# An Efficient MAC Protocol for Blockchain-Enabled Patient Monitoring in a Vehicular Network
###### Abstract  
Blockchain is an emerging computing platform that provides recording and tracking facilities to substantially increase the security issues in healthcare systems. The evolution of wireless body area networks requires the continuous monitoring of the health parameters of traveling patients while traveling on road. The health parameter data of each patient are sent to the Road Side Units (RSUs) for generating the blocks by computing the required hash functions. A major challenge in such a network is to efficiently exchange the data blocks between mining RSUs and vehicles using a medium access protocol with a reduced number of collisions. The medium access problem becomes more challenging due to the vehicle mobility, high vehicle density and the varying nature of the data generated by the vehicles. In this work, a TDMA-based MAC protocol to meet an Adaptive Patients Data traffic for Vehicular Network (\(TAPD_{VN}\)) is proposed. \(TAPD_{VN}\) is specifically designed for patients in a vehicular network by considering the frequent entry and exit of vehicles in a mining node's coverage area. It allows mining nodes to adjust time slots according to the sensitive patient's data and allows the maximum number of patient vehicular nodes by considering their sensitivity to send their data in a session to compute their hash values accordingly. Simulation results verify that the proposed scheme accommodates the maximum number of high-risk patient data and improves bandwidth utilization by 20%. v 2022  
required hash functions and validate blocks in the [7; 8]. In a healthcare system, a group of medical hospitals with their medical advisors can use decentralized consortium-based blockchain technology for transferring patients' data. In this paper, the focus is on the monitoring of patients who are traveling on the road. Blockchain-based data mining in such scenarios may utilize vehicular networks comprising vehicles, Road Side Units (RSUs) and a Traffic Command Center (TCC) [9; 10; 11; 12; 13; 14; 15; 16]. Placing a mining computing node adjacent to each RSU as shown in Figure 2 provides the trustworthiness of data. Moreover, due to its proximity to vehicles, it provides quick data delivery to its mining node. A major challenge in blockchain-enabled patient monitoring in a vehicular network is that at a higher data generation rate, the transmission of data from the vehicles to the mining nodes increases the chances of collision, thus resulting in poor Quality of Service (QoS). To avoid these collisions, dedicated time slots for each patient data vehicular node need to be used. As such patient data vary in its sensitivity in different time intervals, hence, data requests to RSUs vary in different time intervals. A classic Time Division Multiple Access (TDMA)-based MAC protocol does not fulfill these adaptive data traffic requirements. In addition, vehicle mobility and high vehicle density also add further complexity for efficient data sharing with the mining nodes. In this work, a TDMA-based MAC protocol to meet an Adaptive Patients Data block in a vehicular network (\(\mathit{TAPD}_{\mathit{VN}}\)) between the patient vehicle and RSU nodes for consortium blockchain is proposed. \(\mathit{TAPD}_{\mathit{VN}}\) allows RSU to adapt guaranteed time slots in a session according to the patients' data requirements within its session limits and prioritize the patients' data block to compute their Nonce value according to their sensitivity levels. The salient features of \(\mathit{TAPD}_{\mathit{VN}}\) are mentioned below:  
1. The proposed MAC protocol prioritizes patient data for mining nodes to compute their valid nonce value by considering their sensitivity. 2. \(\mathit{TAPD}_{\mathit{VN}}\) improves the Guaranteed Time Slot (GTS) utilization by reducing the size of data slots when data requests are less than the available data capacity in a session. 3. \(\mathit{TAPD}_{\mathit{VN}}\) accommodates maximum patient data in a session by extending the number of slots to a maximum capacity of 255. 4.