EAGER: NeTS: Pilot Studies on Proximity for Taming the Wireless Data Tsunami
EAGER: NeTS: Pilot Studies on Proximity for Taming the Wireless Data Tsunami
批准号:
1500004
负责人:
Aaron Striegel
金额:
$4.95万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-01-15 至 2016-12-31
中文摘要
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英文摘要
The past few years have seen unprecedented growth in mobile data consumption. Powered in large part by the rapid adoption of smart phones and tablets, the growth in wireless data creates phenomenal challenges for the wireless industry, which has been unable to meet the demand for rich mobile content through cellular networks. This has led to the investigation of solutions by network operators that aim to utilize WiFi radios present in these mobile devices to deliver content without using the cellular radio links, also known as content-offloading. Industry-led approaches aim to utilize WiFi infrastructure in the form of access points to offload this content, but these have various deployment issues. Research has lately focused on the potential of proximity-based peer content sharing, since proximity enables low-power, high speed data exchanges which in turn allows mobile devices to proactively share data with one another. No large-scale study using real-world situations has established the potential for such content-sharing to provide capacity gains, until now. This proposal aims to conduct solid, preliminary pilot studies evaluating several of the foundational claims in this area, specifically as to whether sufficient potential exists in the right time, right place, and with reasonably viable deployment scenarios. The proposed work will gather and evaluate pilot data in both highly amenable environments (WiFi across multiple tailgate offerings of hundreds of users) as well as more challenging environments (daily commuter trains to / from Chicago).The broader impact of the work will be to either demonstrate the potential viability for proximity-based solutions or to present compelling evidence that such proximity solutions are unlikely to yield significant benefits. Further broader impacts for the work include data sharing capabilities with respect to temporal characterizations of redundancy across mobile devices in several real-world scenarios.
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