Abstract. Publication of moving objects' everyday life trajectories may cause serious personal privacy leakage. Existing trajectory privacy-preserving methods try to anonymize k whole trajectories together, which may result in complicated algorithms and extra information loss. We observe that, background information are more relevant to where the moving objects really visit rather than where they just pass by. In this paper, we propose an approach called You Can Walk Alone (YCWA) to protect trajectory privacy through generalization of stay points on trajectories. By protecting stay points, sensitive information is protected, while the probability of whole trajectories' exposure is reduced. Moreover, the information loss caused by the privacy-preserving process is reduced. To the best of our knowledge, this is the first research that protects trajectory privacy through protecting significant stays or similar concepts. At last, we conduct a set of comparative experimental study on real-world dataset, the results show advantages of our approach.
Many efforts have been devoted to maximizing the network throughput with limited channel resources in multi-radio multi-channel wireless mesh networks. It has been believed that the limited spectrum resource can be fully exploited by utilizing partially overlapping channels in addition to nonoverlapping channels in 802.11b/g networks. However, there are only few studies of channel assignment algorithms for partially overlapping channels. In this paper, an extension to the traditional conflict graph model, weighted conflict graph, is proposed to model the interference between wireless links more accurately. Based on this model, we first present a greedy algorithm for partially overlapping channel assignment, and then propose a novel genetic algorithm, which has the potential to obtain better solutions. Through evaluation, we demonstrate that the network performance can be dramatically improved by properly utilizing the partially overlapping channels. In addition, the genetic algorithm outperforms the greedy algorithm in mitigating the interference within the network and therefore leads to higher network throughput.
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