The implementation of the proposed system is carried out considering the practical environment of the vehicular network. To target the processing of a massive stream of data between two communicating mobile nodes, various scenarios must be considered and implemented in developing this framework.
5.1 Smart OBU for Infotainment System
OBU or On-Board Unit is an embedded device that acts as a communication bridge between the vehicle and transceiver (road-side unit) in a vehicular network. The proposed system assumes that the infotainment system is directly connected to the OBU. Resources for both OBU and infotainment are limited concerning memory, processing capability, and operational speed. The only difference is the memory of OBU cannot be extended, while that of the infotainment system can always is extended using an external storage unit. Hence, one of the challenges in this design process is how to optimize the performance of OBU with limited resources. The proposed system considers a finite number of supportable services by the considered infotainment system and a fixed number of inlet/outlet connections. This connectivity port acts as a bridge of internal interaction between the vehicle/user and OBU.
Figure 5 highlights that the OBU unit is connected to various components, which increasing its processing capability, in fact, indirectly. This makes the OBU unit smarter when it works alongside with infotainment system. Using the infotainment system's extensive resources, a buffer can be constructed to store the incoming queue of the data stream and filter out quality-oriented data. The proposed system can be considered a set of algorithms that are now possible to be executed within these smart OBU units to process a massive data stream.
5.2 Clusteringgrid
The proposed system introduces a novel and simplified topology of the vehicular network to facilitate quality data transmission among the vehicular nodes. Consider the following scenario of data transmission, as exhibited in Fig. 6. Assume a segment of a cross-section of a road with three vehicular nodes, i.e.,n1, n2, and n4, moving at a variable speed. These vehicular nodes have smart OBU and assume RSU stationed at a uniform distance over the road's edge. Considering a scenario that n1 is interested in forwarding a message to n4. However, n1 is only in the communication range of n2 vehicle and not n4 vehicle (Fig. 6(a)). Consider a scenario where a third vehicular node n3 is approaching towards the range's direction, which connects n2 and n4so that n3 becomes an intermediate node (Fig. 6(b)). A third scenario where the third vehicular node n3 (acting as an intermediate node between n2 and n4) is found to move away. Consider a parameter θ to represent the degree of orientation over the vehicular cloud representing the affinity of establishing established communication among the communicating vehicular nodes. A closer look over the scenario stated in Fig. 6(b), and Fig. 6(c) will show that the parameter θ is highly dependent on the quality of signal exchange between the OBU of all the vehicular nodes (n1, n2, n3, and n4) that are associated with multihop-based connectivity. It will also mean that maximization of this parameter θ will also reduce the propagation of artifacts present in the communication process (owing to density, interference, scattering, fading, etc., in wireless vehicular nodes). Therefore, the proposed system emphasizes evaluating this parameter θ before processing massive streams of data. Hence, the proposed system's topology is formulated in the grid, where clustering is carried out to offer better distinction among the communicating zones.
The proposed system considers the complete area of simulation and classifies them equally in multiple coverage areas. The coverage area is decided based on the presence of RSU, where each area has one RSU and multiple vehicular nodes with smart OBU. This coverage area is termed a cluster maintained in the form of a grid for the uniform division of the complete simulation area. The study also assumes that each cluster executes a local communication protocol followed by vehicles within the respective cluster. It will mean that two different vehicles in two different clusters are assumed to have two different communication protocols. Therefore, this makes the environment more practical and assists in communication. The study also considers that gateway nodes are connected to all RSU to assists in translational services of heterogeneous routing for two vehicular nodes under different clusters. Apart from this, each cluster also keeps track of the parameter θ for all local active communicating nodes, assisting nodes in other clusters for undertaking decisions while performing massive data streaming. Figure 7 pictorially showcase the connectivity among vehicles, RSU, and gateway node. The proposed system considers a case study of an urban vehicular network where the vehicles are authorized to move on a defined route over the deployment area. It is to be noted that Line-of-Sight (LOS) issues in the wireless transmission are considered in this deployment region.
5.3 Selection of Relay Node
The conventional vehicular network is constructed considering the position, speed, and several vehicles as elementary simulation parameters before constructing the routing process. However, the practical scenario slightly differs from this simulated scenario in various aspects. The proposed system hypothesizes that the distance between two vehicular nodes and their movement direction plays an essential role. Hence, the inclusion of these parameters is required to construct a practical scenario of implementation. The adoption of this scenario helps the information of a better form of stabilized link in the presence of a challenging mobility context.
Figure 8 highlights the vehicle's movement's pictorial representation in a different direction and its possible effect on establishing the communication link between the source and destination node. The mobility pattern of a vehicle is completely an unpredictable process, and there is a higher probability of having inclusion of various forms of artifacts over the routes of mobility. This artifact could be high if a vehicular cloud is considered in the mobility model. Hence the formulation of a stabilized communication link between the transmitting and vehicular receiver nodes is quite challenging to be established. The proposed model uses the degree of orientation θ associated with the vehicular node to decide the routes with a higher probability of delivering the data packet. The degree of orientation θ is based on the highest probability of the data transmission from the first (transmitting node or relay node) to the second node (relay node or destination node). Therefore, the proposed system undertakes multiple test scenarios of mobility with the presence of three types of nodes, i.e., i) transmitting nodes, ii) receiving nodes, and iii) relay nodes. The test scenario also considers all these vehicular nodes traveling over specific routes equivalent to practical world routes while they move in different directions.
i) Test-Scenario-1: In this test scenario, all the vehicular nodes are moving on routes in a similar direction with different coverage capabilities (Fig. 8(a)). This scenario states that the degree of orientation is much favorable for n2, n4, and n7 vehicular nodes. The relative degree of orientation for this test environment is shown in Table 1. The inference of the expression associated with the selection of routes is as follows: owing to the weak coverage range of n5, the neighboring node n2 will select n4 where the probability of degree of orientation is better compared to n5 (although a degree of orientation for n5 is maximum at this point.). Similarly, assuming n6 is out of the coverage area of n4, n7 is the best possibility with the highest degree of orientation. Hence, the selected relay nodes are n2, n4, and n7.
Table.1 Exploring Route in the first Case of Mobility
Vehicular Nodes
|
Respective Degree of Orientation
|
Relative Degree of Orientation
|
Selected Relay
|
n1
|
θ1
|
θ1 > θ2
|
n2→n4→n7
|
n2
|
θ2
|
θ3 > θ4
|
n3
|
θ3
|
θ2 = 0
|
n4
|
θ4
|
θ7 > θ6
|
n5
|
θ5
|
θ5 = max
|
n6
|
θ6
|
θ8 > θ6
|
n7
|
θ7
|
θ8 > θ2
|
ii) Test Scenario-2:In this case (Fig. 8(b)), the environment chooses certain relay vehicular nodes (n2 and n5) to be moving in opposite direction excluding transmitting (n1) and vehicular receiver node (n6).In this case (Table 2), the favorable relay nodes selected are n2, n5, n4, and n7. The justification is: vehicular node n2 is the most eligible node which carries the data from n1 owing to two reasons, e.g., i) n3 moves far away from the destination node, and the degree of orientation of n3 is 0 and ii) degree of orientation of n2 is higher compared to n3. The system selectsn4 via selected n5 as the degree of orientation for n4 is better than that of n5. A closer look at this scenario is that node n4 is a very important relay node as it offers the higher assurance of data delivery right from node n2 or node n5. Hence, in case of failure to receive data from n5, it will always have a significant chance to obtain the same from the n2 node. Hence, the reversed direction of nodes n2 and n5 compliments the data delivery process. Similarly, node n7 offers the highest degree of orientation in the intermittent link between n4 and n6.
Table 2
Exploring Route in the second Case of Mobility
Vehicular Nodes
|
Respective Degree of Orientation
|
Relative Degree of Orientation
|
Selected Relay
|
n1
|
θ1
|
θ1 = max
|
n2→n5→
n4→n7
|
n2
|
θ2
|
θ4 > θ3,θ2 = 0
|
n3
|
θ3
|
θ2 = 0
|
n4
|
θ4
|
θ7>>θ6
|
n5
|
θ5
|
θ5 > θ4
|
n6
|
θ6
|
θ8 > θ6
|
n7
|
θ7
|
θ8 = max
|
iii) Test Scenario-3: In this test scenario, the most challenging and practical situation is considered where transmitting node n1 and receiving node n6 are traveling in the reverse direction (Fig. 5(c)). The scenario also considers certain candidate relay nodes are also reverse to each other in the movement on the specific routes. The selection of the first relay node n2 bears a similar condition-based on the degree of orientation, as discussed in the prior two test scenarios. The next possibilities are vehicular relay nodes n5 and n4. A closer look at the vehicular node n5 shows a better probability of orientation than the other relay node n4, which is traversing in a direction opposite to itself and receiver node n6. Based on the relative values of degree of orientation (Table 3), this scenario does not call for selecting n4 as a relay node, and hence both n4, as well as n7, are not selected as relay node owing to lesser probability to reach receiver node n6 on time. Hence, the only probability for a better degree of orientation and reach ability relies on vehicular relay node n5. Therefore, this test scenario selects only n2 and n5 as a relay node.
Table 3
Exploring Route in the first Case of Mobility
Vehicular Nodes
|
Respective Degree of Orientation
|
Relative Degree of Orientation
|
Selected Relay
|
n1
|
θ1
|
θ1 = max
|
n2→n5
|
n2
|
θ2
|
θ3<<θ4,θ2 = 0
|
n3
|
θ3
|
θ2 = 0
|
n4
|
θ4
|
θ7>>θ6
|
n5
|
θ5
|
θ5>>θ4
|
n6
|
θ6
|
θ6 = max
|
n7
|
θ7
|
θ8 = max
|
Hence, the degree of orientation not only depends upon the distance, but it also depends upon the probability of higher proximity of the relay nodes to the receiver node for the successful delivery of data packets. Therefore, this process results in the establishment of multiple hops between the transmitting and receiving vehicular nodes. It should also be understood that this process results in the exploration of stabilized routes in vehicular networks' dynamic scenario. After the effective multi-hop routes are explored and confirmed, then the data packets are transmitted. However, the study does not allow any waiting period for routes to be established between the transmitting and receiving node as this will further lead to uncertainty in established route formation. Hence, for faster delivery, the proposed system permits the transmitting node to explore the neighboring relay node and transmit the data packet to it. All the relay nodes further contribute to this process until the data packet reaches the destination node. To support the streaming of signals, the proposed system formulates a multi-hop communication system. To deal with the network resources' restrictive capacity (e.g., bandwidth), the proposed system splits the streamed data-based on several relay nodes being found in the route exploration process. This mechanism ensures faster transmission with higher reliability to forward the data packet towards its destination node.