Designing a Combinatorial Market for Offloading Cellular Traffic via Wireless Access Points
Event details
| Date | 04.06.2015 |
| Hour | 15:15 › 16:15 |
| Speaker | Sven Seuken, University of Zurich (Switzerland) |
| Location | |
| Category | Conferences - Seminars |
Every year, mobile network operators (MNOs) around the world
spend billions of dollars expanding their mobile networks, to cope with
the exponentially increasing demand for 3G and 4G bandwidth. Cellular
capacity is particularly scarce in inner-city locations during the
middle of the day. At the same time, the majority of wireless access
points (residential and commercial) are largely idle most of the time,
i.e., the cheap Internet bandwidth provided by Internet Service
Providers (ISPs) remains largely unused. This gives rise to
opportunities for trade, where some of the peak-time cellular traffic
from the MNOs is offloaded via wireless access points, in exchange for
payments from the MNOs to the ISPs. However, determining optimal
allocations and prices is challenging from a computational and economic
perspective, in particular because MNOs have complex, combinatorial
preferences: their need and their value for offloading traffic vary by
location and by time-of-day.
In this paper, we propose a market design solution for this problem,
where an intermediary sets up a smart market platform that automatically
establishes trades between sellers and buyers. We first describe how the
preferences of the sellers and buyers in this domain can be modeled
succinctly. Then we introduce a combinatorial allocation mechanism that
computes an optimal allocation, i.e., which MNOs get to offload how much
of their traffic in which of their cell sectors and at what time of the
day. Finally, we show how to use core-selecting combinatorial auctions
in this domain to computes prices for each MNO, while minimizing the
incentives for the MNOs to misreport their values. We conclude by
discussing a number of challenges that arise in fielding this mechanism
in practice.
spend billions of dollars expanding their mobile networks, to cope with
the exponentially increasing demand for 3G and 4G bandwidth. Cellular
capacity is particularly scarce in inner-city locations during the
middle of the day. At the same time, the majority of wireless access
points (residential and commercial) are largely idle most of the time,
i.e., the cheap Internet bandwidth provided by Internet Service
Providers (ISPs) remains largely unused. This gives rise to
opportunities for trade, where some of the peak-time cellular traffic
from the MNOs is offloaded via wireless access points, in exchange for
payments from the MNOs to the ISPs. However, determining optimal
allocations and prices is challenging from a computational and economic
perspective, in particular because MNOs have complex, combinatorial
preferences: their need and their value for offloading traffic vary by
location and by time-of-day.
In this paper, we propose a market design solution for this problem,
where an intermediary sets up a smart market platform that automatically
establishes trades between sellers and buyers. We first describe how the
preferences of the sellers and buyers in this domain can be modeled
succinctly. Then we introduce a combinatorial allocation mechanism that
computes an optimal allocation, i.e., which MNOs get to offload how much
of their traffic in which of their cell sectors and at what time of the
day. Finally, we show how to use core-selecting combinatorial auctions
in this domain to computes prices for each MNO, while minimizing the
incentives for the MNOs to misreport their values. We conclude by
discussing a number of challenges that arise in fielding this mechanism
in practice.
Links
Practical information
- General public
- Free
Organizer
- Boi Faltings
Contact
- Sylvie Thomet