## 4 Network Communication
### State-of-the-Art Research on Network Communication
#### 4.1.1 Design Factors  
In BSN design, a lot of research work has been carried out, and the following aspects should be seriously considered. Generally, BSN nodes cannot employ circumscribed wired power, which is a constraint for long time operation. Meanwhile, nodes are designed as small as possible for wearability, so their battery capacity is very limited. For example, the sensor node designed by [PERSON] _et al._, is only in 26 mm size [92]. Some other researchers adopt the energy acquisition technology harvesting power from surrounding electromagnetic environment instead of batteries, but this leads to a stricter power consumption restrictions at the same time [16]. In BSNs, many key applications cannot work well if any node stops working when the energy has run out. Therefore, the network architectures and protocols should guarantee that nodes could complete the data transmission of highest quality with the least power consumption. In addition, BSNs should balance power consumption distribution, avoiding the overload of a few nodes. Radio transmission range of sensor nodes will become smaller along with miniaturization design and energy conservation design. Examples of ultra-low range transceivers in the literature include Reference [93] with 0.2-1 m, Reference [94] with 0.2 m and Reference [95] with 0-1 m transmission ranges. The smaller the transmission range is, the more careful the network topology design should be. In this circumstance, the star topology is not suitable, because nodes far away from sink node are not easy to communicate with. The path loss directly reflects the network communication performance. In BSNs, the electromagnetic waves transmit by diffraction along the body instead of penetrating into the body, which causes a remarkable path loss, especially when transceivers are placed on the different sides of body, _i.e._, one on the chest and the other on the back [91]. Many BSN applications such as fall detection have strong reliability demands [96]. When a fall happens, the whole system must have the ability to collect the fall information immediately, and then send alarms to the appropriate consoles, but if the network encounters heavy congestion or topological partition at the same time, data could not be send out, which will affect the system on making a decision for reaction. In this case, users may be hurt. Therefore, the number of errors of data acquisition must be as small as possible, and so must the delay. Due to the fact the data collected has a close relationship with individual information, it will inevitably involve user data security issues. If personal information leaks, the user will be in danger. Cryptography and trust evaluation methods can effectively solve these issues. In Reference [97], researchers propose a key agreement scheme called ECG-Improved Jules Sudan (ECG-IJS), which is suitable for BSNs. It allows neighboring nodes to share a common key generated by the features which are extracted from ECG signals. The proposed scheme can improve the security of datacommunication and avoid previous key distribution. In addition, because of the fact that BSNs are susceptible to a variety of node misbehaviors, traditional trust evaluation methods are vulnerable to attacks. Recognizing malicious behaviors and excluding malicious nodes need to be considered. Reference [98] presents a distributed trust evaluation model with the feature of application-independent, which allows each node to evaluate integrated trust values of others based on continuously monitoring the behaviors of its neighbors. Trust management is executed by cryptographic techniques such as symmetric encryption/decryption and hash operations. The proposed model can effectively detect and exclude malicious nodes. Similar to the previous study, an attack-resistant and lightweight trust management scheme called ReTrust is proposed in Reference [99]. It adopts a two-tier network architecture in which network nodes are divided into two parts: sensor nodes and master nodes.