# Smart Handoff Technique for Internet of Vehicles Communication using Dynamic Edge-Backup Node
## 3 Proposed Methodology
\begin{table}
\begin{tabular}{l l l l l} \hline \hline \multirow{2}{*}{**S. No**} & \multirow{2}{*}{**Author/Date**} & \multirow{2}{*}{**Technique/Algorithm/Methodology**} & **Decrease** & **Reduce** \\  & & & **Packet Loss** & **Handoff** \\  & & & **Rate** & **Delay/Latency** \\ \hline \multirow{2}{*}{01} & [PERSON], et al. & \multirow{2}{*}{New Optimal handover decision model} & \multirow{2}{*}{✓} & \multirow{2}{*}{\(\times\)} \\  & (2018) [11] & & & \\ \hline \multirow{2}{*}{02} & [PERSON], [PERSON], and [PERSON] & Vehicle Link Expiration Time & \multirow{2}{*}{\(\times\)} & \multirow{2}{*}{✓} \\  & [PERSON], (2018) [1] & & (VLET) Metric & \\ \hline \multirow{2}{*}{03} & [PERSON], et al. (2016) [12] & RFID Tags & \multirow{2}{*}{✓} & \multirow{2}{*}{✓} \\  & [PERSON] and [PERSON]. & \multirow{2}{*}{Multichannel functions} & \multirow{2}{*}{\(\times\)} & \multirow{2}{*}{✓} \\  & (2012) [13] & & & \\ \hline \multirow{2}{*}{05} & [PERSON], et al., (2014) [14] & Turned Detection Scheme and AP & \multirow{2}{*}{\(\times\)} & \multirow{2}{*}{✓} \\  & (2014) [14] & Selection Scheme & \\ \hline \multirow{2}{*}{06} & [PERSON], et al., (2016) [15] & Efficient Proxy Mobile IPv6 (E-PMIPv6) & \multirow{2}{*}{✓} & \multirow{2}{*}{✓} \\  & [PERSON] and [PERSON]. & \multirow{2}{*}{Handover Decision Algorithm} & \multirow{2}{*}{\(\times\)} & \multirow{2}{*}{✓} \\  & (2014) [16] & & & \\ \hline \multirow{2}{*}{08} & [PERSON] and [PERSON]. & \multirow{2}{*}{A proactive approach for fast handoff} & \multirow{2}{*}{\(\times\)} & \multirow{2}{*}{✓} \\  & (2013) [17] & & & \\ \hline \multirow{2}{*}{09} & [PERSON], [PERSON], and [PERSON]. (2017) [18] & Predictive handoff mechanism & \multirow{2}{*}{✓} & \multirow{2}{*}{✓} \\  & [PERSON], et al. (2011) [19] & Pre-scanning method and Quality & \multirow{2}{*}{✓} & \multirow{2}{*}{✓} \\  & (2013) [20] & & & \\ \hline \multirow{2}{*}{11} & [PERSON], [PERSON], and [PERSON] & \multirow{2}{*}{Vertical handoff scheme} & \multirow{2}{*}{✓} & \multirow{2}{*}{✓} \\  & [PERSON]. (2013) [20] & & & \\ \hline \multirow{2}{*}{12} & [PERSON], et al., (2015) [2] & AOA technique & ✓ & ✓ \\ \hline \multirow{2}{*}{13} & [PERSON], et al., (2014) [22] & Full-blown analytical Model & ✓ & \multirow{2}{*}{✓} \\ \hline \multirow{2}{*}{14} & [PERSON], et al., (2017) [23] & Analytical Expression, DMM, & & \\  & (2017) [23] & HO-initiate process & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparative analysis of existing handoff techniques. 1. Provision of non-stop and steady connectivity through handoff performance;
2. Maximized and efficient network performance;
3. Network disconnectivity issue resolved;
4. Reduced problem of the cluster heads' overhead. Cluster stability can be explained with multiple methods; our procedure computes the stability from the distance, variation in speed, and probability arguments. A cluster head is selected with keen value stability. We assume that vehicles are equipped with GPS systems through which each one can gain information related to current position, and IEEE 802.11p radio transceivers which are used for communication with other vehicles. In the proposed algorithm, each vehicle can run the clustering method. When a vehicle needs to discover a cluster head, it propagates a message to its neighbors; if no response is received, it begins the group formation procedure. Vehicles moving in the same direction are grouped in the one cluster. Each vehicle transmits the message to its group vehicle; the message contains: the location, ID, and speed. After that, it places the arguments in an array of the neighborhood and calculates:  
* The distance between the neighbor Q and vehicle N itself: \[Distance_{N,Z}=\sqrt{(x_{N}-x_{Q})^{2}+(y_{N}-y_{Q})^{2}}\] (1) where (x, y) is the location of the vehicle. * The variation in speed among the neighbor \(\Delta\) V and vehicle N itself.