Agent Based Transportation System Using Cloud Computing

Published Date: 02 Nov 2017

ABSTRACT:

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.

INTRODUCTION:

Whereas many accessible works in cloud computing focus on the development of basic organization and tools for puddle together computational resources, this work respects and addition accessible works in cloud computing by introducing "agent-based cloud computing"— applying agent-based approaches to managing cloud computing infrastructures. 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.

EXISTING SYSTEM:

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.

The function of the agents’ scheduling and agent-oriented task decomposition is based on the MA’s knowledge base, which consists of the performances of different agents in various traffic scenes. If the urban management system cannot deal with a transportation scene with its existing agents, it will send a traffic task to the organization layer for help. The traffic task contains the information about the state of urban transportation, so a traffic task can be decomposed into a combination of several typical traffic scenes. With knowledge about the most appropriate traffic strategy agent to deal with any typical traffic scene, when the organization layer receives the traffic task, the MA will return a combination of agents and a map about the distribution of agents to solve it.

PROPOSED SYSTEM:

Urban-traffic management systems using intelligent traffic clouds to overcome the issues we’ve described so far. With the support of cloud computing technologies, it will go far beyond other multi agent traffic management systems, addressing issues such as infinite system Only scalability, an appropriate agent management scheme, reducing the upfront investment and risk for users, and minimizing the total cost of ownership.

Agent-based computing and mobile agents were proposed to handle this vexing problem. requiring a runtime environment, mobile agents can run computations near data to improve performance by reducing communication time and costs. This computing paradigm soon drew much attention in the transportation 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.

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.

RELATED WORK:

When an IBM 650 computer was first introduced to an urban traffic-management system in 1959, the traffic control and management pattern closely associated with the computing pattern in IT science[1]. the research and application of parallel hauling management systems , which consists of artificial systems, linking the use of computer experiments, and parallel execution, has become a hot spot in the traffic research field.[2],[3] the term parallel describes the parallel communication between an actual carrying system and one or more of its equivalent artificial or virtual thing.[4].

Agent technology was used in traffic management systems as early as 1992, while more agent traffic management systems were accessible later.[5] these systems focus on cooperation and association between static agents for coordination and to make something as of its best.[6]–[8] .

The characteristics of third party agents—independent, mobile, and affinity to adapt to different situations—make and changeable states in a forceful environment.[9] the Agent-Based Distributed and capability Platforms for Transportation Systems (Adapts) was

planned as depending on how important they are in urban traffic management system.[10] we set up an ATS to test act of the urban-traffic management system based on the continent showing the distribution of agents.

ATS is a physical representation how it works from the bottom up, and it mirrors the real urban transportation environment.[11] the basic structure of cloud computing,[12] an intelligent traffic clouds have four architecture layers: application, platform, unified source, and stuff shows the association between the layers and the function of each layer.