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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 yeso 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，分布式聚合算法已应用于没有节点搅动率或节点搅动率很低的环境。近年来，移动设备的激增为这些环境带来了高移动性和节点搅动，从而在可伸缩性和融合速度方面对分布式聚合问题提出了新的要求。为了解决这个问题，我们提出了DiVote，这是一种用于移动设备到设备通信的分布式投票协议。我们调查了一个特定的用例，其中配备了手机的行人在市区内漫游，并参与对社区具有时空相关性的分布式“是/否”民意测验。只要在通信范围内，每个节点都会投票，并从系统中的其他参与者收集投票，​​投票会立即集成到本地估计中。 DiVote的目的是在保留节点隐私的同时，将本地估计值精确映射到预期的全球投票结果。由于移动设备可能分配给移动感测活动的资源有限，因此DiVote使用D-GAP压缩。我们通过对真实行人行为的大量跟踪驱动仿真来评估所提出的协议，并证明该协议可随着系统中节点数的扩展而扩展。此外，在人口稠密的地区，参与者的本地估计与整体结果的偏差不超过3％。最后，在某些情况下，对于现实的投票分配，DiVote可以实现的压缩率至少为19％。

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