# Cross-Layer Energy Optimization for IoT Environments: Technical Advances and Opportunities
## 4 Energy Efficient Techniques in the IoT
### Energy Efficient Techniques at Network/Communication Layer
#### 4.3.3 Energy Efficient Communication Techniques
An Energy- and Context-Centric Perspective on IoT Systems and Protocol Design (EC-CENTRIC) [50] has been proposed to provide an optimization framework that analyzes basic functionalities of IoT systems in terms of energy and context. The process of this framework is divided in three technical aspects: providing a balance between communication tasks and processingtechniques dependent on signal-like feature extraction and compression, enhancing network lifetime while designing routing and channel access protocols jointly, and adopting appropriate learning architecture and reconfigurable techniques to provide self-adaptability in various operating conditions as presented in Figure 17.  
Co-locating services in IoT systems to minimize the communication energy cost [51] minimizes computation and communication energy by enabling a service merging technique utilized in mapping and co-located multiple services on devices in IoT applications. After formulating the service co-location problem as a quadratic programming problem, it is reduced to an integer programming problem using a reduction technique in multi hop networks, and modeled as a maximum weighted independent set problem in a single hop network. Using integer programming reduction, the energy cost of a component \(C^{i}\) is expressed as:  
\[\delta\Big{(}C^{i}\Big{)}=\sum_{x}\delta_{T}\Big{(}L^{ix}\Big{)}+\sum_{y} \delta_{R}\Big{(}L^{yi}\Big{)} \tag{26}\]  
where \(\delta_{T}\Big{(}L^{ix}\Big{)}\) and \(\delta_{R}\big{(}L^{yi}\Big{)}\) are transmission cost of its out-links \(L^{ix}\) and receiving cost of its in-links \(L^{yi}\) in FBP respectively. Here \(p^{ij}=1\) if \(C^{i}\) has chosen to be run on device \(D^{i}\) then the energy consumption of a device is formulated as:  
\[\delta\Big{(}D^{j}\Big{)}=\sum_{i}p^{ij}*\delta\Big{(}C^{i}\Big{)} \tag{27}\]  
A summary of related literatures on energy efficient communication techniques is given in Tables 12 and 13, which comprises characteristics/protocol, issues, contributions, techniques, simulation tools used, metrics and research limitations of each paper reviewed. Figure 16: Communication stages of molecular communication using bacteria relay. Figure 17: Energy and context centric framework. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Protocol/Author**} & \multicolumn{6}{c}{**Approaches**} & \multicolumn{6}{c}{**Metrics**} & \multicolumn{6}{c}{**Limitations**} \\ \cline{2-13}  & **MAC** & **BMR** & **DC** & **CA** & **CLT** & **DL** & **EE** & **T-Ratio** & **L-Ratio** & **NL** & **ND** & **NDIB** & **DR** & **QoS** \\ \hline FFSC [48] & \(\surd\) & & \(\surd\) & & & \(\surd\) & & & \(\surd\) & & & \(\surd\) & & \\ MCVB [49] & & \(\surd\) & & \(\surd\) & & \(\surd\) & & & & \(\surd\) & & & \(\surd\) & \\ EC-CENTRIC [50] & \(\surd\) & & \(\surd\) & \(\surd\) & & \(\surd\) & & & \(\surd\) & & \(\surd\) & & \(\surd\) \\ FBP [51] & & & & & \(\surd\) & \(\surd\) & \(\surd\) & & \(\surd\) & & & \(\surd\) & \\ \hline \hline \end{tabular}
\end{table} 
Table 13: Comparative assessment of energy efficient communication techniques.