# Blockchain Based Delay and Energy Harvest Aware Healthcare Monitoring System in WBAN Environment
## 3 Problem Statement  
This section summarizes the main problems that exist in the current literature on WBAN-based IoT. In [45], the authors objective is to minimize the energy consumption for all sensor nodes deployed in the human body. To meet this objective, the energy harvested aware routing protocol (E-HARP) was proposed. In the E-HARP, two tasks are executed \begin{table}
\begin{tabular}{c c c} \hline \hline
**Area Focused** & & **Research Gap** \\ \hline \hline \multirow{7}{*}{_QoS Achievement_[28; 29; 30; 31; 32; 33; 34]_} & Direct data transmissions without considering clustering to the sink nodes were achieved in some of the existing papers which affect the _QoS_ in terms of high latency. \\  & Many of the existing papers perform clustering however, the clustered data in the gateway was not efficiently handled in terms of delay and throughput which also affects the _QoS_. \\  & The routing protocols used in the existing research are limited with less reliability in communication and suffer from transmission errors which also affect the _QoS_. \\ \hline \multirow{7}{*}{Security Provisioning_[36; 37; 38; 39]_} & Some of the existing works not considered authentication rather they consider data security which also affects the patient’s privacy. Most state-of-the-art works employ heavy-weight cryptographic algorithms for data encryption and authentication, however, which leads to high energy consumption in the WBAN-IoT networks. Some of the existing work limits with considering the minimal amount of security metrics for providing security in WBAN-IoT however, which imposes major attacks in the WBAN-IoT environment such as false injection attacks, impersonation attacks, etc. \\ \hline \multirow{7}{*}{Blockchain_[41; 42; 43; 44]_} & Conventional blockchain models are limited with high energy consumption, latency, and scalability issues in terms of block creation and validation time.These problems in the conventional blockchain are not suitable for resource-constrained WBAN-IoT. \\ \cline{1-1}  & & Conventional blockchain models are limited with high energy consumption, latency, and scalability issues in terms of block creation and validation time.These problems in the conventional blockchain are not suitable for resource-constrained WBAN-IoT. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Research gaps. such as dynamic CH election and data routing in a cooperative manner. Initially, CHs are elected by the cost factor (CF), which is calculated by the node residual energy, transmission power needed, signal-to-noise ratio (SNR) and energy loss. The problems in this work are as follows,  
* The clustering process is not effective since it does not ensure that the CF computation always produces the optimum solution and the computation of CF tends to be time consuming when a large number of sensors are used. This paper minimizes the redundant data, but it does not eliminate anomaly (faulty) data. Thus, it results in large bandwidth and energy consumption for CHs. * When two sensors communicate with the same channel concurrently, they interfere with each other. Multihop transmission via nonoptimal nodes increases energy consumption and reduces the delivery rate. Then, the optimal cost function (CF) was computed [46] in the E-HARP. The optimal cost function was computed using thellink SNR, transmission power required, distance between nodes and total energy harvested and residual. Two sink nodes are deployed according to the LOS and high _RSSI_ value, and these nodes act as CHs. However, a patient's critical packets tend to be waiting for a longer time, and thus energy consumption is higher. It is not suitable for large scale environments. It is required to sense the environment because of the large size of faulty packets generated in body sensors, which also consume more energy. A remote monitoring system was presented in [47], which contains a patient centric agent (PCA) that collects and processes the sensed packets from body sensors.