Publications

A framework for programming sensor networks with scheduling and resource-sharing optimizations

Gupta V., Tovar E., Lakshmanan K., Rajkumar R.

Proceedings - 1st International Workshop on Cyber-Physical Systems, Networks, and Applications, CPSNA 2011, Workshop Held During RTCSA 2011

2011

Conference Paper

Abstract:

Several projects in the recent past have aimed at promoting Wireless Sensor Networks as an infrastructure technology, where several independent users can submit applications that execute concurrently across the network. Concurrent multiple applications cause significant energy-usage overhead on sensor nodes, that cannot be eliminated by traditional schemes optimized for single-application scenarios. In this paper, we outline two main optimization techniques for reducing power consumption across applications. First, we describe a compiler based approach that identifies redundant sensing requests across applications and eliminates those. Second, we cluster the radio transmissions together by concatenating packets from independent applications based on Rate-Harmonized Scheduling.

A Framework for Structural Input/Output and Control Configuration Selection in Large-Scale Systems

Pequito S., Kar S., Aguiar A.P.

IEEE Transactions on Automatic Control

2016

Article

Abstract:

This paper addresses problems on the structural design of large-scale control systems. An efficient and unified framework is proposed to select the minimum number of manipulated/measured variables to achieve structural controllability/observability of the system, and to select the minimum number of feedback interconnections between measured and manipulated variables such that the closed-loop system has no structural fixed modes. Global solutions are computed using polynomial complexity algorithms in the number of the state variables of the system. Finally, graph-theoretic characterizations are proposed, which allow a characterization of all possible solutions.

A graph structure approach to improving message dissemination in vehicular networks

Monteiro R., Viriyasitavat W., Sargento S., Tonguz O.K.

Wireless Networks

2016

Article

Abstract:

Efficient message dissemination in vehicular ad-hoc networks (VANETs) is crucial for supporting communication among vehicles and also between users and the Internet, with minimal delay and overhead but maximum reachability. To improve the message dissemination in these networks, we show the need to study the graph-theoretic properties of VANETs, since they neither follow the small-world nor the scale-free network characteristics often found in large self-organized networks. We consider three fundamental properties: connectivity, node degree, and clustering coefficient. For each property, we develop and validate analytical models for both the urban and highway scenarios, building an extensive graph structure perspective on VANETs. With this, we see how connectivity changes with network density, that VANETs exhibit truncated Gaussian node degree distributions, and that network clustering coefficients do not depend on the network’s size or density. We then show how these results can be used to generate individual behavior favorable to the whole network using local information. The usefulness of this new approach is demonstrated by proposing new mechanisms to enhance the urban vehicular broadcasting protocol UV-CAST. Our results show that these new mechanisms lead to excellent performance while reducing the overhead in the UV-CAST protocol.

A learning-based approach to secure JTAG against unseen scan-based attacks

Ren X., Blanton R.D., Tavares V.G.

Proceedings of IEEE Computer Society Annual Symposium on VLSI, ISVLSI

2016

Conference Paper

Abstract:

Security is becoming an essential problem for integrated circuits (ICs). Various attacks, such as reverse engineering and dumping on-chip data, have been reported to undermine IC security. IEEE 1149.1, also known as JTAG, is primarily used for IC manufacturing test but inevitably provides a “backdoor” that can be exploited to attack ICs. Encryption has been used extensively as an effective mean to protect ICs through authentication, but a few weaknesses subsist, such as key leakage. Signature-based techniques ensure security using a database that includes known attacks, but fail to detect attacks that are not contained by the database. To overcome these drawbacks, a two-layer learning-based protection scheme is proposed. Specifically, the scheme monitors the execution of JTAG instructions and uses support vector machines (SVM) to identify abnormal instruction sequences. The use of machine learning enables the detection of unseen attacks without the need for key-based authentication. The experiments based on the OpenSPARC T2 platform demonstrate that the proposed scheme improves the accuracy of detecting unseen attacks by 50% on average when compared to previous work.

A linear logic programming language for concurrent programming over graph structures

Cruz F., Rocha R., Goldstein S.C., Pfenning F.

Theory and Practice of Logic Programming

2014

Conference Paper

Abstract:

We have designed a new logic programming language called LM (Linear Meld) for programming graph-based algorithms in a declarative fashion. Our language is based on linear logic, an expressive logical system where logical facts can be consumed. Because LM integrates both classical and linear logic, LM tends to be more expressive than other logic programming languages. LM programs are naturally concurrent because facts are partitioned by nodes of a graph data structure. Computation is performed at the node level while communication happens between connected nodes. In this paper, we present the syntax and operational semantics of our language and illustrate its use through a number of examples.

A linguistically motivated taxonomy for Machine Translation error analysis

Costa A., Ling W., Luis T., Correia R., Coheur L.

Machine Translation

2015

Article

Abstract:

A detailed error analysis is a fundamental step in every natural language processing task, as to be able to diagnose what went wrong will provide cues to decide which research directions are to be followed. In this paper we focus on error analysis in Machine Translation (MT). We significantly extend previous error taxonomies so that translation errors associated with Romance language specificities can be accommodated. Furthermore, based on the proposed taxonomy, we carry out an extensive analysis of the errors generated by four different systems: two mainstream online translation systems Google Translate (Statistical) and Systran (Hybrid Machine Translation), and two in-house MT systems, in three scenarios representing different challenges in the translation from English to European Portuguese. Additionally, we comment on how distinct error types differently impact translation quality.

A Mean-Field Game Approach to Price Formation

Gomes D., Saúde J.

Dynamic Games and Applications (2020)

2020

Article

Abstract:

Here, we introduce a price formation model where a large number of small players can store and trade a commodity such as electricity. Our model is a constrained mean-field game (MFG) where the price is a Lagrange multiplier for the supply versus demand balance condition. We establish the existence of a unique solution using a fixed-point argument. In particular, we show that the price is well defined, and it is a Lipschitz function of time. Then, we study linear-quadratic models that can be solved explicitly and compare our model with real data.

A Mean-Field Game Approach to Price Formation

Gomes D.A., Saúde J.

Dynamic Games and Applications

2020

Article

Abstract:

Here, we introduce a price formation model where a large number of small players can store and trade a commodity such as electricity. Our model is a constrained mean-field game (MFG) where the price is a Lagrange multiplier for the supply versus demand balance condition. We establish the existence of a unique solution using a fixed-point argument. In particular, we show that the price is well defined, and it is a Lipschitz function of time. Then, we study linear-quadratic models that can be solved explicitly and compare our model with real data.

A mean-field game approach to price formation in electricity markets

Gomes A.D.; Saúde J.

arXiv:1807.07088v1 [math.AP] 18 Jul 2018

2018

Article

Abstract:

Here, we introduce a price-formation model where a large number of small players can store and trade electricity. Our model is a constrained mean-field game (MFG) where the price is a Lagrange multiplier for the supply vs. demand balance condition. We establish the existence of a unique solution using a fixed-point argument. In particular, we show that the price is well-defined and it is a Lipschitz function of time. Then, we study linear-quadratic models that can be solved explicitly and compare our model with real data.