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DiVote: A Distributed Voting Protocol for Mobile Device-to-Device Communication

机译:divote:用于移动设备到设备通信的分布式投票协议

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Distributed aggregation algorithms have traditionally been applied to environments with no or rather low rates of node churn. The proliferation of mobile devices in recent years introduces high mobility and node churn to these environments, thus imposing a new dimension on the problem of distributed aggregation in terms of scalability and convergence speed. To address this, we present DiVote, a distributed voting protocol for mobile device-to-device communication. We investigate a particular use case, in which pedestrians equipped with mobile phones roam round in an urban area and participate in a distributed yes/no poll, which has both spatial and temporal relevance to the community. Each node casts a vote and collects votes from other participants in the system whenever in communication range, votes are immediately integrated into a local estimate. The objective of DiVote is to produce a precise mapping of the local estimate to the anticipated global voting result while preserving node privacy. Since mobile devices may have limited resources allocated for mobile sensing activities, DiVote utilizes D-GAP compression. We evaluate the proposed protocol via extensive trace-driven simulations of realistic pedestrian behavior, and demonstrate that it scales well with the number of nodes in the system. Furthermore, in densely populated areas the local estimate of participants does not deviate by more than 3 % from the global result. Finally, in certain scenarios the achievable compression rate of DiVote is at least 19 % for realistic vote distributions.
机译:传统上,分布式聚合算法已经应用于没有或相当低的节点流失率的环境。近年来移动设备的扩散引入了对这些环境的高移动性和节点流失,从而对可扩展性和收敛速度的分布式聚集问题强加了新的维度。为了解决这个问题,我们提出了一种用于移动设备到设备通信的分布式投票协议的Divote。我们调查了一个特定用例,其中,配备手机的行人在城市地区漫游,并参加分布式是/否的民意调查,这与社区有空间和时间相关。每当在通信范围内,每个节点投票并从系统中的其他参与者收集投票,​​投票立即集成到本地估计中。除以在保留节点隐私的同时,生成对预期的全球投票结果的本地估计的精确映射。由于移动设备可以为移动感测活动分配有限的资源,因此除以D-GAP压缩。我们通过大量的追踪仿真模拟来评估所提出的协议,并证明它与系统中的节点数量良好。此外,在密集的地区中,参与者的当地估计不会偏离全球结果的3%以上。最后,在某些情况下,对于现实投票分布,除法的可实现的压缩率至少为19%。

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