Multi-threads computation for aggregation of time-series data Online publication date: Mon, 21-Jan-2019
by Wang Jie; Lu Jingyi
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 16, No. 1, 2019
Abstract: Time-series data involved applications have become popular with the rapid improvement of smart terminals and wireless networks. For example, in the case of mobile sensing, a sensing user will get a private input in each time period. And during the same period, the aggregator wants to calculate the aggregation statistics from the private inputs of sensing users. The privacy issue becomes much more challenging in the case of an untrusted aggregator. We are trying to increase the computation efficiency of the untrusted aggregator. Multi-cores architecture based CPU has been widely applied for not only personal computers but also servers. And it has been an indispensible field in our everyday life. In this paper, we take advantages of multi-threads computation to a scalable basic aggregation protocol, and improve the computation efficiency of the untrusted aggregator. We conduct some experiments to compare it with the basic protocol. The conducted experiments show the computation efficiency of our proposed protocol.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Wireless and Mobile Computing (IJWMC):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook