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Doctoral candidates who complete a doctoral degree will have acquired the following competencies, which are needed to carry out quality research (Royal Decree 99/2011, of 28 January, which regulates official doctoral studies):

a) A systematic understanding of the field of study and a mastery of the research skills and methods related to the field.
b) An ability to conceive, design or create, put into practice and adopt a substantial process of research or creation.
c) An ability to contribute to pushing back the frontiers of knowledge through original research.
d) A capacity for critical analysis and an ability to assess and summarise new and complex ideas.
e) An ability to communicate with the academic and scientific community and with society in general as regards their fields of knowledge in the manner and languages that are typical of the international scientific community to which they belong.
f) An ability to foster scientific, technological, social, artistic and cultural progress in academic and professional contexts within a knowledge-based society.

The award of a doctoral degree must equip the graduate for work in a variety of settings, especially those requiring creativity and innovation. Doctoral graduates must have at least acquired the personal skills needed to:

a) Develop in contexts in which there is little specific information.
b) Find the key questions that must be answered to solve a complex problem.
c) Design, create, develop and undertake original, innovative projects in their field.
d) Work as part of a team and independently in an international or multidisciplinary context.
e) Integrate knowledge, deal with complexity and make judgements with limited information.
f) Offer criticism on and intellectually defend solutions.

Finally, with respect to competencies, doctoral students must:

a) have acquired advanced knowledge at the frontier of their discipline and demonstrated, in the context of internationally recognised scientific research, a deep, detailed and well-grounded understanding of theoretical and practical issues and scientific methodology in one or more research fields;
b) have made an original and significant contribution to scientific research in their field of expertise that has been recognised as such by the international scientific community;
c) have demonstrated that they are capable of designing a research project that serves as a framework for carrying out a critical analysis and assessment of imprecise situations, in which they are able to apply their contributions, expertise and working method to synthesise new and complex ideas that yield a deeper knowledge of the research context in which they work;
d) have developed sufficient autonomy to set up, manage and lead innovative research teams and projects and scientific collaborations (both national and international) within their subject area, in multidisciplinary contexts and, where appropriate, with a substantial element of knowledge transfer;
e) have demonstrated that they are able to carry out their research activity in a socially responsible manner and with scientific integrity;
f) have demonstrated that they are able to participate in scientific discussions at the international level in their field of expertise and disseminate the results of their research activity to audiences of all kinds;
g) have demonstrated, within their specific scientific context, that they are able to make cultural, social or technological advances and promote innovation in all areas within a knowledge-based society.

Number of places

40

Duration of studies and dedication regime

Duration
The maximum period of study for full-time doctoral studies is three years, counted from the date of admission to the programme to the date of submission of the doctoral thesis. The academic committee of the doctoral programme may authorise a doctoral candidate to pursue doctoral studies on a part-time basis. In this case, the maximum period of study is five years, counting from the date of admission to the programme to the date of submission of the doctoral thesis. For calculating these periods, the date of admission is considered to be the date of the first enrolment for tutorials, and the date of submission the moment in which the Doctoral School officially deposits the doctoral thesis.

For full-time doctoral candidates, the minimum period of study is two years, counted from the date of an applicant's admission to the programme until the date on which the doctoral thesis is deposited; for part-time doctoral candidates it is four years. When there are justified grounds for doing so, and the thesis supervisor and academic tutor have given their authorisation, doctoral candidates may request that the academic committee of their doctoral programme exempt them from the minimum period of study requirement.

The calculation of periods of study will not include periods of absence due to illness, pregnancy or any other reason provided for in the regulations in force. Students who find themselves in any of these circumstances must notify the academic committee of the doctoral programme, which, where appropriate, must inform the Doctoral School. Doctoral candidates may also temporarily withdraw from the programme for up to one year, and this period may be extended for an additional year. Doctoral candidates who wish to interrupt their studies must submit a justified request to the academic committee of the doctoral programme, which will decide whether or not to approve the request. Each programme will establish conditions for readmission to doctoral studies.

Extension
If full-time doctoral candidates have not applied to deposit their thesis by the end of the three-year period of study, the academic committee of the programme may authorise an extension of up to one year. In exceptional circumstances, a further one-year extension may be granted, subject to the conditions established by the corresponding doctoral programme. In the case of part-time doctoral candidates, an extension of two years may be authorised. In both cases, in exceptional circumstances a further one-year extension may be granted by the Doctoral School's Standing Committee, upon the submission of a reasoned application by the academic committee of the doctoral programme.

Dismissal from the doctoral programme
A doctoral candidate may be dismissed from a doctoral programme for the following reasons:

• The doctoral candidate submitting a justified application to withdraw from the programme.
• The maximum period of study and of extensions thereof ending.
• The doctoral candidate not having enrolled every academic year (unless he or she has been authorised to temporarily withdraw).
• The doctoral candidate failing two consecutive assessments.
• The doctoral candidate having disciplinary proceedings filed against him or her that rule that he or she must be dismissed from the UPC.

Dismissal from the programme implies that doctoral candidates cannot continue studying at the UPC and the closing of their academic record. This notwithstanding, they may apply to the academic committee of the programme for readmission and the committee must reevaluate them in accordance with the criteria established in the regulations.

Organization

• Masip Bruin, Xavier

• Ayguade Parra, Eduard
• Barcelo Ordinas, Jose Maria
• Masip Bruin, Xavier

• Department of Computer Architecture (PROMOTORA)

Doctoral Unit - ICT North Campus Management and Support Unit (UTGCNTIC). C. Jordi Girona, 1-3. Building B4-003 (North Campus)
Tel.: 934 054 198
E-mail: doctorat.ac@upc.edu

Agreements with other institutions

BSC (Barcelona Supercomputing Center)

Access profile

Access requirements

Applicants must hold a Spanish bachelor’s degree or equivalent and a Spanish master’s degree or equivalent, provided they have completed a minimum of 300 ECTS credits on the two degrees (Royal Decree 43/2015, of 2 February)

In addition, the following may apply:

• Holders of an official degree awarded by a university in Spain or any other country in the European Higher Education Area, pursuant to the provisions of Article 16 of Royal Decree 1393/2007, of 29 October, which establishes official university course regulations, who have completed a minimum of 300 ECTS credits on official university degrees, of which at least 60 must be at the master's degree level.
• Holders of an official Spanish bachelor’s degree comprising at least 300 credits, as provided for by EU regulations. Holder of degrees of this kind must complete bridging courses unless the curriculum of the bachelor’s degree in question included research training credits equivalent in value to those which would be earned on a master's degree.
• Holders of an official university qualification who, having passed the entrance examination for specialised medical training, have completed at least two years of a training course leading to an official degree in a health-sciences specialisation.
• Holders of a degree issued under a foreign education system. In these cases, homologation is not required, but the UPC must verify that the degree certifies a level of training equivalent to an official Spanish master's degree and qualifies the holder for admission to doctoral studies in the country where it was issued. Admission on this basis does not imply homologation of the foreign degree or its recognition for any purpose other than admission to doctoral studies.
• Holders of a Spanish doctoral qualification issued under previous university regulations.

Note 1: Doctoral studies entrance regulations for holders of an undergraduate degree awarded before the introduction of the EHEA (CG 47/02 2014)

Note 2: Governing Council Decision 64/2014, which approves the procedure and criteria for assessing the fulfilment of academic admission requirements for doctoral studies by holders of non-homologated foreign degrees (CG 25/03 2014)

Admission criteria and merits assessment

Given the highly heterogeneous academic environment, to ensure that applicants have an appropriate background, the programme has modified its internal admission procedure. Admission requirements are now grouped in two categories: formal and conceptual. If an applicant does not meet the formal conditions, the conceptual requirements are not considered.

Formal analysis (FA)

Applicants must meet the requirements established in the administrative regulations for programme. The focus here is on ensuring that applicants have the level of studies and the number of credits required. Applicants who do not meet these requirements will not be admitted to the programme.

Conceptual analysis (CA)

This includes points related to the applicant’s level of knowledge and capabilities. Another factor taken into account is whether there is a research group interested in the work the applicant wishes to undertake. In this section, the following requirements apply:

• ED: An engineering degree related to the subject area of the programme, preferably in informatics or telecommunications. In exceptional cases, students with other qualifications, such as a degree in mathematics or a master's degree in computer science, may also be admitted.

• RG: Whether or not the applicant has the support of a research group linked to the programme and a supervisor/tutor to complete their doctoral thesis.

• BA: Experience or explicit knowledge of computer architecture; acquired, for example, by completing a master’s thesis in this area, collaborating with a group working in the field, etc.

• EN: Proficiency in English, certified by an internationally accepted testing system (TOEFL, etc.).

• FU: Availability of funding for the student’s research, whether through the institution where they completed their previous studies or through the group in which the thesis work would be carried out.

All of these factors will be taken into account by applying the following formula:
Admission: FA*(0.1ED + 0.4RG + 0.1BA + 0.2EN + 0.2FU)

Training complements

To ensure that students admitted to the programme have the knowledge they need to make good progress, the academic committee of the doctoral programme may require that they pass specific bridging courses. Additional training requirements will be determined based on each student's academic background. In such cases, the committee will keep track of the bridging courses completed and establish appropriate criteria to limit their duration. Bridging courses may provide research or cross-disciplinary training, but in no case may doctoral students be required to enrol for 60 or more ECTS credits. Taking into account the doctoral student activity report, the academic committee may propose measures that complement those specified in the regulations and which result in doctoral students who do not meet the specified requirements being excluded from the programme.

Therefore, the organisers of the doctoral programme may admit students on the condition that they complete specific bridging courses to fill gaps identified in their academic background and ensure that they have the knowledge needed to successfully complete their doctoral studies. The number of bridging courses required will depend on each student's background and may require the completion of 18 or 30 additional ECTS credits. The following considerations will apply: 

• Credits for additional training will correspond to three or five master's level subjects, selected from among master’s degrees linked to the doctoral programme. 

• The academic committee will decide how many credits a student must take by reviewing the subjects they took to earn their entrance qualification in order to identify possible gaps in their knowledge. A range of factors are taken into account to determine what subjects a student must take. Apart from subject names, other points considered include the number of hours of study completed for each subject, the topics covered, and even the university where the subjects were taken. The syllabus for each subject will be reviewed, with particular attention to the number of hours allocated in the syllabus. 

• The specific subjects to be taken will be determined by the academic committee in agreement with the student's tutor. Subjects will be selected with the aim of achieving two key goals: i) increasing the student’s knowledge in areas where gaps have been identified; ii) increasing their knowledge in the area of their doctoral thesis.

Enrolment period for new doctoral students

Students enrolling in the doctoral programme for the first time must do so by the deadline specified in the admission decision.
Unless otherwise expressly indicated, enrolments corresponding to admission decisions issued from the second half of April on must be completed within the ordinary enrolment period for the current academic year. 

More information at the registration section for new doctoral students

Enrolment period

Ordinary period for second and successive enrolments: first half of October.

More information at the general registration section

Procedure for the preparation and defense of the research plan

Doctoral candidates must submit a research plan, which will be included in their doctoral student activity report, before the end of the first year. The plan may be improved over the course of the doctoral degree. It must be endorsed by the tutor and the supervisor, and it must include the method that is to be followed and the aims of the research.

At least one of these annual assessments will include a public presentation and defence of the research plan and work done before a committee composed of three doctoral degree holders, which will be conducted in the manner determined by each academic committee. The examination committee awards a Pass or Fail mark. A Pass mark is a prerequisite for continuing on the doctoral programme. Doctoral candidates awarded a Fail mark must submit a new research plan for assessment by the academic committee of the doctoral programme within six months.

The committee assesses the research plan every year, in addition to all of the other activities in the doctoral student activity report. Doctoral candidates who are awarded two consecutive Fail marks for the research plan will be obliged to definitely withdraw from the programme.

If they change the subject of their thesis, they must submit a new research plan.

Formation activities

Tutorial hours are considered highly important for training students and monitoring their progress. Time spent on tutorials is estimated as follows:

Activity: Tutorial.

Hours: 2 hours/week × 48 weeks of class × 3 years = 288 hours. 

Type: compulsory

In weekly tutorials, students will discuss their work and the progress they are making with their tutor. Tutors may provide students with guidance based on the results obtained and anticipated progress with the aim of facilitating achievement of objectives that have been set. During the hours allocated for these sessions, tutors may also talk to students about research groups that are working in areas closely related to the topic of their thesis and that may be interested in engaging with the work to be carried out by the student, or that it may be worthwhile for the student to contact to discuss possible collaborations. Tutorials may also include internal meetings with other members of the research group to discuss issues of common interest in relation to the research being conducted.

This activity will continue throughout the time that it takes a student to complete their doctoral thesis (estimated at three years).

Procedure for assignment of tutor and thesis director

The academic committee of the doctoral programme assigns a thesis supervisor to each doctoral candidate when they are admitted or enrol for the first time, taking account of the thesis supervision commitment referred to in the admission decision.

The thesis supervisor will ensure that training activities carried out by the doctoral candidate are coherent and suitable, and that the topic of the candidate’s doctoral thesis will have an impact and make a novel contribution to knowledge in the relevant field. The thesis supervisor will also guide the doctoral candidate in planning the thesis and, if necessary, tailoring it to any other projects or activities undertaken. The thesis supervisor will generally be a UPC professor or researcher who holds a doctoral degree and has documented research experience. This includes PhD-holding staff at associated schools (as determined by the Governing Council) and UPC-affiliated research institutes (in accordance with corresponding collaboration and affiliation agreements). When thesis supervisors are UPC staff members, they also act as the doctoral candidate’s tutor.

PhD holders who do not meet these criteria (as a result of their contractual relationship or the nature of the institution to which they are attached) must be approved by the UPC Doctoral School's Standing Committee in order to participate in a doctoral programme as researchers with documented research experience.

The academic committee of the doctoral programme may approve the appointment of a PhD-holding expert who is not a UPC staff member as a candidate’s thesis supervisor. In such cases, the prior authorisation of the UPC Doctoral School's Standing Committee is required. A UPC staff member who holds a doctoral degree and has documented research experience must also be proposed to act as a co-supervisor, or as the doctoral candidate’s tutor if one has not been assigned.

A thesis supervisor may step down from this role if there are justified reasons (recognised as valid by the committee) for doing so. If this occurs, the academic committee of the doctoral programme will assign the doctoral candidate a new thesis supervisor.

Provided there are justified reasons for doing so, and after hearing any relevant input from the doctoral candidate, the academic committee of the doctoral programme may assign a new thesis supervisor at any time during the period of doctoral study.

If there are academic reasons for doing so (an interdisciplinary topic, joint or international programmes, etc.) and the academic committee of the programme gives its approval, an additional thesis supervisor may be assigned. Supervisors and co-supervisors have the same responsibilities and academic recognition.

The maximum number of supervisors of a doctoral thesis is two: a supervisor and a co-supervisor.

For theses carried out under a cotutelle agreement or as part of an Industrial Doctorate, if necessary and if the agreement foresees it this maximum number of supervisors may not apply. This notwithstanding, the maximum number of supervisors belonging to the UPC is two.

More information at the PhD theses section

Permanence

The academic committee of the programme may authorise an extension of up to one year for full-time doctoral candidates who have not applied to deposit their thesis by the end of the three-year period of study, in the terms outlined in the Academic Regulations for Doctoral Studies of the Universitat Politècnica de Catalunya. In the case of part-time candidates, an extension of two years may be authorised. In both cases, in exceptional circumstances a further one-year extension may be granted by the Doctoral School's Standing Committee, upon the submission of a reasoned application by the academic committee of the doctoral programme.

A doctoral candidate may be dismissed from a doctoral programme for the following reasons:

• The doctoral candidate submitting a justified application to withdraw from the programme.
• The maximum period of study and of extensions thereof ending.
• The doctoral candidate not having enrolled every academic year (unless he or she has been authorised to temporarily withdraw).
• The doctoral candidate failing two consecutive assessments.
• The doctoral candidate having disciplinary proceedings filed against him or her that rule that he or she must be dismissed from the UPC.

Dismissal from the programme implies that doctoral candidates cannot continue studying at the UPC and the closing of their academic record. This notwithstanding, they may apply to the academic committee of the programme for readmission and the committee must reevaluate them in accordance with the criteria established in the regulations.

International Mention

The doctoral degree certificate may include International Doctorate mention. In this case, the doctoral candidate must meet the following requirements:

a) During the period of study leading to the award of the doctoral degree, the doctoral candidate must have spent at least three months at a respected higher education institution or research centre outside Spain to complete courses or do research work. The stays and activities carried out must be endorsed by the thesis supervisor and authorised by the academic committee of the programme. The candidate must provide a certifying document issued by the person responsible for the research group of the body or bodies where the stay or activity was completed. This information will be added to the doctoral student’s activity report.
b) Part of the thesis (at least the summary and conclusions) must be written and presented in one of the languages commonly used for science communication in the relevant field of knowledge, which must not be an official language of Spain. This rule does not apply to stays and reports in Spanish or to experts from Spanish-speaking countries.
c) At least two PhD-holding experts belonging to a higher education institution or research centre outside Spain must have issued officially certified reports on the thesis.
d) The thesis examination committee must have included at least one PhD-holding expert from a higher education or research institution outside Spain who was not responsible for the candidate’s stay abroad (point a) above).
e) The thesis defence must have taken place on UPC premises or, in the case of joint programmes, at the location specified in the collaboration agreement.

List of authorized thesis for defense

• CARDONA NADAL, JORDI: Practical strategies to monitor and control contention in shared resources of critical real-time embedded systems
  
  Author: CARDONA NADAL, JORDI
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN COMPUTER ARCHITECTURE
  Department: (DAC)
  Mode: Normal
  Deposit date: 06/03/2023
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: CAZORLA ALMEIDA, FRANCISCO JAVIER | HERNANDEZ LUZ, CARLES
  Committee:
       PRESIDENT: BEIVIDE PALACIO, JULIO RAMON
       SECRETARI: ROYUELA ALCÁZAR, SARA
       VOCAL NO PRESENCIAL: BENEDICTE ILLESCAS, PEDRO
  Thesis abstract: In the last decade performance needs in Critical Real-Time Embedded Systems (CRTES) domains like automotive, avionics, railway or space have been steadily on the rise due to the unprecedented computational power required for the new complex and performance-eager emerging applications. To meet these computational needs, CRTES industry has been increasingly resorting to high-performance multicore and manycore processors that can cater for the required performance in a cost-efficient manner. To that end, relatively simple bus-based multicore processor designs have been successfully deployed in general-purpose computing to provide good performance at low energy and area cost. However, these solutions quickly become ineffective with larger core counts as the bus becomes a major performance bottleneck. For this reason, bus-based designs have started migrating to Networks on Chips (NoCs) designs like trees, rings, meshes or torus topologies, which are being increasingly adopted in CRTES to offer multiple point-to-point connections.Software timing is a paramount concern in the design and deployment of CRTES as correctness of the provided functions is typically not only determined by the delivered results, but also by the time at which those results are delivered. Domain-specific safety standards advocate for the adoption of software timing analysis techniques in the software development life-cycles as a necessary step to ascertain and guarantee all functions in the system execute timely and to prevent timing misbehavior to arise at run time. Timing concerns become particularly relevant to support three main phases in the CRTES development process: Verification Phase (budgeting), Validation Phase (testing) and Enforcement.Performing an efficient, industrial-quality timing analysis in the presence of complex multicore and manycore processors with complex hardware features like NoCs is complicated by the non-negligible timing interference arising when multiple cores contend in parallel to the same shared hardware resources through the interconnects. Multicore interference causes the execution time of a task to depend on the other tasks in the system, making it extremely difficult to characterize software timing in a trustworthy yet tight manner.The main challenges arise (i) in the budgeting phase, when deriving tight upper-bounds to the worst theoretical contention impact that requests can experience in traversing the NoC from their source to their destination, and (ii) in the validation phase, when tracking the actual multicore contention tasks generate on each other.This Thesis addresses the problem of enabling efficient and effective contention analysis and characterization in NoC-based CRTES. While most of the works have focused on the verification phase, this Thesis addresses all three main steps in the overall software timing analysis in manycore processors. On the verification side, we propose EOmesh and NoCo solutions that optimize wormhole NoCs¿ (wNoCs) configuration to lower WCET and obtain tight WCET estimates while improving CRTES performance. On the validation phase, we propose a technique to breakdown the contention that cores generate each other in wNoCs. To that end, we introduce a Golden Reference Value (GRV) on top of a PairWise Contention (PWC) metric that accurately identifies contention sources in wNoCs and provides a detailed multi-dimension contention breakdown, and a comparative analysis on the evolution of source contention identification in wNoCs. Finally, we cover a fundamental requirement in the enforcement phase by proposing MCCU, a software/hardware solution that performs fine-grain tracking of cores accesses in shared resources and enables, via configuration registers, preventing cores to cause more interference on its contenders than budgeted by the system designer.
  

Last update: 25/03/2023 05:45:14.

List of lodged theses

• FERRER CID, PAU: On the data quality improvement of air pollution monitoring low-cost sensor networks using data-driven techniques
  
  Author: FERRER CID, PAU
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN COMPUTER ARCHITECTURE
  Department: (DAC)
  Mode: Normal
  Deposit date: 17/03/2023
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: GARCÍA VIDAL, JORGE | BARCELÓ ORDINAS, JOSE MARIA
  Committee:
       PRESIDENT: GHANDEHARI, MASOUD
       SECRETARI: NAVARRO MOLDES, LEANDRO
       VOCAL: FORTINO, GIANCARLO
  Thesis abstract: Nowadays, authorities monitor the concentrations of regulated air pollutants in order to assist in decision-making processes, e.g., for the implementation of traffic restrictions, and mitigate the effects of air pollution. For this purpose, they deploy high-precision instrumentation, the cost of which makes the number of sensors deployed over a region very low. The advent of air pollution low-cost sensors (LCSs) has opened up the possibility of complementing the authorities' instruments with more measurement points.Unfortunately, LCSs present inaccuracies, which makes it difficult to include them in a regulated way for decision-making processes of authorities.In recent years, enabling technologies such as the internet of things (IoT) and machine learning (ML) have allowed the improvement of the data quality of LCSs. Therefore, this thesis is devoted to the improvement of the data quality of air pollution monitoring LCS networks focusing on two aspects; i) the improvement of data quality at node level using ML-based sensor calibration, and ii) theimprovement of the sensor network data quality by using measurements from the network sensors with a graph-based approach.In the first part of the thesis, the improvement of the data quality of individual sensors is investigated. First, it is evaluated how thesensor sampling affects the representativeness of the samples. Then, the use of ML techniques, both linear and nonlinear, for the in-situ calibration of LCSs is analyzed. The in-situ sensor calibration task can be seen as a supervised ML learning problem, so techniques such as multiple linear regression (MLR) or support vector regression (SVR) are evaluated. The evaluation shows hownonlinear techniques improve the quality of pollution estimates significantly. In addition, given the inaccuracies present in LCSs and the difference that exists from one sensor to another of the same manufacturer, the inclusion in the calibration of multiple sensors measuring the same pollutant is investigated. Thereby, the proposed multisensor calibration approach based on ML results inincreased calibration accuracy.The second part of the thesis focuses on the quality of the data reported by a sensor network once deployed over an area. A graph-based approach is proposed to describe the existing relationships between sensors using a graph topology and represent the network measurements as signals defined on the graph, as realized in the graph signal processing (GSP) field. First, differenttechniques have been evaluated to correctly learn the relationships between sensors in a network that can contain both LCSs and high-precision nodes. The most suitable option has proven to be the data-driven GSP model based on signal smoothness. Then, different signal reconstruction techniques coupled with the graph have been studied in order to reconstruct pollution measurements reported by different sensors in a network. Kernel-based techniques and those based on the weights of the Laplacian have been themost effective ones. Once these main components have been studied, a graph-based data reconstruction framework has been proposed for different post-processing applications that appear in LCS networks, e.g., missing value imputation and virtual sensing.The results have shown how this framework allows for dealing with a wide variety of applications and scenarios that can occur in this context with precision. Finally, another important aspect of this type of network has been addressed, which is the detection of outliers. The Volterra graph-based outlier detection (VGOD) has been proposed, using a graph learned from the data and a signalreconstruction model based on the Volterra series, to detect and locate outliers. Therefore, the proposed algorithm has been provento improve the monitoring and maintenance of heterogeneous air pollution sensor networks by identifying abnormal measurementsand malfunctioning sensors.
  

Last update: 25/03/2023 05:30:23.

List of defended theses by year

• VILARDELL MORENO, SERGI: Modelling and predicting extreme behavior in critical real-time systems with advanced statistics
  
  Author: VILARDELL MORENO, SERGI
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN COMPUTER ARCHITECTURE
  Department: (DAC)
  Mode: Normal
  Reading date: 13/03/2023
  Thesis director: SERRA MOCHALES, ISABEL | ABELLA FERRER, JAIME
  

  Committee:
       PRESIDENT: BOLANCÉ LOSILLA, CATALINA
       SECRETARI: RADOJKOVIC, PETAR
       VOCAL NO PRESENCIAL: TRILLA RODRÍGUEZ, DAVID
  Thesis abstract: Critical Real-Time Embedded Systems (CRTES) are used in domains like transportation (e.g. avionics, automotive, space, and railway), healthcare, and industrial machinery. This subset of embedded systems requires undergoing a stringent Validation & Verification (V&V) process before they are allowed to enter in operation since any misbehavior can result in harm of humans or even fatalities. Software timing behavior is a key element to cover in the V&V process, providing with evidence that software runs timely. Software timing analysis, in turn, requires deriving bounds to each application task¿s execution time. These bounds are referred to as Worst-Case Execution Time (WCET) estimates. As CRTES implement more complex safety-related functionalities in every new product, more complex software and consequently more performant computing hardware is used to satisfy the high-performance requirements. The side effect, however, of using more complex hardware and software is challenging state-of-the-art software timing analysis techniques.Measurement-Based Probabilistic Timing Analysis (MBPTA) techniques have been proposed to handle such hardware and software complexity providing tight and trustworthy WCET bounds (estimates). Specifically, Extreme Value Theory (EVT) has been used to provide with models for the most extreme occurrences in form of a probabilistic distribution. The output of the timing model is referred as a probabilistic WCET (pWCET). However trustworthy, EVT models can be cumbersome toapply and they sometimes can be exceedingly pessimistic which adds extra cost into timing budgets.This thesis investigates MBPTA techniques and develops novel methodologies within this framework in three distinct fronts. Firstly, by improving the tightness of pWCET models on sky-high quantiles with two models. A first one that combines risk analysis with EVT for a safe and accurate pWCET. And a second one that introduces Markov¿s Inequality to the pWCET estimation problem, which provides with trustworthy guarantees with less requirements for its correct application. Secondly,in order to boost the use of data coming from performance monitoring counters - increasingly used by MBPTA techniques to tighten estimates-, this thesis shows two mathematically-based ways of merging multiple disjointed readings based on order statistics and copula models. Finally, this thesis proposes a model for the contention of competing tasks, when the timing profile obtained is limited, that allows to provide with more extreme WCET scenarios based on the dependenciesbetween tasks.Summarizing, this thesis pushes the state-of-the-art forward in the V&V methodologies for CRTES in the framework of MBPTA in terms of WCET estimation and data gathering.
  

Last update: 25/03/2023 06:00:21.

Research groups

• ARCO-Microarchitecture and Compilers
• CAP-High Performace Computing Group
• CBA-Communications and Broadband Architectures Lab
• CNDS-Computer Networks and Distributed Systems
• CRAAX-Advanced Network Architectures Lab
• DAMA-UPC-Data Management Group
• GCO-Optical Communications Group
• ICARUS-Intelligent Communications and Avionics for Robust Unmanned Aerial Systems
• IMP-Information Modelling and Processing
• VIRTUOS-Virtualisation and Operating Systems

Research entities:

Teachers

• Alvarez Martinez, Carlos
• Ayguade Parra, Eduard
• Badia Sala, Rosa Maria
• Barcelo Ordinas, Jose Maria
• Barlet Ros, Pere
• Barrado Muxi, Cristina
• Becerra Fontal, Yolanda
• Bofill Soliguer, Pau
• Cabellos Aparicio, Alberto
• Canal Corretger, Ramon
• Careglio, Davide
• Cazorla Almeida, Francisco Javier
• Cela Espin, Jose M.
• Cerdà Alabern, Llorenç
• Corbalan Gonzalez, Julita
• Cortes Rossello, Toni
• Cristal Kestelman, Adrian
• Cruellas Ibarz, Juan Carlos
• Delgado Merce, Jaime M.
• Domingo Pascual, Jordi
• Espasa Sans, Roger
• Fernandez Jimenez, Agustin
• Freitag, Felix
• Gallego Fernandez, M. Isabel
• Garcia Almiñana, Jordi
• Garcia Vidal, Jorge
• Gil Gomez, Marisa
• Gonzalez Colas, Antonio Maria
• Gonzalez Tallada, Marc
• Guerrero Zapata, Manel
• Guitart Fernandez, Jordi
• Herrero Zaragoza, Josep Ramon
• Jimenez Castells, Marta
• Jimenez Gonzalez, Daniel
• Juan Hormigo, Antonio
• Labarta Mancho, Jesus Jose
• Larriba Pey, Josep
• Llaberia Griño, Jose M.
• Llorente Viejo, Silvia
• Llosa Espuny, Josep
• Lopez Alvarez, David
• Lopez Rubio, Juan
• Marin Tordera, Eva
• Martorell Bofill, Xavier
• Masip Bruin, Xavier
• Medina Llinas, Manel
• Monreal Arnal, Teresa
• Morancho Llena, Enric
• Moreto Planas, Miquel
• Navarro Moldes, Leandro
• Olive Duran, Angel
• Otero Calviño, Beatriz
• Pajuelo Gonzalez, Alex
• Parcerisa Bundo, Joan Manuel
• Pastor Llorens, Enric
• Perello Muntan, Jordi
• Reyes Muñoz, Angelica
• Rodriguez Luna, Eva
• Royo Valles, Maria Dolores
• Salami San Juan, Esther
• Sanchez Carracedo, Fermin
• Sanchez Lopez, Sergio
• Santos Boada, German
• Serral Gracia, Rene
• Sole Pareta, Josep
• Torres Viñals, Jordi
• Tous Liesa, Ruben
• Tubella Murgadas, Jordi
• Utrera Iglesias, Gladys Miriam
• Valero Cortes, Mateo
• Valero Garcia, Miguel
• Vazquez, Mariano
• Velasco Esteban, Luis Domingo
• Verdu Mula, Javier

• Alarcon Cot, Eduard
• Alvarez Marti, Lluc
• Arias Vicente, Marta
• Armejach Sanosa, Adria
• Arnau Montañes, Jose Maria
• Berral Garcia, Josep Lluis
• de Almeida Amazonas, Jose Roberto
• Giro Nieto, Xavier
• Kosmidis, Leonidas
• Oller Arcas, Antonio
• Perez Casany, Marta