# A Cache Placement Strategy with Energy Consumption Optimization in Information-Centric Networking
## 4 Simulation Results and Analysis
### Energy Savings  
Energy savings are the energy saved by the content being acquired at the cache node compared with the other nodes. In this paper, the process of obtaining information includes the user sending a request and the content being returned. The more energy is saved, the better the cache strategy is used. The comparison results of the energy savings of each strategy are shown in Figure 3a,b when the number of user \(m\) changes (100 to 1000). The analysis is performed under the parameter configurations of the best and worst case conditions. That is to say, \(P_{c}\) is 0.1 and 1, respectively. Figure 2: The effect of cache node change energy consumption on energy savings. From Figure 3a, we can see that the order of saving energy consumption from high to low is: ESCPS > Random > LCD. With the increasing number of users, the three curves show an increasing trend. Among them, the increase of ESCPS is the largest, indicating that these three strategies have their own effects in terms of energy saving, and all save a certain amount of energy consumption. By comparison, the LCD's energy-saving effect is not good, with the smallest increase. The main reason is that the location of the selected cache is narrowed by one jump relative to the user to the source server. The essence is to move the content forward to a node and not make a choice according to the specific situation of the network. The choice is too limited. Compared with LCD, the placement of cache placement nodes in Random is equal probability, which has better flexibility so that the deficiency of simplification is made up. Therefore, the achieved energy saving effect is slightly better than LCD. After comparison, it can be clearly seen that ESCPS has the best energy saving effect. Because it is based on energy consumption optimization, the sum of energy consumed by each user for content acquisition is taken into consideration. Therefore, when the number of users increases, the growth rate is the largest, and a good energy saving effect is always maintained. At the same time, LCD and Random have not considered the placement of cache from the perspective of the user [6; 7], and the importance of user distribution is ignored. From Figure 3b and the above comparison, we can see that when \(P_{c}\) increases, the number of the users' increases, the energy consumption of LCD is significantly reduced or even negative, and the energy saving effect has not been achieved. This is because LCD consumes a certain amount of energy consumption of cache nodes when selecting nodes, and it is related to the number of users; that is, \(mP_{c}\). Then, when the number of users is increased and \(P_{c}\) is also increased, the cost and energy consumption will also be greatly increased, thus saving energy consumption will be greatly reduced to negative value. It is shown that the cache node selected by this strategy can no longer achieve energy saving in content distribution. Compared with other placement nodes, energy is not only saved, but it also consumes more energy. Compared with LCD, Random is slightly better in energy saving stability, but the energy saving of the cached node is greatly reduced when the energy consumption and the number of users are increased. This is due to the random probability of randomness of Random, which is also affected by the energy consumption of replacement of cache nodes. Therefore, when both \(P_{c}\) and \(m\) increase, we can see that this is because the random probability of Random is also affected by the replacement energy consumption of the cache node. Therefore, when both \(P_{c}\) and \(m\) increase, Random has almost no negative value but the energy-saving effect is almost zero. Compared with the other two strategies, ESCPS can still maintain a good energy-saving effect and is particularly prominent in stability. In comparison, the ESCPS strategy has more advantages in saving energy consumption when hotspot information erupts and the user requests are mostly consistent.