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Tons of online user behavior data are being generated every day on the booming and ubiquitous Internet. Growing efforts have been devoted to mining the abundant behavior data to extract valuable information for research purposes or business interests. However, online users’ privacy is thus under the risk of being exposed to third-parties. The last decade has witnessed a body of research works trying...
Online user behavior analysis is becoming increasingly important, and offers valuable information to analysts for developing better e-commerce strategies. However, it also raises significant privacy concerns. Recently, growing efforts have been devoted to protecting the privacy of individuals while data aggregation is performed, which is a critical operation in behavior analysis. Unfortunately, existing...
In wireless sensor networks, in-network data aggregation is an efficient way to reduce energy consumption in network. However, most of the existing data aggregation scheduling methods try to aggregate the data from all the nodes at all time-instances. It is neither energy efficient nor practical because of the link unreliability and spatial and temporal data correlations. In this paper, we propose...
Data aggregation is a primitive communication task in wireless sensor networks (WSNs). In this paper, we study designing data aggregation schedules under the Protocol Interference Model for answering queries. Given a network consisting of a set of nodes V distributed in a two-dimensional plane, we address different kinds of queries in this paper. First and foremost, we consider a single one-off query...
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