Intelligent Transport System (ITS) is a transport system that uses communicating technologies such as cellular network communication, digital video broadcasting and adhoc wireless communication to link people on the road, vehicles with aim of solving various traffic related issues. Vehicle to infrastructure (V2I) communication is an important research area to develop cooperative self-driving support system using DSRC technology. V2I develops an environment friendly system that also accelerates the fuel efficiency by establishing high quality links between vehicles to roadside infrastructure. It is a system to prevent and help drivers to overlooking or missing the red lights at junctions. V2I system along the road side and intersections continuously transmit the traffic signal information to vehicles by warning the driver about red lights and thus help us to prevent road rule violations. ITS helps to prevent drivers’ oversight about signals right/left turn collision avoidance and timely activation of brake system. In the proposed work we used a three-layer Vehicle to Infrastructure (V2I) network architecture to collect and disseminate the safety information using static and dynamic agents. These methods help us to quickly selecting high quality error free links to forward the data packets. In a highway road scenario with moderate traffic density, the proposed system gives an improved performance in terms of coverage area, lossless transmission and reduced latency. Finally, qualitative comparison is made with present V2I system and found significance improvement in its performance metrics. The outcome of the proposed system improved by 23%, 13%, 15% compared to the existing system in terms of end-to-end delay, communication overhead and energy consumption respectively considering V2I network architecture.

In modern world of sensing and distributive systems, traditional Wireless Sensor Networks (WSN) has to deal with new challenges, such as multiple application requirements, dynamic and heterogeneous networks. Senor nodes in WSN are resource constrained in terms of energy, communication range, bandwidth, processing delay and memory. Numerous solutions are proposed to optimize the performance and to increase the lifetime of WSN by introducing new resource management principles. Effective and intelligent resource management in WSN involves in resource identification, resource scheduling, and resource utilization. This paper proposes a Bayesian Game Model (BGM) approach to efficiently identify the best node with the maximum resource in WSN for data transmission, considering energy, bandwidth, and computational delay. The scheme operates as follows: (1) Sensor nodes information such as residual energy, available bandwidth, and node ID, etc., is gathered (2) Energy and bandwidth of each node are used to generate the payoff matrix (3) Implementation of node identification scheme is based on payoff matrix, utilities assigned, strategies and reputation of each node (4) Find Bayesian Nash Equilibrium condition using Starring algorithm (5) Solving the Bayesian Nash Equilibrium using Law of Total Probability and identifying the best node with maximum resources (6) Adding/Subtracting reward (reputation factor) to winner/looser node. Simulation results show that the performance of the proposed Bayesian game model approach for resource identification in WSN is better as compared with the Efficient Neighbour Discovery Scheme for Mobile WSN (ENDWSN). The results indicate that the proposed scheme has up to 12% more resource identification accuracy rate, 10% increase in the average number of efficient resources discovered and 8% less computational delay as compared to ENDWSN.

The safety information dissemination plays a vital role in the VANET communication. It is a technique of transmitting the information at scheduled intervals or during road hazards by detecting the events using onboard system and interfaces. Information is shared between vehicles and road side units which are further used to predict vehicle collisions, road line crossings, environmental warnings, traffic data and road hazards. Interestingly the risk of lateral collisions and dense traffic for vehicles can be avoided by accomplishing fast data dissemination i.e. warning alerts by event detection. Vehicular technology which supports the safe mode of transportation is growing faster due to the deployment of new automated technology in the intelligent transportation system (ITS). The different scenarios used in vehicular communication are Vehicle to Vehicle (V-V), Vehicle to Infrastructure (V-I) and Vehicle to Internet. Some of the important characteristics of vehicular communications are the mobility, frequent changes in topology, varying transmission power of antennas, intermittent connectivity. ITS providing the solutions for most critical transportation issues and inspiring the researchers for the betterment of road safety. In this paper, we propose a multi agent based safety information dissemination scheme for vehicle to vehicle communication. The proposed algorithm performs the safety information dissemination with help of intelligent agents by optimizing the channel access techniques, message encoding and selection of intermediate nodes. Here the communication between source and destination is achieved with fever number of intermediate links by selecting the nodes in the special zone. Short interval codes which represent safety information are effectively transmitted in the intermittent nature of wireless connectivity. This proposed work describes the details of algorithm with associated network environment, multi agent functions and dissemination mechanism to illustrate the improvement in end to end delay, PDR, energy constraints etc. This method reduces the problem of broadcast storm by delivering the information to intended node. Simulation of the proposed work gives the improved results on PDR, latency and connection overhead.

To discover computing resources available for any application before they are allocated to requests dynamically on demand, developing effective mechanism for resource discovery in Vehicular Cloud Networks (VCN) is very important. Providing the services to the requested vehicle in time is a major concern in the VCN environment. Dynamic and intelligent resource discovery schemes are essential in VCN environment so that services are provided to the vehicles in time. Resource discovery is key characteristic of VCN. VCN requires intelligent algorithms for resource discovery. Creating a mechanism for resource management and search resources is the largest challenge in VCN. There is a need to consider for dynamic way to discover the resources in the VCN. The lack of intelligence in resource handling, less flexible for dynamic simultaneous requests, and low scalability are issues to be addressed for the resource discovery in VCN. In this paper we proposed dynamic resource discovery scheme in VCN. Proposed resource discovery scheme uses Honey Bee Optimization (HBO) technique integrated with static and mobile agents. Mobile agent collects the vehicular cloud information and static agent intelligently identifies the required resources by the vehicle. Dynamic discovery model will take into account different parameters influencing the task execution time to optimize subsequent schedule. To test the performance effectiveness of the scheme, proposed dynamic resource discovery scheme is compared with fixed time scheduling algorithm. The objective of the proposed scheme is to search the resources in VCN with a minimum delay.  The simulation results of the proposed scheme is better than the existing scheme.

In order to enhance the driving experience with increased security and privacy, a category of MANET has emerged i.e VANET. The nodes are highly mobile, uncoordinated and dynamic in nature. An progressive step in this vision is Vehicular Cloud (VC) the advancement in Intelligent Transport System (ITS).The resources are shared between the vehicle nodes to provide the services at a economical cost. In order to provide them there should be hassle free secure communication link established between the Vehicle nodes, Road side unit (RSU) and the Cloud. Trust establishment in VC between vehicle nodes enhances the security aspects in VC. In this paper we put forth an trust evaluation scheme based on Dempster Shafer theory. The trust evaluation is based on Direct trust and Indirect trust, the priority of which can be accustomed.