# HCLE: Hybrid Clustering Approach for Extending WBAN Lifetime
## 2 Related Work  
WBANs encounter many challenges due to the nature of the sensors and the environments in which they operate. One of the challenges in WBANs is the limited data rate, which ranges from a few kilobits per second (kbps) to several megabits per second (Mbps) [12; 13]. This limitation poses a hurdle for transmitting sensor data to the sink node. Furthermore, the movement and dynamic nature of the human body [26; 27] alter the radio frequency environment, resulting in interference and signal attenuation [11]. The security and privacy of the data transmitted in a WBAN can also be another challenge. Special precautions must be taken to maintain data privacy and integrity due to the sensitive nature of physiological data acquired in WBANs [28; 29; 30; 31]. Some methods can be used to guarantee data confidentiality and integrity, such as access control systems or encryption algorithms. However, using these techniques incurs overhead for data transmission. One of the most significant challenges in designing WBANs is the restricted energy source for wearable sensors. A constrained network lifetime is the result of these sensors often being battery-powered and difficult to recharge or replace. In other words, the energy constraints are mainly due to the limited battery capacity, the small size of the sensors, and the need for the sensors to be continuously operational [7; 13]. Therefore, optimizingenergy consumption is essential to extending the WBAN's lifespan. The challenge of energy efficiency in WBANs has been addressed using several techniques. One technique is replenishing the sensors' battery using energy harvesting techniques [16; 17; 18; 32], such as solar or kinetic energy. This approach can increase the lifetime of the WBAN by reducing the need for battery replacement or recharging. Energy harvesting techniques, however, require appropriate hardware and are not ideal for all kinds of sensors. Additionally, sleep scheduling and duty cycling techniques can be used to conserve energy by turning off the sensors when not needed [12; 33; 34]. In conjunction with the previous techniques, one of the most common techniques is the development of energy-efficient routing protocols [19; 35; 36]. When designing WBANs, routing is paramount to ensuring effective and reliable data transmission [8; 21]. A routing protocol determines the optimal path for data transmission from the sensors to the sink node to minimize the sensors' energy consumption during data transmission. The lifetime and performance of the WBAN are increased by reducing the energy consumption of the sensors. Routing protocols in WBANs can be classified into several categories according to their functionality and mode of operation, including cross-layer, postural, QoS-aware, thermal-aware, and cluster-based [8; 11; 12; 13; 15; 19; 21]. In cross-layer routing protocols, the routing decision is made based on information gathered from different layers of the protocol stack, such as physical, MAC, and network layers, to optimize network performance [35; 37]. In traditional networking, each layer operates independently, and information flows only vertically between adjacent layers. However, in cross-layer design, information can be exchanged horizontally between different layers, allowing for more efficient use of network resources and better performance. It is particularly beneficial for optimizing energy consumption and network lifetime [37; 38]. By leveraging information from different protocol stack layers, cross-layer routing protocols can make more informed decisions about routing paths and power management. For example, using information from the MAC layer, such as the status of the medium access control protocol and the buffer status of the nodes, cross-layer routing protocols can make more efficient use of the available bandwidth and reduce collisions, leading to improved network performance.