Academic literature on the topic 'Burstiness'
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Journal articles on the topic "Burstiness"
Cruz, Rene L. "Service Burstiness and Dynamic Burstiness Measures: A Framework." Journal of High Speed Networks 1, no. 2 (1992): 105–27. http://dx.doi.org/10.3233/jhs-1992-1201.
Full textHartleb, Detlef, Andreas Ahrens, and Jelena Zascerinska. "EXPLORING THE IMPACT OF BURSTINESS ON THE SERVICE PROCESS AT THE CASH REGISTER." ENVIRONMENT. TECHNOLOGIES. RESOURCES. Proceedings of the International Scientific and Practical Conference 3 (June 16, 2021): 104–9. http://dx.doi.org/10.17770/etr2021vol3.6563.
Full textDeSimone, Antonio. "Generating burstiness in networks." ACM SIGCOMM Computer Communication Review 21, no. 1 (January 2, 1991): 24–31. http://dx.doi.org/10.1145/116030.116032.
Full textNguyen, Ngoc Huy, and Myung Kyun Kim. "Link Quality Estimation from Burstiness Distribution Metric in Industrial Wireless Sensor Networks." Energies 13, no. 23 (December 4, 2020): 6430. http://dx.doi.org/10.3390/en13236430.
Full textD'Auria, Bernardo, and Sidney I. Resnick. "Data network models of burstiness." Advances in Applied Probability 38, no. 02 (June 2006): 373–404. http://dx.doi.org/10.1017/s0001867800001014.
Full textNeuts, Marcel F. "The burstiness of point processes∗." Communications in Statistics. Stochastic Models 9, no. 3 (January 1993): 445–66. http://dx.doi.org/10.1080/15326349308807275.
Full textWoodward, M. E. "Burstiness of interrupted Bernoulli process." Electronics Letters 30, no. 18 (September 1, 1994): 1466–67. http://dx.doi.org/10.1049/el:19941042.
Full textD'Auria, Bernardo, and Sidney I. Resnick. "Data network models of burstiness." Advances in Applied Probability 38, no. 2 (June 2006): 373–404. http://dx.doi.org/10.1239/aap/1151337076.
Full textGuillemin, Fabrice, Jacqueline Boyer, and Alain Dupuis. "Burstiness in broadband integrated networks." Performance Evaluation 15, no. 3 (September 1992): 163–76. http://dx.doi.org/10.1016/0166-5316(92)90032-c.
Full textOudah, Hussein, Bogdan Ghita, Taimur Bakhshi, Abdulrahman Alruban, and David J. Walker. "Using Burstiness for Network Applications Classification." Journal of Computer Networks and Communications 2019 (August 20, 2019): 1–10. http://dx.doi.org/10.1155/2019/5758437.
Full textDissertations / Theses on the topic "Burstiness"
Dimopoulos, Peter, and dimpet@gmail com. "Modeling and Improving the Performance of Interactive TCP Traffic in Computer Networks." RMIT University. Computer Science and Information Technology, 2007. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080208.150856.
Full textPola, Tommaso. "Statistical analysis of written languages." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amslaurea.unibo.it/6307/.
Full textBingmer, Markus [Verfasser], Gaby [Akademischer Betreuer] Schneider, and Anton [Akademischer Betreuer] Wakolbinger. "A stochastic model for the joint evaluation of burstiness and regularity in oscillatory spike trains / Markus Bingmer. Gutachter: Gaby Schneider ; Anton Wakolbinger. Betreuer: Gaby Schneider." Frankfurt am Main : Univ.-Bibliothek Frankfurt am Main, 2013. http://d-nb.info/1043977996/34.
Full textClinchant, Stéphane. "Modèles probabilistes pour les fréquences de mots et la recherche d'information." Thesis, Grenoble, 2011. http://www.theses.fr/2011GRENT046/document.
Full textThe present study deals with word frequencies distributions and their relation to probabilistic Information Retrieval (IR) models. We examine the burstiness phenomenon of word frequencies in textual collections. We propose to model this phenomenon as a property of probability distributions and we study the Beta Negative Binomial and Log-Logistic distributions to model word frequencies. We then focus on probabilistic IR models and their fundamental properties. Our analysis reveals that probability distributions underlying most state-of-the-art models do not take this phenomenon into account , even if fundamental properties of IR models such as concavity enable implicitly to take it into account. We then introduce a novel family of probabilistic IR model, based on Shannon information. These new models bridge the gap between significant properties of IR models and the burstiness phenomenon of word frequencies. Lastly, we study empirically and theoretically pseudo relevance feedback models. We propose a theoretical framework which explain well the empirical behaviour and performance of pseudo relevance feedback models. Overall, this highlights interesting properties for pseudo relevance feedback and shows that some state-of-the-art model are inadequate
Huselius, Gylling Kira. "Quadratic sample entropy as a measure of burstiness : A study in how well Rényi entropy rate and quadratic sampleentropy can capture the presence of spikes in time-series data." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-130593.
Full textAnrop till internetservrar beter sig i allmänhet inte på sätt som lätt kan modelleras och prediceras med typiska tidsseriemetoder, utan har ofta en signifikant andel spikar i datan, en egenskap som kallas “burstiness” (adekvat svensk översättning saknas). I den här uppsatsen studerar vi diverse entropimått och deras egenskaper för olika fördelningar, både teoretiskt och via simulering, för att kunna ta reda på hur dessa mått kan användas för att karaktärisera förutsägbarhet och burstiness hos tidsserier. Vi finner att en låg entropi kan indikera en tungsvansad fördelning, vilket för tidsserier motsvarar hög burstiness. Genom att använda ett tidigare resultat som sammankopplar kvadratisk stickprovsentropi med Rényis entropitakt av ordning 2 föreslår vi ett sätt att upptäcka burstiness genom att jämföra den kvadratiska stickprovsentropin för en tidsserie med Rényis entropitakt av ordning 2 för en symmetrisk och en tungsvansad fördelning.
Chen, Yuh-Jih, and 陳育智. "Burstiness, Delay and Loss Patterns of Correlated Packet traffic." Thesis, 1995. http://ndltd.ncl.edu.tw/handle/68794863978325511259.
Full text國立交通大學
資訊科學學系
83
Due to there exists correlation within packets, traffic tends to arrive in bursts. This phenomenon may congest the network and reduce the system performance. To improve the system performance, we need to study the characteristics of correlated packet traffic. In this thesis, we use HAP model, a traffic model to capture correlation within packet traffic, as our traffic source to measure burstiness, delay and loss. When measuring burstiness, it is important and necessary to determine a burst. if we regard traffic as consecutive burst periods and silent periods. We propose three burst definitions which can be used to determine a burst. To observe the mean number of bursts, mean burst length and burstiness from these definitions, we find their advantages and suggest a hybrid method. We measure mean delay, delay variance and loss ratio by varying server queue size to see the behaviors of delay and loss patterns of correlated packet traffic. We find that HAP traffic suffers serious delay and loss. We also chart delay and loss curves to see thetradeoff between them.
Wu, Chung-Shong, and 吳中雄. "A Simulation Study of ATM Rate-based Flow Control with Call- level and Cell-level Burstiness." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/36365070271917353833.
Full text國立交通大學
資訊科學學系
84
The appearance of ATM(Asynchronous Transfer Mode) networks brings the possible solution for those applications demanding more bandwidth, low jitters, and limited cell loss and delay. It also supports LAN emulation and IP-over-ATM for the existing applications to run on ATM networks. These applications use ATM ABR (Available Bit Rate) services and are subject to flow control. Effects of flow controlling these bursty traffic sources should be carefully examined to avoid inferior performance in ATM than in slower networks. In this work, we simulate a rate-based flow control scheme called ERMC (Explicit Rate based on Multiple Conditions) under burstiness at call and cell levels. Rather than fixing the number of sources, the number of sources is variable. In addition, the cell transmission rate, instead of arrival rate, of a source is adjusted based on the congestion state of the feedback point. Moreover, the control mechanism is based on ER-type feedback. Using the traffic and network models, we obtain the average cell loss probability and average waiting time. With these results, we find that the cell loss probability under burstiness at the cell-level is more sensitive than under burstiness at the call-level. Also, the performance measures of using the function, based on fixed number of sources and probability, is not a good approximation to the performance of variable number of sources. About the control mechanism, the multiple-threshold mechanism has better performance than single- threshold mechanism. Moreover, the flow control is suitable on LAN rather than on WAN. Hence, the flow control on WAN environment would also be an interesting topic.
Xue, Cheng. "Neuronal representation and attentional modulation of space and feature information in primate vision." Doctoral thesis, 2016. http://hdl.handle.net/11858/00-1735-0000-0023-3F35-2.
Full textSchaigorodsky, Ana Laura. "Procesos de memoria en sistemas con distribuciones de Zipf-Pareto." Doctoral thesis, 2018. http://hdl.handle.net/11086/6072.
Full textEstudios recientes realizados en una base de datos de Ajedrez cronológicamente ordenada, han mostrado que la distribución de popularidades de líneas de juego de Ajedrez se ajusta a una ley de Zipf. La ley de Zipf es común a muchos sistemas y es usualmente observada en conjunto con efectos de memoria tales como correlaciones de largo alcance y burstiness. Sin embargo los modelos existentes que estudian estos fenómenos no dan cuenta simultáneamente con la ley de Zipf y los efectos de memoria. En este trabajo de tesis, mediante una variante del modelo de crecimiento preferencial de Yule-Simon, introducido por Cattuto et al., se provee una explicación de la aparición simultanea de la ley de Zipf y los efectos de memoria en forma de correlaciones de largo alcance en la base de datos de Ajedrez. Se encuentra que el modelo de Cattuto et al. es capaz de reproducir ambos fenómenos, la ley de Zipf y las correlaciones de largo alcance, incluyendo además los efectos de tamaño del exponente de Hurst de las correspondientes series temporales. Más aún, se encuentra burstiness en la actividad de los grupos de jugadores más activos, aunque la actividad agregada del conjunto completo de jugadores presenta una distribución de tiempos entre eventos sin burstiness. Dado que el modelo de Cattuto et al. no es capaz de producir series temporales con comportamiento ’bursty ’, se realiza una modificación al núcleo de memoria que permite lograr una dinámica bursty. Introduciendo un núcleo de memoria finito, se mantiene el comportamiento de ley de potencia en la distribución de popularidades y, al mismo tiempo se obtienen series temporales que presentan burstiness como consecuencia de una transición de fase, en la cual, en el estado crítico, la dinámica está dominada por las fluctuaciones.
Recent works studying a chronologically sorted chess database have shown that the popularity distribution of opening lines in the game of chess follow a Zipf law. Zipf law is common to many systems and is usually observed together with memory effects, such as long-range correlations and burstiness. Nevertheless, existing models that study these phenomena do not account for the Zipf’s law and memory effects simultaneously. In this thesis, using a variant of the Yule-Simon preferential growth model, introduced by Cattuto et al., we provide an explanation of the simultaneous emergence of Zipf’s law and memory effects in the form of long-range correlations in the chess database. We find that Cattuto’s model is able to reproduce both phenomena, Zipf’s law and the long-range correlations., including the size effects displayed by the Hurst exponent of the corresponding time series. Furthermore, we find burstiness in the activity of the most active players, although the aggregated activity of all players in the database presents an interevent time distribution without burstiness. Since Cattuto’s model is not able to generate times series with a bursty behavior, we made a modification to the memory kernel that allows a bursty dynamics. By introducing a finite memory kernel, we keep the power-law behavior in the popularity distribution and, at the same time, we obtain time series that present burstiness as a consequence of a phase transition in which, at the critical point, the dynamic is ruled by fluctuations.
Books on the topic "Burstiness"
Burstiness Management for Smart, Sustainable and Inclusive Growth: Emerging Research and Opportunities. IGI Global, 2018.
Find full textBook chapters on the topic "Burstiness"
Buckley, James J. "Burstiness." In Fuzzy Probabilities and Fuzzy Sets for Web Planning, 131–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-36426-9_15.
Full textMin, Byungjoon, and K. I. Goh. "Burstiness: Measures, Models, and Dynamic Consequences." In Understanding Complex Systems, 41–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36461-7_3.
Full textWang, Mao, Qiang Liu, Yuewei Ming, and Jianping Yin. "Group Burstiness Weighting for Image Retrieval." In Advances in Multimedia Information Processing – PCM 2017, 244–53. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77383-4_24.
Full textPierrehumbert, Janet B. "Burstiness of Verbs and Derived Nouns." In Shall We Play the Festschrift Game?, 99–115. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30773-7_8.
Full textShakkottai, Srinivas, Nevil Brownlee, and kc claffy. "A Study of Burstiness in TCP Flows." In Lecture Notes in Computer Science, 13–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-31966-5_2.
Full textYing, Yu, Ravi Mazumdar, Catherine Rosenberg, and Fabrice Guillemin. "The Burstiness Behavior of Regulated Flows in Networks." In NETWORKING 2005. Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communications Systems, 918–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11422778_74.
Full textMandjes, Michel, and Remco van de Meent. "Inferring Traffic Burstiness by Sampling the Buffer Occupancy." In NETWORKING 2005. Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communications Systems, 303–15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11422778_25.
Full textRolland, Chloé, Julien Ridoux, and Bruno Baynat. "Catching IP Traffic Burstiness with a Lightweight Generator." In NETWORKING 2007. Ad Hoc and Sensor Networks, Wireless Networks, Next Generation Internet, 924–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72606-7_79.
Full textGómez, María E., and Vicente Samonja. "On the Impact of Workload Burstiness on Disk Performance." In Workload Characterization of Emerging Computer Applications, 181–201. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1613-2_9.
Full textWei, Jinwu, and Jiangxing Wu. "Nonstationarity of Network Traffic Within Multi-scale Burstiness Constraint." In Computational Intelligence and Security, 971–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11596981_144.
Full textConference papers on the topic "Burstiness"
Alves, Rodrigo Augusto da Silva, Renato Martins Assuncao, and Pedro Olmo Stancioli Vaz de Melo. "Burstiness Scale." In KDD '16: The 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2939672.2939852.
Full textKalogeratos, Argyris, Panagiotis Zagorisios, and Aristidis Likas. "Improving Text Stream Clustering using Term Burstiness and Co-burstiness." In SETN '16: 9th Hellenic Conference on Artificial Intelligence. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2903220.2903229.
Full textAli-Eldin, Ahmed, Oleg Seleznjev, Sara Sjostedt-de Luna, Johan Tordsson, and Erik Elmroth. "Measuring Cloud Workload Burstiness." In 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing (UCC). IEEE, 2014. http://dx.doi.org/10.1109/ucc.2014.87.
Full textPapathanasiou and Scott. "Energy efficiency through burstiness." In Proceedings DARPA Information Survivability Conference and Exposition MCSA-03. IEEE, 2003. http://dx.doi.org/10.1109/mcsa.2003.1240766.
Full textRevaud, Jerome, Matthijs Douze, and Cordelia Schmid. "Correlation-based burstiness for logo retrieval." In the 20th ACM international conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2393347.2396358.
Full textStarobinski, D., and M. Sidi. "Stochastically bounded burstiness for communication networks." In IEEE INFOCOM '99. Conference on Computer Communications. Proceedings. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. The Future is Now (Cat. No.99CH36320). IEEE, 1999. http://dx.doi.org/10.1109/infcom.1999.749250.
Full textDoyle, Gabriel, and Charles Elkan. "Accounting for burstiness in topic models." In the 26th Annual International Conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1553374.1553410.
Full textJegou, Herve, Matthijs Douze, and Cordelia Schmid. "On the burstiness of visual elements." In 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshops). IEEE, 2009. http://dx.doi.org/10.1109/cvpr.2009.5206609.
Full textJegou, H., M. Douze, and C. Schmid. "On the burstiness of visual elements." In 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2009. http://dx.doi.org/10.1109/cvprw.2009.5206609.
Full textWoodruff, Jackson, Andrew W. Moore, and Noa Zilberman. "Measuring Burstiness in Data Center Applications." In BS '19: 2019 Workshop on Buffer Sizing. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3375235.3375240.
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