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Runrev Revolution
Revolution is a powerful graphical Integrated Development Environment; it has very simple programming language called Transcript. It is compatible to Java and Basic applications.
Why Revolution is used? It has true, native colour [4] It has three versions: MEDIA (beginner) Studio (core product) and Enterprise (Business). Runrev Revolution can be a major project that disposable tools for word processing, complex applications, prototypes are used and can be created by professionals, beginners can apply. This language is very easy to use; it can be used for Web-based applications to multiple platforms with a single click, and uses the power of multi-user database systems. It can for improvement of desktop applications, and internal productivity. It’s simple, very easy maintenance and English language makes it easy to write and understand users. It is easily the right environment for development environment, drag and drop tools to create objects such as buttons and text box which is to be shown on the right side of the screen. Runrev Revolution connects directly with the object code. Then copy the object code and do it so no need to write new code for each item. There is no compile / link / run cycle test Runtime Environment, software-user interface builder and editor, and the same.
Following are the features of Runrev Revolution environment. [4]
• Runrev revolution uses Up to 10x more productive than traditional development systems. [5]
• Write up to 90% less code
• The application created by revolution is possible to run on web, desktop or server/client.
• It includes all the common features to any third generation language like JAVA, C and C++.
• To solve the problem in Runrev Revolution any other language can be used like java, C or C++ to improve the performance.
• Run and edit live
• Edit server/client scripts directly on the server/client.
• Achieve your goals in a fraction of the time it would take using any other development platform
• High-performance script execution
• Cross-platform delivery; It can be created on MAC and work on the Windows and Linux as well.
• External database access.
• Great support for Internet protocols
• A scripting language that contains about five times as many keywords and commands.
• Revolution adds a huge number of professional features, high end development tool that comes with additional business features, including true compilation, Linux, interacting with web sites and database connectivity.
• Revolution allows to Develop, test, and deploying work on multiple platforms.
• Revolution can exchange files between the two platforms. It usually takes only a little time to test and make sure everything looks just right.
• Revolution supports Unicode.
• Windows and Linux with native appearance and behaviours
• English-like programming language with 1601 commands and functions
• Support for encryption and Secure Sockets Layer (SSL)
The flexibility of Runrev Revolution allows users/developers on any platform and deploys true, native application or Web content to any desktop (windows or Linux). Runrev Revolution use English like sentences. In java the programmer having year of experience, can write the java code in short. Whereas Runrev Revolution can do it 90 % less. Next figures shows the comparison of The Java Agent Development Environment (JADE) toolkit have three parts , library of classes assisting for agent development, a runtime environment with FIPA-specified for agent management services and a set of graphical tools for monitoring and debugging purposes. The goal of JADE is to make development easy, while the standard for compliance through a comprehensive set of system services and agents. JADE provides the following functions to agents [6].
Multi-agent systems
An agent is a computer system that acts in an environment. It has the capability to self-directed action in the environment in order to meet its goals [7]. It gets input from the environment and it should give back output to the system.
Intelligent agents come into view in Computer Science (CS) and Artificial Intelligence (AI) literature in the late 1980s as a result of work within the objected orientation and distributed AI fields (Jennings et al., 1998). Schleiffer (2005) states that “intelligent agent technology is the articulation of human decision-making behaviour in the form of a computer program” [7]
Multi-agent systems (MAS) are those systems which comprise on two or more agents. In MAS the Agents can interact with each other to find the result/goal, they share common information and may achieve the goal with other Agents. Cooperation is a general form of interaction between these agents, the cooperation including coordination of action and resolution [8]. Collaboration is about the allocation of tasks and resources between multiple agents, whether decentralized or centralized technologies. Coordination is about the way in which the actions of different agents in time and space are organized in order to achieve their goals. But when conflict occurs, the negotiating techniques are used to satisfy all parties.
MAS are often used in AI, distributed systems, software development, computer communications and other fields. MAS can communicate with each other to achieve a specific Objective.
Agents needs each other for sharing full information and problem solving, the ability to embed multiple objective functions and the fact that design can be a wise step, as additional benefits of the MAS. Three most important potential of MAS are, organization of the company itself, which makes it easier to understand for programmers and analysts to their function and behaviour. Second, problem-solving in the system is based on problem solving in the organization (decentralized: no « agent » includes the owns system). Third, as autonomous agents, and is always active, the system is responsive the changes and problems. [7]
The methods implemented to achieve the communication and coordination between the essential characteristic of MAS (Odell et al. 2002): “designing an agent-based system is not just about designing the agents; it is also about designing the agent environment and interaction.” Agents exchange the message and communication with each other. Agent coordination – or « interaction » – concerns the mechanism to organize by the agents themselves, to describe Efforts to bring the system problems. The agent communication is communication from both linguistic semantics and protocols dialogue dominates. Semantics refer to the importance that is in a language or code to express. A dialog protocol is a series of Rules for the dialogue between two or more communicating agents (Endriss et al., 2003).
Multi Agent system using JADE
A lot of researches and commercial organizations are involved in the development of agent applications and a large number of agent building tools have been developed [10]. JADE is a software framework which makes it easy to develop the multi-agent applications in compliance with the FIPA specifications.
JADE agent platform keep the high performance of a distributed agent system implemented with Java language. JADE uses the agent model and Java implementation which allows the good runtime effectiveness, software reprocesses, agent mobility and understanding the different agent architectures.
In these days, the agent-base technology are to be consider the most capable to implement worldwide applications that often must work across corporation and continents and inter-operate with other varied systems. It can manage complex applications.
Use of Agents in logistic related problems
Most of the logistics model has central information processing. However, the key solution is to a high complexity (Marike and McFarlane, 2005). A distributed solution, including MAS is an example of the suitable circumstances where there is a traditional centralized solution is less than an adequate and dissemination of information and decision-making process seems necessary. McFarlane and Marike identified three possible objects in a distributed solution approach. First among these is a centralized solution of (theoretical) is not practical.
At any moment, no decision nodes are available, only a portion of the requested information is utilised for decision-making. Impractical is the second feature. Although all data available for each decision is crucial for the implementation of synchronized, centralized decision-making may inhibit a centrally-based decisions. The third factor is inappropriate. Although the centralized decision making is possible and practical, it may still be inappropriate. For example, one of the benefits of distributed programming to more computing power into a better basis for decision (Monk et al., 2006). Logistics real estate problems are exactly the ideal multi-agent systems, according to Davidsson et al. (2005). Fischer et al. (1996) briefly outlines four main reasons for using MAS is congestion appealing. Firstly, the distributed nature of transportation contract jobs. Trucks and jobs is not only geographically but also has a certain autonomy area. In the second wagon handle dynamic events. Agent architectures have ability to handle this dynamic. Thirdly, the traditional methods of traffic planning, large amounts of information are managed centrally. The fourth company in the transport sector to a strong participation of negotiations and cooperation in carrying out their daily tasks.
The main specific logistics computational problem requirement has been identified as follows. When the system capabilities are set apart into independent units/agents they may be intrinsically distributed over a large network of computers. Logistic applications are especially suitable for the application of techniques such as task decomposition, where the schedule for each vehicle is computed by a single agent. Computation and system control are distributed among the agents. Each agent can be designed to act autonomously, in a decentralized manner, by computing a part of the schedule without needing knowledge, or reasoning, about the global process of the whole system. In order to achieve a better global solution, the agents must cooperate by exchanging client orders between one other and adjusting their schedules accordingly with the goal of minimizing the overall cost. Based on our practical experience with transportation scheduling in medium and large-size shipping companies, we can testify to the suitability of multi-agent techniques to real-world problems. [3] MAS have the ability, even though the cooperative skills, not optimization algorithms.
2.6 The role of humans in software systems
An important factor for success is the role of humans in the developed system. In most Agent based systems designs, human Agents playas big role. They play no specific data in the system or monitor system status. Nissen and Sengupta (2006) that « if the data is particularly complex, novel, or risky, are the people, decision makers, supported by Smart software support systems. « They appeal to the simple operational data, which makes the People to focus more on strategic processes. People monitor operational transactions and can intervene and correct decisions when necessary. Roll program differs from the type of decision available. More strategic tasks, which have a high (ER) impact using information Collection and the preparation of these decisions, not so much by automation.
Socket:
A socket is one end-point which makes communication between two programs which are running on the same machine or over network. Sockets are used to represent the connectivity between client and server. Socket is bound to an IP address and port number so that the TCP layer can identify the application.
Table of contents :
CHAPTER 1 Introduction
1.1 Multi-Agents in JADE:
1.2 BIOSIM:
1.3 Problem Definition:
1.4 Validation:
1.5 Goals and Objectives:
CHAPTER 2
2.1 Runrev Revolution
2.2 JADE
2.3 Multi-agent systems
2.4 Multi Agent system using JADE
2.5 Use of Agents in logistic related problems
2.6 The role of humans in software systems
2.7 Socket:
2.7.1 Overview of JAVA Socket:
2.8 TCP/IP layer of Socket Communication
CHAPTER 3 Design and methodology Pseudocode of Socket Programming to linking Runrev Revolution and JADE
3.1 Runrev part of execution:
3.2 JADE (Socket of execution):
CHAPTER 4 Establishing the connection:
4.1 Structure of Runrev Revolution:
4.2 Setting Socket in Runrev Revolution:
4.2.1 Setting Socket in JADE:
4.3 Establishing communication between BioSim and JADE:
4.4 Messaging System:
CHAPTER 5 Implementation
5.1 Implementation of Socket on BioSim:
5.2 Implementation of Socket on JADE:
5.3 JADE multi-Agent:
Architecture:
CHAPTER 6 Result and Analysis:
6.1 Call/process the JADE directly from Runrev Revolution (BIOSIM):
6.2 Connectivity through TCP/IP
CHAPTER 7 Conclusion and Future Works:
7.1 Conclusion
7.2 Future Work
References
Appendix A
Dictionary
