# A Novel Algorithm to Optimize the Energy Consumption Using IoT and Based on Ant Colony Algorithm
## 2 Literature Review
### Routing Algorithms in IoT Platform
In this protocol, the best neighbor in the terminal node is selected, and the network traffic is balanced when the source of the terminal node is limited, and the wireless routing network is used. The simulation results show that the conditions for achieving load equilibrium with energy-limited nodes are limited. Compared to the original AODVjr protocol, the method proposed in this paper achieves load balancing with better conditions, and this is due to better neighbor node access technology, which achieves better balance in the local network traffic, and the average latency due to better routing. In 2014, researchers proposed two methods for routing the Internet of Things based on the ant colony algorithm [23]. The EEPR method, which routes to missing packets, is probabilistic. The EEPR algorithm controls the requested packets to reduce missing packets and network traffic in the AODV protocol. A source node forwards Route Request (RREQ) packets to neighboring nodes to send the data packet. In all types of AODV protocols, each node that forwards an RREQ packet sends the same packet to neighboring nodes. In other words, any node that does not forward RREQ packets indicates that it has disconnected the entire connection. The energy distance function is used to implement the EEPR method. Therefore, in this paper, two different routings were developed. One is Expected Transmission Count (ETX), which creates a good connection between the nodes. Each node periodically receives packets from a small band and sends them to neighboring nodes. In the second method, through the energy variance of adjacent nodes, the probability of a link between two nodes is performed. The simulation results in an extensive network with a high lifetime using the cloning algorithm and showing better results than the AODV algorithm. [PERSON] et al. proposed a method called \"distribution and focusing\" to limit the overhead of delivering a message [24]. In this method, we first enter the distribution phase, in which the source generates L number up to the sending signal with each new message. The token means that the host node can generate and send another copy of a specific message. When a replay node has only one signal to send, we enter the focus phase, where the message can be sent to another replay node according to specific criteria. These sending criteria are based on timers that record the time elapsed since the two nodes met. In 2018, [PERSON] et al. presented a clustering scheme to extend nodes' lifespans in the Internet of Things [25]. One of the most critical problems and challenges in the Internet of Things is reducing power consumption to extend the network's lifespans. The clustering method is one of the approaches which is used to consume energy efficiency. However, most of the clustering schemes are chosen randomly without considering important parameters or based on a centralized approach using a base station that can affect the network's scalability. In addition, single-hop communications are used by clusters to send their measured data to clusters, leading to increased cluster energy consumption in large-scale networks. Therefore, in this paper, a clustering scheme based on a distributed approach is proposed. Different parameters are considered for cluster head selection as well as for multi-hop communication. The results show that the proposed scheme has better performance in energy consumption and the number of viable nodes. In 2015, [PERSON] and colleagues proposed a new way to reduce energy consumption in the IoT. The optimal use of energy in these types of networks is crucial. Recent research shows that organizing network nodes in some clusters increases energy efficiency and ultimately increases network lifespan. Therefore, controlling the number and location of cluster heads and the size of the cluster in terms of the number of nodes leads to a balance in the energy use of the cluster heads and increases the network lifespan.