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.

Parallel computing is widely adotped in scientific and engineering applications to enhance the efficiency. Moreover, there are increasing research interests focusing on utilizing distributed networked computers for parallel computing. The Message Passing Interface (MPI) standard was designed to support portability and platform independence of a developed parallel program. However, the procedure to start an MPI-based parallel computation among distributed computers lacks autonomicity and flexibility. An autonomic dynamic parallel computing framework is presented which provides autonomicity and flexibility that are important and necessary to some parallel computing applications involving resource constrained and heterogeneous platforms. In this framework, an MPI parallel computing environment consisting of multiple computing entities is dynamically established through inter-agent communications using the IEEE Foundation for Intelligent Physical Agents (FIPA) compliant Agent Communication Language (ACL) messages. For each computing entity in the MPI parallel computing environment, a load-balanced MPI program C source code along with the MPI environment configuration statements are dynamically composed as a mobile agent code. A mobile agent, wrapping the mobile agent code, is created and sent to the computing entity where the mobile agent code is retrieved and interpretively executed. An example of autonomic parallel matrix multiplication is used to demonstrate the self-configuration and self-optimization properties of the presented framework.

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/

This projects aims to realize the conversion from traffic control algorithms to traffic control agents and validate the control effects of these agents through simulation. It also studies the coordination method of control agents. Control agent communicates and negotiates with the adjacent intersections' control agents. Afterwards, it adjusts its control behaviors and parameters through fuzzy reasoning based on predefined rules and the control optimization of the whole area is realized. The running mechanism and switched rules of traffic control agent are studied. The system's structure is divided into three levels: center organization level, area coordination level and field execution level using the hierarchical architecture developed for intelligent control systems.

http://www.compsys.ia.ac.cn

Wireless sensor networks (WSN) are increasingly being used for critical safety monitoring systems. In these systems, the reliability level for the data is of paramount importance especially when emergency situations occur and may involve material and life losses. Therefore, it is important that every incident can be tracked down throughout the event. Clearly, the information flow from the sensors, in these environments, should continuously feed a monitoring system throughout the incident. Moreover, monitoring all phases of the incident can be used for further investigation and future prevention by revealing the source of the problem. It also helps the rescue team in the action management and in the decision-making. Typical video monitoring systems do not have all these features, due to the lack of sensing feedback of what is happening in the physical environment. Thus, there is no way to know exactly where, why and how some fire emergency happened. In our solution, we use the integration of WSN and Radio Frequency ID tags (RFIDs) to provide accurate localization reference and other relevant contexts on the emergency on course. Data from sensors and RFID tags at the location of the incident are submitted to a fusion process to eliminate redundant data and noise and so saving energy for the whole network. The usage of mobile agents eliminates the need for all sensors to send their readings back to a sink whenever some problem occurs. In our solution the mobile agent, held by the sensors, and tailored according to application needs (lowest latency, highest delivery rate etc) is responsible for migrating, collecting the data and performing data fusion at each step. The novelty of our solution is the agents flexibility to behavior and structure changes to guarantee the required quality of service by the application when data is gathered and delivered in harsh conditions.

http://www.ufscar.br

The objective of this work is to develop a wireless sensors network:

each node of the network must be autonomous
enable the network to remain operational even after the occasional failures of nodes
nodes must be able to self-manage, using protocols to find items such as: network topology, the relative positioning of sensors within the network, the possible routes to communicate with other nodes
the sensor network should be tolerant to failures of one of its components and therefore must have the capacity to self-organize

http://www.eseco.fr

Project codename darkwolf is a very large multistage and multibranch project. It is run as a Yamika core project (largest classification for any company project). We will use this software along with software from over 350 other software vendors in combonation for a large scale launch of state of the art software and websites (projects range from small html chatrooms to apple inc. grade technologies and intel grade technologies already designed and are now in progress). We hope everything goes as planned and we have many sub vendors lined up under vendors so odds of failure are at extremely low probability even in spite of the project scale.

First stage of this project is to build a mobile robotic sensored vehicle, capable of being controlled wirelessly, and via the agent protocol, give status of the vehicle, as well as, serving, as logging all movements, back to the agent server controller. Next stage requires multiple vehicles to communicate with each other, via agent protocols, and based on a given algorithm, divide and conquer tasks in order to accomplish a set goal (ie, such as best way to traverse a given course).
http://www.austincc.edu

In this project innovative concepts for in-network processing and system autonomy for a fast-deployable, self-configuring and self managing Intelligent Video Sensor Network (InViNe) will be researched and developed taking into consideration the resource constraints, variable network capacity and dynamic topology found in ad-hoc wireless mesh networks. The enabler of the InViNe system will be an embedded middleware supporting the interaction between distributed network and sensor devices by providing an interface between the operating system on the embedded device and a wide variety of video sensor network applications. In order to facilitate distributed sensor data processing, the concept of mobile software agents will be used. Mobile agent-based systems allow the execution of certain software components called agents to migrate across a network. Mobile agent oriented middleware has many advantages over typical clientserver communication such as reduced network load, greater ability to adapt to a dynamic network and support for autonomous execution. Video analysis and system management tasks will be mapped to mobile agents and these agents will dynamically migrate through the network from video sensors to network nodes in order to optimally utilize the available network capacity and in-network processing resources. Low-level processing tasks can be done directly on the resource limited sensors thereby limiting the amount of data which must be transported into the network. High-level or collaborative processing tasks can migrate to network nodes with higher processing capabilities. The location of agents will be continuously optimized adapting to network topology changes due to node mobility as well as nodes entering and leaving the network.
http://www.hslu.ch/iimsn

TIPS (Transparent IP Sockets) is a wrapping implementation of specific functions of the BSD sockets API to provide support for transparent IP mobility at the application level. Implemented on top of the transport layer it allows UDP and TCP communications to be immune to both client and server terminal migration (single and double jump). Location independent identification, and lossless data transmissions are provided with reduced overhead. The use of a Distributed Hash Table for keeping terminal location information also allows for scalable operation.
http://www.usp.br