Information Technology Reference
In-Depth Information
Chapter 6
Conclusion and Future Work
6.1
Conclusion
With continuing technological advances, the past few years have witnessed the per-
vasive penetration of wireless networks in people's lives. On the other hand, social
relationships play an increasingly important role in people's interactions with each
other, due to the rapid growth of online social networking services. In this brief, we
advocate to leverage wireless users' social ties to stimulate their cooperative behav-
iors in order to enhance their interactions in wireless networks. In general, wireless
users have diverse social ties while their wireless devices have diverse physical rela-
tionships. To capture both the social coupling and physical coupling among wireless
users, we develop a social group utility maximization (SGUM) framework. In the
SGUM game, each user aims to maximize its social group utility, which is the sum
of its own utility and the weighted sum of the utilities of the users having social tie
with it. To illustrate how to apply the SGUM framework for cooperative wireless
networking, we study its application in some specific contexts as follows.
•
We study the SGUM-based random access control and power control. For the
SGUM-based random access control game, we derive the unique SNE. For the
SGUM-based power control game, we show that it is a supermodular game and
thus there exists an SNE. We also derive the unique SNE for the two-user case of
the SGUM-based power control game. For both games, we show that as social tie
levels increase, each user's SNE strategy is decreasing and the social welfare of
the SNE is increasing.
•
We study the SGUM-based database assisted spectrum access. We show that
the SGUM-based spectrum access game is a potential game and thus always
admits a SNE. Then we design a distributed spectrum access algorithm that can
achieve the socially-aware Nash equilibrium. We also derive the upper-bound
of the performance gap of the socially-aware Nash equilibrium from the NUM
solution. Numerical results demonstrate that the performance gap between the
SGUM solution and the NUM solution is at most 15 %.
•
We study the SGUM-based pseudonym change for personalized location privacy.
The SGUM-based pseudonym change game (PCG) is based on a general
