Готові списки джерел за темами / Scalability

Добірка наукової літератури з теми "Scalability"

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Опубліковано: 4 червня 2021

Оновлено: 25 травня 2024

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Статті в журналах з теми "Scalability"

Katata, Hiroyuki. "Scalability." Journal of the Institute of Image Information and Television Engineers 51, no. 12 (1997): 1983. http://dx.doi.org/10.3169/itej.51.1983.

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Merrell, Ronald C., and Charles R. Doarn. "Scalability." Telemedicine and e-Health 25, no. 4 (April 2019): 261–62. http://dx.doi.org/10.1089/tmj.2019.29021.crd.

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Muslihaeny, Siti, Muhammad Ainul Yaqin, and Syahiduz Zaman. "Simulasi Pertumbuhan Scalable Business Process Model pada ERP Pondok Pesantren berbasis Production Rule Cellular Automata." ILKOMNIKA: Journal of Computer Science and Applied Informatics 1, no. 2 (December 31, 2019): 30–38. http://dx.doi.org/10.28926/ilkomnika.v1i2.16.

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Penelitian ini bertujuan untuk mensimulasi scalable business process model dari ERP Pondok Pesantren guna mendapatkan variasi proses bisnis yang mungkin terjadi menggunakan teori Production Rule Cellular Automata. Inputan untuk sistem ini adalah model proses bisnis dari empat tipe Pondok Pesantren yang dimodelkan menggunakan Petri net berupa file PNML. Parameter yang digunakan untuk mensimulasikan pertumbuhan proses bisnis adalah scalability. Scalability / skalabilitas adalah potensi proses bisnis untuk tumbuh atau kemampuan pertumbuhan dari proses bisnis. Nilai scalability dapat diukur dengan perhitungan kemiripan workflow dan skala model proses bisnis. Pertumbuhan proses bisnis terjadi pada model A dengan pembanding model B. Syarat untuk dapat terjadi pertumbuhan pada proses bisnis yaitu complexity model A harus lebih kecil daripada model B. Pola pertumbuhan proses bisnis dilakukan secara random dengan dua pembobotan yaitu secara percabangan dan sequence. Pertumbuhan berhenti jika scalabiltiy pada nilai “>=0” dan “<1” Hasil dari penelitian ini menunjukkan bahwa sistem mampu melakukan simulasi pertumbuhan pada file PNML yang ditandai dengan nilai recent scalability lebih kecil dibandingkan scalability awal. Kemudian output sistem adalah file PNML hasil dari simulasi pertumbuhan proses bisnis dengan pertumbuhan elemen baru. Berdasarkan hasil pengujian dari segi nilai scalability, penelitian terbukti berhasil dengan fakta penurunan nilai scalability.

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Horrocks, Ian. "Semantics ⊓ scalability ⊨ ⊥?" Journal of Zhejiang University SCIENCE C 13, no. 4 (April 2012): 241–44. http://dx.doi.org/10.1631/jzus.c1101001.

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Eick, Stephen G., and Alan F. Karr. "Visual Scalability." Journal of Computational and Graphical Statistics 11, no. 1 (March 2002): 22–43. http://dx.doi.org/10.1198/106186002317375604.

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ACM Case Study. "Photoshop scalability." Communications of the ACM 53, no. 10 (October 2010): 32–38. http://dx.doi.org/10.1145/1831407.1831423.

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Surridge, Christopher. "Scale and scalability." New Phytologist 170, no. 3 (May 2006): 426–28. http://dx.doi.org/10.1111/j.1469-8137.2006.01734.x.

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Macri, Dean. "The Scalability Problem." Queue 1, no. 10 (February 2004): 66–73. http://dx.doi.org/10.1145/971564.971594.

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Brataas, Gunnar, and Peter Hughes. "Exploring architectural scalability." ACM SIGSOFT Software Engineering Notes 29, no. 1 (January 2004): 125–29. http://dx.doi.org/10.1145/974043.974064.

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Falatah, Maram Mohammed, and Omar Abdullah Batarfi. "Cloud Scalability Considerations." International Journal of Computer Science & Engineering Survey 5, no. 4 (August 31, 2014): 37–47. http://dx.doi.org/10.5121/ijcses.2014.5403.

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Дисертації з теми "Scalability"

Singh, Arjun. "The scalability of AspectJ." Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/32349.

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To assess the scalability of using AspectJ, we refactored concerns that crosscut over half of the plug-ins that comprise the Eclipse IDE. Eclipse is a suitable candidate for furthering other studies on AspectJ's scalability because the system has an additional modularization mechanism typical of large systems that introduces new complexities for defining advice and aspects. We evaluated quantitative and qualitative properties of our AO refactored version of Eclipse and compared them to their equivalents in the original, OO version of Eclipse. Quantitatively, we evaluated execution time and memory usage. Qualitatively, we evaluated changes in scattering, coupling, and abstractions. Our assessment of the scalability of AspectJ shows that using the language in Eclipse resulted in changes in performance and improvements in code similar to those seen in previous studies on the scalability of AspectJ. This leads us to conclude that AspectJ scales up to large systems. We also conclude that it may be necessary for the system to be aware of aspects in order to deal with defining advice that cross system boundaries.
Science, Faculty of
Computer Science, Department of
Graduate

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Li, Yan. "Scalability of RAID systems." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/3382.

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RAID systems (Redundant Arrays of Inexpensive Disks) have dominated backend storage systems for more than two decades and have grown continuously in size and complexity. Currently they face unprecedented challenges from data intensive applications such as image processing, transaction processing and data warehousing. As the size of RAID systems increases, designers are faced with both performance and reliability challenges. These challenges include limited back-end network bandwidth, physical interconnect failures, correlated disk failures and long disk reconstruction time. This thesis studies the scalability of RAID systems in terms of both performance and reliability through simulation, using a discrete event driven simulator for RAID systems (SIMRAID) developed as part of this project. SIMRAID incorporates two benchmark workload generators, based on the SPC-1 and Iometer benchmark specifications. Each component of SIMRAID is highly parameterised, enabling it to explore a large design space. To improve the simulation speed, SIMRAID develops a set of abstraction techniques to extract the behaviour of the interconnection protocol without losing accuracy. Finally, to meet the technology trend toward heterogeneous storage architectures, SIMRAID develops a framework that allows easy modelling of different types of device and interconnection technique.Simulation experiments were first carried out on performance aspects of scalability. They were designed to answer two questions: (1) given a number of disks, which factors affect back-end network bandwidth requirements; (2) given an interconnection network, how many disks can be connected to the system. The results show that the bandwidth requirement per disk is primarily determined by workload features and stripe unit size (a smaller stripe unit size has better scalability than a larger one), with cache size and RAID algorithm having very little effect on this value. The maximum number of disks is limited, as would be expected, by the back-end network bandwidth. Studies of reliability have led to three proposals to improve the reliability and scalability of RAID systems. Firstly, a novel data layout called PCDSDF is proposed. PCDSDF combines the advantages of orthogonal data layouts and parity declustering data layouts, so that it can not only survivemultiple disk failures caused by physical interconnect failures or correlated disk failures, but also has a good degraded and rebuild performance. The generating process of PCDSDF is deterministic and time-efficient. The number of stripes per rotation (namely the number of stripes to achieve rebuild workload balance) is small. Analysis shows that the PCDSDF data layout can significantly improve the system reliability. Simulations performed on SIMRAID confirm the good performance of PCDSDF, which is comparable to other parity declustering data layouts, such as RELPR. Secondly, a system architecture and rebuilding mechanism have been designed, aimed at fast disk reconstruction. This architecture is based on parity declustering data layouts and a disk-oriented reconstruction algorithm. It uses stripe groups instead of stripes as the basic distribution unit so that it can make use of the sequential nature of the rebuilding workload. The design space of system factors such as parity declustering ratio, chunk size, private buffer size of surviving disks and free buffer size are explored to provide guidelines for storage system design. Thirdly, an efficient distributed hot spare allocation and assignment algorithm for general parity declustering data layouts has been developed. This algorithm avoids conflict problems in the process of assigning distributed spare space for the units on the failed disk. Simulation results show that it effectively solves the write bottleneck problem and, at the same time, there is only a small increase in the average response time to user requests.

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Duong, Tuyet. "BLOCKCHAIN SCALABILITY AND SECURITY." VCU Scholars Compass, 2018. https://scholarscompass.vcu.edu/etd/5559.

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Cryptocurrencies like Bitcoin have proven to be a phenomenal success. The underlying techniques hold huge promise to change the future of financial transactions, and eventually the way people and companies compute, collaborate, and interact. At the same time, the current Bitcoin-like proof-of-work based blockchain systems are facing many challenges. In more detail, a huge amount of energy/electricity is needed for maintaining the Bitcoin blockchain. In addition, their security holds if the majority of the computing power is under the control of honest players. However, this assumption has been seriously challenged recently and Bitcoin-like systems will fail when this assumption is broken. This research proposes novel blockchain designs to address the challenges. We first propose a novel blockchain protocol, called 2-hop blockchain, by combining proof-of-work and proof-of-stake mechanisms. That said, even if the adversary controls more than 50% computing power, the honest players still have the chance to defend the blockchain via honest stake. Then we revise and implement the design to obtain a practical cryptocurrency system called Twinscoin. In more detail, we introduce a new strategy for difficulty adjustment in the hybrid blockchain and provide an analysis of it. We also show how to construct a light client for proof-of-stake cryptocurrencies and evaluate the proposal practically. We implement our new design. Our implementation uses a recent modular development framework for blockchains, called Scorex. It allows us to change only certain parts of an application leaving other codebase intact.

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Ben, Alaya Mahdi. "Towards interoperability, self-management, and scalability for scalability for machine-to-machine systems." Thesis, Toulouse, INSA, 2015. http://www.theses.fr/2015ISAT0052/document.

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La communication Machine-to-Machine (M2M) est l'un des principaux fondements de l'Internet des Objets (IoT). C'est un phénomène qui a évolué discrètement au cours du temps et vient d’émerger à la surface pour do! nner naissance à une explosion de nouveaux usages et services. Capteurs, actionneurs, tags, véhicules et objets intelligents ont tous la possibilité de communiquer. Le nombre de connexions M2M est en constante augmentation et il est prévu de voir des milliards d’objets connectés dans un futur proche. Les applications M2M offrent des avantages dans divers domaines à savoir les villes intelligentes, les voitures connectées, les usines du futures, l’agriculture de précision, l’environnement, la santé, etc. La croissance rapide de cet écosystème est entrain de conduire le M2M vers un avenir prometteur. Cependant, les opportunités d'expansion des marchés M2M ne sont pas évidentes. En effet, un ensemble de challenges doivent être surmontés afin de permettre un déploiement à grande échelle dans des domaines diverses et variés à savoir les défis d’interopérabilité, de complexité et de scalabilité. Actuellement, le marché du M2M souffre d'une fragmentation verticale importante touchant la majorité des domaines industriels. En effet, diverses solutions propriétaires ont été conçues pour répondre à des applications spécifiques engendrant ainsi un sérieux problème d''interopérabilité. Pour adresser ce challenge, nous avons conçu, développer et expérimenté la plateforme OM2M offrant une architecture opérationnelle, flexible et extensible pour l'interopérabilité M2M conforme à la norme SmartM2M. Pour supporter les environnements contraints, nous avons proposé une nouvelle convention de nommage basée sur une structure de ressources non-hiérarchique permettant d’optimiser la taille des messages échangés. Pour assurer l’interopérabilité sémantique entre les applications et les machines, nous avons proposé l'ontologie IoT-O. Cette dernière est composée de cinq modèles de base représentant les capteurs, les actionneurs, les observations, les actuations et les web ! services pour permettre de converger rapidement vers un vocabulaire commun pour l'IoT. Une plateforme M2M horizontale permet d'interconnecter des machines hétérogènes largement distribués et qui évoluent fréquemment en fonction des changements de l’environnement. Maintenir ces systèmes complexes en vie est coûteux en termes de temps et d'argent. Pour adresser ce challenge, nous avons conçu, développé et intégré le framework FRAMESELF afin d'ajouter des capacités d'autogestion aux systèmes M2M basées sur le paradigme de l'informatique autonome. En étendant le modèle d'architecture de référence MAPE-K, notre solution permet d'adapter dynamiquement le comportement de la plateforme OM2M par en fonctions des changements du contexte et des politiques haut niveaux. Nous avons défini un ensemble de règles sémantiques pour faire du raisonnement sur l'ontologie IoT-O en tant que modèle de connaissance. Notre objectif est de permettre la découverte automatique entre les machines et les applications à travers un appariement sémantique et une reconfiguration dynam! ique de l'architecture des ressources. L’interopérabilité et l’autogestion ouvrent la voie à un déploiement de masse des systèmes M2M. Par contre, ces derniers se basent sur l'infrastructure actuelle d'internet qui n'a jamais été conçu pour ce genre de d'utilisation ce qui pose de nouvelles exigences en termes de scalabilité. Pour adresser ce challenge, nous avons conçu, simulé et validé l'approche OSCL proposant une nouvelle topologie de réseau maillé M2M comme alternative à l'approche centralisée actuelle. OSCL s'appuie sur les techniques de routage centrées sur l'information favorisant les communications à sauts multiples et un cache distribué pour une meilleure dissémination des données. Nous avons développé le simulateur OSCLsim pour valider l'approche proposée.[...]
Machine-to-Machine (M2M) is one of the main features of Internet of Things (IoT). It is a phenomenon that has been proceeding quietly in the background, and it is coming into the surface, where explosion of usage scenarios in businesses will happen. Sensors, actuators, tags, vehicles, and intelligent things all have the ability to communicate. The number of M2M connections is continuously increasing, and it has been predicted to see billions of machines interconnected in a near future. M2M applications provide advantages in various domains from smart cities, factories of the future, connected cars, home automation, e-health to precision agriculture. This fast-growing ecosystem is leading M2M towards a promising future. However, M2M market expansion opportunities are not straightforward. A set of challenges should be overcome to enable M2M mass-scale deployment across various industries including interoperability, complexity, and scalability issues. Currently, the M2M market is suffering from a high vertical fragmentation affecting the majority of business sectors. In fact, various vendor-specific M2M solutions have been designed independently for specific applications, which led to serious interoperability issues. To address this challenge, we designed, implemented, and experimented with the OM2M platform offering a flexible and extensible operational architecture for M2M interoperability compliant with the SmartM2M standard. To support constrained environments, we proposed an efficient naming convention relying on a non-hierarchical resource structure to reduce the payload size. To reduce the semantic gap between applications and machines, we proposed the IoT-O ontology for an effective semantic interoperability. IoT-O consists of five main parts, which are sensor, actuator, observation, actuation and service models and aims to quickly converge to a common IoT vocabulary. An interoperable M2M service platform enables one to interconnect heterogeneous devices that are widely distributed and frequently evolving according to their environment changes. Keeping M2M systems alive is costly in terms of time and money. To address this challenge, we designed, implemented, and integrated the FRAMESELF framework to retrofit self-management capabilities in M2M systems based on the autonomic computing paradigm. Extending the MAPE-K reference architecture model, FRAMESELF enables one to dynamically adapt the OM2M system behavior according to high level policies how the environment changes. We defined a set of semantic rules for reasoning about the IoT-O ontology as a knowledge model. Our goal is to enable automatic discovery of machines and applications through dynamic reconfiguration of resource architectures. Interoperability and self-management pave the way to mass-scale deployment of M2M devices. However, current M2M systems rely on current internet infrastructure, which was never designed to address such requirements, thus raising new requirements in term of scalability. To address this challenge, we designed, simulated and validated the OSCL overlay approach, a new M2M meshed network topology as an alternative to the current centralized approach. OSCL relies on the Named Data Networking (NDN) technique and supports multi-hop communication and distributed caching 5 to optimize networking and enhance data dissemination. We developed the OSCLsim simulator to validate the proposed approach. Finally, a theoretical model based on random graphs is formulated to describe the evolution and robustness of the proposed system

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Jenefeldt, Andreas, and Jakobsson Erik Foogel. "Scalability in Startups : A Case Study of How Technological Startup Companies Can Enhance Scalability." Thesis, Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-168150.

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Startups and new businesses are important for the development of technology, the economy, and the society as a whole. To be able to contribute towards this cause, startups need to be able to survive and grow. It is therefore important for startups to understand how they can scale up their business. This led to the purpose of this study: to determine success factors for technological startup companies to increase their scalability. Five areas were identified to have an impact on the scalability of a business, namely; partnerships, cloud computing, modularity, process automation and business model scalability. Within these areas, several subareas were found, which were certain areas of interest within the theory. Together, these subareas helped answer how companies can work with scalability in each area. These areas, and their subareas, went into an analytical model that formed the structure of the empirical and analytical parts of the study. The study is a multicase study, consisting of 15 B2B companies, of varying size and maturity, whom all offered software as a part of their solutions. The study concludes that there are six important factors for succeeding with scalability. An important factor to succeed with scalability is to adopt partnerships, since this will allow for outsourcing, and give access to resources, markets and customers. It is also concluded that cloud computing is a very scalable delivery method, but that it requires certain success factors, such as working with partners, having a customer focus, having the right knowledge internally, and having a standardized product. Further, modularity can enable companies to meet differing customer needs since it increases flexibility, can expand the offer, and make sales easier. The study concludes that process automation increases the efficiency in the company, and can be done through automating a number of processes. Focusing both internally and externally is another important factor for success, by allowing companies to develop a scalable product that is demanded by customers. Lastly, a scalable business model is found to be the final objective, and that it is important to work with the other areas to get there, something that includes trial and error to find what works best for each individual company. The six important factors formed the basis for the recommendations. The study recommend that startups should utilize partnerships and process automation. Startups should also be aware of, and work with, the success factors of cloud computing, use modularity when selling to markets with different customer needs, automate other processes before automating sales, keep customer focus when developing the product, and work actively to become more scalable.

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Krishna, Chaitanya Konduru. "Scalability Drivers in Requirements Engineering." Thesis, Blekinge Tekniska Högskola, Institutionen för programvaruteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13480.

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Mir, Taheri Seyed M. "Scalability of communicators in MPI." Thesis, University of British Columbia, 2011. http://hdl.handle.net/2429/33128.

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This thesis offers a novel framework for representing groups and communicators in Message Passing Interface (MPI) middleware. MPI is a widely used paradigm in a cluster environment that supports communication between the nodes. In our framework, we have implemented and evaluated scalable techniques for groups and communicators in MPI. We have tested this framework using FG-MPI, a fine-grain version of MPI that scales millions of MPI processes. Groups in MPI are the primary means for creating communicators. A group map is the underlying structure that stores participating processes in the communication. We introduce a framework for concise representations of the group map. This framework is based on the observation that a map can be decomposed into a set and a permutation. This decomposition allows us to use a compact set representation for the cases where specific mapping is not required i.e. lists with monotonically increasing order. In other cases, the representation adds a permutation as well. A variety of set compression techniques has been used. Furthermore, the framework is open to integration of new representations. One advantage of such decomposition is the ability to implicitly represent a set with set representations such as BDD. BDD and similar representations are well-suited for the types of operations used in construction of communicators. In addition to set representations for unordered maps, we incorporated Wavelet Trees on Runs. This library is designed to represent permutation. We have also included general compression techniques in the framework such as BWT. This allows some degree of compression in memory-constrained environments where there is no discernible pattern in the group structure. We have investigated time and space trade-offs among the representations to develop strategies available to the framework. The strategies tune the framework based on user's requirements. The first strategy optimizes the framework to be fast and is called the time strategy. The second strategy optimizes the framework in regard to space. The final hybrid strategy is a hybrid of both and tries to strike a reasonable trade-off between time and space. These strategies let the framework accommodate a wider range of applications and users.

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Hao, Fang. "Scalability techniques in QoS networks." Diss., Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/9175.

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Wen, Yang Ph D. Massachusetts Institute of Technology. "Scalability of dynamic traffic assignment." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/47739.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2009.
Includes bibliographical references (p. 163-174).
This research develops a systematic approach to analyze the computational performance of Dynamic Traffic Assignment (DTA) models and provides solution techniques to improve their scalability for on-line applications for large-scale networks. DTA models for real-time use provide short-term predictions of network status and generate route guidance for travelers. The computational performance of such systems is a critical concern. Existing methodologies, which have limited capabilities for online large-scale applications, use single-processor configurations that are less scalable, and rely primarily on trade-offs that sacrifice accuracy for improved computational efficiency. In the proposed scalable methodology, algorithmic analyses are first used to identify the system bottlenecks for large-scale problems. Our analyses show that the computation time of DTA systems for a given time interval depends largely on a small set of parameters. Important parameters include the number of origin-destination (OD) pairs, the number of sensors, the number of vehicles, the size of the network, and the number of time-steps used by the simulator. Then scalable approaches are developed to solve the bottlenecks. A constraint generalized least-squares solution enabling efficient use of the sparse-matrix property is applied to the dynamic OD estimation, replacing the Kalman-Filter solution or other full-matrix algorithms. Parallel simulation with an adaptive network decomposition framework is proposed to achieve better load-balancing and improved efficiency. A synchronization-feedback mechanism is designed to ensure the consistency of traffic dynamics across processors while keeping communication overheads minimal. The proposed methodology is implemented in DynaMIT, a state-of-the-art DTA system. Profiling studies are used to validate the algorithmic analysis of the system bottlenecks.
(cont.) The new system is evaluated on two real-world networks under various scenarios. Empirical results of the case studies show that the proposed OD estimation algorithm is insensitive to an increase in the number of OD pairs or sensors, and the computation time is reduced from minutes to a few seconds. The parallel simulation is found to maintain accurate output as compared to the sequential simulation, and with adaptive load-balancing, it considerably speeds up the network models even under non-recurrent incident scenarios. The results demonstrate the practical nature of the methodology and its scalability to large-scale real-world problems.
by Yang Wen.
Ph.D.

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Persson, Jonna. "SCALABILITY OF JAVASCRIPTLIBRARIES FOR DATAVISUALIZATION." Thesis, Högskolan i Skövde, Institutionen för ingenjörsvetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-19994.

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Visualization is an important tool for making data understandable. Visualization can be used for many different purposes, such as charts on the web used to visualize a dataset. Render time is important for websites since slow response times can cause users to leave the site. When creating a website with fast render times in mind, the selection of JavaScript library may be crucial. This work aims to determine if dataset size and/or chart type affects the render time of charts created by different JavaScript libraries. The comparison is done by a literature search to identify suitable libraries, followed by an experiment in which 40 websites are created to compare the performance of selected JavaScript libraries for rendering selected chart types. The results show that while both dataset size and chart type affect the render time in most cases, the libraries scale differently depending on the dataset size.

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Книги з теми "Scalability"

Dhall, Chander. Scalability Patterns. Berkeley, CA: Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-1073-4.

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Zheng, Zibin, Wuhui Chen, and Huawei Huang, eds. Blockchain Scalability. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1059-5.

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Liu, Henry H. Software Performance and Scalability. New York: John Wiley & Sons, Ltd., 2009.

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Bulka, Dov. Java performance and scalability. Reading, Mass: Addison-Wesley, 2000.

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Lanning, Kevin. Consistency, Scalability, and Personality Measurement. New York, NY: Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4612-3072-4.

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Sadre, Ramin, and Aiko Pras, eds. Scalability of Networks and Services. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02627-0.

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Acetozi, Jorge. Pro Java Clustering and Scalability. Berkeley, CA: Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2985-9.

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Paliouras, Georgios. Scalability of machine learning algorithms. Manchester: University of Manchester, 1993.

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Lanning, Kevin Dorsey. Consistency, scalability, and personality measurement. New York: Springer-Verlag, 1991.

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Lanning, Kevin Dorsey. Consistency, scalability, and personality measurement. New York: Springer-Verlag, 1991.

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Частини книг з теми "Scalability"

Palladino, Santiago. "Scalability." In Ethereum for Web Developers, 275–319. Berkeley, CA: Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-5278-9_8.

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Wu, Xingfu. "Scalability." In Performance Evaluation, Prediction and Visualization of Parallel Systems, 65–101. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-5147-8_3.

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Strauss, Rebecca, Austin Volz, and William Lidwell. "Scalability." In The Elements of Education for Curriculum Designers, 78–79. New York: Routledge, 2022. http://dx.doi.org/10.4324/9780429321283-39.

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Weik, Martin H. "scalability." In Computer Science and Communications Dictionary, 1517. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_16622.

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Dongarra, Jack, Piotr Luszczek, Felix Wolf, Jesper Larsson Träff, Patrice Quinton, Hermann Hellwagner, Martin Fränzle, et al. "Scalability." In Encyclopedia of Parallel Computing, 1773. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-09766-4_2046.

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Taylor, Ian J., and Andrew B. Harrison. "Scalability." In From P2P and Grids to Services on the Web, 197–211. London: Springer London, 2009. http://dx.doi.org/10.1007/978-1-84800-123-7_11.

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Stephens, Matt, and Doug Rosenberg. "Scalability." In Extreme Programming Refactored: The Case Against XP, 313–35. Berkeley, CA: Apress, 2003. http://dx.doi.org/10.1007/978-1-4302-0810-5_14.

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Kale, Vivek. "Scalability." In Digital Transformation of Enterprise Architecture, 169–87. Boca Raton, Florida : CRC Press, [2020]: CRC Press, 2019. http://dx.doi.org/10.1201/9781351029148-10.

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Williams, Michael J. "Scalability." In Preventing and Countering Violent Extremism, 81–84. Abingdon, Oxon; New York, NY: Routledge, 2021. | Series: Political violence: Routledge, 2020. http://dx.doi.org/10.4324/9780429441738-14.

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Slama, Dirk. "Scalability." In The Digital Playbook, 103–15. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-88221-1_11.

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Анотація:

AbstractThe ultimate goal of the business strategy is to ensure that the business can be scaled up to the level that matches the business objectives. This is usually a step-by-step process, involving exploration, acquiring early adopters, and then continuously growing the business. Which of the methods that have worked for successfully scaling purely digital businesses can be adopted by AIoT-enabled businesses? What are the pitfalls of scaling up a digital/physical business? (Fig. 11.1).

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Тези доповідей конференцій з теми "Scalability"

Timmerman, Benoit, Peter Amon, Andreas Hutter, and Francois-Xavier Coudoux. "Motion information scalability for SNR scalability." In Visual Communications and Image Processing 2005. SPIE, 2005. http://dx.doi.org/10.1117/12.631417.

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Leesatapornwongsa, Tanakorn, Cesar A. Stuardo, Riza O. Suminto, Huan Ke, Jeffrey F. Lukman, and Haryadi S. Gunawi. "Scalability Bugs." In HotOS '17: Workshop on Hot Topics in Operating Systems. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3102980.3102985.

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Heyman, Thomas, Davy Preuveneers, and Wouter Joosen. "Scalar: Systematic Scalability Analysis with the Universal Scalability Law." In 2014 2nd International Conference on Future Internet of Things and Cloud (FiCloud). IEEE, 2014. http://dx.doi.org/10.1109/ficloud.2014.88.

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Chauhan, Anamika, Om Prakash Malviya, Madhav Verma, and Tejinder Singh Mor. "Blockchain and Scalability." In 2018 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C). IEEE, 2018. http://dx.doi.org/10.1109/qrs-c.2018.00034.

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Rosenblum, David S. "Software system scalability." In Proceeding of the 2nd annual conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1506216.1506217.

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Dumitru, Alex Mircea, Vlad Merticariu, and Peter Baumann. "Array Database Scalability." In SSDBM '16: Conference on Scientific and Statistical Database Management. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2949689.2949717.

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Caprarescu, Bogdan Alexandru. "Robustness and scalability." In the Fourth European Conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1842752.1842759.

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Brataas, Gunnar, and Peter Hughes. "Exploring architectural scalability." In the fourth international workshop. New York, New York, USA: ACM Press, 2004. http://dx.doi.org/10.1145/974044.974064.

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Ye, Fangdan, Da Yu, Ennan Zhai, Hongqiang Harry Liu, Bingchuan Tian, Qiaobo Ye, Chunsheng Wang, et al. "Accuracy, Scalability, Coverage." In SIGCOMM '20: Annual conference of the ACM Special Interest Group on Data Communication on the applications, technologies, architectures, and protocols for computer communication. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3387514.3406217.

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Hasselbring, Wilhelm. "Microservices for Scalability." In ICPE'16: ACM/SPEC International Conference on Performance Engineering. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2851553.2858659.

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Звіти організацій з теми "Scalability"

Pressel, Daniel M. Scalability vs. Performance. Fort Belvoir, VA: Defense Technical Information Center, September 2001. http://dx.doi.org/10.21236/ada396665.

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Weinstock, Charles B., and John B. Goodenough. On System Scalability. Fort Belvoir, VA: Defense Technical Information Center, March 2006. http://dx.doi.org/10.21236/ada457003.

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Clay, Robert L., and Max S. Shneider. iSIGHT-FD scalability test report. Office of Scientific and Technical Information (OSTI), July 2008. http://dx.doi.org/10.2172/973656.

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Pressel, Daniel M. The Scalability of Loop-Level Parallelism. Fort Belvoir, VA: Defense Technical Information Center, August 2001. http://dx.doi.org/10.21236/ada395393.

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Pascucci, V. ViSUS: Visualization Streams for Ultimate Scalability. Office of Scientific and Technical Information (OSTI), February 2005. http://dx.doi.org/10.2172/15014677.

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Pascucci, V. ViSUS: Visualization Streams for Ultimate Scalability. Office of Scientific and Technical Information (OSTI), February 2005. http://dx.doi.org/10.2172/918411.

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Lipari, D., and M. Jette. Purple Milestone Report System Software and Scalability. Office of Scientific and Technical Information (OSTI), December 2006. http://dx.doi.org/10.2172/896604.

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Tkac, Peter, David Rotsch, Kevin Quigley, and George Vandegrift. SCALABILITY OF THE LEU-MODIFIED CINTICHEM PROCESS. Office of Scientific and Technical Information (OSTI), October 2014. http://dx.doi.org/10.2172/1165454.

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Nookala, Munichandraiah. Lithium-Air Battery: Study of Rechargeability and Scalability. Fort Belvoir, VA: Defense Technical Information Center, July 2012. http://dx.doi.org/10.21236/ada564754.

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Sweeney, John D., Huan Li, Roderic A. Grupen, and Krithi Ramamritham. Scalability and Schedulability in Large, Coordinated, Distributed Robot Systems. Fort Belvoir, VA: Defense Technical Information Center, January 2005. http://dx.doi.org/10.21236/ada438795.

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