# Realistic Simulation for Body Area and Body-To-Body Networks
## 2 Related Works, Simulators and Theirs Limits
### BAN-Specific Frameworks
#### 2.2.2 Network-Oriented Frameworks  
The authors in [49; 50] present a System-C-based fast simulator that can provide accurate timing and energy estimation for health monitoring applications for BAN. This simulator is able to obtain timing and energy measurements for each function in the program, as well as for each module in the hardware, which is then used for the optimization towards critical functions and/or components. The authors in [51; 52] present another System-C simulator using a joint mobility and semi-deterministic BAN channel model with a spatial and temporal dependency based on ray tracing techniques and benchmarked with a measurement campaign. This simulator and its BAN dedicated protocol in [53] have also been validated through the implementation and tests on a real platform.  
To create a complete simulation tool for BANs, PyLayers [9] has been interfaced in real time with WSNet. The idea is to simulate in real time the PyLayers mobility feature with statistical radio channel models (PHY layer) and WSNet (upper layers), calculating the performance of the simulated scenario. The simulator embeds several modules, including: an agent mobility simulator based on a discrete event simulator to which a multi-cylinder body model can be associated; a deterministic channel propagation simulator based on a ray tracing approach for body-to-body and off-body communications; a statistical model for on-body communications taking into account the environment and the body shadowing effects. Nevertheless, in this co-simulation, the resultant models are highly complex and difficult to develop. In this regard, the realistic channel, mobility and radio link models introduced later in Section 3 can provide a realistic platform for BAN-specific performance evaluation and comparative studies for novel algorithms and protocols.  
In Castalia, NICTA [54] has contributed to developing BAN-specific wireless channels, mobility and radio models, _etc._[15; 40]. Channel measurements of the test bed are incorporated into the simulator. The measurements are analyzed to provide accurate models for both the average path losses around the body and, more importantly, the temporal variation behavior of the channel. Log-normal and custom path loss models based on the measurements are available. The radio module consists of cc1000 and cc2420 transceiver parameters along with the support of several modulation schemes, including frequency shift keying (FSK), phase shift keying (PSK), differential binary phase shift keying (DBPSK) and differential quadrature phase shift keying (DQPSK). Baseline MAC (IEEE 802.15.6 draft proposal) is partially available. The advantages of Castalia include specific BAN's channel models to realistically simulate BAN. Finally, with regards to BAN and BBN, MAC and routing protocols are proposed in [55; 56; 57], respectively. The baseline IEEE 802.15.6 MAC is enhanced by using models with temporal variations and average path losses based on real-body measurements [56]. Whereas, the other studies do not use BAN-specific channel and propagation models; further, all of these studies lack a realistic radio link and mobility models.  
With all the above-mentioned key features, Castalia seems an attractive choice. However, it has certain key limitations with respect to diverse mobility modeling, the IEEE 802.15.6 standard compliance protocol and communication stack, as well as the lack of BBN modules. In mobility modeling, only the line mobility (forward and backward movement) model is available, which is a very basic mobility pattern. Complete IEEE 802.15.6 PHY and MAC are not implemented.