22-12-2012, 04:29 PM
CLOUD COMPUTING FOR INTELLIGENT TRANSPORTATION SYSTEM
CLOUD COMPUTING FOR INTELLIGENT.docx (Size: 902.37 KB / Downloads: 41)
INTRODUCTION
Agent-based traffic management systems can use the autonomy, mobility, and adaptability of mobile agents to deal with dynamic traffic environments. Cloud computing can help such systems cope with the large amounts of storage and computing resources required to use traffic strategy agents and mass transport data effectively. This article reviews the history of the development of traffic control and management systems within the evolving computing paradigm and shows the state of traffic control and management systems based on mobile multi agent technology. Intelligent transportation clouds could provide services such as decision support, a standard development environment for traffic management strategies, and so on. With mobile agent technology, an urban-traffic management system based on Agent-Based Distributed and Adaptive Platforms for Transportation Systems (Adapts) is both feasible and effective. However, the large-scale use of mobile agents will lead to the emergence of a complex, powerful organization layer that requires enormous computing and power resources. To deal with this problem, we propose a prototype urban-traffic management system using intelligent traffic clouds. Local area networks (LANs) appeared to enable resource sharing and handle the increasingly complex requirements. One such LAN, the Ethernet, was invented in 1973 and has been widely used since. During the same period, urban-traffic-management systems took advantage of LAN technology to develop into a hierarchical model. Network communication enabled the layers to handle their own duties while cooperating with one another. In the following Internet era, users have been able to retrieve data from remote sites and process them locally, but this wasted a lot of precious network bandwidth. Agent based computing and mobile field. From multi agent systems and agent structure to ways of negotiating between agents to control agent strategies, all these fields have had varying degrees of success. Now, the IT industry has ushered in the fifth computing paradigm: cloud computing. Based on the Internet, cloud computing provides on demand computing capacity to individuals and businesses in the form of heterogeneous and autonomous services. With cloud computing, users do not need to understand the details of the infrastructure in the “clouds;” they need only know what resources they need and how to obtain appropriate services, which shields the computational complexity of providing the required services. In recent years, the research and application of parallel transportation management systems (PtMS), which consists of artificial systems, computational experiments, and parallel execution, has become a hot spot in the traffic research field.2,3 Here, the term parallel describes the parallel interaction between an actual transportation system and one or more of its corresponding artificial or virtual counterparts.4 Such complex systems make it difficult or even impossible to build accurate models and perform experiments, so PtMSs use artificial transportation systems (ATS) to compensate for this defect. Moreover, ATSs also help optimize and evaluate large amounts of traffic-control strategies. Cloud computing caters to the idea of “local simple, remote complex” in parallel traffic systems. Such systems can take advantage of cloud computing to organize computing experiments, test the performance of different traffic strategies, and so on. Thus, only the optimum traffic strategies will be used in urban-traffic control and management systems.
OVERVIEW
Agent-Based Traffic Management Systems:
Agent technology was used in traffic management systems as early as 1992, while multi agent traffic management systems were presented later however; all these systems focus on negotiation and collaboration between static agents for coordination and optimization. In 2004, mobile agent technology began to attract the attention of the transportation field. The characteristics of mobile agents autonomous, mobile, and adaptive make them suitable to handling the uncertainties and inconstant states in a dynamic environment. The mobile agent moves through the network to reach control devices and implements appropriate strategies in either autonomous or passive modes. In this way, traffic devices only need to provide an operating platform for mobile traffic agents working in dynamic environments, without having to contain every traffic strategies. This approach saves storage and computing capacity in physical control devices, which helps reduce their update and replacement rates. Moreover, when faced with the different requirements of dynamic traffic scenes, a multi agent system taking advantage of mobile agents will perform better than any static agent system. In 2005, the Agent-Based Distributed and Adaptive Platforms for Transportation Systems (Adapts) was proposed as a hierarchical urban traffic- management system. The three layers in Adapts are organization, coordination, and execution, respectively. Mobile agents play a role as the carrier of the control strategies in the system. In the follow-up articles, both the architecture and the function of mobile traffic control agents were defined clearly. The static agents in each layer were also depicted in detail. What’s more, a new traffic signal controller was designed to provide the runtime environment for mobile agent. Currently, Adapts is part of PtMS, which can take advantage of mobile traffic strategy agents to manage a road map. The organization layer, which is the core of our system, has four functions: agent-oriented task decomposition, agent scheduling, encapsulating traffic strategy, and agent management The organization layer consists of a management agent (MA), three databases (control strategy, typical traffic scenes, and traffic strategy agent), and an artificial transportation system. As one traffic strategy has been proposed, the strategy code is saved in the traffic strategy database. Then, according to the agent’s prototype, the traffic strategy will be encapsulated into a traffic strategy agent that is saved in the traffic strategy agent database. Also, the traffic strategy agent will be tested by the typical traffic scenes to review its performance. Typical traffic scenes, which are stored in a typical intersections database, can determine the performance of various agents. With the support of the three databases, the MA embodies the organization layer’s Intelligence. In recent years, the research and application of parallel transportation management systems (PtMS), which consists of artificial systems, computational experiments, and parallel execution, has become a hot spot in the traffic research field. Here, the term parallel describes the parallel interaction between an actual transportation system and one or more of its corresponding artificial or virtual counterparts. Such complex systems make it difficult or even impossible to build accurate models and perform experiments, so PtMSs use artificial transportation systems (ATS) to compensate for this defect. Moreover, ATSs also help optimize and evaluate large amounts of traffic-control strategies. Cloud computing caters to the idea of “local simple, remote complex” in parallel traffic systems. Such systems can take advantage of cloud computing to organize computing experiments, test the performance of different traffic strategies, and so on. Thus, only the optimum traffic strategies will be used in urban-traffic control and management systems.
INPUT DESIGN
The input design is the link between the information system and the user. It comprises the developing specification and procedures for data preparation and those steps are necessary to put transaction data in to a usable form for processing can be achieved by inspecting the computer to read data from a written or printed document or it can occur by having people keying the data directly into the system. The design of input focuses on controlling the amount of input required, controlling the errors, avoiding delay, avoiding extra steps and keeping the process simple. The input is designed in such a way so that it provides security and ease of use with retaining the privacy. Input Design considered the following things:
What data should be given as input?
How the data should be arranged or coded?
The dialog to guide the operating personnel in providing input.
Methods for preparing input validations and steps to follow when error occur.
OBJECTIVES
1. Input Design is the process of converting a user-oriented description of the input into a computer-based system. This design is important to avoid errors in the data input process and show the correct direction to the management for getting correct information from the computerized system.
2. It is achieved by creating user-friendly screens for the data entry to handle large volume of data. The goal of designing input is to make data entry easier and to be free from errors. The data entry screen is designed in such a way that all the data manipulates can be performed. It also provides record viewing facilities.
3. When the data is entered it will check for its validity. Data can be entered with the help of screens. Appropriate messages are provided as when needed so that the user will not be in maize of instant. Thus the objective of input design is to create an input layout that is easy to follow
OUTPUT DESIGN
A quality output is one, which meets the requirements of the end user and presents the information clearly. In any system results of processing are communicated to the users and to other system through outputs. In output design it is determined how the information is to be displaced for immediate need and also the hard copy output. It is the most important and direct source information to the user. Efficient and intelligent output design improves the system’s relationship to help user decision-making.
1. Designing computer output should proceed in an organized, well thought out manner; the right output must be developed while ensuring that each output element is designed so that people will find the system can use easily and effectively. When analysis design computer output, they should Identify the specific output that is needed to meet the requirements.
2. Select methods for presenting information.
3. Create document, report, or other formats that contain information produced by the system.
The output form of an information system should accomplish one or more of the following objectives.
Convey information about past activities, current status or projections of the
Future.
Signal important events, opportunities, problems, or warnings.
Trigger an action.
Confirm an action.
Literature survey
Literature survey is the most important step in software development process. Before developing the tool it is necessary to determine the time factor, economy n company strength. Once these things r satisfied, ten next steps are to determine which operating system and language can be used for developing the tool. Once the programmers start building the tool the programmers need lot of external support. This support can be obtained from senior programmers, from book or from websites. Before building the system the above consideration r taken into account for developing the proposed system.