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Статті в журналах з теми "Throughput allocation"
Ismail, M. S., Noorhafiza Muhammad, M. I. Hussain, Zuraidah Mohd Zain, and R. Ahmad. "Buffer Allocation Using 6 Steps Oba Method: A Case Study." Applied Mechanics and Materials 815 (November 2015): 287–92. http://dx.doi.org/10.4028/www.scientific.net/amm.815.287.
Повний текст джерелаSK, Khaleelahmed, Venkateswararao N, Varshasree KN, and P. V. Naidu. "Improving MIMO system throughput using power transmission scheduling." International Journal of Engineering & Technology 7, no. 3 (June 23, 2018): 1181. http://dx.doi.org/10.14419/ijet.v7i3.13097.
Повний текст джерелаBonald, Thomas, Léonce Mekinda, and Luca Muscariello. "Fair throughput allocation in Information-Centric Networks." Computer Networks 125 (October 2017): 122–31. http://dx.doi.org/10.1016/j.comnet.2017.05.019.
Повний текст джерелаTassiulas, Leandros, and Partha P. Bhattacharya. "Allocation of interdependent resources for maximal throughput." Communications in Statistics. Stochastic Models 16, no. 1 (January 2000): 27–48. http://dx.doi.org/10.1080/15326340008807575.
Повний текст джерелаGao, Sixiao, Toshimitsu Higashi, Toyokazu Kobayashi, Kosuke Taneda, Jose I. U. Rubrico, and Jun Ota. "Buffer Allocation via Bottleneck-Based Variable Neighborhood Search." Applied Sciences 10, no. 23 (November 30, 2020): 8569. http://dx.doi.org/10.3390/app10238569.
Повний текст джерелаAbuajwa, Osama, Mardeni Bin Roslee, and Zubaida Binti Yusoff. "Simulated Annealing for Resource Allocation in Downlink NOMA Systems in 5G Networks." Applied Sciences 11, no. 10 (May 18, 2021): 4592. http://dx.doi.org/10.3390/app11104592.
Повний текст джерелаLe, Van Hoa, Viet Minh Nhat Vo, and Manh Thanh Le. "Throughput-based fair bandwidth allocation in OBS networks." ETRI Journal 40, no. 5 (September 15, 2018): 624–33. http://dx.doi.org/10.4218/etrij.2017-0253.
Повний текст джерелаHong, Bo, and Viktor Prasanna. "Adaptive Allocation of Independent Tasks to Maximize Throughput." IEEE Transactions on Parallel and Distributed Systems 18, no. 10 (October 2007): 1420–35. http://dx.doi.org/10.1109/tpds.2007.1042.
Повний текст джерелаMaeng, Juhyun, Mwamba Kasongo Dahouda, and Inwhee Joe. "Optimal Power Allocation with Sectored Cells for Sum-Throughput Maximization in Wireless-Powered Communication Networks Based on Hybrid SDMA/NOMA." Electronics 11, no. 6 (March 8, 2022): 844. http://dx.doi.org/10.3390/electronics11060844.
Повний текст джерелаDiamantidis, A. C., and C. T. Papadopoulos. "A dynamic programming algorithm for the buffer allocation problem in homogeneous asymptotically reliable serial production lines." Mathematical Problems in Engineering 2004, no. 3 (2004): 209–23. http://dx.doi.org/10.1155/s1024123x04402014.
Повний текст джерелаДисертації з теми "Throughput allocation"
PUNYALA, SRINIVASA REDDY. "THROUGHPUT OPTIMIZATION AND RESOURCE ALLOCATION ON GPUS UNDER MULTI-APPLICATION EXECUTION." OpenSIUC, 2017. https://opensiuc.lib.siu.edu/theses/2255.
Повний текст джерелаSrinivasan, Ramya. "Throughput optimization in MIMO networks." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/42735.
Повний текст джерелаCardany, John Paul. "Node to processor allocation for large grain data flow graphs in throughput-critical applications." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1994. http://handle.dtic.mil/100.2/ADA283607.
Повний текст джерелаGarau, Luis Juan Jose. "A Comparison of artificial intelligence algorithms for dynamic power allocation in flexible high throughput satellites." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/127074.
Повний текст джерелаCataloged from the official PDF of thesis.
Includes bibliographical references (pages 117-123).
The Dynamic Resource Management (DRM) problem in the context of multibeam satellite communications is becoming more relevant than ever. The future landscape of the industry will be defined by a substantial increase in demand alongside the introduction of digital and highly flexible payloads able to operate and reconfigure hundreds or even thousands of beams in real time. This increase in complexity and dimensionality puts the spotlight on new resource allocation strategies that use autonomous algorithms at the core of their decision-making systems. These algorithms must be able to find optimal resource allocations in real or near-real time. Traditional optimization approaches no longer meet all these DRM requirements and the research community is studying the application of Artificial Intelligence (AI) algorithms to the problem as a potential alternative that satisfies the operational constraints.
Although multiple AI approaches have been proposed in the recent years, most of the analyses have been conducted under assumptions that do not entirely reflect the new operation scenarios' requirements, such as near-real time performance or high-dimensionality. Furthermore, little work has been done in thoroughly comparing the performance of different algorithms and characterizing them. This Thesis considers the Dynamic Power Allocation problem, a DRM subproblem, as a use case and compares nine different AI algorithms under the same near-real time operational assumptions, using the same satellite and link budget models, and four different demand datasets. The study focuses on Genetic Algorithms (GA), Simulated Annealing (SA), Particle Swarm Optimization (PSO), Deep Reinforcement Learning (DRL), and hybrid approaches, including a novel DRL-GA hybrid. The comparison considers the following characteristics: time convergence, continuous operability, scalability, and robustness.
After evaluating the algorithms' performance on the different test scenarios, three algorithms are identified as potential candidates to be used during real satellite operations. The novel DRL-GA implementation shows the best overall performance, being also the most robust. When the update frequency is in the order of seconds, DRL is identified as the best algorithm, since it is the fastest. Finally, when the online data substantially diverges from the training dataset of the DRL algorithm, both DRL and DRL-GA hybrid might not perform adequately and an individual GA might be the best option instead.
by Juan Jose Garau Luis.
S.M.
S.M. Massachusetts Institute of Technology, Department of Aeronautics and Astronautics
Ji, Bo. "Design of Efficient Resource Allocation Algorithms for Wireless Networks: High Throughput, Small Delay, and Low Complexity." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1354641556.
Повний текст джерелаToktas, Engin. "Subcarrier Allocation In Ofdma Systems With Time Varying Channel And Packet Arrivals." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/3/12610029/index.pdf.
Повний текст джерелаCao, Fei. "Efficient Scientific Workflow Scheduling in Cloud Environment." OpenSIUC, 2014. https://opensiuc.lib.siu.edu/dissertations/802.
Повний текст джерелаMaaz, Mohamad. "Allocation de ressource et analyse des critères de performance dans les réseaux cellulaires coopératifs." Thesis, Rennes, INSA, 2013. http://www.theses.fr/2013ISAR0036/document.
Повний текст джерелаIn wireless systems, transmitting large amounts of information with low energetic cost are two main issues that have never stopped drawing the attention of the scientific community during the past decade. Later, it has been shown that cooperative communication is an appealing technique that exploits spatial diversity in wireless channel. Therefore, this technique certainly promises a robust and reliable communications, higher quality-of-service (QoS) and makes the cooperation concept attractive for future cellular systems. Typically, the QoS requirements are the packet error rate, throughput and delay. These metrics are affected by the delay, where each erroneous packet is retransmitted several times according to Hybrid-Automatic Repeat-Request (HARQ) mechanism inducing a delay on the demanded QoS but a temporal diversity is created. Therefore, adopting jointly cooperative communications and HARQ mechanisms could be beneficial for designing cross-layer schemes. First, a new rate maximization strategy, under heterogeneous data rate constraints among users is proposed. We propose an algorithm that allocates the optimal power at the base station (BS) and relays, assigns subcarriers and selects relays. The achievable data rate is investigated as well as the average starvation rate in the network when the load, i.e. the number of active users in the network, is increasing. It showed a significant gain in terms of global capacity compared to literature. Second, in block fading channel, theoretical analyses of the packet error rate, delay and throughput efficiency in relayassisted HARQ networks are provided. In slow fading channels, the average delay of HARQ mechanisms w.r.t. the fading states is not relevant due to the non-ergodic process of the fading channel. The delay outage is hence invoked to deal with the slow fading channel and is defined as the probability that the average delay w.r.t. AWGN channel exceeds a predefined threshold. This criterion has never been studied in literature, although being of importance for delay sensitive applications in slow fading channels. Then, an analytical form of the delay outage probability is proposed which might be useful to avoid lengthy simulations. These analyses consider a finite packet length and a given modulation and coding scheme (MCS) which leads to study the performance of practical systems. Third, a theoretical analysis of the energy efficiency (bits/joule) in relay-assisted HARQ networks is provided. Based on this analysis, an energy minimization problem in multiuser relayassisted downlink cellular networks is investigated. Each user has an average delay constraint to be satisfied such that a total power constraint in the system is respected. The BS is assumed to have only knowledge about the average channel statistics but no instantaneous channel state information (CSI). Finally, an algorithm that jointly allocates the optimal power at BS, the relay stations and selects the optimal relay in order to satisfy the delay constrains of users is proposed. The simulations show the improvement in terms of energy consumption of relay-assisted techniques compared to nonaided transmission in delay-constrained systems. Hence, the work proposed in this thesis can give useful insights for engineering rules in the design of the next generation energyefficient cellular systems
Yassin, Mohamad. "Inter-cell interference coordination in wireless networks." Thesis, Rennes 1, 2015. http://www.theses.fr/2015REN1S106/document.
Повний текст джерелаThe exponentially increasing demand for mobile broadband communications have led to the dense deployment of cellular networks with aggressive frequency reuse patterns. The future Fifth Generation (5G) networks are expected to overcome capacity and throughput challenges by adopting a multi-tier architecture where several low-power Base Stations (BSs) are deployed within the coverage area of the macro cell. However, Inter-Cell Interference (ICI) caused by the simultaneous usage of the same spectrum in different cells, creates severe problems. ICI reduces system throughput and network capacity, and has a negative impact on cell-edge User Equipment (UE) performance. Therefore, Inter-Cell Interference Coordination (ICIC) techniques are required to mitigate the impact of ICI on system performance. In this thesis, we address the resource and power allocation problem in multiuser Orthogonal Frequency Division Multiple Access (OFDMA) networks such as LTE/LTE-A networks and dense small cell networks. We start by overviewing the state-of-the-art schemes, and provide an exhaustive classification of the existing ICIC approaches. This qualitative classification is followed by a quantitative investigation of several interference mitigation techniques. Then, we formulate a centralized multi-cell joint resource and power allocation problem, and prove that this problem is separable into two independent convex optimization problems. The objective function of the formulated problem consists in maximizing system throughput while guaranteeing throughput fairness between UEs. ICI is taken into account, and resource and power allocation is managed accordingly in a centralized manner. Furthermore, we introduce a decentralized game-theoretical method to solve the power allocation problem without the need to exchange signaling messages between the different cells. We also propose a decentralized heuristic power control algorithm based on the received Channel Quality Indication (CQI) feedbacks. The intuition behind this algorithm is to avoid power wastage for UEs that are close to the serving cell, and reducing ICI for UEs in the neighboring cells. An autonomous ICIC scheme that aims at satisfying throughput demands in each cell zone is also introduced. The obtained results show that this technique improves UE throughput fairness, and it reduces the percentage of unsatisfied UEs without generating additional signaling messages. Lastly, we provide a hybrid ICIC scheme as a compromise between the centralized and the decentralized approaches. For a cluster of adjacent cells, resource and power allocation decisions are made in a collaborative manner. First, the transmission power is adjusted after receiving the necessary information from the neighboring cells. Second, resource allocation between cell zones is locally modified, according to throughput demands in each zone
Wu, Fei. "Ultra-Low Delay in Complex Computing and Networked Systems: Fundamental Limits and Efficient Algorithms." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu155559337777619.
Повний текст джерелаКниги з теми "Throughput allocation"
Shroff, Ness, Xiaojun Lin, and Bo Ji. Advances in Multi-Channel Resource Allocation: Throughput, Delay, and Complexity. Springer International Publishing AG, 2016.
Знайти повний текст джерелаLin, Xiaojun, Bo Ji, and Ness B. Shroff. Advances in Multi-Channel Resource Allocation: Throughput, Delay, and Complexity. Morgan & Claypool Publishers, 2016.
Знайти повний текст джерелаLin, Xiaojun, Bo Ji, and Ness B. Shroff. Advances in Multi-Channel Resource Allocation: Throughput, Delay, and Complexity. Morgan & Claypool Publishers, 2016.
Знайти повний текст джерелаScholnick, Ellin K., and Patricia H. Miller. Categories, Gender, and Development. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190658540.003.0014.
Повний текст джерелаAustralian Soil and Land Survey Field Handbook. CSIRO Publishing, 2009. http://dx.doi.org/10.1071/9780643097117.
Повний текст джерелаSime, Stuart. A Practical Approach to Civil Procedure. 25th ed. Oxford University Press, 2022. http://dx.doi.org/10.1093/he/9780192859365.001.0001.
Повний текст джерелаЧастини книг з теми "Throughput allocation"
Gao, Xiaozheng, Kai Yang, Dusit Niyato, and Shimin Gong. "Throughput-Maximized Relay Mode Selection and Resource Sharing." In Resource Allocation in Backscatter-Assisted Communication Networks, 73–96. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5127-4_5.
Повний текст джерелаGarnaev, Andrey, Shweta Sagari, and Wade Trappe. "Fair Allocation of Throughput Under Harsh Operational Conditions." In Multiple Access Communications, 108–19. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23440-3_9.
Повний текст джерелаAmaldi, Edoardo, Stefano Coniglio, and Leonardo Taccari. "Maximum Throughput Network Routing Subject to Fair Flow Allocation." In Lecture Notes in Computer Science, 1–12. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-14115-2_1.
Повний текст джерелаAmaldi, Edoardo, Stefano Coniglio, and Leonardo Taccari. "Maximum Throughput Network Routing Subject to Fair Flow Allocation." In Lecture Notes in Computer Science, 1–12. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09174-7_1.
Повний текст джерелаKucharzak, Michal, and Krzysztof Walkowiak. "On Modelling of Fair Throughput Allocation in Overlay Multicast Networks." In Smart Spaces and Next Generation Wired/Wireless Networking, 529–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22875-9_48.
Повний текст джерелаHong, Bo, and Viktor Prasanna. "Bandwidth-Aware Resource Allocation for Heterogeneous Computing Systems to Maximize Throughput." In High-Performance Computing, 295–312. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/0471732710.ch15.
Повний текст джерелаHuang, Zheng, Wenbin Gong, and FengWei Shao. "A Beidou Laser Link Allocation Scheme Based on Network Throughput Optimization." In Lecture Notes in Electrical Engineering, 505–14. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3142-9_48.
Повний текст джерелаMishra, Sadhana, Ranjeet Singh Tomar, and Mayank Sharma. "Analysis of Throughput and Spectral Efficiency of the CR Users with Channel Allocation." In Lecture Notes in Electrical Engineering, 1–13. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8554-5_1.
Повний текст джерелаLi, Wei, Kai Xing, and Jing Xu. "A Localized Channel Allocation Approach for Realtime Reliable and High Throughput Communication in Multi-channel Networks." In Wireless Algorithms, Systems, and Applications, 602–11. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21837-3_59.
Повний текст джерелаZhao, Wei, Yanlong Zhai, Han Zhang, and Duzheng Qing. "Resource Allocation and Optimization of Simulation Models Based on Improved Genetic Algorithm in High-Throughput Simulation." In Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems, 632–41. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2669-0_67.
Повний текст джерелаТези доповідей конференцій з теми "Throughput allocation"
Gelado, Isaac, and Michael Garland. "Throughput-oriented GPU memory allocation." In PPoPP '19: 24th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3293883.3295727.
Повний текст джерелаYao, Chuting, Jia Guo, and Chenyang Yang. "Achieving high throughput with predictive resource allocation." In 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP). IEEE, 2016. http://dx.doi.org/10.1109/globalsip.2016.7905946.
Повний текст джерелаLi, Dong, Minsoo Rhu, Daniel R. Johnson, Mike O'Connor, Mattan Erez, Doug Burger, Donald S. Fussell, and Stephen W. Redder. "Priority-based cache allocation in throughput processors." In 2015 IEEE 21st International Symposium on High Performance Computer Architecture (HPCA). IEEE, 2015. http://dx.doi.org/10.1109/hpca.2015.7056024.
Повний текст джерелаNissel, Ronald, and Markus Rupp. "Dynamic spectrum allocation in cognitive radio: Throughput calculations." In 2016 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom). IEEE, 2016. http://dx.doi.org/10.1109/blackseacom.2016.7901564.
Повний текст джерелаKhan, Humayun Zubair, Mudassar Ali, Muhammad Naeem, Imran Rashid, Adil Masood Siddiqui, Muhammad Imran, and Shahid Mumtaz. "Resource Allocation and Throughput Maximization in Decoupled 5G." In 2020 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2020. http://dx.doi.org/10.1109/wcnc45663.2020.9120853.
Повний текст джерелаPo-Hao Chang, Chia-Hong Jhang, and Kuo-Hsiang Kuo. "Throughput-based subcarrier allocation for multiuser OFDM system." In 2009 IEEE Radio and Wireless Symposium (RWS). IEEE, 2009. http://dx.doi.org/10.1109/rws.2009.4957366.
Повний текст джерелаHofmann, Sandra, Dominic Schupke, and Frank H. P. Fitzek. "Optimal Throughput Allocation in Air-to-Ground Networks." In GLOBECOM 2020 - 2020 IEEE Global Communications Conference. IEEE, 2020. http://dx.doi.org/10.1109/globecom42002.2020.9348270.
Повний текст джерелаZhang, Dan, Kai Su, and Narayan B. Mandayam. "Network coding aware resource allocation to improve throughput." In 2012 IEEE International Symposium on Information Theory - ISIT. IEEE, 2012. http://dx.doi.org/10.1109/isit.2012.6283070.
Повний текст джерелаGupta, Piyush, and Alexander Stolyar. "Optimal Throughput Allocation in General Random-Access Networks." In 2006 40th Annual Conference on Information Sciences and Systems. IEEE, 2006. http://dx.doi.org/10.1109/ciss.2006.286657.
Повний текст джерелаJar, Marcel, and Gerhard Fettweis. "Throughput maximization for LTE uplink via resource allocation." In 2012 9th International Symposium on Wireless Communication Systems (ISWCS 2012). IEEE, 2012. http://dx.doi.org/10.1109/iswcs.2012.6328347.
Повний текст джерелаЗвіти організацій з теми "Throughput allocation"
McPhedran, R., K. Patel, B. Toombs, P. Menon, M. Patel, J. Disson, K. Porter, A. John, and A. Rayner. Food allergen communication in businesses feasibility trial. Food Standards Agency, March 2021. http://dx.doi.org/10.46756/sci.fsa.tpf160.
Повний текст джерелаZilberman, David, Amir Heiman, and B. McWilliams. Economics of Marketing and Diffusion of Agricultural Inputs. United States Department of Agriculture, November 2003. http://dx.doi.org/10.32747/2003.7586469.bard.
Повний текст джерела