Evolution of network computing paradigms: applications of mobile agents in wired and wireless networks

The World Wide Web (or Web for short) is the largest client-server computing system commonly available, which is used through its widely accepted universal client (the Web browser) that uses a standard communication protocol known as the HyperText Transfer Protocol (HTTP) to display information described in the HyperText Markup Language (HTML). The current Web computing model allows the execution of server-side applications such as Servlets and client-side applications such as Applets. However, it offers limited support for another model of network computing where users would be able to use remote, and perhaps more powerful, machines for their computing needs. The client-server model enables anyone with a Web-enabled device ranging from desktop computers to cellular telephones, to retrieve information from the Web. In today's information society, however, users are overwhelmed by the information with which they are confronted on a daily basis. For subscribers of mobile wireless data services, this may present a problem. Wireless handheld devices, such as cellular telephones are connected via wireless networks that suffer from low bandwidth and have a greater tendency for network errors. In addition, wireless connections can be lost or degraded by mobility. Therefore, there a need for entities that act on behalf of users to simplify the tasks of discovering and managing network computing resources. It has been said that software agents are a solution in search of a problem. Mobile agents, however, are inherently distributed in nature, and therefore they represent a natural view of a distributed system. They provide an ideal mechanism for implementing complex systems, and they are well suited for applications that are communicationscentric such as Web-based network computing. Another attractive area of mobile agents is processing data over unreliable networks (such as wireless networks). In such an environment, the low reliability network can be used to transfer agents rather than a chunk. of data. The agent can travel to the nodes of the network, collect or process information without the risk of network disconnection, then return home. The publications of this doctorate by published works report on research undertaken in the area of distributed systems with emphasis on network computing paradigms, Web-based distributed computing, and the applications of mobile agents in Web-based distributed computing and wireless computing. The contributions of this collection of related papers can be summarized in four points. First, I have shown how to extend the Web to include computing resources; to illustrate the feasibility of my approach I have constructed a proof of concept implementation. Second, a mobile agent-based approach to Web-based distributed computing, that harness the power of the Web as a computing resource, has been proposed and a system has been prototyped. This, however, means that users will be able to use remote machines to execute their code, but this introduces a security risk. I need to make sure that malicious users cannot harm the remote system. For this, a security policy design pattern for mobile Java code has been developed. Third, a mediator-based approach to wireless client/server computing has been proposed and guidelines for implementing it have been published. This approach allows access to Internet services and distributed object systems from resource-constraint handheld wireless devices such as cellular telephones. Fourth and finally, a mobile agent-based approach to the Wireless Internet has been designed and implemented. In this approach, remote mobile agents can be accessed and used from wireless handheld devices. Handheld wireless devices will benefit greatly from this approach since it overcomes wireless network limitations such as low bandwidth and disconnection, and enhances the functionality of services by being able to operate without constant user input

A Lightweight and Flexible Mobile Agent Platform Tailored to Management Applications

Mobile Agents (MAs) represent a distributed computing technology that promises to address the scalability problems of centralized network management. A critical issue that will affect the wider adoption of MA paradigm in management applications is the development of MA Platforms (MAPs) expressly oriented to distributed management. However, most of available platforms impose considerable burden on network and system resources and also lack of essential functionality. In this paper, we discuss the design considerations and implementation details of a complete MAP research prototype that sufficiently addresses all the aforementioned issues. Our MAP has been implemented in Java and tailored for network and systems management applications.Comment: 7 pages, 5 figures; Proceedings of the 2006 Conference on Mobile Computing and Wireless Communications (MCWC'2006

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

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

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

Development of mobile agent framework in wireless sensor networks for multi-sensor collaborative processing

Recent advances in processor, memory and radio technology have enabled production of tiny, low-power, low-cost sensor nodes capable of sensing, communication and computation. Although a single node is resource constrained with limited power, limited computation and limited communication bandwidth, these nodes deployed in large number form a new type of network called the wireless sensor network (WSN). One of the challenges brought by WSNs is an efficient computing paradigm to support the distributed nature of the applications built on these networks considering the resource limitations of the sensor nodes. Collaborative processing between multiple sensor nodes is essential to generate fault-tolerant, reliable information from the densely-spatial sensing phenomenon. The typical model used in distributed computing is the client/server model. However, this computing model is not appropriate in the context of sensor networks. This thesis develops an energy-efficient, scalable and real-time computing model for collaborative processing in sensor networks called the mobile agent computing paradigm. In this paradigm, instead of each sensor node sending data or result to a central server which is typical in the client/server model, the information processing code is moved to the nodes using mobile agents. These agents carry the execution code and migrate from one node to another integrating result at each node. This thesis develops the mobile agent framework on top of an energy-efficient routing protocol called directed diffusion. The mobile agent framework described has been mapped to collaborative target classification application. This application has been tested in three field demos conducted at Twentynine palms, CA; BAE Austin, TX; and BBN Waltham, MA

Software agents to support mobile services

The paper discusses mobile services (m-services) in the wireless world. This world has its own features that make it different from the wired world. For instance, new communication channels need to be used, new user-friendly services need to be suggested, and new types of computing resources need to be involved. The paper also discusses the use of software agents in addressing those features

Data Aggregation Scheme Using Multiple Mobile Agents in Wireless Sensor Network

Wireless sensor networks (WSNs) consist of large number of sensor nodes densely deployed in monitoring area with sensing, wireless communications and computing capabilities. In recent times, wireless sensor networks have used the concept of mobile agent for reducing energy consumption and for effective data collection. The fundamental functionality of WSN is to collect and return data from the sensor nodes. Data aggregation’s main goal is to gather and aggregate data in an efficient manner. In data gathering, finding the optimal itinerary planning for the mobile agent is an important step. However, a single mobile agent itinerary planning approach suffers from two drawbacks, task delay and large size of the mobile agent as the scale of the network is expanded. To overcome these drawbacks, this research work proposes: (i) an efficient data aggregation scheme in wireless sensor network that uses multiple mobile agents for aggregating data and transferring it to the sink based on itinerary planning and (ii) an attack detection using TS fuzzy model on multi-mobile agent-based data aggregation scheme is shortly named as MDTSF model