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Relevant bibliographies by topics / Multi-tenant patterns

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Academic literature on the topic 'Multi-tenant patterns'

Author: Grafiati

Published: 4 June 2021

Last updated: 13 February 2022

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Journal articles on the topic "Multi-tenant patterns"

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Meheden, Maria, Andrei Musat, Andrei Traciu, Andrei Viziteu, Adrian Onu, Constantin Filote, and Maria Simona Răboacă. "Design Patterns and Electric Vehicle Charging Software." Applied Sciences 11, no. 1 (December 25, 2020): 140. http://dx.doi.org/10.3390/app11010140.

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The development and maintenance of complex software systems, with ever-changing requirements has benefited from the implementation of design patterns, which ensure a higher degree of maintainability. The present article illustrates the essential role of design patterns in sketching the software architecture for an electric vehicle charging management platform. We have integrated a series of design patterns to create a solid base structure for the API (Application Programming Interface). Furthermore, we have explored cloud design patterns in the deployment process to ensure a proper multi-tenant cloud application with the best possible tenant isolation for the cost. The aim of this paper is to offer readers an introduction in the case study theme, to describe a complex platform development through design patterns. With proper examples from real projects debated in the industry. The paper demonstrates the design patterns applicability from software level to cloud resources plan and advocates for a high-quality solution in every segment of project development. In conclusion, the results are promising, and the functionality of the established methods on this type of platforms will be evaluated during the implementation period. Overall, design patterns have proven to be essential in the development process, ensuring effective team communication and the delivery of qualitative software solutions.

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Kazhmaganbetova, Zarina, Shnar Imangaliyev, and Altynbek Sharipbay. "Machine Learning for the Communication Optimization in Distributed Systems." International Journal of Engineering & Technology 7, no. 4.1 (September 12, 2018): 47. http://dx.doi.org/10.14419/ijet.v7i4.1.19491.

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The objective of the work that is presented in this paper was the problem of the communication optimization and detection of the issues of computing resources performance degradation [1, 2] with the usage of machine learning techniques. Computer networks transmit payload data and the meta-data from numerous sources towards vast number of destinations, especially in multi-tenant environments [3, 4]. Meta data describes the payload data and could be analyzed for anomalies detection in the communication patterns. Communication patterns depend on the payload itself and technical protocol used. The technical patterns are the research target as their analysis could spotlight the vulnerable behavior, for example: unusual traffic, extra load transported and etc.There was a big data used to train model with a supervised machine learning. Dataset was collected from the network interfaces of the distributed application infrastructure. Machine Learning tools had been retained from the cloud services provider – Amazon Web Services. The stochastic gradient descent technique was utilized for the model training, so that it could represent the communication patterns in the system. The learning target parameter was a packet length, the regression was performed to understand the relationship between packet meta-data (timestamp, protocol, the source server) and its length. The root mean square error calculation was applied to evaluate the learning efficiency. After model was prepared using training dataset, the model was tested with the test dataset and then applied on the target dataset (dataset for prediction) to check whether it was capable to detect anomalies.The experimental part showed the applicability of machine learning for the communication optimization in the distributed application environment. By means of the trained artificial intelligence model, it was possible to predict target parameters of traffic and computing resources usage with purpose to avoid service degradation. Additionally, one could reveal anomalies in the transferred traffic between application components. The application of techniques is envisioned in information security field and in the field of efficient network resources planning.Further research could be in application machine learning techniques for more complicated distributed environments and enlarging the number of protocols to prepare communication patterns.

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Granath Hansson, Anna, Peter Ekbäck, and Jenny Paulsson. "The Sliding Scale between Usufruct and Ownership: The Example of Swedish Multi-Family Housing." Land 10, no. 3 (March 18, 2021): 311. http://dx.doi.org/10.3390/land10030311.

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This paper aims to elucidate the sliding scale between usufruct and ownership by applying a property rights framework to three Swedish forms of tenure in multifamily housing. The framework deconstructs the bundles of rights of rental, tenant-ownership and ownership to highlight commonalities and differences connected to the right to use and exclude, the right to transfer and the right to the value. It is concluded that the three tenure forms have many traits in common but that there are distinct differences in some areas, most notably in connection to the right to the value. The property rights framework applied in the study may be applicable also on a general level as a method to analyze and compare tenures of different types in different countries. Further, ways to improve the framework and cover more facets of outcomes of property rights patterns are suggested.

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Renugha, K., P. Shanthi, and A. Umamakeswari. "Multi-Keyword Ranked Search in Cloud Storage using Homomorphic Indexing." International Journal of Engineering & Technology 7, no. 2.24 (April 25, 2018): 243. http://dx.doi.org/10.14419/ijet.v7i2.24.12057.

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In the cloud environment, the main issue is outsourcing of the information to the cloud service provider and outsider. Consider this, the cloud tenant store data in an encrypted form to achieve data security and privacy. The data owner needs the secure information sharing from the cloud and without leak of access pattern to the eavesdroppers. XOR homomorphic encryption searchable algorithm along with ranking is proposed to provide the security over the network. In addition our scheme provides secure Multi-keyword ranked search over encrypted data. Efficient ranked search algorithm returns the relevant document based on the results for the given multiple keywords. The experimental results prove that the system is efficient.

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Derdus, Kenga Mosoti, Vincent Oteke Omwenga, and Patrick Job Ogao. "Energy-Aware Virtual Machine Clustering for Consolidation in Multi-tenant IaaS Public Clouds." International Journal of Scientific Research in Computer Science, Engineering and Information Technology, April 1, 2019, 1123–36. http://dx.doi.org/10.32628/cseit1952309.

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Cloud computing has gained a lot of interest from both small and big academic and commercial organizations because of its success in delivering service on a pay-as-you-go basis. Moreover, many users (organizations) can share server computing resources, which is made possible by virtualization. However, the amount of energy consumed by cloud data centres is a major concern. One of the major causes of energy wastage is the inefficient utilization of resources. For instance, in IaaS public clouds, users select Virtual Machine (VM) sizes set beforehand by the Cloud Service Providers (CSPs) without the knowledge of the kind of workloads to be executed in the VM. More often, the users overprovision the resources, which go to waste. Additionally, the CSPs do not have control over the types of applications that are executed and thus VM consolidation is performed blindly. There have been efforts to address the problem of energy consumption by efficient resource utilization through VM allocation and migration. However, these techniques lack collection and analysis of active real cloud traces from the IaaS cloud. This paper proposes an architecture for VM consolidation through VM profiling and analysis of VM resource usage and resource usage patterns, and a VM allocation policy. We have implemented our policy on CloudSim Plus cloud simulator and results show that it outperforms Worst Fit, Best Fit and First Fit VM allocation algorithms. Energy consumption is reduced through efficient consolidation that is informed by VM resource consumption.

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Dissertations / Theses on the topic "Multi-tenant patterns"

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Nikola, Dalčeković. "Platforma za transformaciju softverskih rešenja pametnih elektroenergetskih mreža na cloud bazirani višeorganizacijski SaaS." Phd thesis, Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, 2019. https://www.cris.uns.ac.rs/record.jsf?recordId=110701&source=NDLTD&language=en.

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Sve češćom upotrebom cloud okruženja dolazi do potrebe da se postojeća softverska rešenja migriraju. Metodologija za migraciju na cloud postoji više, gde se u finalnim fazama planiraju modifikacije nad arhitekturom softvera tako da se iskoriste prednosti cloud sistema. Za ekonomsku efikasnost usled uštede resursa je neophodna višeorganizacijska osobina. Svrha ovog istraživanja je da pojasni višeorganizacijsko svojstvo i da predloži rešenje za migraciju postojećih softvera na višeorganizacijski SaaS ali sa što manje neophodnih modifikacija ciljnog softvera. S toga je predloženo rešenje platforma koja omogućuje lakšu migraciju. Nakon faze istraživanja i sagledavanja domena pametnih elektroenergetskih mreža, kreiran je prototip predloženog rešenja kao i niz eksperimenata u skladu sa definisanim naučnim pitanjima. Eksperimenti su izvršeni u privatnom cloud okruženju. Hipoteze su adresirane kroz viziju primene rešenja na NDMS (Napredni distributivni menadžment sistem) u slučaju šest organizacija, a doneti su sledeći zaključci: višeorganizacijskim modelom se ostvaruju uštede u resursima od 32%, za tri reda veličine veća visoka dostupnost, ali uz usporenja do 20 milisekundi po svakom servisnom zahtevu. Takođe, aplikativni model učesnika modernih PaaS usluga nije primeren gde je sinhronizam zahtevan, niti u slučajevima gde se očekuju odgovori nad skupom učesnika u realnom vremenu. Istraživanje ukazuje na mogućnost primene višeorganizacijskog modela čak i u slučaju kompleksnih rešenja kakva se sreću u domenu pametnih elektroenergetskih mreža, a akademskom validacijom potvrđuju način implementacije važnog finalnog koraka u procesu migracije softvera na cloud bazirani SaaS.
Progressive cloud adoption requires migration of existing software solutions. Today, many cloud adoption methodologies exist. Usually, the final phase in cloud adoption include software architecture modifications to make the most of the benefits of cloud computing, like multi-tenancy which enables economic efficiency. The aim of this research is to explain the multi-tenancy and to provide a solution for migration of existing software to multi-tenant SaaS while modifying the target software as little as possible. Therefore, the research proposes a platform that enables easier cloud adoption. After the research phase focused on a smart grid domain, the prototype was created with experiments targeting formulated research questions. The experiments were conducted in a private cloud environment. Research hypotheses were analyzed using hypothetical multi-tenant ADMS (Advanced Distribution Management System) in case of six tenants, with the following conclusions: multi-tenancy saves 32% of resources, it provides three orders of magnitude higher availability, but affects performances by introducing a delay of up to 20 milliseconds per service request. Also, reliable actors programing model used in modern PaaS services is not suitable in use cases with needs for synchronous behavior, nor in in use cases where querying a set of actors is needed in real time. The research demonstrates feasibility of applying multi-tenancy even in cases of complex software solutions like the ones in the smart grid domain. The proposed solution is academically validated and it can be used as a final important step in migration of existing software to cloud based multi-tenant SaaS.

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Books on the topic "Multi-tenant patterns"

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Betts, Dominic, Masashi Narumoto, Hanzhong Zhang, Alejandro Jezierski, and Alex Homer. Developing Multi-tenant Applications for the Cloud on Windows Azure (Microsoft patterns & practices). Microsoft patterns & practices, 2013.

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Book chapters on the topic "Multi-tenant patterns"

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Kabbedijk, Jaap, and Slinger Jansen. "Variability in Multi-tenant Environments: Architectural Design Patterns from Industry." In Advances in Conceptual Modeling. Recent Developments and New Directions, 151–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24574-9_20.

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Birke, Robert, Lydia Chen, and Evgenia Smirni. "Usage Patterns in Multi-tenant Data Centers: a Large-Case Field Study." In Handbook on Data Centers, 1257–66. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2092-1_43.

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Kuriata, Andrzej, and Ramesh G. Illikkal. "Predictable Performance for QoS-Sensitive, Scalable, Multi-tenant Function-as-a-Service Deployments." In Agile Processes in Software Engineering and Extreme Programming – Workshops, 133–40. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58858-8_14.

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Abstract In this paper we present the results of our studies focused on enabling predictable performance for functions executing in scalable, multi-tenant Function-as-a-Service environments. We start by analyzing QoS and performance requirements and use cases from the point of view of End-Users, Developers and Infrastructure Owners. Then we take a closer look at functions’ resource utilization patterns and investigate functions’ sensitivity to those resources. We specifically focus on the CPU microarchitecture resources as they have significant impact on functions’ overall performance. As part of our studies we have conducted experiments to research the effect of co-locating different functions on the compute nodes. We discuss the results and provide an overview of how we have further modified the scheduling logic of our containers orchestrator (Kubernetes), and how that impacted functions’ execution times and performance variation. We have specifically leveraged the low-level telemetry data, mostly exposed by the Intel® Resource Director Technology (Intel® RDT) [1]. Finally, we provide an overview of our future studies, which will be centered around node-level resource allocations, further improving a function’s performance, and conclude with key takeaways.

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Balasubramanian, Nagarajan, and Suguna Jayapal. "Enhanced Scaffold Design Pattern for Seculde Multi-tenant SaaS Application." In Advances in Intelligent Systems and Computing, 671–80. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2471-9_65.

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Conference papers on the topic "Multi-tenant patterns"

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Birke, Robert, Lydia Y. Chen, and Evgenia Smirni. "Usage patterns in multi-tenant data centers." In the 9th international conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2371536.2371565.

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Kalra, Sumit, and T. V. Prabhakar. "Patterns for Managing Tenants in a Multi-tenant Application." In EuroPLoP '17: European Conference on Pattern Languages of Programs. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3147704.3147722.

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Kabbedijk, J., and S. Jansen. "The role of variability patterns in multi-tenant business software." In the WICSA/ECSA 2012 Companion Volume. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2361999.2362029.

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Abdul, Adeniyi O., Julian M. Bass, Hossein Ghavimi, and Peter Adam. "A performance evaluation of multi-tenant data tier design patterns in a containerized environment." In 2017 International Conference on Information Society (i-Society). IEEE, 2017. http://dx.doi.org/10.23919/i-society.2017.8354684.

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Wang, Zhi Hu, Chang Jie Guo, Bo Gao, Wei Sun, Zhen Zhang, and Wen Hao An. "A Study and Performance Evaluation of the Multi-Tenant Data Tier Design Patterns for Service Oriented Computing." In 2008 IEEE International Conference on e-Business Engineering. IEEE, 2008. http://dx.doi.org/10.1109/icebe.2008.60.

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"Hierarchical multi-tenant pattern." In 2014 International Conference on Computing, Management and Telecommunications (ComManTel). IEEE, 2014. http://dx.doi.org/10.1109/commantel.2014.6825597.

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Bien, Ngo Huy, and Tran Dan Thu. "Multi-tenant web application framework architecture pattern." In 2015 2nd National Foundation for Science and Technology Development Conference on Information and Computer Science (NICS). IEEE, 2015. http://dx.doi.org/10.1109/nics.2015.7302219.

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Grund, Martin, Matthieu Schapranow, Jens Krueger, Jan Schaffner, and Anja Bog. "Shared Table Access Pattern Analysis for Multi-Tenant Applications." In 2008 IEEE Symposium on Advanced Management of Information for Globalized Enterprises, AMIGE. IEEE, 2008. http://dx.doi.org/10.1109/amige.2008.ecp.37.

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Sellami, Wael, Hatem Hadj Kacem, and Ahmed Hadj Kacem. "Elastic Multi-tenant Business Process Based Service Pattern in Cloud Computing." In 2014 IEEE 6th International Conference on Cloud Computing Technology and Science (CloudCom). IEEE, 2014. http://dx.doi.org/10.1109/cloudcom.2014.151.

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