Predictive Data Dissemination in Vanet aims to efficiently disseminate data in vehicular ad hoc networks (VANETs) by using predictive mechanisms. The presented techniques take advantage of GPS and map data to select vehicles that will further broadcast information to designated areas. Simulation results showed these techniques can alleviate broadcast storms while effectively disseminating data in both urban and highway scenarios. The document discusses several challenges for future work, including intermittent connectivity, high mobility, heterogeneous vehicles, privacy and security, and enabling network intelligence in large-scale VANETs.

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

4. Introduction
TECHNIQUES
APPLICATION’s
CHALLENGES /
FUTURE WORK
CONCLUSION
REFERENCES

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.