# A Comprehensive Review on Network Protocol Design for Autonomic Internet of Things
## 3 Review of Protocol Designs
### Protocol Designs for Clustering
#### (4) EE-LEACH  
[PERSON] and [PERSON] in [20] proposed the Energy Efficient LEACH (EE-LEACH) protocol that improves the CH selection by creating an energy consumptionmodel and then calculating the intra cluster residual energy of the CH candidates and all neighbor nodes. This approach is expected to form cluster and select CH in more optimal ways in terms of energy consumption efficiency. Through simulation, it can be shown that this protocol can provide longer network lifetime, higher packet delivery ratio, and lower end-to-end delay than the original LEACH protocol. (5) Digital Hormone Model  
Besides the clustering protocols with the algorithm based on conventional method, some other clustering protocols are developed with the algorithm inspired by the behavior of living creatures and referred to as a bio-inspired algorithm. These protocols mimic the behavior of self-organization of living creatures, and heuristically perform self-healing and self-optimization. The implementation of the algorithm is also expected to have a faster optimization process than other algorithms. [PERSON] et al. at [21] proposed the Digital Hormone Model (DHM) protocol which is inspired by the behavior of Honey Bee. The system will execute the rule in the model based on the information that is locally obtained from the sensor. The information is mainly in the form of spatial and temporal data. The nodes communicate with each other through the exchange of this digital information hormone, which can lead to the optimal clustering result. The DHM protocol is validated through simulation. The simulation results have shown that it balances the energy saving and the tolerance for the network reconstruction error. A large number of nodes can share tasks in clusters, thereby increasing the data collection efficiency. The protocol still has a weakness. It has a bias that causes the system to tend to save energy and reduce the accuracy of the collected data in an area. The protocol also cannot be applied to a small number of nodes since they are not effective for collaboration. (6) Flower Pollination Optimization Algorithm  
[PERSON] et al. in [22] proposed an optimization algorithm for network clustering, which is known as the Flower Pollination Optimization Algorithm (FPOA). This algorithm is inspired by the movement of insects in the process of flower pollination and takes it as the model for network clustering. The algorithm takes the intra-cluster distances as the input parameter. The purpose is to achieve the global optimization with the objective function including the intra-cluster distances. The FPOA clustering algorithm is validated through simulation. The simulation results have shown that the algorithm can balance the use of energy among nodes and the network lifetime better than the LEACH's algorithm. The implementation of the algorithm also improves network throughput and network stability. The limitation of the algorithm is still that it uses only one objective in the calculation and does not take into account other variables that may need to be optimized. (7) Synchronous Firefly Algorithm  
[PERSON] and [PERSON] in [23] proposed an optimization algorithm for network clustering, which is known as the Synchronous Firefly Algorithm (SFA). This algorithm is inspired by the firefly colony. The algorithm selects the best CH by assuming the node profiles like fireflies. The best fireflies are selected using a competition. It allows the reproduction of fireflies through the mechanism of crossover and mutation. In the calculation, an objective function is determined by three variables, i.e., the energy consumption, the end-to-end delay, and the packet loss rate. The SFA clustering algorithm is validated through simulation. The simulation results have shown that the calculation for the selection of the best CH can achieve a fast convergence and avoid multiple local optima. The result also shows the decrease in packet loss rate and a significant improvement in energy efficiency and network lifetime compared with the LEACH protocol.