Articles

Dual decomposition with many overlapping components

Martins A.F.T., Smith N.A., Aguiar P.M.Q., Figueiredo M.A.T.

EMNLP 2011 - Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference

2011

Abstract:

Dual decomposition has been recently proposed as a way of combining complementary models, with a boost in predictive power. However, in cases where lightweight decompositions are not readily available (e.g., due to the presence of rich features or logical constraints), the original subgradient algorithm is inefficient. We sidestep that difficulty by adopting an augmented Lagrangian method that accelerates model consensus by regularizing towards the averaged votes. We show how first-order logical constraints can be handled efficiently, even though the corresponding subproblems are no longer combinatorial, and report experiments in dependency parsing, with state-of-the-art results.

Dynamic Doxastic Differential Dynamic Logic for Belief-Aware Cyber-Physical Systems

Martin J., Platzer A., Leite J.

Automated Reasoning with Analytic Tableaux and Related Methods, 28th International Conference, TABLEAUX 2019

2019

Abstract:

Cyber-physical systems (CPS), such as airplanes, operate based on sensor and communication data, i.e. on potentially noisy or erroneous beliefs about the world. Realistic CPS models must therefore incorporate the notion of beliefs if they are to provide safety guarantees in practice as well as in theory. To fundamentally address this challenge, this paper introduces a first-principles framework for reasoning about CPS models where control decisions are explicitly driven by controller beliefs arrived at through observation and reasoning. We extend the differential dynamic logic Open image in new window for CPS dynamics with belief modalities, and a learning operator for belief change. This new dynamic doxastic differential dynamic logic Open image in new window does due justice to the challenges of CPS verification by having (1) real arithmetic for describing the world and beliefs about the world; (2) continuous and discrete world change; (3) discrete belief change by means of the learning operator. We develop a sound sequent calculus for Open image in new window , which enables us to illustrate the applicability of Open image in new window by proving the safety of a simplified belief-triggered controller for an airplane.

Dynamic Doxastic Differential Dynamic Logic for Belief-Aware Cyber-Physical Systems?

Martins J., Platzer A., Leite J.

TABLEAUX, LNCS

2019

Abstract:

Cyber-physical systems (CPS), such as airplanes, operate based on sensor and communication data, i.e. on potentially noisy or erroneous beliefs about the world. Realistic CPS models must therefore incorporate the notion of beliefs if they are to provide safety guarantees in practice as well as in theory. To fundamentally address this challenge, this paper introduces a first-principles framework for reasoning about CPS models where control decisions are explicitly driven by controller beliefs arrived at through observation and reasoning. We extend the differential dynamic logic dL for CPS dynamics with belief modalities, and a learning operator for belief change. This new dynamic doxastic differential dynamic logic d4L does due justice to the challenges of CPS verification by having 1) real arithmetic for describing the world and beliefs about the world; 2) continuous and discrete world change; 3) discrete belief change by means of the learning operator. We develop a sound sequent calculus for d4L, which enables us to illustrate the applicability of d4L by proving the safety of a simplified belief-triggered controller for an airplane.

Dynamic dual-reinforcement-learning routing strategies for quality of experience-aware wireless mesh networking

Coutinho N., Matos R., Marques C., Reis A., Sargento S., Chakareski J., Kassler A.

Computer Networks

2015

Abstract:

The impact of transmission impairments such as loss and latency on user perceived quality (QoE) depends on the service type. In a real network, multiple service types such as audio, video, and data coexist. This makes resource management inherently complex and difficult to orchestrate. In this paper, we propose an autonomous Quality of Experience management approach for multiservice wireless mesh networks, where individual mesh nodes apply reinforcement learning methods to dynamically adjust their routing strategies in order to maximize the user perceived QoE for each flow. Within the forwarding nodes, we develop a novel packet dropping strategy that takes into account the impact on QoE. Finally, a novel source rate adaptation mechanism is designed that takes into account the expected QoE in order to match the sending rate with the available network capacity. An evaluation of our mechanisms using simulations demonstrates that our approach is superior to the standard approaches, AODV and OLSR, and effectively balances the user perceived QoE between the service flows.

Dynamic power allocation in server farms: A real time optimization approach

Aghajani M., Parolini L., Sinopoli B.

Proceedings of the IEEE Conference on Decision and Control

2010

Abstract:

This paper concerns the power minimization problem in server farms. The power minimization problem over dynamic power allocation schemes is formally defined and formulated as an optimization problem. It is shown that finding the optimal solution for this optimization problem is not feasible. Inspired by control theory, a well-established method to optimize a cost function over the constraints imposed by the evolution of a dynamical system, called Real-Time Optimization (RTO), is invoked to find a sub-optimal solution for the power minimization problem. The obtained algorithm is simulated and compared with the state-of-the-art optimal static power allocation solution. A considerable improvement in energy consumption is attained for the same quality of service (QoS) level, when dynamic power allocation is used

Dynamic primary-secondary spectrum sharing with cellular systems

Saruthirathanaworakun R., Peha J.M.

2010 Proceedings of the 5th International Conference on Cognitive Radio Oriented Wireless Networks and Communications, CROWNCom 2010

2010

Abstract:

This paper considers primary-secondary spectrum sharing when the primary is a cellular system. Sharing is allowed if primary communications can withstand additional interference, rather than if there are no primary communications. We consider cases when primary and secondary systems cooperate (cooperative sharing) and when they do not (coexistent sharing). For coexistent sharing, we have devised novel mechanisms that allow secondaries to determine whether they can transmit and at what power without causing harmful interference to the primary by querying a sensor network rather than communicating with the primary system. A sensor network observes a primary’s downstream communications to estimate upstream communications, and thus when additional interference would be tolerable. We show that even in highly utilized spectrum like a cellular band, a significant amount of communications among secondaries is possible. Moreover, if primary power consumption is a consideration, coexistent sharing is roughly as effective as cooperative sharing.

Dynamic sparse state estimation using ℓ1-ℓ1 minimization: Adaptive-rate measurement bounds, algorithms and applications

Mota J., Deligiannis N., Sankaranarayanan A.C., Cevher V., Rodrigues M.

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

2015

Abstract:

We propose a recursive algorithm for estimating time-varying signals from a few linear measurements. The signals are assumed sparse, with unknown support, and are described by a dynamical model. In each iteration, the algorithm solves an ℓ 1 -ℓ 1 minimization problem and estimates the number of measurements that it has to take at the next iteration. These estimates are computed based on recent theoretical results for ℓ 1 -ℓ 1 minimization. We also provide sufficient conditions for perfect signal reconstruction at each time instant as a function of an algorithm parameter. The algorithm exhibits high performance in compressive tracking on a real video sequence, as shown in our experimental results

Economic analysis of the profitability of existing wind parks in Portugal

Pena I., Lima Azevedo I., Ferreira L.A.F.M.

Energy Economics

2014

Abstract:

Discussions on the appropriate policy design and level of incentive to promote renewable energy adoption and meet the 20/20/20 goals have spurred recently in the European Union. These discussions are also ongoing in Portugal, namely in what concerns the level and duration of feed-in tariffs that should be provided to independent power producers. This, in turn, raises the question of whether the past feed-in tariff levels were well designed to achieve the goals of a larger penetration of renewables in the Portuguese grid. The policies to induce wind adoption have led to a growth in wind installed capacity and share of electricity generated by wind in Portugal, but questions arise on their cost-effectiveness and whether alternative policy designs would have led to the same goal. In this work, we estimate profits made by wind independent power producers for wind parks that were connected in Portugal between 1992 and 2010, and conclude that the feed-in tariffs have overcompensated some wind power producers. We also discuss the recent changes in feed-in tariff legislation published in February 2013 and estimate the expected costs of the introduced changes.

Economic incentives in information-centric networking: Implications for protocol design and public policy

Agyapong P.K., Sirbu M.

IEEE Communications Magazine

2012

Abstract:

n this article, we build a simple engineering-economic model to evaluate the incentives of various network players to deploy distributed storage nodes (content stores and caches) to support information-centric network (ICN) architectures and the implications of those incentives on protocol design, industry structure and other policy issues, such as competition and network- neutrality. We find that without some explicit monetary compensation from publishers, networks will fail to deploy the socially optimal number of caches. We also study the social welfare implications of different cache deployment scenarios and identify two deployment scenarios that maximize social welfare. Finally, we show that ICN architectures provide numerous opportunities for large eyeball networks to leverage their terminating access monopoly to extract more profits from other network players. Hence, regulators must take steps to address issues such as interconnection and the role of caching infrastructure in differential quality of service provisioning in an ICN-based network architecture, in order to ensure socially desirable outcomes from their deployment.