Mobile web traffic and application data demands are growing at a rapid rate and are at odds with resource-constrained, data-capped, wireless mobile devices. Data compression can be used to reduce web traffic, save energy, and make network transfers faster. Compression can, however, hurt performance if not used judiciously. We propose Locomotive, a library that improves the performance of network transfers in wireless mobile networks by employing selective compression based on data type and network conditions. We demonstrate that Locomotive improves performance of web transfers by roughly 12-24% while reducing data usage by 39%.
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FastHLA: Energy-Efficient Mobile Data Transfer Optimization Based on Historical Log Analysis
Mobile data traffic will exceed PC Internet traffic by 2020. As the number of smartphone users and the amount of data transferred per smartphone grow exponentially, limited battery power is becoming an increasingly critical problem for mobile devices which depend on the network I/O. Despite the growing body of research in power management techniques for the mobile devices at the hardware layer as well as the lower layers of the networking stack, there has been little work focusing on saving energy at the application layer for the mobile systems during network I/O. In this paper, we propose a novel technique, called FastHLA, that can achieve significant energy savings at the application layer during mobile network I/O without sacrificing the performance. FastHLA is based on historical log analysis and real-time dynamic tuning of mobile data transfers to achieve the optimization goal. FastHLA can increase the data transfer throughout by up to 10X and decrease the energy consumption by up to 5X compared to state-of-the-art HTTP/2.0 transfers.
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- NSF-PAR ID:
- 10074017
- Date Published:
- Journal Name:
- MobiWac'18 Proceedings of the 16th ACM International Symposium on Mobility Management and Wireless Access
- Page Range / eLocation ID:
- 59 to 66
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3265863.3265871
