Investigating Energy Consumption in Social Aware Opportunistic Networks with High Data Traffic

In Opportunistic Networks (OppNets), mobility of and contact between nodes are explored to create communication opportunities, exchange messages, and information. In the era of data sharing, the data traffic from messages may be higher with nodes exchanging text messages, media or streaming. The use of social aspects to find better relay nodes has become popular in forwarding strategies to increase network performance. However, due to resource constraints such as energy level and buffer space, social aspects applied to forwarding strategies may lead to unexpected behaviors or even harvest more energy from the chosen relay nodes. This work designed a set of experiments to investigate the relationship between energy consumption and social aspects. It is evaluated three trace-based mobility models with increasing contact densities. In addition, it is implemented and collected some social aspects from the investigated scenarios: centrality, betweenness, and local clustering coefficient (LCC). The results presented that the mean contact time of node has more correlation to energy consumption than social aspects (Pearson correlation= 0.99792) for the mobility traces evaluated. Further, when the mean contact time is extensive, the energy consumption increases from 210% to the more sparse to the denser scenario. We also verified that when the conditions for message exchanges are better, i.e., when contact time is enough to exchange all messages, the correlation between centrality and energy consumption is higher. Finally, with the extensive contact time, the energy of popular nodes was entirely harvested in our densest scenario.