STORM PROBLEM IN VANET

Storm Problem in VANET

Abstract

The researches on IVCs can be approximately split up into three categories: UNICAST, inundating, and diffusion in the literature. Traditional Ad hoc mesh routing protocols or position-based routing protocols can be utilised to set up general unicast connection in a VANET. A service breakthrough means is then established to permit each node to get the required data . Carnet: a scalable Ad hoc wireless mesh system. Nevertheless, the overhead for example the latency and the weakened mesh capability initiated by the service breakthrough means and routing table upkeep makes this procedure infeasible for most security critical applications.

The transmission expertise for smart transport schemes can be normally classified into two classes, namely, road-to-vehicle connection (RVC) and inter-vehicle connection (IVC). RVCs present the data connection service offer from street to vehicle while the IVCs present the data connection through vehicles. This work suggests value of service (QoS)-aware roadside groundwork position aided routing means to set up a routing route in IVC with the aid of roadside groundwork station. A connection malfunction avoidance means is engaged to competently assemble alternate routing route needed by the volatile mesh topology in vehicular Ad hoc networks. Besides, a bandwidth utilisation predictor is offered to bypass lowering packets be obliged to insufficient bandwidth throughout handoffs. A neural mesh with very fast discovering algorithm is taken up as the centre module for approximating the parameters utilised in the suggested schemes. Simulation outcomes illustrate the effectiveness and feasibility of the suggested work.

Table of Content

Abstract2

1.1 Overview5

1.2 Historical Development6

1.3 Typical Characteristics8

1.4 Research Review9

1.5 Problem Statement10

1.6 Aim of the Research12

1.7 Limitation of the Study13

1.8 Assumptions & Limitation13

CHAPTER 02: LITERATURE REVIEW15

2.1 Introduction15

2.2 Vehicular Network Applications20

2.3 Safety-related Applications20

2.4 Comfort (commercial) Applications22

2.5 VANET: Overview and Why it is Suitable for Vehicular Network Applications22

2.6 Features24

2.7 Wireless Access Technology25

2.8 IEEE 802.11p Based Technology25

2.9 Combined Wireless Access26

2.10 Spectrum Issues26

2.11 Routing Issues26

2.12 Broadcasting and Message Dissemination27

2.13 V2V Data Distribution28

2.14 Security and Privacy31

2.15 Other Solutions34

2.16 Why VANET is Better than 3G34

2.17 Infostations35

2.18 Why VANET is Better than Infostations36

2.19 Target Applications and Properties39

2.20 Wireless access methods in vehicular environments40

2.20.1 DSRC/WAVE40

2.20.2 Cellular networks41

2.20.3 WiMAX/802.16e42

2.20.4 WLAN43

2.20.5 Routing in vehicular networks43

2.20.6 Unicast routing45

2.20.7 Geocast46

2.20.8 Infrastructure-assisted hybrid routing47

2.20.9 Mobile sensing and sensor storage49

2.21 Vehicular sensing applications51

2.21.1 Street-level traffic flow estimation52

2.21.2 Proactive urban Surveillance57

2.21.3 Vehicular Safety Warning Services58

2.21.4 Ride Quality Monitoring58

2.22 Location-Aware Micro-Blogging59

2.23 V2V-based VSN platforms60

2.24 MobEyes: proactive urban monitoring services60

2.25 MobEyes Protocols61

2.26 Meta-Data Diffusion62

2.27 Virtual information exchange bazaar63

2.28 FleaNet query dissemination protocol64

2.29 Performance Analysis65

2.30 Impact of Density/Speed66

2.31 V2V Content Distribution66

2.32 SensterDB: distributed database over SensterKBR67

2.33 Performance Analysis68

2.34 Intermittently Connected DB (ICEDB)69

2.35 Carry-and-Forward Network (CafNet)70

2.36 Applications71

2.37 Mobile Objects72

2.38 Sensor Nodes73

2.39 Query Generation and Routing74

2.40 Query Injection76

2.41 Routing in the Sensor Network Layer76

2.42 Routing Protocols Review78

2.43 Terminode Routing80

CHAPTER 03: METHODOLOGY86

3.1Research Method (Qualitative/Quantitative)86

3.2Primary or secondary / Qualitative or Quantitative87

3.3Research Method87

3.4Literature Selection Criteria88

3.5Search Technique88

3.6Link Enhancement Mechanism for IVC via RVC88

3.7Link failure avoidance based on link break and congestion Indicators89

3.8Fast Learning Neural Networks92

Inputs of FLA:97

3.9Step 1: Sorting and grouping inputs.97

3.10Step 2: Determination of weights and biases of two hidden ...