An Energy Efficiency Approach via Self-Adaptive Duty-Cycle in Social Contacts Scenario

With the implementation arriving of the Internet of Things, multi-hop transmission by short-range communication becomes more important than ever before in DTN research areas. The energy efficiency has been received more attention by researchers due to constrained energy battery. From earlier research, the vast majority of energy consumption is used for neighbors detecting. Duty-cycle strategy is an efficient way to improve power efficiency, whereas it is too simple to take advantage of contacting opportunities. Therefore, we designed a sleeping strategy for the mobile devices, and named self-adaptive duty-cycle, which based on the social contacts of the devices in the urban scenario. This approach mainly focuses on the historical encounters of the devices, and then it uses the weighted moving average approach to predict the encounter situation of the mobile device, and adjust the size of the duty-cycle to achieve the energy-saving purpose. Our simulation results show that self-adaptive duty-cycle is superior to other fixed ratio of duty-cycles in energy efficiency, network lifetimes. Meanwhile, the main indicators of network performance are not affected by sleeping behavior.