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Статті в журналах з теми "Information freshness"
Sun, Yin, Igor Kadota, Rajat Talak, and Eytan Modiano. "Age of Information: A New Metric for Information Freshness." Synthesis Lectures on Communication Networks 12, no. 2 (December 11, 2019): 1–224. http://dx.doi.org/10.2200/s00954ed2v01y201909cnt023.
Повний текст джерелаXu, Jin, and Yu Chen. "Information Freshness in Sleep-Wake Server Systems." IEEE Communications Letters 25, no. 7 (July 2021): 2186–90. http://dx.doi.org/10.1109/lcomm.2021.3072071.
Повний текст джерелаBastopcu, Melih, Baturalp Buyukates, and Sennur Ulukus. "Selective Encoding Policies for Maximizing Information Freshness." IEEE Transactions on Communications 69, no. 9 (September 2021): 5714–26. http://dx.doi.org/10.1109/tcomm.2021.3059871.
Повний текст джерелаXu, Chao, Howard H. Yang, Xijun Wang, and Tony Q. S. Quek. "Optimizing Information Freshness in Computing-Enabled IoT Networks." IEEE Internet of Things Journal 7, no. 2 (February 2020): 971–85. http://dx.doi.org/10.1109/jiot.2019.2947419.
Повний текст джерелаArceLopera, C., K. Okajima, Y. Wada, and T. Masuda. "Luminance Information Suffices to Model Vegetable Freshness Perception." Journal of Vision 12, no. 9 (August 10, 2012): 865. http://dx.doi.org/10.1167/12.9.865.
Повний текст джерелаLee, Y. "Freshness ratio of information: a new metric for age of information." Electronics Letters 56, no. 3 (February 2020): 139–41. http://dx.doi.org/10.1049/el.2019.2020.
Повний текст джерелаCho, Junghoo, and Hector Garcia-Molina. "Synchronizing a database to improve freshness." ACM SIGMOD Record 29, no. 2 (June 2000): 117–28. http://dx.doi.org/10.1145/335191.335391.
Повний текст джерелаLiu, Pan. "Investment Decisions of Blockchain-Based Anti-Counterfeiting Traceability Services in a High-Quality Fresh Supply Chain of China." Agriculture 12, no. 6 (June 9, 2022): 829. http://dx.doi.org/10.3390/agriculture12060829.
Повний текст джерелаChen, Zhengchuan, Mingjun Xu, Min Wang, and Yunjian Jia. "Joint Optimization of Data Freshness and Fidelity for Selection Combining-Based Transmissions." Entropy 24, no. 2 (January 28, 2022): 200. http://dx.doi.org/10.3390/e24020200.
Повний текст джерелаNguyen, Gam D., Sastry Kompella, Clement Kam, and Jeffrey E. Wieselthier. "Information freshness over a Markov channel: The effect of channel state information." Ad Hoc Networks 86 (April 2019): 63–71. http://dx.doi.org/10.1016/j.adhoc.2018.10.010.
Повний текст джерелаДисертації з теми "Information freshness"
Bedewy, Ahmed M. "OPTIMIZING DATA FRESHNESS IN INFORMATION UPDATE SYSTEMS." The Ohio State University, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu1618573325086709.
Повний текст джерелаWang, Qian. "Information freshness-oriented scheduling in modern wireless communication systems." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/25537.
Повний текст джерелаMaatouk, Ali. "Optimization of Wireless Networks : Freshness in Communications." Electronic Thesis or Diss., université Paris-Saclay, 2020. http://www.theses.fr/2020UPASG038.
Повний текст джерелаThe proliferation of smartphones, along with the ubiquitous connectivity and cheap hardware cost, has paved the way for new applications that rely on the timely delivery of packets from one end of the network to another. From monitoring home appliances back at the house to vehicular networks where the vehicle’s velocity and position information are disseminated, these applications require fresh data to have optimal performance. To quantify this notion of freshness, the concept of the Age of Information (AoI) was born, and research attention has been put heavily on its analysis and optimization in various network settings. This thesis explores the AoI in numerous system environments,sheds light on its shortcomings, and accordingly provides solutions to them in several real-time monitoring applications.In the first part of the thesis, we focus on optimizing age-based metrics in fundamental communication systems. Specifically, in the third chapter,we examine age-based metrics in multi-class environments that are abundant in real-time applications.A simple example is vehicular networks where safety-related data are considered more sensitive.Consequently, they have a higher priority than the other data in the system. We derive a closed-form expression of each stream’s average age and provide substantial insights into the interaction between the multiple classes. This paves theway for the second part of the chapter, where we introduce a new AoI-based optimization framework in multi-class systems. Therein, we characterize the gains in terms of information freshness when our framework is adopted compared to state-of-the art approaches. The fourth chapter deals with a distributed scheduling environment, where devices contend for the channel using the well-known carrier sense multiple access scheme (CSMA). CSMAis considered one of the most renowned and widely spread distributed scheduling schemes (e.g., CSMAis the primary medium access in Wi-Fi). We characterize,through rigorous theoretical analyses, the operating point that minimizes the average AoI.In the second part of the thesis, we shed light on the shortcomings of the age of information and standard error metrics in many real-time applications.Toward that end, we introduce a new performance metric, which we refer to as the Age of Incorrect Information (AoII). AoII deals with these shortcomings as it extends the notion of fresh updates and captures the deteriorating effect wrong information can have with time on the system. In both unconstrained and resource-constraint scenarios, we derive optimal sampling policies that minimize the AoII. We also high light their advantages compared to both the age-optimal and error-optimal policies in a variety of real-life applications. Our results and analyses provide key insights into the age metric and lead the way to novel research directions for real-time monitoring applications
Kacem, Sahraoui Ameni. "Personalized information retrieval based on time-sensitive user profile." Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30111/document.
Повний текст джерелаRecently, search engines have become the main source of information for many users and have been widely used in different fields. However, Information Retrieval Systems (IRS) face new challenges due to the growth and diversity of available data. An IRS analyses the query submitted by the user and explores collections of data with unstructured or semi-structured nature (e.g. text, image, video, Web page etc.) in order to deliver items that best match his/her intent and interests. In order to achieve this goal, we have moved from considering the query-document matching to consider the user context. In fact, the user profile has been considered, in the literature, as the most important contextual element which can improve the accuracy of the search. It is integrated in the process of information retrieval in order to improve the user experience while searching for specific information. As time factor has gained increasing importance in recent years, the temporal dynamics are introduced to study the user profile evolution that consists mainly in capturing the changes of the user behavior, interests and preferences, and updating the profile accordingly. Prior work used to discern short-term and long-term profiles. The first profile type is limited to interests related to the user's current activities while the second one represents user's persisting interests extracted from his prior activities excluding the current ones. However, for users who are not very active, the short-term profile can eliminate relevant results which are more related to their personal interests. This is because their activities are few and separated over time. For users who are very active, the aggregation of recent activities without ignoring the old interests would be very interesting because this kind of profile is usually changing over time. Unlike those approaches, we propose, in this thesis, a generic time-sensitive user profile that is implicitly constructed as a vector of weighted terms in order to find a trade-off by unifying both current and recurrent interests. User profile information can be extracted from multiple sources. Among the most promising ones, we propose to use, on the one hand, searching history. Data from searching history can be extracted implicitly without any effort from the user and includes issued queries, their corresponding results, reformulated queries and click-through data that has relevance feedback potential. On the other hand, the popularity of Social Media makes it as an invaluable source of data used by users to express, share and mark as favorite the content that interests them
Fujdiak, Radek. "Analýza a optimalizace datové komunikace pro telemetrické systémy v energetice." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2017. http://www.nusl.cz/ntk/nusl-358408.
Повний текст джерелаLewandowski, Dirk, Henry Wahlig, and Gunnar Meyer-Bautor. "The freshness of Web search engine databases." 2005. http://hdl.handle.net/10150/105302.
Повний текст джерелаJayaram, Deepak. "Cooperative Caching in Vehicular Networks - Distributed Cache Invalidation Using Information Freshness." Master's thesis, 2018. http://tuprints.ulb.tu-darmstadt.de/7354/1/MasterThesis_Deepak-Jayaram_KOM-M-0622.pdf.
Повний текст джерелаКниги з теми "Information freshness"
Modiano, Eytan, Yin Sun, Igor Kadota, and Rajat Talak. Age of Information: A New Metric for Information Freshness. Springer International Publishing AG, 2022.
Знайти повний текст джерелаModiano, Eytan, Yin Sun, Igor Kadota, and Rajat Talak. Age of Information: A New Metric for Information Freshness. Springer International Publishing AG, 2019.
Знайти повний текст джерелаSun, Yin, Igor Kadota, and Rajat Talak. Age of Information: A New Metric for Information Freshness. Morgan & Claypool Publishers, 2020.
Знайти повний текст джерелаSun, Yin, Igor Kadota, and Rajat Talak. Age of Information: A New Metric for Information Freshness. Morgan & Claypool Publishers, 2020.
Знайти повний текст джерелаModiano, Eytan, Yin Sun, R. Srikant, Igor Kadota, and Rajat Talak. Age of Information: A New Metric for Information Freshness. Morgan & Claypool Publishers, 2019.
Знайти повний текст джерелаMartin, Keith M. Entity Authentication. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198788003.003.0008.
Повний текст джерелаHorsfall, Mary. Fabulous Food from Every Small Garden. CSIRO Publishing, 2009. http://dx.doi.org/10.1071/9780643097957.
Повний текст джерелаЧастини книг з теми "Information freshness"
Bouneffouf, Djallel. "Freshness-Aware Thompson Sampling." In Neural Information Processing, 373–80. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12643-2_46.
Повний текст джерелаGarnaev, Andrey, Jing Zhong, Wuyang Zhang, Roy D. Yates, and Wade Trappe. "Proportional Fair Information Freshness Under Jamming." In Lecture Notes in Computer Science, 91–102. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30523-9_8.
Повний текст джерелаLiang, Zhiyao, and Rakesh M. Verma. "Complexity of Checking Freshness of Cryptographic Protocols." In Information Systems Security, 86–101. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-89862-7_6.
Повний текст джерелаKavitha, Veeraruna, and Eitan Altman. "Controlling Packet Drops to Improve Freshness of Information." In Network Games, Control and Optimization, 60–77. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87473-5_7.
Повний текст джерелаRajani, Meena, Uwe Röhm, and Akon Dey. "Consistent Freshness-Aware Caching for Multi-Object Requests." In Web Information Systems Engineering – WISE 2014, 262–77. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11746-1_19.
Повний текст джерелаDas, Sikha, Prabir Mondal, Md Iqbal Quraishi, Samarjit Kar, and Arif Ahmed Sekh. "Freshness Quality Detection of Tomatoes Using Computer Vision." In Communications in Computer and Information Science, 243–55. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-22485-0_22.
Повний текст джерелаMartins, Pedro, Maryam Abbasi, and Pedro Furtado. "AScale: Big/Small Data ETL and Real-Time Data Freshness." In Communications in Computer and Information Science, 315–27. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-34099-9_25.
Повний текст джерелаDas, Sikha, Samarjit Kar, and Arif Ahmed Sekh. "FGrade: A Large Volume Dataset for Grading Tomato Freshness Quality." In Communications in Computer and Information Science, 455–66. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1092-9_38.
Повний текст джерелаQi Chen, Da, Lin An, Aidin Niaparast, R. Ravi, and Oleksandr Rudenko. "Timeliness Through Telephones: Approximating Information Freshness in Vector Clock Models." In Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), 2411–28. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2023. http://dx.doi.org/10.1137/1.9781611977554.ch93.
Повний текст джерелаPapastavrou, Stavros, Panos K. Chrysanthis, and George Samaras. "Exploring Content Dependencies to Better Balance Performance and Freshness in Web Database Applications." In Web Information Systems Engineering - WISE 2012, 512–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35063-4_37.
Повний текст джерелаТези доповідей конференцій з теми "Information freshness"
Garnaev, Andrey, Wuyang Zhang, Jing Zhong, and Roy D. Yates. "Maintaining Information Freshness under Jamming." In IEEE INFOCOM 2019 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). IEEE, 2019. http://dx.doi.org/10.1109/infcomw.2019.8845146.
Повний текст джерелаBastopcu, Melih, and Sennur Ulukus. "Cache Freshness in Information Updating Systems." In 2021 55th Annual Conference on Information Sciences and Systems (CISS). IEEE, 2021. http://dx.doi.org/10.1109/ciss50987.2021.9400310.
Повний текст джерелаBastopcu, Melih, and Sennur Ulukus. "Partial Updates: Losing Information for Freshness." In 2020 IEEE International Symposium on Information Theory (ISIT). IEEE, 2020. http://dx.doi.org/10.1109/isit44484.2020.9174078.
Повний текст джерелаAbu-Akleek, Fatima Khattab, and Abdallah Alma'aitah. "Information Freshness and System Performance Trading-off." In 2021 12th International Conference on Information and Communication Systems (ICICS). IEEE, 2021. http://dx.doi.org/10.1109/icics52457.2021.9464535.
Повний текст джерелаKam, Clement, Sastry Kompella, Gam D. Nguyen, Jeffrey E. Wieselthier, and Anthony Ephremides. "Information freshness and popularity in mobile caching." In 2017 IEEE International Symposium on Information Theory (ISIT). IEEE, 2017. http://dx.doi.org/10.1109/isit.2017.8006505.
Повний текст джерелаDeng, Dapeng, Zhengchuan Chen, Howard H. Yang, Nikolaos Pappas, Limei Hu, Min Wang, Yunjian Jia, and Tony Q. S. Quek. "Information Freshness in A Dual Monitoring System." In GLOBECOM 2022 - 2022 IEEE Global Communications Conference. IEEE, 2022. http://dx.doi.org/10.1109/globecom48099.2022.10000990.
Повний текст джерелаVahdani, Elahe, Amotz Bar-Noy, Matthew P. Johnson, and Tarek Abdelzaher. "Gathering Information in Sensor Networks for Synchronized Freshness." In 2017 14th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON). IEEE, 2017. http://dx.doi.org/10.1109/sahcn.2017.7964937.
Повний текст джерелаHan, Hao, Takashi Nakayama, Junxia Guo, and Keizo Oyama. "Towards Serving "Delicious" Information within Its Freshness Date." In WWW '15: 24th International World Wide Web Conference. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2740908.2742747.
Повний текст джерелаFeng, Songtao, and Jing Yang. "Information Freshness for Timely Detection of Status Changes." In 2020 54th Annual Conference on Information Sciences and Systems (CISS). IEEE, 2020. http://dx.doi.org/10.1109/ciss48834.2020.1570627788.
Повний текст джерелаLi, Bohai, He Chen, Nikolaos Pappas, and Yonghui Li. "Optimizing Information Freshness in Two-Way Relay Networks." In 2020 IEEE/CIC International Conference on Communications in China (ICCC). IEEE, 2020. http://dx.doi.org/10.1109/iccc49849.2020.9238858.
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