Vehicular Ad Hoc Network Lab Report

The stream of complex numbers is rearranged so that the pilots can be inserted. In each OFDM symbol, four pilot signals are inserted in order to make the coherent detection robust against frequency offsets and phase noise. The pilots are BPSK modulated by a pseudo binary sequence to prevent the generation of spectral lines [18]. A zero padded block adds zeros, in the right places, to adjust the IFFT bin size to length N. Selector block rearranges the sub-carriers so that real signal output can be generated. The IFFT block then computes the Inverse Fast Fourier Transform (IFFT) of length N, where, for ease of implementation, N is a power of

Figure 8.3(a) demonstrates a portion of a wireless ad hoc network where a source node S has a data packet to be sent to a destination node that is

The transmission rate and contact rates between D2D pairs are often quasi-statistic information. In cellular network, all the nodes of the network can be known by their contact rates and transmission rate to the source node, as they can access the services provided by the network. In D2D communication, where the base station is not taking part of the data transmission, the D2D pair can transmit the contact rates and transmission rate by opportunistic contacts. Therefore, the information for the source node for content transmission and resource allocation of D2D pairs are distributed in the

All vehicles transmit a 200-byte safety message at 10Hz with data rate of 6 Mbps. All vehicles attempt to continuously route 64-byte packets at an application rate of 2.048 Kbps to one of 10 other vehicles, selected as sink vehicles. The antenna height AHk of each vehicle is 1.5m. Transmit power is set to 10 dBm and the transmission range for safety message packet delivery is 145 m. For each experiment PCAP trace file per node is enabled. The routing statistics are gathered and compared for each experiment, i-e, with NS2 mobility trace file and with PySNS3. The simulation parameters for performance evaluation of PySNS3 are shown in Table III. In order to calculate packet delivery ratio (PDR), we must count; i) the packets that are actually received, and ii) the transmitted packets that are expected to be received. Both are relative to a specified (circular) coverage area shown in Fig. 6. Let's assume that the transmission range of vehicle A, is in meters, such that TRA > dAB. Where, dAB is distance between A and B, and dBC is the distance between B and

In order to mix the good strings and protect the effective ones simultaneously, the probability of crossover and mutation are considered as 0.8 and 0.1 respectively. This entire process is repeated, until the improvement in fitness values (from previous to current Pareto-optimal set) is less than a chosen precision, ǫ. Undoubtedly, actual precision value (ǫ) will be distinct according to corresponding QoS parameters. 10−6, 10−5 and 10−3 are chosen as the precision values for the probabilities of end-to-end delay, total bandwidth and overall energy consumption respectively. Finally, the strategy returns the results of the discovered QoS-route (whether success or failure and the set of routes) to the cross-layer QoS-provisioning algorithm shown in Figure

This protocol use Dijkstra algorithm. It maintains a complex data base, also called as link state database, which contains full information about the remote routers and the exact network topology. The goal from this protocol is to provide similar information about network connection to each router, so each router can calculate the best route to each network this is happen when each router generates information about itself and pass these information to other routers in the network so each router make a copy of this information without changing it.

From the figure, it can be seen that host1, host3, host 4 sends messages through the times say t1,t2,t3,t4 and the times are increasing.

In the fig1 represents the number of nodes varying with respect to the delay as compared with MILP optimal formulation. It explained our proposed algorithm is better than the MILP formulation.

Step4. Calculate distance from BS to each node for all nodes. for i=1 to n do DBSi = Distance from BS to Si endfor Step5. Calculate the net distance with base station for each node for i =1 to n do NDBSi= DBSi + Di endfor Step6.

To ensure QoS in our proposed algorithm we calculate the utility of a node e.g. $node_i$ as the summation of remaining CPU cycle ($R_{CPU_i}$), remaining memory in that node ($R_{mem_i}$), remaining bandwidth available for that node ($R_{bw_i}$), remaining data reside in the buffer to transmit ($R_{data_i}$), data rate ($Data_{rate_i}$) and priority of data to be transmitted $Pri_{data_i}$.

The propagation delay = 2d x (20ms/km) = (2x10) x (20ms/km) = 0.4 seconds or 400 ms.

This book was very inspirational. It is not only inspiring to people with bipolar disorder but to all other people that are suffering from any kind of mental illness. It also speaks to people that do not have a mental illness by giving them and inside look of what someone’s life is like and how they deal with their problems. The book shows how not only is life possible with mental illness but that it is also worth living.

The Mobile ad hoc networks is one of the emerging technologies today. The instability of the nodes in a mobile ad hoc network makes it difficult to calculate the reliability of the network. When a node moves freely move in a

Mobile ad hoc network is dynamic network topology without any central network for control. All the nodes in the network participate in networking functions like routing and packet forwarding as per the requirement. Nodes which  are in direct contact with each other communicate with single hop and those which are not in range takes multiple hops through intermediate nodes to reach destination

Ad hoc networks consist of a set of self-organized of mobile nodes which cooperate using a routing protocol to facilitate the communication. They have become very popular in recent years due to their characteristics: easy deployment, lack of infrastructure, dynamic topology, mobility and minimum commissioning costs.