# 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
#### 4.3.2 Energy Efficient Routing Techniques  
Energy-efficient probabilistic routing (EEPR) [43] has been suggested to control the transmission of routing packets randomly using flooding technique while enhancing the network lifetime and minimizing the packet loss rate. EEPR utilizes two metrics: expected transmission count and residual energy of every node simultaneously in the context of typical ad-hoc on demand vector protocol. While using the expected transmission count metric, EEPR composes the routing route with better link quality, while using the residual energy of every node as a routing metric makes it possible the utilization of energy more evenly for all the IoT nodes across the network. The transmission count metric is induced not by using the heuristic method but by using the bit error rate based on the path-loss model. The second routing metric used is residual energy which results in even use of it among all the nodes (Figure 14). Then, the forwarding probability \(p\) of a node under the proposed EEPR algorithm is determined as:  
\[ \begin{split} p=[P_{min}+E_{i}A[1+\frac{\left(ETX_{(i-1,i)}-ETX _{max}\right)}{(1-ETX_{max})}]]^{1/\infty},\\ A=\ \frac{1-P_{min}}{2\times E_{max}}\end{split}  \tag{14}\]  
where \(E_{i}\) and \(E_{max}\) are residual energy and maximum residual energy of node \(i\), and \(P_{min},\ \text{and}\ \ \infty\) are predefined minimum forwarding probability, and the weighted factor for variation of \(p\) respectively. The forwarding probability is better, with high residual energy of the node and low ETX value of the link, but in case of far lower ETX value of link and less residual energy of the node, the forwarding probability is low. Figure 13: System model. EEPR algorithm results in slightly more route setup delay and slightly lesser routing success probability. EEPR does not consider the delay. Equation (14) has been illustrated by Figure 15. Figure 15a shows that how forwarding probability of a node varies as \(ETX_{(i-1,i)}\) varies in Equation (14), while Figure 15b shows the relation between forwarding probability and residual energy of node \(i\). Here \(E_{max}\) has been considered as 100 joule to calculate \(A\). Routing protocol based on Energy and Link quality (REL) [44] is based on optimization of the route selection mechanism while utilizing link quality estimation, energy evaluation, hop count and load balancing mechanisms, so it increases the system's reliability and prevents premature death of nodes. REL uses three metrics: residual energy, link quality based on weak links, and hop count to minimize long and inefficient paths. For the route selection process, there are two threshold values: first threshold is \(E_{th}\)(energy threshold) used in load balancing technique and finding route. The second threshold is \(HCdiffer^{\max,allow}\) (maximum-hop-count-difference) which calculates the maximum difference of hops to the present route. The prime technique of fault tolerance and load balancing in WSNs/IoT applications is the usage of multiple routes to control traffic across various paths. By using multiple routes, throughput and data reliability can be increased by balancing utilized energy and bandwidth aggregation. In REL, route selection is processed on the basis of three rules. If \(R_{a}\) is current route and \(R_{b}\) is alternative route and \(E_{th}\) is energy threshold then both routes are compared based on the metrics and there is a switch from \(R_{a}\) to \(R_{b}\) if the comparison satisfied the rules described below:  
1. \(R_{a}\) energy = \(R_{b}\) energy, \(R_{a}\) hopcount = \(R_{b}\) hopcount + \(HCdiffer^{\max,allow}\) and \(R_{a}\) weak links = \(R_{b}\) weak links
2. \(R_{a}\) energy < \(R_{b}\) energy, \(R_{a}\) hopcount \(\geq\)\(R_{b}\) hopcount + \(HCdiffer^{\max,allow}\) and \(R_{a}\) weak links \(\geq\)  
Figure 14: EEPR algorithm. Figure 15: Representation of equation 14: (**a**) forwarding probability of a node via \(ETX_{(i-1,i)}\); (**b**) forwarding probability via residual energy of node \(i\). 3.