WiFi is increasingly used by carriers for opportunistically
offloading the cellular network infrastructure or even for
increasing their revenue through WiFi-only plans and WiFi ondemand
passes. Despite the importance and momentum of this
technology, the current deployment of WiFi access points (APs)
by the carriers follows mostly a heuristic approach. In addition,
the prevalent free-of-charge WiFi access policy may result in
significant opportunity costs for the carriers as this traffic could
yield non-negligible revenue. In this paper, we study the problem
of optimizing the deployment of WiFi APs and pricing the WiFi
data usage with the goal of maximizing carrier profit. Addressing
this problem is a prerequisite for the efficient integration of WiFi
to next-generation carrier networks. Our framework considers
various demand models that predict how traffic will change in
response to alteration in price and AP locations. We present
both optimal and approximate solutions and reveal how key
parameters shape the carrier profit. Evaluations on a dataset of
WiFi access patterns indicate that WiFi can indeed help carriers
reduce their costs while charging users about 50% lower than
the cellular service.
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D2D Communications Assisted Traffic Offloading in Integrated Cellular-WiFi Networks
Offloading cellular traffic to WiFi networks plays an important role in alleviating the increasing burden on cellular networks. However, excessive traffic offloading brings severe packet collisions into a WiFi network due to its contention-based medium access scheme, which significantly reduces the WiFi network’s throughput. In this paper, we propose DAO, a device-to-device (D2D) communications assisted traffic offloading scheme to improve the amount of traffic offloaded from cellular to WiFi in integrated cellular and WiFi networks. Specifically, in an integrated cellular-WiFi network, the cellular network exploits D2D communications in licensed cellular bands to aggregate traffic from cellular users before offloading it to the WiFi network to reduce the number of contending users in WiFi access. The traffic offloading process in DAO is formulated as an optimization problem that jointly takes into account the activations of aggregation nodes (ANs) and the connections between ANs and offloading users to maximize the offloaded traffic while guaranteeing the long-term data rates required by the offloading users. Extensive simulation results reveal the significant performance gain achieved by DAO over the existing schemes.
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- NSF-PAR ID:
- 10112934
- Date Published:
- Journal Name:
- IEEE Internet of Things Journal
- ISSN:
- 2372-2541
- Page Range / eLocation ID:
- 1 to 1
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1109/JIOT.2019.2922550
