  An effective way for a Mobile network operator (MNO) to improve its revenue
is price discrimination, i.e., providing different combinations of data caps
and subscription fees. Rollover data plan (allowing the unused data in the
current month to be used in the next month) is an innovative data mechanism
with time flexibility. In this paper, we study the MNO's optimal multi-cap data
plans with time flexibility in a realistic asymmetric information scenario.
Specifically, users are associated with multi-dimensional private information,
and the MNO designs a contract (with different data caps and subscription fees)
to induce users to truthfully reveal their private information. This problem is
quite challenging due to the multi-dimensional private information. We address
the challenge in two aspects. First, we find that a feasible contract
(satisfying incentive compatibility and individual rationality) should allocate
the data caps according to users' willingness-to-pay (captured by the slopes of
users' indifference curves). Second, for the non-convex data cap allocation
problem, we propose a Dynamic Quota Allocation Algorithm, which has a low
complexity and guarantees the global optimality. Numerical results show that
the time-flexible data mechanisms increase both the MNO's profit (25% on
average) and users' payoffs (8.2% on average) under price discrimination.
