Controlled text generation is very important for the practical use of language models because it ensures that the produced text includes only the desired attributes from a specific domain or dataset.Existing methods, however, are inapplicable to black-box models or suffer a significant trade-off between controlling the generated text and maintaining its fluency.This paper introduces the Score-based Progressive Editor (ScoPE), a novel approach designed to overcome these issues.ScoPE modifies the context at the token level during the generation process of a backbone language model.This modification guides the subsequent text to naturally include the target attributes.To facilitate this process, ScoPE employs a training objective that maximizes a target score, thoroughly considering both the ability to guide the text and its fluency.Experimental results on diverse controlled generation tasks demonstrate that ScoPE can effectively regulate the attributes of the generated text while fully utilizing the capability of the backbone large language models.Our codes are available at https://github.com/ysw1021/ScoPE.

Despite the success of neural machine translation models, tensions between fluency of optimizing target language modeling and sourcefaithfulness remain as challenges.Previously, Conditional Bilingual Mutual Information (CBMI), a scoring metric for the importance of target sentences and tokens, was proposed to encourage fluent and faithful translations.The score is obtained by combining the probability from the translation model and the target language model, which is then used to assign different weights to losses from sentences and tokens.Meanwhile, we argue this metric is not properly normalized, for which we propose Normalized Pointwise Mutual Information (NPMI).NPMI utilizes an additional language model on source language to approximate the joint likelihood of source-target pair and the likelihood of the source, which is then used for normalizing the score.We showed that NPMI better captures the dependence between source-target and that NPMI-based token-level adaptive training brings improvements over baselines with empirical results from En-De, De-En, and En-Ro translation tasks.

The data explosion and resource scarcity of mobile cellular networks require new paradigms to effectively integrate heterogeneous radio resources. Of many candidate approaches, smart aggregation of LTE and Wi-Fi radios is a promising solution that bonds heterogeneous links to meet a mobile terminal's bandwidth need. Motivated by the existence of a significant number of carrier operated Wi-Fi APs, we propose an easily deployable mechanism, called LTE-W, which efficiently utilizes LTE and Wi-Fi links only with the minimum change of eNodeBs, LTE backhaul networks, and mobile terminals. LTE-W, which is a link-level aggregation mechanism, has the following two key components: 1) mode selection and 2) bearer-split scheduling. First, in the mode selection, LTE-W internally decides who should be served by either LTE-only or LTE-Wi-Fi aggregation considering intra-cell fairness rather than just following users' intention of aggregation. For the users' preference to be offered the aggregation service, we choose a bearer (roughly defined in LTE as a set of flows with a similar QoS) as a basic unit of aggregation and propose a smart intra-bearer scheduling algorithm that splits a bearer's traffic into LTE and Wi-Fi links, considering the performance of TCP flows that take two heterogeneous wireless links. We evaluate our mechanism using the NS-3 with LENA, under various configurations, including nodes with mobility and HTTP traffic, and compare it with a transport-level aggregation mechanism, multipath TCP (MPTCP), demonstrating that LTE-W significantly improves MPTCP, e.g., up to 75% in terms of Jain's fairness index.

People are seeking solutions in diverse directions to cope with mobile data explosion and resource scarcity in mobile cellular networks. Of many candidate approaches, smart aggregation of LTE and Wi-Fi radios is a promising solution that bonds heterogeneous links to meet a mobile terminal's available bandwidth need. Motivated by the existence of a significant number of carrier-operated Wi-Fi APs, we propose a mechanism, called LTE-W, of efficiently utilizing LTE and Wi-Fi links only with the minimum changes of eNodeBs, LTE backhaul networks, and mobile terminals. Our mechanism has the following two key components: (i) mode selection and (ii) bearer-split scheduling. In the mode selection, LTE-W internally decides who should be served by either of LTE or LTE-Wi-Fi aggregation considering intra-cell fairness rather than just following users' intention of aggregation. For the users decided to be offered the aggregation service, we choose a bearer (roughly defined a set of flows with a similar QoS in LTE) as a basic unit of aggregation and propose a smart intra-bearer scheduling algorithm that splits a bearer's traffic into LTE and Wi-Fi links, considering the tuning of TCP flows that take two heterogeneous wireless links. We evaluate our mechanism using the NS-3 with LENA, and compare it to a transport-level aggregation mechanism, MPTCP, demonstrating that LTE-W significantly improves MPTCP, e.g., up to 75% in terms of Jain's fairness index.

This paper proposes a new protocol called Optimal DCF (O-DCF). O-DCF modifies the rule of adapting CSMA parameters, such as backoff time and transmission length, based on a function of the demand-supply differential of link capacity captured by the local queue length. O-DCF is fully compatible with 802.11 hardware, so that it can be easily implemented only with a simple device driver update. O-DCF is inspired by the recent analytical studies proven to be optimal under assumptions, which often generates a big gap between theory and practice. O-DCF effectively bridges such a gap, which is implemented in off-the-shelf 802.11 chipset. Through extensive simulations and real experiments with a 16-node wireless network testbed, we evaluate the performance of O-DCF and show that it achieves near-optimality in terms of throughput and fairness and outperforms other competitive ones, such as 802.11 DCF, optimal CSMA, and DiffQ for various scenarios. Also, we consider the coexistence of O-DCF and 802.11 DCF and show that O-DCF fairly shares the medium with 802.11 via its parameter control.

Optimal CSMA, which is fully distributed wireless MAC theory, has provided a rule of dynamically adapting CSMA parameters according to some theoretically developed principles, and has reported to offer nice analytical guarantees on throughput and fairness. Despite a couple of research efforts that transfer Optimal CSMA to practical protocols, e.g., O-DCF, our evaluation results show that they are still far from being deployable in practice mainly due to bad performance with TCP. In this paper, we first investigate how Optimal CSMA based MAC conflicts with TCP and degrades end-to-end performance, if poorly transferred to practice. Then, we propose a new wireless MAC protocol, called A-DCF, that inherits the basic framework and rationale of Optimal CSMA and O-DCF, but are largely redesigned to make A-DCF work well with TCP. The key idea of A-DCF lies in smartly exploiting both queue length and delay which widens our design space for compatibility with TCP. Our extensive simulation and experimental results demonstrate that A-DCF outperforms the traditional 802.11 and O-DCF. Particularly, we report our implementation code of A-DCF as a device driver module. To our knowledge, it is the first driver-level implementation of an Optimal CSMA based MAC protocol, being of broad interest to the community.

This paper proposes a new wireless MAC protocol called Optimal DCF (O-DCF). O-DCF modifies the rule of adapting CSMA parameters, such as backoff time and transmission length, based on a function of the supply-demand differential captured by the local queue length. O-DCF is fully compatible with 802.11 hardware, so that it can be easily implemented only with a simple device driver update. O-DCF is inspired by the recent theoretical studies on queue-based CSMA for high throughput and fairness. O-DCF effectively bridges the gap between theory and practice, implemented and tested in an off-the-shelf 802.11 chipset. Through extensive simulations and real experiments with a 16-node wireless network testbed, we evaluate the performance of O-DCF and show that it outperforms other competitive ones, such as 802.11 DCF, optimal CSMA, and DiffQ for various scenarios.

ABSTRACT In wireless network convergence, each mobile host is expected to have multiple kinds of wireless interfaces. Multicast‐based applications are expected to be widely deployed. In this paper, a new network selection scheme is proposed for a mobile host to select the most appropriate wireless access network to maximize user satisfaction and ISP's profit, simultaneously. We have devised a metric to measure a user's satisfaction and we also developed a ‘normalized network resource’ metric for system profit measure. We have compared our scheme with three other reference schemes, through simulations. Depending on the network deployment situations, our scheme exhibits one‐fifth service disruption time of other reference schemes, while the resource consumption of our scheme is comparable to that of the minimum resource scheme. Overall, the gain of our scheme becomes higher as users move faster and/or the population density increases. Copyright © 2010 John Wiley & Sons, Ltd.

Finding a reliable and efficient routing path in vehicular ad hoc networks (VANETs) is a challenging issue due to high mobility of vehicles and frequent link breakage. Motivated by this, we propose a robust and efficient routing protocol, called MMR. The contribution of this paper is two-fold: two-level routing and a new routing metric. A routing process of MMR consists of the macro level and the micro level. MMR forwards a packet to an approximate location of the destination at the macro level and then forwards a packet to the exact location of the destination at the micro level. This two-level routing reduces the protocol overhead and improves scalability in terms of the number of nodes. MMR also introduces a new routing metric that reduces the protocol overhead and path breakage by considering velocities of vehicles. Through simulations, we show that MMR improves the routing performance by about 30~40% in highly mobile environments, compared to the existing ad hoc routing protocols such as AODV and GPSR.

In this paper, we propose a hybrid query tree protocol that combines a tree based query protocol with a slotted backoff mechanism. The proposed protocol decreases the average identification delay by reducing collisions and idle time. To reduce collisions, we use a 4-ary query tree instead of a binary query tree. To reduce idle time, we introduce a slotted backoff mechanism to reduce the number of unnecessary query commands. For static scenarios of tags, we extended the proposed protocol by adopting two phases. First, inleafqueryphasefor existing tags, the interrogator queriesleaf-nodes directly to reuse query strings in the previous session. Second, inrootqueryphasefor new arriving tags, the interrogator starts the query process from theroof-node. Simulation reveals that the proposed protocol achieves lower identification delay than existing tag collision arbitration protocols regardless of whether tags are mobile or not.

In vehicular ad hoc networks (VANETs), geographic routing protocols appear to be a fascinating option since they have generally low delay and small routing overhead and GPS devices are becoming affordable. However, we reveal that geographic routing protocols suffer from routing holes when nodes are distributed only on lines such as cars on roads, trains on rails, and ships on courses. To tackle this problem, we propose a novel geographic routing protocol, virtual vertex routing (VVR), which uses the information of the lines. Using graph formulation, we introduce a new concept, the proximity of a vertex (or a virtual vertex). An intermediate node in this proximity performs routing toward the destination by Floyd algorithm. For routing holes, we propose two countermeasures: greedy routing (VVR-GR) and face routing (VVR-FR). The latter can guarantee the packet delivery. Extensive simulations are performed to show that VVR outperforms GPSR and AODV.

IEEE 802.11 WLAN has been widely accepted throughout the world. However, it has large overhead due to idle backoff slots and frequent collisions depending on the number of nodes. In this paper, we propose a novel medium access control scheme, scheduling-based coordination function (SCF). SCF polls the next station to be serviced by piggybacking. The selection of the next station is based on self-clocked fair queueing (SCFQ) scheduling in a distributed manner. Due to polling, SCF does not suffer from collisions and is efficient owing to the SCFQ scheme. SCF improves the system throughput up to 63.2% compared to IEEE 802.11 DCF. Comprehensive simulation is performed to compare SCF with DCF, PCF, and fast collision resolution (FCR).