# An Energy-Saving Forwarding Mechanism Based on Clustering for Opportunistic Networks
## 2 Related Works  
Recent forwarding strategies adopt social aspects at the core of their decisions. OppNet users carry mobile devices; thus, it is reasonable to claim that social network models are suitable for designing routing protocols [11]. Most of them emphasize the role of social aspects in the design phase, such as tie strength, popularity, or centrality metrics [12; 13]. Recently, [PERSON] et al. [14] researched opportunistic routing algorithms that use social features to stimulate the performance of message forwarding. The authors conducted comparative research on these algorithms, analyzing three social characteristics, namely centrality, similarity, and tie strength, in addition to simulation experiments, demonstrating the impact of these algorithms on the network. They reinforced the idea that, although much work has already been performed on opportunistic routing algorithms, they still need to explore social features more effectively in designing new routing algorithms. Despite the significance of social aspects, resource constraints also play an essential role in nodes deciding to cooperate in network transactions. Whereas opportunistic contacts are the primary reason to yield communication, the node's unwillingness to cooperate affects the network performance and may be harmful [15]. In a questionnaire applied by [PERSON] et al. [16], 10% of the mobile users at the Federal University of Amazonas (UFAM) claimed they would share data with other devices, even though they had a low battery level, and 55% of the users would prefer to recharge their battery fully. [PERSON] et al. [17] showedthat network performance degrades to about 62% when the proportion of non-cooperating nodes goes from 0% to 50%. In OppNets, nearby devices may cooperate by sharing data. However, the interaction and data transfer among nodes can consume different energy levels depending on the operation, since mobile nodes are battery operated. Therefore, even discovering if a neighbor device is near may consume an extensive amount of energy. In [17], the authors define the following modes as energy-consuming: scanning, transmission, reception, and inactive mode. A study by [PERSON] and [PERSON] [18] on the evaluation and comparison of energy consumption in OppNets takes into account mobility models relating them to energy consumption and selfish nodes, concluding that routing protocols in opportunistic networks focus on decreasing the average delay and the overhead and increasing the message delivery rate. For this, they increase the number of copies of packets on the network. Therefore, more energy is consumed by the nodes, making the environment more hostile, as the energy consumption plays a crucial role in modifying the behavior of nodes in the network because nodes with low battery power can become selfish and uncooperative. The authors [PERSON] et al. [19] emphasized the formation of communities based on social characteristics, proposing an opportunistic network routing strategy based on individual communities of nodes. The algorithm builds social relationships through the probabilistic encounter between them; individual communities are formed based on the centrality of nodes. Another approach in [20] is to form user clusters through the probability of meeting between the nodes. This reflects the degree of connection between them, which can be used for forwarding future messages. The idea is that users with a high probability of finding each other must be in the same cluster. The work of [PERSON] et al. [12] demonstrates that social communities positively affect data transmission. However, in [2], the authors conclude that using social characteristics might be unfair and may cause node overload. Their results showed that only 10% of nodes handle 63% of all data traffic. [PERSON] and [PERSON] [3] proposed a modified version of Bubble Rap [12] by randomly choosing some nodes among the most central (a popularity metric) nodes to reduce their load.