Predictive Data Dissemination in Vanet
- 2. Government Engineering College, Ajmer Seminar Presentation On “Predictive Data Dissemination in Vanet” Student Name: Dhruv Marothi Roll no: 16CS23 Submitted to: Mr.Ravinder Singh Mentor: Mr. Deepak Gupta
- 5. Introduction : Vehicular Ad hoc Networks (VANET) is a new technology. VANET is type of an ad hoc mobile network which offer facilities like security, traffic proficiency, driving ease, etc. Traffic information is especially useful for the driver while driving, such as an accident alert or else traffic jam alert. In ad hoc vehicle networks, data transmission is usually performed by multihop communication in which high-speed vehicles act as a data carrier. Vehicles are forced to navigate a defined route, depending on the route layout and traffic conditions. In an ad hoc vehicle network, delivering data to multiple stores is a very complicated job because of the high mobility and frequent disconnections that occur in vehicle networks. The biggest challenge in ad hoc vehicle networks is to gather information such as accidents, speed limits, road obstacles, road conditions, traffic conditions, commercial advertising, etc. for safety and convenience. In many diffusion techniques, the vehicle transports the package until it finds another vehicle heading towards destination and at that point passes the package to that vehicle.
- 7. Predictive Data Dissemination in Vanet : Vehicular Ad hoc Networks (VANETs) enable inter-vehicular data exchange that has a great potential to help resolving numerous issues on our roads, such as the dissemination of emergency information, traffic condition, infotainment data and other delay tolerant data. While disseminating data within a certain area of interest, the Flooding scheme provides the best delivery ratio, but it suffers from the well-known broadcast storm problem. To overcome this, a protocol that takes advantage of the Global Positioning System (GPS) with integrated maps is found. Using the data from a map together with its predictive mechanism, the data sender elects the further nodes that will rebroadcast the information. It works in both urban and highway scenarios. Once it has the snapshot, the sender chooses the further rebroadcasting vehicle. A low signal handling mechanism was developed to handle the cases in which the reply response messages cannot be delivered. A set of simulation experiments was conducted and results show that the found scheme alleviates the broadcast storm problem.
- 8. TECHNIQUES : VADD MODEL : Find out the next forwarding direction with probabilistically the shortest delay. Output:- Priority list of the outgoing directions for the packet forwarding.
- 9. Network Coding in Multi-RSU VANET : The usage of Road Side Units (RSUs) acting as a buffer point in VANETs alleviates the intermittent vehicle-to vehicle (V2V) connectivity problem. However, due to the vehicle mobility and the short RSU-transmission-range, a vehicle dwells short time inside an RSU. Nevertheless, quick response from the RSU server, helps a driver to make a quick decision while driving. Network coding is known to be efficient for broadcasting multiple data items in a single packet by encoding requested data items based on the cache information of the vehicles. This can significantly improve the broadcast bandwidth usage as well as reduce the response time of the system. However, this requires the prior knowledge of cached data items of vehicles. Hence vehicles need to upload the cache information to the RSU server. This wastes upload bandwidth. Applying network coding improves the broadcast performance of an RSU in terms of minimizing the deadline miss ratio of the generated requests by vehicles, and reducing the response time of serving requests by the RSU server.
- 11. Clustering and Probabilistic Broadcasting in VANETs With the aim to guarantee the stable and reliable communication between nodes. A clustering algorithm is first presented according to the driving directions of vehicles, by which vehicles could exchange their data in a clustered way with sufficient connection duration. In the constructed clustering structure, a probabilistic forwarding is presented to disseminate data among vehicles. Each cluster member forwards the received packet to its cluster head with a calculated probability which is associated with the number of times the same packet is received during one interval. When receiving the sent packet, the elected cluster header continues to disseminate it toward the transmission direction.
- 12. Delay Tolerant and Predictive Data Dissemination Protocol (DTP-DDP) A protocol that uses the GPS with integrated maps. By means of the map data in conjunction with the prediction mechanism, the sender of the data selects additional nodes to reproduce the data. Also, the procedure worked on both municipal and highway roads. After registering, the sender selects the vehicle for further transmissions. Key returns of their approach the procedure itself is adaptive and can be used in both municipal and highway areas. In this procedure, the first information sender, the source or forwarding node of the event, acts as a central vehicle that selects additional nodes to resend the event. Hence, two additional messages are required for the protocol to function properly, despite containing information about the events. These posts are the response of the recipient to the transmitter and the response of the transmitter to those selected for further dissemination. Using GPS, the projected protocol can gather the essential data and further disseminate information about events. After the data has been transmitted, the algorithm selects at most one vehicle in each road and different road direction to transfer the data. However, to achieve this, the protocol requires further delay so that the data sender can collect responses from other nodes in the sender area.
- 14. Trustworthy Event-Information Dissemination: In vehicular networks, trustworthiness of exchanged messages is very important since a fake message might incur catastrophic accidents on the road. In this a new scheme to disseminate trustworthy event information while mitigating Message modification attack and fake message generation attack. This scheme attempts to suppress those attacks by exchanging the trust level information of adjacent vehicles and using a two-step procedure. In the first step, each vehicle attempts to determine the trust level, which is referred to as truth-telling probability, of adjacent vehicles. The truth- telling probability is estimated based on the average of opinions of adjacent vehicles, and it applies a new clustering technique to mitigate the effect of malicious vehicles on this estimation by removing their opinions as outliers. Once the truth-telling probability is determined, the trustworthiness of a given message is determined in the second step by applying a modified threshold random walk (TRW) to the opinions of the majority group obtained in the first step.
- 17. SAI: Safety Application Identifier Algorithm Vehicular safety applications have much significance in preventing road accidents and fatalities. An algorithm that uses the concept of quality of service (QoS) class identifiers (QCIs) along with dynamic adaptive awareness range. Furthermore, we investigate the impact of background traffic on the proposed algorithm. Finally, we utilize medium access control (MAC) layer elements in order to fulfill vehicular application requirements through extensive system-level simulations. The results show that, by using an awareness range of up to 250 m, the LTE system is capable of fulfilling the safety application requirements for up to 10 beacons/s with 150 vehicles in an area of 2 × 2 km2. This algorithm reduces the amount of vehicular application traffic from 21Mbps to 13Mbps, while improving the probability of end-to-end delay being ≤100ms by 20%. Lastly, use of MAC layer control elements brings the processing of messages towards the edge of network increasing capacity of the system by about 50%.
- 19. Real traffic-data based evaluation of vehicular traffic environment: Vehicular traffic environments and location-centric data dissemination have been critically reviewed for identifying future design issues in location-centric data dissemination in VANETs. Real traffic data is utilized for analyzing the impact of physical parameters and weather conditions on traffic environments. State-of-the-art techniques of location-centric data dissemination have been qualitatively investigated considering functional and qualitative behavior of protocols, properties, and strengths and weaknesses for both urban and highway traffic environments. Traffic environment analysis helps in incorporating the behavior of physical parameters and weather conditions into data dissemination design. The classified study of location centric data dissemination techniques assists in identifying appropriate techniques for specific ITS applications and suitable traffic environments as well as gives clear insight to researchers in understanding and differentiating various geocast routing protocols.
- 22. Future Work: Intermittent connectivity: The control and management of network connection among vehicles and infrastructure is a key challenge. The intermittent connections due to the high mobility of vehicles or high packet loss in vehicular networks must be avoided. High mobility and location awareness: Future VANETs require high mobility and location awareness of the vehicles participating in communication. Each vehicle should have the correct position of other vehicles in the network to cope with an emergency situation. Heterogeneous vehicle management: In the future, there will be a large number of heterogeneous smart vehicles. The management of heterogeneous vehicles and their sporadic connections is another challenge of future VANETs. Security: There is always a risk to the privacy of user’s data content and location. The vehicles communicating within the infrastructure should allow users to decide what information should be exchanged and what information should be kept private. Privacy can be assured by examining sensitive data locally, instead of sending it to the cloud for analysis. Support of network intelligence: In future VANETs, there will be a large number of sensors installed in vehicles, and the edge cloud collects and preprocesses the collected data before sharing them with other parts of the network, for example, conventional cloud servers.
- 24. Conclusion: Wireless automobile communication is an important and effective technology for future smart transport systems, smart vehicles and smart infrastructure. The dawn of automobile grids opens up many applications that include vehicles with the capability to create wireless communications and manage networks, and help users drive more safely, more efficiently, and in a fun way. Because innovation relies too much on technical support, innovation must be heavily involved in distribution, and there are many interesting research issues that have not been addressed in many areas. Over the past decade, VANETs have made considerable progress in research and related technologies, and have attracted significant interest in several research communities such as transportation, wireless communications, and networking. This presentation describes the key features of vehicle systems, building information, legal regulations, protocols, applications, and future approaches. It also tries to analyse and assess the key ideas of how to overcome with the context data dissemination and how to reduce the amounts of transferred and stored data in vehicular cooperation environment.
- 26. References: On Efficient Data Dissemination using Network Coding in Multi-RSU VANET, 2016 IEEE 83rd Vehicular Technology Conference (VTC Spring). Delay Tolerant and Predictive Data Dissemination Protocol (DTP-DDP) for urban and highway vehicular ad hoc networks (VANETs) ,Publication: DIVANet '16: Proceedings of the 6th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications November 2016 Pages 67–74. A Data Dissemination Scheme based on Clustering and Probabilistic Broadcasting in VANETs, published by ELSEVIER Vehicular Communications Volume 13. Trustworthy Event Information Dissemination in Vehicular Ad Hoc Networks, Published in Hindawi Mobile Information Systems Volume 2017, Article ID 9050787, 16 pages. SAI: Safety Application Identifier Algorithm at MAC Layer for Vehicular Safety Message Dissemination Over LTE VANET Networks, Published in Hindawi Wireless Communications and Mobile Computing Volume 2018, Article ID 6576287. Real traffic-data based evaluation of vehicular traffic environment and state of the art with future issues in location-centric data dissemination for VANETs, published by ELSEVIER Digital Communications and Networks Volume 3, Issue 3.