76,776 research outputs found
Energy efficient and fair resource allocation for LTE-unlicensed uplink networks: A two-sided matching approach with partial information
LongâTerm Evolutionâunlicensed (LTEâU) has recently attracted worldwide interest to meet the explosion in cellular traffic data. By using carrier aggregation, licensed and unlicensed bands are integrated to enhance transmission capacity while maintaining reliable and predictable performance. As there may exist other conventional unlicensed band users, such as WiFi users, LTEâU users have to share the same unlicensed bands with them. Thus, an optimized resource allocation scheme to ensure the fairness between LTEâU users and conventional unlicensed band users is critical for the deployment of LTEâU networks. In this paper, we investigate an energy efficient resource allocation problem in LTEâU coexisting with other wireless networks, which aims at guaranteeing fairness among the users of different radio access networks. We formulate the problem as a multiobjective optimization problem and propose a semidistributed matching framework with a partial informationâbased algorithm to solve it. We demonstrate our contributions with simulations in which various network densities and traffic load levels are considered
Preference Elicitation in Matching Markets Via Interviews: A Study of Offline Benchmarks
In this paper we study two-sided matching markets in which the participants do not fully know their preferences and need to go through some costly deliberation process in order to learn their preferences. We assume that such deliberations are carried out via interviews, thus the problem is to find a good strategy for interviews to be carried out in order to minimize their use, whilst leading to a stable matching. One way to evaluate the performance of an interview strategy is to compare it against a nave ĂŻalgorithm that conducts all interviews. We argue however that a more meaningful comparison would be against an optimal offline algorithm that has access to agents' preference orderings under complete information. We show that, unless P=NP, no offline algorithm can compute the optimal interview strategy in polynomial time. If we are additionally aiming for a particular stable matching, we provide restricted settings under which efficient optimal offline algorithms exist
OPR
The ability to reproduce a parallel execution is desirable for debugging and program reliability purposes. In debugging (13), the programmer needs to manually step back in time, while for resilience (6) this is automatically performed by the the application upon failure. To be useful, replay has to faithfully reproduce the original execution. For parallel programs the main challenge is inferring and maintaining the order of conflicting operations (data races). Deterministic record and replay (R&R) techniques have been developed for multithreaded shared memory programs (5), as well as distributed memory programs (14). Our main interest is techniques for large scale scientific (3; 4) programming models
College admissions and the role of information : an experimental study
We analyze two well-known matching mechanismsâthe Gale-Shapley, and the Top
Trading Cycles (TTC) mechanismsâin the experimental lab in three different informational
settings, and study the role of information in individual decision making. Our results suggest
thatâin line with the theoryâin the college admissions model the Gale-Shapley mechanism
outperforms the TTC mechanisms in terms of efficiency and stability, and it is as successful as
the TTC mechanism regarding the proportion of truthful preference revelation. In addition, we
find that information has an important effect on truthful behavior and stability. Nevertheless,
regarding efficiency, the Gale-Shapley mechanism is less sensitive to the amount of information
participants hold
Preference Elicitation in Matching Markets Via Interviews: A Study of Offline Benchmarks
The stable marriage problem and its extensions have been
extensively studied, with much of the work in the literature
assuming that agents fully know their own preferences over
alternatives. This assumption however is not always practical
(especially in large markets) and agents usually need
to go through some costly deliberation process in order to
learn their preferences. In this paper we assume that such
deliberations are carried out via interviews, where an interview
involves a man and a woman, each of whom learns
information about the other as a consequence. If everybody
interviews everyone else, then clearly agents can fully learn
their preferences. But interviews are costly, and we may
wish to minimize their use. It is often the case, especially
in practical settings, that due to correlation between agentsâ
preferences, it is unnecessary for all potential interviews to
be carried out in order to obtain a stable matching. Thus
the problem is to find a good strategy for interviews to be
carried out in order to minimize their use, whilst leading to a
stable matching. One way to evaluate the performance of an
interview strategy is to compare it against a na¨Ĺve algorithm
that conducts all interviews. We argue however that a more
meaningful comparison would be against an optimal offline
algorithm that has access to agentsâ preference orderings under
complete information. We show that, unless P=NP, no
offline algorithm can compute the optimal interview strategy
in polynomial time. If we are additionally aiming for a
particular stable matching (perhaps one with certain desirable
properties), we provide restricted settings under which
efficient optimal offline algorithms exist
Contractual Structure and Endogenous Matching in Partnershipso
We analyze optimal contracts and optimal matching patterns in a simple model of partnership where there is a double-sided moral hazard problem and potential partners differ in their productivity in two tasks. It is possible for one individual to accomplish both tasks (sole production) and there are no agency costs associated with this option but partnerships are a better option if comparative advantages are significant. We show that the presence of moral hazard can reverse the optimal matching pattern relative to the first best, and that even if partnerships are optimal for an exogenously given pair of types, they may not be observed in equilibrium when matching is endogenous, suggesting that empirical studies on agency costs are likely to underestimate their extent by focusing on the intensive margin and ignoring the extensive margin.Endogenous matching, partnerships, contractual structure
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