Javier Cano

Genetic Algorithm for Boolean minimization in an FPGA cluster

Evolutionary algorithms are an alternative option to the Boolean synthesis due to that they allow one to create hardware structures that would not be able to be obtained with other techniques. This paper shows a parallel genetic programming (PGP) Boolean synthesis implementation based on a cluster of FPGAs that takes full advantage of parallel programming and hardware/software co-design techniques. The performance of our cluster of FPGAs implementation has been compared with an HPC implementation. The experimental results have shown an excellent behavior in terms of speed up (up to ×500) and in terms of solving the scalability problems of this algorithms present in previous works.

Bayesian Reliability, Availability and Maintainability Analysis for Hardware Systems Described Through Continuous Time Markov Chains

Hardware systems are present in many fields of human activity. Markov models are sometimes used in hardware reliability, availability, and maintainability (RAM) modeling. They are especially useful in situations in which the system we want to analyze may be modeled with several states through which the system evolves, some of them corresponding to ON states, the rest to OFF states. We provide here RAM analyses of such systems within a Bayesian framework, addressing both short-term and long-term performance.

To Fuel or Not to Fuel? Is that the Question?

According to the International Air Transport Association, the industry fuel bill accounts for more than 25% of the annual airline operating costs. In times of severe economic constraints and increasing fuel costs, air carriers are looking for ways to reduce costs and improve fuel efficiency without putting flight safety into jeopardy. In particular, this is inducing discussions on how much additional fuel to put in a planned route to avoid diverting to an alternate airport due to Air Traffic Flow Management delays. We provide here a general model to support such decisions. We illustrate it with a case study and provide comparison with the current practice, showing the relevance of our approach.

Security economics: an adversarial risk analysis approach to airport protection

We analyze the case of protecting an airport, in which there is concern with terrorist threats against the Air Traffic Control Tower. To deter terrorist actions, airport authorities rely on various protective measures, which entail multiple consequences. By deploying them, airport authorities expect to reduce the probabilities and potential impacts of terrorist actions. We aim at giving advice to the airport authorities by devising a security resource allocation plan. We use the framework of adversarial risk analysis to deal with the problem.

Cost-efficient equitable water distribution in Algeria: a bicriteria fair division problem with network constraints

We deal with a complex water distribution problem through a bicriteria fair division model over time with network constraints: we aim at distributing water fairly in a cost-efficient manner. The problem is illustrated for the region of Kabylia, Algeria. It involves the optimization of pump operational schedules as well as strategic planning issues. Complex rules establish energy tariffs depending on the time of day and the contractual issues of the pump facilities. We discuss the relevance and implementation of different solution concepts, showing various alternatives that improve upon current management procedures.

Symmetric Multiprocessor Systems on FPGA

Advances in FPGA technologies allow designing highly complex systems using on-chip FPGA resources and intellectual property (IP) cores. Furthermore, it is possible to build multiprocessor systems using hard-core or soft-core processors, increasing the range of applications that can be implemented on an FPGA. In this paper we propose a symmetric multiprocessor architecture using the Microblace soft-core processor, and the operating system support needed for running multithreaded applications. Four systems with different shared memory configurations have been implemented on FPGA and tested with parallel applications to show its performance.

Critical networked infrastructure protection from adversaries

Abstract We use the adversarial risk analysis (ARA) framework to deal with the protection of a critical networked infrastructure from the attacks of intelligent adversaries. We deploy an ARA model for each relevant element (node, link, hotspot in link) in the network, using a Sequential Defend–Attack–Defend template as a reference. Such ARA models are related by resource constraints and result aggregation over various sites, for both the Defender and the Attacker. As a case study, we consider the protection of a section of the Spanish railway network from a potential terrorist attack.

Content-based image retrieval algorithm acceleration in a low-cost reconfigurable FPGA cluster

The SMILE project main aim is to build an efficient low-cost cluster based on FPGA boards in order to take advantage of its reconfigurable capabilities. This paper shows the cluster architecture, describing: the SMILE nodes, the high-speed communication network for the nodes and the software environment. Simulating complex applications can be very hard, therefore a SystemC model of the whole system has been designed to simplify this task and provide error-free downloading and execution of the applications in the cluster. The hardware-software co-design process involved in the architecture and SystemC design is presented as well. The SMILE cluster functionality is tested executing a real complex Content-Based Information Retrieval (CBIR) parallel application and the performance of the cluster is compared (time, power and cost) with a traditional cluster approach.

Multithreat multisite protection: A security case study

We provide a novel adversarial risk analysis approach to security resource allocation decision processes for an organization which faces multiple threats over multiple sites. We deploy a Sequential Defend-Attack model for each type of threat and site, under the assumption that different attackers are uncoordinated, although cascading effects are contemplated. The models are related by resource constraints and results are aggregated over the sites for each participant and, for the Defender, by value aggregation across threats. We illustrate the model with a case study in which we support a railway operator in allocating resources to protect from two threats: fare evasion and pickpocketing. Results suggest considerable expected savings due to the proposed investments.

Selection of Evolutionary Multicriteria Strategies: Application in Designing a Regional Water Restoration Management Plan

Sustainability of water resources has become a challenging problem worldwide, as the pollution levels of natural water resources (particularly of rivers) have increased drastically in the last decades. Nowadays, there are many Waste Water Treatment Plant (WWTP) technologies that provide different levels of efficiency in the removal of water pollutants, leading to a great number of combinations of different measures (PoM) or strategies. The management problem, then, involves finding which of these combinations are efficient, regarding the desired objectives (cost and quality). Therefore, decisions affecting water resources require the application of multi-objective optimization techniques which will lead to a set of tradeoff solutions, none of which is better or worse than the others, but, rather, the final decision must be one particular PoM including representative features of the whole set of solutions. Besides, there is not a universally accepted standard way to assess the water quality of a river. In order to consider simultaneously all these issues, we present in this work a hydroinformatics management tool, designed to help decision makers with the selection of a PoM that satisfies the WFD objectives. Our approach combines: 1) a Water Quality Model (WQM), devised to simulate the effects of each PoM used to reduce pollution pressures on the hydrologic network; 2) a Multi-Objective Evolutionary Algorithm (MOEA), used to identify efficient tradeoffs between PoMs’ costs and water quality; and 3) visualization of the Pareto optimal set, in order to extract knowledge from optimal decisions in a usable form. We have applied our methodology in a real scenario, the inner Catalan watersheds with promising results.