# Multipath Routing in Wireless Body Area Sensor Network for Healthcare Monitoring
## 2 Literature Review  
This section contains a discussion of important works related to energy-efficient solutions in wireless body area sensor networks (WBASN) for healthcare monitoring. The existing work is evaluated against different comparison parameters, such as end-to-end delay, throughput, packet-delivery ratio, and approaches used to prolong the network lifetime of medical sensors. The proposed approaches are weighed based on routing strategies for energy-efficient WBASN, identifying the need for a multipath routing protocol. In [1], an energy-efficient clustering mechanism is proposed to extend the battery life of medical implants by forming clusters in immediate proximity. The implementation is based on a modified low-energy adaptive clustering hierarchy (LEACH), and the results are compared with pure ALOHA. The data of non-critical events are aggregated, whereas, in case of an emergency, the implant data are immediately transmitted to the sink node. The evaluation providing a comparison with a trivial medium access control protocol lacks the routing parameters imperative to justify the novelty of the proposed scheme. Authors in [2] proposed an optimization method to address poor channel conditions leading to low network utility and delivery probability. The method quantitatively analyzes the relationship between the factors, which reduces the waiting delay and sets the data frame length considering the channel model. The method achieves comparable performance in terms of network utility, frame delivery probability, delay, and energy efficiency. Further improvement in QoS and energy efficiency needs the incorporation and evaluation of various routing strategies. [PERSON] et al. [3] presented an ERQTM scheme realizing an energy-efficient routing protocol and QoS traffic management mechanism, aiming to elongate the network lifetime, ensuring network reliability. The energy-efficient routing selects an optimal cluster head considering different QoS metrics, such as nodes' residual energies, energy consumption rates, distance to a controller, and path loss effect, to define the objective function genetic algorithm. The proposed scheme also cuts off the routing delay by prioritizing the emergency data with a high transmission rate. The proposed scheme is compared with the other priority-based scheme to demonstrate better network stability, network lifetime, residual energy, throughput, and end-to-end delay. A robust optimization algorithm is proposed in [7] to save the power of energy-constrained sensors by using a generalized gamma distribution considering outage probability and packet retransmission. The authors proposed an alternative optimization approach to determine the solution, formulating an optimization problem as semi-strictly quasi-convex in each decision variable, at reduced complexity. The result evaluation concludes that transmission in smaller packets is preferable to avoid the retransmission request, thus achieving 47% more energy efficiency. [PERSON] et al. [8] developed an energy-efficient data aggregation technique for WBAN using bee swarm optimization that optimizes energy efficiency by reducing the retransmission and controlling the packet congestion which ultimately results in improved energy efficiency. The bee swarm optimization approach is used to choose appropriate cluster heads from the randomly chosen cluster heads. The cluster formation step ensures that an equal and small number of nodes is allowed in each cluster to allow transmission from a member node to the sink node with less energy. [PERSON] et al. [9] presented an energy-efficient cooperative routing scheme for heterogeneous sensor networks, where a sensor relays a packet of not only its wireless sensor networks (WSN), but also the packets of other WSNs by dynamically established routing paths based on the residual energy, underlying sensors, and their neighbors. The proposed scheme is compared with DEEC, M1-LEACH, and M2-LEACH, showing significant improvement in the lifetime of sensors. [PERSON] et al.