Articles

Design of an Integrative System for Configurable Exergames Targeting the Senior Population

Paulino T., Munoz J., Bermudez S., Cameirão S.

HSED 2018: Human Systems Engineering and Design

2018

Abstract:

Physical activity plays a key role in the prevention and delay of health problems associated with sedentarism in the senior population. Configurable exergames that can be adapted to fit different needs have been proposed to address this issue because they are fun and enjoyable while promoting physical exercise. This paper describes the design process of an integrative system for Exergaming targeting the senior population that combines human-centred and software engineering methods. An initial requirements elicitation was carried out involving 12 health professionals. This resulted in a list of 110 design requirements, such as customization of games and activities, visualization of historical data, management of plans and sessions, and automatic recommendation of games. The software design was developed using the Unified Modelling Language (UML). Finally, we present two iterations with human-centred techniques, namely, card sorting and paper prototype evaluations, which will serve as basis for future implementations.

Design of communication networks for distributed computation with privacy guarantees

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

Proceedings of the IEEE Conference on Decision and Control

2014

Abstract:

In this paper we address a communication network design problem for distributed computation with privacy guarantees. More precisely, given a possible communication graph between different agents in a network, the objective is to design a protocol, by proper selection of the weights in the dynamics induced by the communication graph, such that 1) weighted average consensus of the initial states of all the agents will be reached; and 2) there are privacy guarantees, where each agent is not able to retrieve the initial states of non-neighbor agents, with the exception of a small subset of agents (that will be precisely characterized). In this paper, we assume that the network is cooperative, i.e., each agent is passive in the sense that it executes the protocol correctly and does not provide incorrect information to its neighbors, but may try to retrieve the initial states of non-neighbor agents. Furthermore, we assume that each agent knows the communication protocol.

Designing decentralized control systems without structural fixed modes: A multilayer approach ?

Pequito S., Agbi C., Popli N., Kar S., Aguiar A.P., Ilic M.

IFAC Proceedings Volumes (IFAC-PapersOnline)

2013

Abstract:

In this paper we propose a methodology to design decentralized controllers applied to large-scale systems. The key idea is to split the design into two control layers. The first layer, consists mainly in a pre-processing step, where an optimal subset of inputs and outputs are used for feedback to close the loop, such that the resulting associated state matrix of the closed-loop system has two desirable structural properties: it has no structural fixed modes and it is structurally controllable and observable thru any single state variable. After this first layer, we can select an arbitrary decentralization control scheme to achieve some specified performance, which is the second layer of the proposed approach. We illustrate this methodology for the following applications: a two zones temperature regulation and a frequency regulation of a 3-bus system.

Detection of illegitimate access to JTAG via statistical learning in chip

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

Proceedings -Design, Automation and Test in Europe, DATE

2015

Abstract:

IEEE 1149.1, commonly known as the joint test action group (JTAG), is the standard for the test access port and the boundary-scan architecture. The JTAG is primarily utilized at the time of the integrated circuit (IC) manufacture but also in the field, giving access to internal sub-systems of the IC, or for failure analysis and debugging. Because the JTAG needs to be left intact and operational for use, it inevitably provides a “backdoor” that can be exploited to undermine the security of the chip. Potential attackers can then use the JTAG to dump critical data or reverse engineer IP cores, for example. Since an attacker will use the JTAG differently from a legitimate user, it is possible to detect the difference using machine-learning algorithms. A JTAG protection scheme, SLIC-J, is proposed to monitor user behavior and detect illegitimate accesses to the JTAG. Specifically, JTAG access is characterized using a set of specifically-defined features, and then an on-chip classifier is used to predict whether the user is legitimate or not. To validate the effectiveness of the approach, both legitimate and illegitimate JTAG accesses are simulated using the OpenSPARC T2 benchmark. The results show that the detection accuracy is 99.2%, and the escape rate is 0.8%.

Diagnosing architectural run-time failures

Casanova P., Garlan D., Schmerl B., Abreu R.

ICSE Workshop on Software Engineering for Adaptive and Self-Managing Systems

2013

Abstract:

Self-diagnosis is a fundamental capability of self-adaptive systems. In order to recover from faults, systems need to know which part is responsible for the incorrect behavior. In previous work we showed how to apply a design-time diagnosis technique at run time to identify faults at the architectural level of a system. Our contributions address three major shortcomings of our previous work: 1) we present an expressive, hierarchical language to describe system behavior that can be used to diagnose when a system is behaving different to expectation; the hierarchical language facilitates mapping low level system events to architecture level events; 2) we provide an automatic way to determine how much data to collect before an accurate diagnosis can be produced; and 3) we develop a technique that allows the detection of correlated faults between components. Our results are validated experimentally by injecting several failures in a system and accurately diagnosing them using our algorithm.

Diagnosing unobserved components in self-adaptive systems

Casanova P., Garlan D., Schmerl B., Abreu R.

9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2014 - Proceedings

2014

Abstract:

Availability is an increasingly important quality for today’s software-based systems and it has been successfully addressed by the use of closed-loop control systems in self-adaptive systems. Probes are inserted into a running system to obtain information and the information is fed to a controller that, through provided interfaces, acts on the system to alter its behavior. When a failure is detected, pinpointing the source of the failure is a critical step for a repair action. However, information obtained from a running system is commonly incomplete due to probing costs or unavailability of probes. In this paper we address the problem of fault localization in the presence of incomplete system monitoring. We may not be able to directly observe a component but we may be able to infer its health state. We provide formal criteria to determine when health states of unobservable components can be inferred and establish formal theoretical bounds for accuracy when using any spectrum-based fault localization algorithm.

Diffusion and topology: Large densely connected bipartite networks

Santos A., Moura J.M.F.

Proceedings of the IEEE Conference on Decision and Control

2012

Abstract:

Viral diffusion is an important area of research in networks, with applications from epidemiology to cyber and cuberphysical systems security. To study the infection dynamics of a single virus in a complete network, it suffices to study the dynamics of a single statistic – the fraction of infected nodes in the network. Here, we consider multiple viruses (two viruses for simplicity.) To go beyond the complete network, we consider a (special type of) bipartite network and show that, in this case and with two viruses, the state of the network is a four dimensional Markov process that collects the fractions of infected nodes in each island (bipartite classes) for each type of infection. The dynamics of this Markov process is described by a system of coupled stochastic integral equations. The stochastic dynamics leads, in the large scale limit (mean field), to four coupled nonlinear ordinary differential equations. To study the system qualitative behavior and determine the asymptotic distributions of infected nodes by each virus in each island, we resort to studying simpler configurations whose dynamics bound the dynamics of the original system and exhibit the same attractor.

Discovery of “comet” communities in temporal and labeled graphs Com (Formula presented.)

Araujo M., Gunnemann S., Papadimitriou S., Faloutsos C., Basu P., Swami A., Papalexakis E.E., Koutra D.

Knowledge and Information Systems

2016

Abstract:

While the analysis of unlabeled networks has been studied extensively in the past, finding patterns in different kinds of labeled graphs is still an open challenge. Given a large edge-labeled network, e.g., a time-evolving network, how can we find interesting patterns? We propose Com 2 , a novel, fast and incremental tensor analysis approach which can discover communities appearing over subsets of the labels. The method is (a) scalable, being linear on the input size, (b) general, (c) needs no user-defined parameters and (d) effective, returning results that agree with intuition. We apply our method to real datasets, including a phone call network, a computer-traffic network and a flight information network. The phone call network consists of 4 million mobile users, with 51 million edges (phone calls), over 14 days, while the flights dataset consists of 7733 airports and 5995 airline companies flying 67,663 different routes. We show that Com 2 spots intuitive patterns regarding edge labels that carry temporal or other discrete information. Our findings include large “star”-like patterns, near-bipartite cores, as well as tiny groups (five users), calling each other hundreds of times within a few days. We also show that we are able to automatically identify competing airline companies.

Distortion optimized multi-service scheduling for next-generation wireless mesh networks

Reis A.B., Chakareski J., Kassler A., Sargento S.

Proceedings - IEEE INFOCOM

2010

Abstract:

Distributing multimedia content over wireless networks is challenging due to the limited resource availability and the unpredictability of wireless links. As more and more users demand wireless access to (real-time) multimedia services, the impact of constrained resources is different for different media types. Therefore, understanding this impact and developing mechanisms to optimize content delivery under resource constraints according to user perception will be key in improving user satisfaction. In this paper, we develop a novel scheduling algorithm for multi-hop wireless networks, which optimizes packet delivery for multiple audio, video and data flows according to user perceivable quality metrics. We formulate a multidimensional optimization problem to minimize the overall distortion while satisfying resource constraints for the wireless links. Our Quality-of-Experience (QoE)-optimized scheduler makes use of models to determine the user’s perception of quality that are specific to the type of service being provided. Our experimental results, obtained with the NS-2 IEEE 802.16 MESH-mode simulator, show that distortion-aware scheduling can significantly increase the perceived quality of multimedia streaming under bandwidth constraints. As the scheduler allows the modeling of fairness constraints among multiple competing flows, we also demonstrate an improvement in fairness across different flows.