Mobile-C

The mobile agent technology can significantly enhance the design and analysis of problem domains under the following three circumstances. (1) the problem domain is geographically distributed; (2) the subsystems exist in a dynamic environment; (3) the subsystems need to interact with each other more flexibly.

Mobile agents can travel between different execution environments. Mobile agents can be created dynamically at runtime and dispatched to source systems to perform tasks with the most updated code. Therefore, the mobility of mobile agents provides distributed applications with significant flexibility and adaptability in dynamically changing environments.

Mobile-C is a general mobile agent platform, it can find its applications in many areas, especially in networked intelligent mechatronic and embedded systems. For example, when dealing with terra mining or planet exploration where multiple mobile units are required to setup equipment or explore the environment, the mobile units are far from the control center and communication is delayed or nonexistent. Intelligent autonomous agent-based systems can collaborate in order to overcome obstacles without the need for continued supervision from the control center. As another example, the ability to travel allows mobile agent systems to move computation to source systems. This decentralized approach improves network efficiency since the processing is performed locally.

To add your application on this page, please send a brief description of your project and web site to
mobilec(@)ucdavus.edu

Agent-based real-time traffic detection and management system (ABRTTDMS) is an IEEE FIPA compliant multi-agent application aimed at providing real-time traffic conditions, predicting potential incidents, and alarming the predefined events to the traffic management center (TMC). The real-time traffic information detected by the system can also be used as the source of intelligent traveler information systems, which provide information, such as travel time, to travelers.

Vision systems have become popular for remote vision sensing in geographically distributed environments due to the vast amount of information they provide. Mobile agent technology is a salient solution in vision sensor fusion since it increases power efficiency by reducing communication requirements and increases fusion processing by allowing in-situ integration of on-demand visual processing and analysis algorithms. Mobile agents can dynamically migrate between multiple vision sensors and combine necessary sensor data in a manner specific to the requesting system.

In this sensor data acquisition experiment, an accelerometer is attached to one surface of a running DC motor and also connected to a gumstix computer. A mobile agent is sent from a local host to the gumstix to get raw data from the accelerometer and process the raw data to produce accelerations in X and Y directions. The acceleration data are carried back by the mobile agent and displayed on the local host.

The Mobile Agent-based Dynamic Interaction and Computational Steering (MADICS) allows users to apply new or modified algorithms to a running application by altering certain sections of the program code without stopping the execution and recompiling the program. The MADICS has been validated through applications including real-time mobile robot control with mobile agents, dynamic improvement of convergence rate for simulation of temperature distribution, and dynamic CFD data post processing.

This project foresees the enlargement of an existing single-source surveillance system, developed at our lab, to a distributed multi-camera video network. Currently, the single-camera video system is applied for fall detection in the so-called Video-Based Intelligent Home (ViBIH). The main goal is thus to improve the accuracy of the fall detection results and, at the same time, enhance the vision field. Since we envision to use smart cameras, where the primary image processing is performed close to the image sensor, the main challenges faced by this project are: (i) the video sensor units' connectivity, and (ii) the communication network. As mentioned above, (i) comprises the process synchronization and the cooperative integration of the multiple video productions. It requires thus the definition of an appropriate data structure, the development of the target algorithms for merging and processing of the correlated info coming from different video sources, as well as the prioritization of related tasks. On the other hand, (ii) includes the definition of the communication protocol and the memory management policy.

In this project, Mobile-C is used in a multi-camera platform to decentralize some of detection algorithms. For example, a human tracking algorithm will move from one smart camera to the other when the target move to the field of vision of another camera. The algorithm is deployed in a mobile agent in Mobile-C.
http://www.he-arc.ch

In recent years, the security issues on MANET have become one of the primary concerns. The MANET is more vulnerable to attacks than wired network. These vulnerabilities are nature of the MANET structure that cannot be removed. As a result, attacks with malicious intent have been and will be devised to exploit these vulnerabilities and to cripple the MANET operation. Mobile agent can be used as tool to collect and process information regarding intrusion data into MANET's nodes. The characteristic of the mobile agent should be light as many limitation on these nodes.

http://www.utm.my/