An Adaptive Probability Prediction Routing Scheme in Urban DTNs Most existing DTN routing algorithms canu0027t show efficient network performance. Prophet is a routing protocol widely used for DTNs. The delivery predictability of active nodes will obviously reduce with the same speed as less active nodes. In this paper, we propose an Adaptive Probability Prediction Routing (APPR) approach, which can dynamically adjust the aging factor based on the active degree of nodes. Leveraging the APPR approach, the delivery predictability of each node can be reduced in different speed if the node does not encounter the other node. Furthermore, when two nodes encounter, the forward decision depends on the distance between each node to the destination node, if the delivery predictabilities of encountered nodes are similar. Compared with the traditional Prophet, simulation results demonstrate the proposed APPR approach can significantly improve successful delivery ratio, reduce overhead ratio and the average latency.

An Energy Efficiency Approach via SelfAdaptive DutyCycle in Social Contacts Scenario With the implementation arriving of the Internet of Things, multihop transmission by shortrange 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. Dutycycle 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 selfadaptive dutycycle, 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 dutycycle to achieve the energysaving purpose. Our simulation results show that selfadaptive dutycycle is superior to other fixed ratio of dutycycles in energy efficiency, network lifetimes. Meanwhile, the main indicators of network performance are not affected by sleeping behavior.