## 7 Cross-Layer Design Schemes
### Application and MAC, Physical Layer Schemes  
Although there are numerous examples of cross-layer schemes involving the lower layers, generally, cross-layer solutions incorporating the application layer do not figure highly in the available literature. Many existing protocols operating at the application layer were designed for wired networks and do not perform optimally in the low power wireless context. Schemes that can perform application level adaptation based on information from lower layers could provide performance benefits in low power wireless networks. The application layer can communicate the applications' QoS needs, _i.e._, data reliability, delay tolerance and response time to other layers [93]. Additionally, information on channel conditions from the MAC/physical layers could be used by the application layer as part of a cross-layer solution to improve performance. [PERSON] _et al._[94] developed an adaptive cross-layer mechanism to control congestion for real- and non-real time data flow to support QoS guarantees at the application layer. Priority was given to real time data in terms of delay and available link capacity. The scheme linked the QoS requirements at the application layer and the packet waiting time, collision resolution and packet transmission time metrics at the MAC layer. Correlation-based Collaborative MAC (CC-MAC) protocol [95] is a cross-layer solution incorporating the application and MAC layers. CC-MAC exploits the spatial correlation between nodes to reduce energy consumption without compromising the estimated reliability achieved at the sink. Experiments showed that CC-MAC delivered improved performance over S-MAC and T-MAC in terms of energy efficiency, packet drop rate, and latency. In their work on a new energy saving MAC model, [PERSON] _et al._[47] developed a cross-layer solution incorporating a fuzzy rule scheduling algorithm and radio activation policy. The researchers present Distributed Queuing Body Area Network (DQBAN) MAC as an enhancement to 802.15.4 for a BSN that extends the research carried out by [PERSON] and [PERSON] [96]. The research incorporates a fuzzy rule scheduler that optimizes the MAC layer to improve overall performance in terms of QoS and energy consumption. The protocol considered the node cross-layer constraints such as physical layer signal quality (SNR), system waiting time, and residual battery life to allocate slots within a superframestructure. Simulations covering homogeneous and heterogeneous scenarios demonstrated that DQBAN MAC can achieve higher reliabilities when compared to 802.15.4 whilst delivering specific latency demands and battery limitations. As part of research that focused on the benefits of cross-layer optimization between application and MAC layers, [PERSON] and [PERSON] [97] illustrated how two examples of an adaptive MAC could benefit in exchanging information with the application layer. To solve the problems of rapidly draining power sources and congestion in the network, the research exploited the high degree of spatial correlation that exists between the readings of adjacent nodes in a densely deployed network by utilizing a distributed and self organizing scheduling algorithm. The scheduling algorithm prevented two adjacent nodes acting as correlating nodes simultaneously and increased the robustness and accuracy of the data by giving every node a chance to act as a correlating node. Although simulations showed energy savings of up to 42% when using the cross-layer information, the researchers recognized that disturbances in the lower layers could have a detrimental effect on the upper layers. In particular, changes in link quality may lead to a reduction in the efficiency of the algorithm owing to the continuous rearranging of the scheduling scheme. This highlights the need for the upper layers to be adequately insulated from the instability of the lower layers. [PERSON] and [PERSON] [98] proposed an application and MAC cross-layer solution for packet loss mitigation for WBANs using CS based on ECG signals.