5 research outputs found

    On the nature and impact of self-similarity in real-time systems

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    In real-time systems with highly variable task execution times simplistic task models are insufficient to accurately model and to analyze the system. Variability can be tackled using distributions rather than a single value, but the proper charac- terization depends on the degree of variability. Self-similarity is one of the deep- est kinds of variability. It characterizes the fact that a workload is not only highly variable, but it is also bursty on many time-scales. This paper identifies in which situations this source of indeterminism can appear in a real-time system: the com- bination of variability in task inter-arrival times and execution times. Although self- similarity is not a claim for all systems with variable execution times, it is not unusual in some applications with real-time requirements, like video processing, networking and gaming. The paper shows how to properly model and to analyze self-similar task sets and how improper modeling can mask deadline misses. The paper derives an analyti- cal expression for the dependence of the deadline miss ratio on the degree of self- similarity and proofs its negative impact on real-time systems performance through system¿s modeling and simulation. This study about the nature and impact of self- similarity on soft real-time systems can help to reduce its effects, to choose the proper scheduling policies, and to avoid its causes at system design time.This work was developed under a grant from the European Union (FRESCOR-FP6/2005/IST/5-03402).Enrique Hernández-Orallo; Vila Carbó, JA. (2012). On the nature and impact of self-similarity in real-time systems. Real-Time Systems. 48(3):294-319. doi:10.1007/s11241-012-9146-0S294319483Abdelzaher TF, Sharma V, Lu C (2004) A utilization bound for aperiodic tasks and priority driven scheduling. IEEE Trans Comput 53(3):334–350Abeni L, Buttazzo G (1999) QoS guarantee using probabilistic deadlines. 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In: Proc of the 23rd IEEE real-time systems symposium, pp 289–300Erramilli A, Narayan O, Willinger W (1996) Experimental queueing analysis with long-range dependent packet traffic. IEEE/ACM Trans Netw 4(2):209–223Erramilli A, Roughan M, Veitch D, Willinger W (2002) Self-similar traffic and network dynamics. Proc IEEE 90(5):800–819Gardner M (1999) Probabilistic analysis and scheduling of critical soft real-time systems. Phd thesis, University of Illinois, Urbana-ChampaignGarrett MW, Willinger W (1994) Analysis, modeling and generation of self-similar vbr video traffic. In: ACM SIGCOMMHarchol-Balter M (2002) Task assignment with unknown duration. J ACM 49(2):260–288Harchol-Balter M (2007) Foreword: Special issue on new perspective in scheduling. SIGMETRICS Perform Eval Rev 34(4):2–3Harchol-Balter M, Downey AB (1997) Exploiting process lifetime distributions for dynamic load balancing. ACM Trans Comput Syst 15(3):253–285Hernandez-Orallo E, Vila-Carbo J (2007) Network performance analysis based on histogram workload models. In: Proceedings of the 15th international symposium on modeling, analysis, and simulation of computer and telecommunication systems (MASCOTS), pp 331–336Hernandez-Orallo E, Vila-Carbo J (2010) Analysis of self-similar workload on real-time systems. In: IEEE real-time and embedded technology and applications symposium (RTAS). IEEE Computer Society, Washington, pp 343–352Hernández-Orallo E, Vila-Carbó J (2010) Network queue and loss analysis using histogram-based traffic models. Comput Commun 33(2):190–201Hughes CJ, Kaul P, Adve SV, Jain R, Park C, Srinivasan J (2001) Variability in the execution of multimedia applications and implications for architecture. SIGARCH Comput Archit News 29(2):254–265Leland W, Ott TJ (1986) Load-balancing heuristics and process behavior. SIGMETRICS Perform Eval Rev 14(1):54–69Leland WE, Taqqu MS, Willinger W, Wilson DV (1994) On the self-similar nature of ethernet traffic (extended version). IEEE/ACM Trans Netw 2(1):1–15Liu CL, Layland JW (1973) Scheduling algorithms for multiprogramming in a hard-real-time environment. J ACM 20(1):46–61Mandelbrot B (1965) Self-similar error clusters in communication systems and the concept of conditional stationarity. IEEE Trans Commun 13(1):71–90Mandelbrot BB (1969) Long run linearity, locally Gaussian processes, h-spectra and infinite variances. Int Econ Rev 10:82–113Norros I (1994) A storage model with self-similar input. Queueing Syst 16(3):387–396Norros I (2000) Queueing behavior under fractional Brownian traffic. In: Park K, Willinger W (eds) Self-similar network traffic and performance evaluation. Willey, New York, Chap 4Park K, Willinger W (2000) Self-similar network traffic: An overview. In: Park K, Willinger W (eds) Self-similar network traffic and performance evaluation. 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    Séptimo desafío por la erradicación de la violencia contra las mujeres del Institut Universitari d’Estudis Feministes i de Gènere "Purificación Escribano" de la Universitat Jaume

    La lectura del territorio como herramienta de proyecto: propuestas de estructura urbana basadas en el soporte territorial.

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    Presentación de la sesión Premium 4. Ámbito temático: Metrópolis Barcelona, a cargo de Loles Herrero y Sebastià Jornet. Orden de las Ponencias: 1. Objetivos y estrategias para el proyecto territorial de los espacios abiertos metropolitanos: hacia una ecologia regional | Lorena Maristany (Escola Tècnica Superior d'Arquitectura del Vallès). 2. Base territorial para la soberanía alimentaria en la Región Metropolitana de Barcelona | Manel Cunill Llenas (Agraria del Vallés, sccl). 3. Planificación para una gestión dinámica y adaptativa de la infraestructura verde metropolitana: el PEPNat como caso de estudio | Eugenia Vidal (Àrea Metropolitana de Barcelona); Laura Cid (Àrea Metropolitana de Barcelona); Antoni Farrero (Àrea Metropolitana de Barcelona); Patricia García Rodríguez (Àrea Metropolitana de Barcelona); Loles Herrero (Àrea Metropolitana de Barcelona); Kyriaki Ilousi (Àrea Metropolitana de Barcelona); Oriol Monclús (Àrea Metropolitana de Barcelona); Jordi Vila (Àrea Metropolitana de Barcelona). 4. El encaje entre las zonas urbanas y el entorno natural: los espacios fluviales del Área metropolitana de Barcelona | Patricia García Rodríguez (Àrea Metropolitana de Barcelona); José Alonso (Àrea Metropolitana de Barcelona); Laura Cid (Àrea Metropolitana de Barcelona); Antoni Farrero (Àrea Metropolitana de Barcelona); Martín Gullón (Àrea Metropolitana de Barcelona); Kyrian Ilousi (Àrea Metropolitana de Barcelona); Eugenia Vidal Casanovas (Àrea Metropolitana de Barcelona). 5. Modelizando el futuro territorio metropolitano: cálculo de potenciales urbanísticos en la metrópolis de Barcelona | Pere Manubens (Àrea Metropolitana de Barcelona); Laura Bertran (Àrea Metropolitana de Barcelona); Judith Recio (Àrea Metropolitana de Barcelona); Sandra Quesada (Àrea Metropolitana de Barcelona); Javier Alarcón (Àrea Metropolitana de Barcelona). 6. Las necesidades de la población metropolitana desde las tramas residenciales: las dotaciones socioambientales: vivienda, equipamientos y espacios verdes | Alexandra Quesada (Àrea Metropolitana de Barcelona); Mireia Peris (Àrea Metropolitana de Barcelona); Mercè González (Àrea Metropolitana de Barcelona); Elena Castellà (Àrea Metropolitana de Barcelona); Judith Recio (Àrea Metropolitana de Barcelona); Laia Molist (Àrea Metropolitana de Barcelona); Mariona Figueras (Àrea Metropolitana de Barcelona). 7. La participación en la planificación urbanística metropolitana. De la diagnosis compartida a la estrategia participada del Avance del PDU metropolitano | Mireia Peris (Àrea Metropolitana de Barcelona); Joan Caba (Àrea Metropolitana de Barcelona); Laura Ferreres (Àrea Metropolitana de Barcelona); Teresa Gómez Fabra (Àrea Metropolitana de Barcelona); Isabel Tomé (Àrea Metropolitana de Barcelona). 8. La lectura del territorio como herramienta de proyecto: propuestas de estructura urbana basadas en el soporte territorial | Anna Majoral (Àrea Metropolitana de Barcelona); Gavina Corbetta (Àrea Metropolitana de Barcelona); Jordi Peralta (Àrea Metropolitana de Barcelona)

    Prevalence and impact of COVID-19 sequelae on treatment and survival of patients with cancer who recovered from SARS-CoV-2 infection: evidence from the OnCovid retrospective, multicentre registry study

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    Background: The medium-term and long-term impact of COVID-19 in patients with cancer is not yet known. In this study, we aimed to describe the prevalence of COVID-19 sequelae and their impact on the survival of patients with cancer. We also aimed to describe patterns of resumption and modifications of systemic anti-cancer therapy following recovery from SARS-CoV-2 infection. Methods: OnCovid is an active European registry study enrolling consecutive patients aged 18 years or older with a history of solid or haematological malignancy and who had a diagnosis of RT-PCR confirmed SARS-CoV-2 infection. For this retrospective study, patients were enrolled from 35 institutions across Belgium, France, Germany, Italy, Spain, and the UK. Patients who were diagnosed with SARS-CoV-2 infection between Feb 27, 2020, and Feb 14, 2021, and entered into the registry at the point of data lock (March 1, 2021), were eligible for analysis. The present analysis was focused on COVID-19 survivors who underwent clinical reassessment at each participating institution. We documented prevalence of COVID-19 sequelae and described factors associated with their development and their association with post-COVID-19 survival, which was defined as the interval from post-COVID-19 reassessment to the patients' death or last follow-up. We also evaluated resumption of systemic anti-cancer therapy in patients treated within 4 weeks of COVID-19 diagnosis. The OnCovid study is registered in ClinicalTrials.gov, NCT04393974. Findings: 2795 patients diagnosed with SARS-CoV-2 infection between Feb 27, 2020, and Feb 14, 2021, were entered into the study by the time of the data lock on March 1, 2021. After the exclusion of ineligible patients, the final study population consisted of 2634 patients. 1557 COVID-19 survivors underwent a formal clinical reassessment after a median of 22·1 months (IQR 8·4-57·8) from cancer diagnosis and 44 days (28-329) from COVID-19 diagnosis. 234 (15·0%) patients reported COVID-19 sequelae, including respiratory symptoms (116 [49·6%]) and residual fatigue (96 [41·0%]). Sequelae were more common in men (vs women; p=0·041), patients aged 65 years or older (vs other age groups; p=0·048), patients with two or more comorbidities (vs one or none; p=0·0006), and patients with a history of smoking (vs no smoking history; p=0·0004). Sequelae were associated with hospitalisation for COVID-19 (p<0·0001), complicated COVID-19 (p<0·0001), and COVID-19 therapy (p=0·0002). With a median post-COVID-19 follow-up of 128 days (95% CI 113-148), COVID-19 sequelae were associated with an increased risk of death (hazard ratio [HR] 1·80 [95% CI 1·18-2·75]) after adjusting for time to post-COVID-19 reassessment, sex, age, comorbidity burden, tumour characteristics, anticancer therapy, and COVID-19 severity. Among 466 patients on systemic anti-cancer therapy, 70 (15·0%) permanently discontinued therapy, and 178 (38·2%) resumed treatment with a dose or regimen adjustment. Permanent treatment discontinuations were independently associated with an increased risk of death (HR 3·53 [95% CI 1·45-8·59]), but dose or regimen adjustments were not (0·84 [0·35-2·02]). Interpretation: Sequelae post-COVID-19 affect up to 15% of patients with cancer and adversely affect survival and oncological outcomes after recovery. Adjustments to systemic anti-cancer therapy can be safely pursued in treatment-eligible patients
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