm; b) the development of MA based resource and network management applications. First, in order to demonstrate the use and benefits of the mobile agent based management paradigm in the network and resource management process, a commercial application of a multioperator network is introduced, and the use of agents to provide the underlying framework and structure for its implementation and deployment is investigated. Then, a general analytical model and framework for the evaluation of various network management paradigms is introduced and discussed. It is also illustrated how the developed analytical framework can be used to quantitatively evaluate the performances and tradeoffs in the various computing paradigms. Furthermore, the design tradeoffs for choosing the MA based management paradigm to develop a flexible resource management scheme in wireless networks is discussed and evaluated. The integration of an advanced bandwidth reservation mechanism with a bandwidth reconfiguration based call admission control strategy is also proposed. A framework based on the technology of mobile agents, is introduced for the efficient implementation of the proposed integrated resource and QoS management, while the achievable performance of the overall proposed management scheme is evaluated via modeling and simulation. Finally the use of a distributed cooperative scheme among the mobile agents that can be applied in the future wireless networks is proposed and demonstrated, to improve the energy consumption for the routine management processes of mobile terminals, by adopting the peer-to-peer communication concept of wireless ad-hoc networks. The performance evaluation process and the corresponding numerical results demonstrate the significant system energy savings, while several design issues and tradeoffs of the proposed scheme, such as the fairness of the mobile agents involved in the management activity, are discussed and evaluated

Energy Efficient Designs for Collaborative Signal and Information Processing inWireless Sensor Networks

Collaborative signal and information processing (CSIP) plays an important role in the deployment of wireless sensor networks. Since each sensor has limited computing capability, constrained power usage, and limited sensing range, collaboration among sensor nodes is important in order to compensate for each other’s limitation as well as to improve the degree of fault tolerance. In order to support the execution of CSIP algorithms, distributed computing paradigm and clustering protocols, are needed, which are the major concentrations of this dissertation. In order to facilitate collaboration among sensor nodes, we present a mobile-agent computing paradigm, where instead of each sensor node sending local information to a processing center, as is typical in the client/server-based computing, the processing code is moved to the sensor nodes through mobile agents. We further conduct extensive performance evaluation versus the traditional client/server-based computing. Experimental results show that the mobile agent paradigm performs much better when the number of nodes is large while the client/server paradigm is advantageous when the number of nodes is small. Based on this result, we propose a hybrid computing paradigm that adopts different computing models within different clusters of sensor nodes. Either the client/server or the mobile agent paradigm can be employed within clusters or between clusters according to the different cluster configurations. This new computing paradigm can take full advantages of both client/server and mobile agent computing paradigms. Simulations show that the hybrid computing paradigm performs better than either the client/server or the mobile agent computing. The mobile agent itinerary has a significant impact on the overall performance of the sensor network. We thus formulate both the static mobile agent planning and the dynamic mobile agent planning as optimization problems. Based on the models, we present three itinerary planning algorithms. We have showed, through simulation, that the predictive dynamic itinerary performs the best under a wide range of conditions, thus making it particularly suitable for CSIP in wireless sensor networks. In order to facilitate the deployment of hybrid computing paradigm, we proposed a decentralized reactive clustering (DRC) protocol to cluster the sensor network in an energy-efficient way. The clustering process is only invoked by events occur in the sensor network. Nodes that do not detect the events are put into the sleep state to save energy. In addition, power control technique is used to minimize the transmission power needed. The advantages of DRC protocol are demonstrated through simulations

Framework for supporting JavaScript-Based Mobile Agents

The evolution of technology in interconnection solutions, such as networks or the Internet, and the emergence both of wireless sensors networks and distributed systems allowed many communication architectures to appear, being the Client-server architecture the most common. Here, we present a dissertation work about the mobile agents computing paradigm. A middleware and a mobile agent framework have been developed using the JavaScript language that allows the development, execution and the ability to move JavaScript mobile agents through the local network and Internet using Node.js for desktop operating systems and React Native for mobile operating systems, such as Android and iOS. This initiative arose as a way of dealing with problems raised by the considerable amount of existing Java based mobile agents platforms, which force the installation of the Java Virtual Machine on the devices, making complicated its execution in operating systems like macOS, iOS and others operating systems not compatible with Java

The migration process of mobile agents: implementation, classification, and optimization

Mobile Agenten stellen ein neues faszinierendes Design-Paradigma für den Aufbau und die Programmierung von verteilten Systemen dar. Ein mobiler Agent ist eine Software-Entität, die von ihrem Besitzer mit einem Auftrag auf einem Knoten eines verteilten Systems gestartet wird und dann zur Laufzeit auf andere Knoten des Netzwerkes migriert. Diese Arbeit konzentriert sich auf den Migrationsprozess für mobile Agenten, dem in der Literatur bisher wenig Aufmerksamkeit geschenkt wurde, obwohl er die Ausführungsgeschwindigkeit eines Agenten entscheidend beeinflusst. Eine detaillierte Analyse der Netzbelastung von mobilen Agenten im Vergleich zum traditionellen Client-Server Ansatz in mehreren typischen Anwendungsszenarien zeigt das Potential von mobilen Agenten zur Verringerung von Verarbeitungszeiten. Allerdings zeigt die Analyse ebenso die Nachteile der in heutigen Agentensystemen verwendenten sehr einfachen Migrationstechniken. Es wird ein neues Migrationsmodell mit Namen Kalong vorgestellt, das den Nachteil der fehlenden Anpassbarkeit heutiger Agentensysteme beseitigt und dem Programmierer eines mobilen Agenten eine sehr flexible Technik für die Migration zur Verfügung stellt

Mobile agent security and reliability issues in electronic commerce.

Chan, Hing-wing.Thesis (M.Phil.)--Chinese University of Hong Kong, 2000.Includes bibliographical references (leaves 76-79).Abstracts in English and Chinese.Abstract --- p.iAbstract (Chinese) --- p.iiAcknowledgements --- p.iiiContents --- p.ivList of Figures --- p.viiList of Tables --- p.viiiChapter Chapter 1. --- Introduction --- p.1Chapter 1.1. --- Mobile Agents and the Problems --- p.1Chapter 1.2. --- Approach --- p.3Chapter 1.3. --- Contributions --- p.3Chapter 1.4. --- Organization of This Thesis --- p.4Chapter Chapter 2. --- The Mobile Code Paradigm --- p.6Chapter 2.1. --- Mobile Code: an Alternative to Client/Servers --- p.6Chapter 2.1.1. --- Classification of Mobile Codes --- p.8Chapter 2.1.2. --- Applications of Mobile Code Paradigms --- p.10Chapter 2.1.3. --- Supporting Implementation Technologies --- p.11Chapter 2.2. --- The Problems of Mobile Code --- p.13Chapter 2.2.1. --- Security Issues in Distributed Systems --- p.13Chapter 2.2.2. --- Security Concerns of Mobile Code Paradigms --- p.15Chapter 2.2.2.1. --- Security Attacks --- p.15Chapter 2.2.2.2. --- Security Mechanisms --- p.17Chapter 2.2.2.3. --- A Security Comparison between Paradigms --- p.20Chapter 2.2.3. --- Security Features of Implementation Technologies --- p.20Chapter 2.2.3.1. --- Security Services of Message-based Technology --- p.21Chapter 2.2.3.2. --- Security Services of Object-based Technology --- p.21Chapter 2.2.3.3. --- Security Services of Mobile Technology --- p.22Chapter 2.2.3.4. --- A Comparison of Technologies on Security Services --- p.22Chapter 2.3. --- Chapter Summary --- p.23Chapter Chapter 3. --- "Mobile Agents, Its Security and Reliability Issues" --- p.24Chapter 3.1. --- Advantages and Applications of Mobile Agents --- p.24Chapter 3.2. --- Security Concerns of Mobile Agents --- p.26Chapter 3.2.1. --- Host Security --- p.27Chapter 3.2.2. --- Agent Security --- p.27Chapter 3.3. --- Techniques to Protect Mobile Agents --- p.29Chapter 3.3.1. --- Protected Agent States --- p.29Chapter 3.3.2. --- Mobile Cryptography --- p.30Chapter 3.4. --- Reliability Concerns of Mobile Agents --- p.31Chapter Chapter 4. --- Security and Reliability Modeling for Mobile Agents --- p.32Chapter 4.1. --- Attack Model and Scenarios --- p.33Chapter 4.2. --- General Security Models --- p.34Chapter 4.2.1. --- Security and Reliability --- p.34Chapter 4.2.2. --- Deriving Security Models --- p.36Chapter 4.2.3. --- The Time-to-Effort Function --- p.38Chapter 4.3. --- A Security Model for Mobile Agents --- p.40Chapter 4.4. --- Discussion of the Proposed Model --- p.43Chapter 4.5. --- A Reliability Model for Mobile Agents --- p.43Chapter Chapter 5. --- The Concordia Mobile Agent Platform --- p.46Chapter 5.1. --- Overview --- p.46Chapter 5.2. --- Special Features --- p.47Chapter Chapter 6. --- SIAS: A Shopping Information Agent System --- p.49Chapter 6.1. --- What the System Does --- p.49Chapter 6.2. --- System Design --- p.50Chapter 6.2.1. --- Object Description --- p.50Chapter 6.2.2. --- Flow Description --- p.52Chapter 6.3. --- Implementation --- p.53Chapter 6.3.1. --- Choice of Programming Language --- p.53Chapter 6.3.2. --- Choice of Mobile Agent Platform --- p.53Chapter 6.3.3. --- Other Implementation Details --- p.54Chapter 6.4. --- Snapshots --- p.54Chapter 6.5. --- Security Design of SIAS --- p.57Chapter 6.5.1. --- Security Problems of SIAS --- p.58Chapter 6.5.2. --- Our Solutions to the Problems --- p.60Chapter 6.5.3. --- Evaluation of the Secure SIAS --- p.64Chapter 6.5.3.1. --- Security Analysis --- p.64Chapter 6.5.3.2. --- Performance Vs Query Size --- p.65Chapter 6.5.3.3. --- Performance Vs Number of Hosts --- p.67Chapter 6.6. --- Reliability Design of SIAS --- p.69Chapter 6.6.1. --- Reliability Problems of SIAS --- p.69Chapter 6.6.2. --- Our Solutions to the Problems --- p.70Chapter 6.6.3. --- Evaluation of the Reliable SIAS --- p.71Chapter Chapter 7. --- Conclusions and Future Work --- p.73Bibliography --- p.7

Performance Analysis of Mobile Agents for Filtering Data Streams on Wireless Networks

Wireless networks are an ideal environment for mobile agents, since their mobility allows them to move across an unreliable link to reside on a wired host, next to or closer to the resources that they need to use. Furthermore, client-specific data transformations can be moved across the wireless link and run on a wired gateway server, reducing bandwidth demands. In this paper we examine the tradeoffs faced when deciding whether to use mobile agents in a data-filtering application where numerous wireless clients filter information from a large data stream arriving across the wired network. We develop an analytical model and use parameters from filtering experiments conducted during a U.S. Navy Fleet Battle Experiment (FBE) to explore the model\u27s implications

An introduction of small-scale intelligent manufacturing system

Embargoed OA, manuscript version after 24 months from publishing date. Link to publishers version: http://doi.org/10.1109/SIMS.2016.7802896Manufacturing companies in Northern Peripheral and Arctic region are predominately small and medium-sized and face considerable challenges like geographical isolation and a lack of benefits offered by industrial clusters. For the ultimate goal of enhancing their competitiveness in a global market, it is imperative for companies to innovate or adopt innovations in order to quickly response to changes in market, meet customer demands, reduce time-to-market and lower cost. A novel concept for small-scale intelligent manufacturing systems (SIMS) is introduced, in which diverse methods and innovative technologies can be applied and integrated. This paper gives an introduction of SIMS, defines its design objectives, and summarizes major relevant tools, techniques and paradigms for the development of SIMS, to generate a facilitative environment for small and medium-scale manufacturing enterprises to embrace new and innovative technologies