Java Agent Development Research Articles

A MAS architecture for dynamic, realtime rescheduling and learning applied to railway transportation

Rescheduling disrupted railway traffic is computationally hard even for small problem instances. Disruptions may not be known beforehand and can manifest themselves even when trains are en-route, and they are usually resolved by human experts. Wide geographical distribution, a dynamically changing environment, complex interdependencies between multiple components, operational criticality and uncertainty being characteristic of railway transportation, human resolutions are inconsistent, scale-inefficient and potentially infeasible with deadlocks. We present a multi-agent system (MAS) model for dynamic and real-time rescheduling (DRR) of bi-directional railway traffic on a single track in this paper. A computational framework to dynamically dispatch the disrupted trains in real-time, based on instantaneous system parameters and to reschedule conflicting trains with inherent deadlock avoidance is incorporated in the agents’ model. A learning architecture is implemented as a proof-of concept to resolve disruptions quickly and to enhance autonomy. The model is evaluated against integer optimal solutions generated by a Mixed-Integer Linear Programming (MILP) model using realistic data. Detailed discussions on architecture, implementation using JADE (Java Agent DEvelopment) toolkit, experimental results, performance analysis, evaluation of the model, insights and limitations are reported. The numerical performance measures of the model are total weighted delay of all trains at their destination terminals and computational time for resolution. The distinguishing research contributions in this paper are a MAS architecture for railway rescheduling, dynamic dispatch priority assignment using bidding and a learning procedure that enhances autonomy.

Multi-Agent Architecture for Business Modeling of Web Services Composition Based on WS2JADE Framework

Web services have gained popularity today for enabling universal interoperability among applications. In order this, to answer the complex service requirements of the user, composite web services has to be constructed correctly and effectively. For this reason, various approaches have been used for web service composition. Among these approaches we quote the one who allows software agents to access and control Web Services, in this approach the integration between agents and web services platforms is important. For this purpose, the toolkit WS2JADE is developed at the Centre of Intelligent Agent and Multi-Agent Systems, it allows deployment of Web services as JADE (JAVA agent DEvelopment Framework) agents services at run time. Therefore, composition of web services is returned to that of JADE agents services. In this paper we propose a new approach for modeling the composition of JADE agents services and thus web services using the Multi-Agent Reactive Decisional System (MARDS) Model.

Multi-Agent Modeling Toolkit – MAMT

Multi-agent system consists of two or more agents which cooperate/coordinate with each other in order to solve a complex problem which would be difficult or inappropriate if solved by single agent. Multi-agents are modeled using Agent Unified Modeling Language (AUML) as Unified Modeling Language (UML) notations do not fully express agent properties/behaviors. In this paper, we have proposed Multi-Agent Modeling Toolkit (MAMT) to help a designer in building rapid multi-agent based applications. The purpose of this toolkit is to create agent development environment where the developer can have various facilities like reusability of existing/developed agents, customize built-in agents, etc. MAMT provides the designer with built-in agents which are developed using Java Agent Development (JADE) framework, with the help of these designers can rapidly build multi-agent based applications. Creation and customization of built-in agents is based on the prototype inclusion design pattern and the designer can add or modify methods/behaviors according to their requirement(s); however the changes should be based on FIPA (Foundation of Intelligent Physical Agents) standards and compatible with JADE. MAMT has been evaluated on large number of sample applications; results were very promising and encourage the use of toolkit.

Multiagent approach to controlling distributed computing in a cluster Grid system

Generally, distributed computing environments have a number of properties that significantly complicate unification of processes of computing control such as their scheduling and resource allocation. Such properties include, for instance, functional-organizing heterogeneity, dynamics and non-complete description of integrated resources; diversity of the spectrum of problems solved using these resources; different classes of users pursuing their own goals and tasks while working with the computing system. Analysis of world trends in this research domain allows stating that solving these problems is directly connected with intellectualization of middleware of distributed computing environments with decentralized control. In this work, a multiagent approach to controlling distributed computing in a cluster Grid system, which is a virtual software-hardware infrastructure with its nodes being computer clusters, is presented. Characteristics of such system are considered. Architecture and principles of operation of the multiagent system are given. A number of important technological features of the proposed approach is singled out. The multiagent system is developed using JADE tools (Java Agent DEvelopment framework). The results of imitation simulation of the processes of operation of the system of agents being developed are given.

Switching mode control strategy in manufacturing execution systems

The paper describes a semi-heterarchical control solution for mixed planning and scheduling, routing and job execution in flexible manufacturing systems based on the paradigms of holonic manufacturing and product-driven automation. The main feature of the control solution is the bidirectional switching of the operating mode (scheduling, routing) between centralised and decentralised in the presence of perturbations to ensure as long as possible both global optimisation and agility to changes in batch orders, while featuring robustness to disturbances in the production environment. At the theoretical level, the control solution is described in terms of generic structural and dynamic models. The implementation is done using a multi-agent Java Agent Development Framework framework.

Modelling Online Admission System: A Multi-Agent Based Approach

We have proposed an integrated Web-based online admission system using multi-agent system and Web-based technologies. Every year, most of the Universities have to organise centralised admission for under-graduate courses of its affiliated colleges. The centralised online admission system is a major reform initiative in education sector to bring about greater transparency, efficiency and accountability in complicated and time-consuming admission process. It encompasses every institution under the university to accomplish the admission process where potential student community is involved. As a result of various agents' involvement in the whole process, coordination and communication among them are the core issue which can be efficiently handled in a multi-agent environment. Thus dynamic behaviours of the agents reveal better results. Multi-agent systems represent a new paradigm for the development of distributed software. Preliminary implementation issues for this system have been discussed with Java Agent Development Environment Technology, a java-based software platform that provides middleware-layer functionalities which facilitate the development of agent-based application, at the end of the paper.

Responsive End-User-Based Demand Side Management in Multimicrogrid Environment

This paper presents an agent-based demand side management framework (ADSMF) as an intelligent solution to shorten the supply–demand gap in microgrids by forming virtual market environments that allow neighboring microgrids to trade with each other. The framework does two essential tasks: 1) routing power from surplus locations to deficit locations by effectively coordinating with distributed energy resources (DERs); and 2) enabling customers’ participation in electricity enterprise through demand response (DR). The low preference loads of the end-users are grouped into two categories, viz. shiftable and curtailable loads, according to the level of flexibility involved in their operation. Also, three smart DR options are identified to allow the customers to choose as per their requirement. The customer’s participation is encouraged through a priority-based incentive mechanism. The proposed incentive mechanism uses frequency of participation of customers in DR and their contribution to benefit gained by the overall system to cater the incentives. The feasibility of the framework is demonstrated by applying on a case study network with two grid-tied microgrids simulated using Java Agent DEvelopment framework (JADE). The extensive simulation studies on the test network have proved the applicability and effectiveness of the proposed agent-based framework in mitigating the supply–demand gap in multimicrogrid environment.

Java Agent Development Framework

Java Agent Development Framework (JADE) is a software in JAVA, which is used for the development of agents, implemented in JAVA. It is a distributed agents platform, which has a container for each host where we run the agents. Additionally the platform has various debugging tools, mobility of code and content agents, the possibility of parallel execution of the behavior of agents, as well as support for the definition of languages and ontologies. In this paper, we will be having a detailed study on the functioning of JADE and we will put forward our conclusions on how its functioning can be enhanced.

Intelligent coordinated adaptive distance relaying

Malfunctioning of distance relay third zone has been identified as one of the leading factors of power system blackouts in several nations. This inconsistency in operation happens when heavy loads start encroaching the zone 3 settings. In this paper, a novel multi-agent system based methodology for power system protection coordination is proposed. Various system agents are designed to collaborate and adaptively modify the setting of distance relay zone 3 via communication with neighboring substations. The proposed coordination scheme aids in preventing fault misjudgment and possible network breakdown because of load encroachment. Furthermore, it enhances the relay selectivity and loadability. It has been tested using MATLAB®/Simulink™ with the agent programming in Java Agent DEvelopment Framework (JADE) platform. Analysis and test results demonstrate that the proposed method effectively mitigates distance relay malfunction under load encroachment.

The Design of Logistics Vehicle Scheduling System Based on Agent

We studied the logistics vehicle scheduling.We have used Unified Modeling Language (UML) for modeling and java agent development framework (JADE) to realize the Agent server-side interactive collaboration features and set up multi-Agent scheduling platform,and have also used the hybrid genetic algorithm to optimize the scheduling task. Through testing examples as well as the combination use of MATLAB and Visual C+ +, the vehicle Gantt chart has been generated to inspect the performance of optimization algorithm.

A multi-level control architecture for master-slave organized microgrids with power electronic interfaces

This paper presents a multi-level control architecture for autonomous operation of islanded microgrids with power electronic interfaces. An upper layer performs calculations for system dispatch while a lower layer computes appropriate control actions for the power electronic interfaces. The upper layer of communication-based intelligent control is realized through a decentralized multi-agent system (MAS). Two control strategies are implemented in this layer: MAS power balance control and economic dispatch. In MAS power balance control, a rational communication scheme is proposed to construct a minimal spanning tree structure among agents, so that the multi-agent system can efficiently discover system global information and dispatch generation and load to maintain real and reactive power balance; in economic dispatch, by comparing incremental cost with neighbors, generator agents can achieve minimum generation cost for system operation. To demonstrate the speed and effectiveness of the proposed algorithms, IEEE 14, 30, 57 and 118 bus systems are studied for the MAS power balance control and economic dispatch in MATLAB. A demonstration presents implementation of multi-agent system using Java agent development framework and includes a viable implementation of the lower layer, which is used to control power electronic interfaced distributed generators, and is realized through conventional local controllers for master-slave organized microgrids. A case study with time-varying loading conditions is demonstrated to validate the proposed multi-level control architecture.

How to select dynamically a QoS-driven composite web service by a multi-agent system using CBR method

Service-oriented architecture permits the composition of web services provided with different Quality of Service (QoS) levels. In a given composition, finding the set of services that optimises some QoS attributes under its constraints is a problem that needs to be solved. Our aim is to propose an intelligent approach to the selection of a Composite Web Service (CWS) based on QoS. This paper reports the authors’ recent research on addressing the issue. An overview on the previously proposed approaches is presented. These approaches correspond to several improvements of an existing multi-agent one, which is well-cited in the specialised literature. Each framework, implemented on JADE (Java Agent Development) framework, improves another one in terms of CPU time and/or QoS score, to reach a new agent-based and scalable framework. The last framework utilises the agents’ ability of negotiation, interaction and cooperation in order to facilitate the selection of composite web services. By using CBR method, the agents can memorise QoS scores and availability. The improvements are related not only to the CPU time but also to the Composite QoS (CQoS) value, while operating in a dynamic environment and taking into account user preferences.

New Framework for Improving Big Data Analysis Using Mobile Agent

the rising number of applications serving millions of users and dealing with terabytes of data need to a faster processing paradigms. Recently, there is growing enthusiasm for the notion of big data analysis. Big data analysis becomes a very important aspect for growth productivity, reliability and quality of services (QoS). Processing of big data using a powerful machine is not efficient solution. So, companies focused on using Hadoop software for big data analysis. This is because Hadoop designed to support parallel and distributed data processing. Hadoop provides a distributed file processing system that stores and processes a large scale of data. It enables a fault tolerant by replicating data on three or more machines to avoid data loss.Hadoop is based on client server model and used single master machine called NameNode. However, Hadoop has several drawbacks affecting on its performance and reliability against big data analysis. In this paper, a new framework is proposed to improve big data analysis and overcome specified drawbacks of Hadoop. These drawbacks are replication tasks, Centralized node and nodes failure. The proposed framework is called MapReduce Agent Mobility (MRAM). MRAM is developed by using mobile agent and MapReduce paradigm under Java Agent Development Framework (JADE).

OJADEAC: An Ontology Based Access Control Model for JADE Platform

Java Agent Development Framework (JADE) is a software framework to make easy the development of Multi-Agent applications in compliance with the Foundation for Intelligent Physical Agents (FIPA) specifications. JADE propose new infrastructure solutions to support the development of useful and convenient distributed applications. Security is one of the most important issues in implementing and deploying such applications. JADE-S security add-ons are one of the most popular security solutions in JADE platform. It provides several security services including authentication, authorization, signature and encryption services. Authorization service will give authorities to perform an action based on a set of permission objects attached to every authenticated user. This service has several drawbacks when implemented in a scalable distributed context aware applications. In this paper, an ontology-based access control model called (OJADEAC) is proposed to be applied in JADE platform by combining Semantic Web technologies with context-aware policy mechanism to overcome the shortcoming of this service. The access control model is represented by a semantic ontology, and a set of two level semantic rules representing platform and application specific policy rules. OJADEAC model is distributed, intelligent, dynamic, context-aware and use reasoning engine to infer access decisions based on ontology knowledge.

A Mobile Multi-Agent Information System for Ubiquitous Fetal Monitoring

Electronic fetal monitoring (EFM) systems integrate many previously separate clinical activities related to fetal monitoring. Promoting the use of ubiquitous fetal monitoring services with real time status assessments requires a robust information platform equipped with an automatic diagnosis engine. This paper presents the design and development of a mobile multi-agent platform-based open information systems (IMAIS) with an automated diagnosis engine to support intensive and distributed ubiquitous fetal monitoring. The automatic diagnosis engine that we developed is capable of analyzing data in both traditional paper-based and digital formats. Issues related to interoperability, scalability, and openness in heterogeneous e-health environments are addressed through the adoption of a FIPA2000 standard compliant agent development platform—the Java Agent Development Environment (JADE). Integrating the IMAIS with light-weight, portable fetal monitor devices allows for continuous long-term monitoring without interfering with a patient’s everyday activities and without restricting her mobility. The system architecture can be also applied to vast monitoring scenarios such as elder care and vital sign monitoring.

Design and Implementation of Real-Time Intelligent Control and Structure Based on Multi-Agent Systems in Microgrids

By consulting various worldwide definitions of microgrids and distributed energy, this study presents a microgrid-structured multi-agent system and uses Matlab/Simulink to construct a circuit with microgrid features, which enables the changes in each electrical source and load in the microgrid to be monitored and controlled. This multi-agent system adheres to the Java Agent Development Framework (JADE) platform specifications of the Foundation for Intelligent Physical Agents (FIPA), facilitating communication, information transfers, and the receipt of real-time information regarding the microgrid and each component in the microgrid. Furthermore, the real-time state in the microgrid can be correspondingly controlled, achieving the most efficient real-time monitoring and control for electrical sources and load management in the microgrid.

ANALYSIS OF INTELLIGENT DATA MINING FOR INFORMATION EXTRACTION USING JAVA AGENT DEVELOPMENT ENVIRONMENT PLATFORM

In this study, the problem of unstructured information extraction has been analyzed and the need for a new Information Extraction algorithm is justified. We propose an Intelligent Information Extraction using Java Agent Development Environment (JADE) to be an optimal solution for intelligent information extraction. This proposed algorithm first assigns intelligent agents to gathering data, which they then classify, match and organize to construct sequential information for a user query. It improves the efficiency and performance for retrieving a proper information results as a sequence that satisfy user’s needs. It gives the user needed documents based on similarity between query matching and relevant document mechanism. The results obtained from the Intelligent Information Extraction are optimal.

A comprehensive distributed architecture for railway traffic control using multi-agent systems

In this paper, we propose a Distributed Architecture for Railway Traffic Control using Multi-Agent Systems called DARTCMAS. It has a hierarchical organizational model that consists of three main layers of diverse agents: “Train Agents” at the bottom, “Station Agents” in the middle and “Center of Traffic Control Agent” in the top layer. Any train in the railway traffic system is considered as an intelligent agent that has reactive, proactive and interactive properties, simultaneously. DARTCMAS considers local traffic control centers that are embedded in some selected stations as “Station Agents”. Lastly, “Center of Traffic Control Agent” acts as a comprehensive monitoring and supporting reference. We define an internal architecture for each of the agents. Furthermore, two types of interactions among agents are developed: first, inter-layer interactions that represent communications between two adjacent layers in the organizational model of DARTCMAS; and second, intra-layer interactions that represent relations between the same agents type in a specific layer. Simulations have been performed using MATLAB and the “Java Agent DEvelopment framework” whose results show the effectiveness of the model.

A Multi-Agent-Based Intelligent Sensor and Actuator Network Design for Smart House and Home Automation

The smart-house technology aims to increase home automation and security with reduced energy consumption. A smart house consists of various intelligent sensors and actuators operating on different platforms with conflicting objectives. This paper proposes a multi-agent system (MAS) design framework to achieve smart house automation. The novelties of this work include the developments of (1) belief, desire and intention (BDI) agent behavior models; (2) a regulation policy-based multi-agent collaboration mechanism; and (3) a set of metrics for MAS performance evaluation. Simulations of case studies are performed using the Java Agent Development Environment (JADE) to demonstrate the advantages of the proposed method.

Detecting and Scheduling Badsmells using Java Agent Development (JADE)

For any software developer it is a fact that as source code is developed, it becomes large and complex .As the code becomes large and complex it moves from its original design and reduces the quality of code. These which reduce the code quality are termed as Bad Smells by experts [1].The methods of removing these Bad Smells are called as Refactoring. These Bad smells have so far been detected and removed manually or semiautomatically.In this paper we say about the automatic detection and resolution of Bad smell with the help of JADE (Java Agent Development Environment).JADE is a middleware developed in Java.