# Multipath Routing in Wireless Body Area Sensor Network for Healthcare Monitoring
## 2 Literature Review
An energy-efficient routing algorithm for patient monitoring in body sensor networks is proposed in [18]. The solution works as a routing algorithm for the efficient and reliable transmission of data from on-body sensors to medical personnel via multi-hop routing, which is critical for continuous health monitoring. The solution works as an energy-efficient routing algorithm by taking it as a multi-objective optimization problem (conflicting objectives combined using a weight vector). The solution obtains routes that characterize the trade-off between energy consumption and throughput. The objective of the proposed scheme is to find routes with minimum energy consumption and maximum throughput at the trade-off of end-to-end latency. [PERSON] et al. [19] proposed anycast Q-routing in WSNs for healthcare monitoring to overcome high network traffic and to reduce large path search delays of multi-hop Zigbee-based systems. The solution works efficiently to route information to the nearest sink, as it takes only local information at each node to reduce computational, storage, and learning overheads. However, the solution works with an assumption of no energy constraint on the sink nodes. The solution takes each node as an independent learning and routing capability for making routing decisions. The anycast Q-routing in WSNs used a greedy approach for the routing decision. An energy-efficient solution for WBAN-based HMS is proposed in [20] to deal with energy losses due to packet collision, over-emitting, over-hearing, and idle listening. The solution uses a base station (WBAN coordinator) as a sink for the WBAN nodes using Zigbee to collect information, such as the electroencephalogram (EEG), blood pressure, glucose level, and pulse rate of the human body. The solution avoids energy consumption in sleep mode; therefore, overall energy consumption is minimized. [PERSON] et al. [21] presented cloud-enabled wireless body area networks for pervasive healthcare that significantly enhanced the deployment of pervasive healthcare applications. The proposed solution presents an integration of WBANs with mobile cloud computing (MCC). This solution takes advantage of dynamic provisioning, scalability, and ease of integration. The conceptual architecture used introduces mobile devices to render data collected from WBAN nodes to access points and base stations. The mobility enhancement of patients' body monitoring based on WBAN with multipath routing is presented in [22]. Supporting mobility is one of the basic needs in the HMS. The presence of small sensors with limited energy leads to a limited sending range and a lack of support for the patient's mobility. The proposed solution presents an ad hoc mode to establish a network and a multi-path routing algorithm. The routing algorithm works in three phases: route discovery, route maintenance, and data transmission. The route discovery is initiated on demand when a node wishes to find a way to the destination through network flooding. The route maintenance phase starts after the route discovery as with the mobility of the patient, the quality of the routing paths may vary. To overcome this issue, a measurement packet is sent by the destination node to the source, traversing all the intermediate nodes. The strength factor is maintained by each node to keep track of the link quality. On the other hand, the source node always tries to send data via two routes simultaneously to maximize successful packet delivery. The literature review clearly reflects that existing schemes are focused on energy conservation mechanisms without considering the inevitable factor of routing protocols. The traditional unicast routing protocols, for mobility support, such as AODV and DSDV, also need improvements considering the special needs of WBASN. The multipath routing protocol supporting mobility has great potential to be adapted for WBASN.