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Добірка наукової літератури з теми "Load balancing in SDN"

Автор: Grafiati
Опубліковано: 30 травня 2022
Оновлено: 31 травня 2022

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Статті в журналах з теми "Load balancing in SDN"

1

Sufiev, Hadar, Yoram Haddad, Leonid Barenboim, and José Soler. "Dynamic SDN Controller Load Balancing." Future Internet 11, no. 3 (March 21, 2019): 75. http://dx.doi.org/10.3390/fi11030075.

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Анотація:
The software defined networking (SDN) paradigm separates the control plane from the data plane, where an SDN controller receives requests from its connected switches and manages the operation of the switches under its control. Reassignments between switches and their controllers are performed dynamically, in order to balance the load over SDN controllers. In order to perform load balancing, most dynamic assignment solutions use a central element to gather information requests for reassignment of switches. Increasing the number of controllers causes a scalability problem, when one super controller is used for all controllers and gathers information from all switches. In a large network, the distances between the controllers is sometimes a constraint for assigning them switches. In this paper, a new approach is presented to solve the well-known load balancing problem in the SDN control plane. This approach implies less load on the central element and meeting the maximum distance constraint allowed between controllers. An architecture with two levels of load balancing is defined. At the top level, the main component called Super Controller, arranges the controllers in clusters, so that there is a balance between the loads of the clusters. At the bottom level, in each cluster there is a dedicated controller called Master Controller, which performs a reassignment of the switches in order to balance the loads between the controllers. We provide a two-phase algorithm, called Dynamic Controllers Clustering algorithm, for the top level of load balancing operation. The load balancing operation takes place at regular intervals. The length of the cycle in which the operation is performed can be shorter, since the top-level operation can run independently of the bottom level operation. Shortening cycle time allows for more accurate results of load balancing. Theoretical analysis demonstrates that our algorithm provides a near-optimal solution. Simulation results show that our dynamic clustering improves fixed clustering by a multiplicative factor of 5.
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2

Perepelkin, D. A., and V. T. Nguyen. "RESEARCH OF LOAD BALANCING PROCESSES IN SOFTWARE-DEFINED NETWORKS BASED ON GENETIC ALGORITHM." Vestnik of Ryazan State Radio Engineering University 77 (2021): 43–57. http://dx.doi.org/10.21667/1995-4565-2021-77-43-57.

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Анотація:
As a new network paradigm, software-defined networks (SDN) are able to cope with the limitations of traditional networks. SDNs use a management controller with a global view of the network and switching devices that act as packet forwarding equipment, known as «OpenFlow switches». Network resources limitations and ensuring quality of service requirements lead to an important need for load balancing between SDN switches. The purpose of work  research and analysis of load balancing processes in SDN based on genetic algorithm. To confirm the effectiveness and correctness of the genetic algorithm in SDN, the software for modeling the load balancing processes has been developed. The simulation results confirmed the efficiency of the genetic algorithm in SDN for balancing and redistributing network traffic in order to ensure the required quality of service and reduce network congestion.
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3

Babbar, Himanshi, and Shalli Rani. "Emerging Prospects and Trends in Software Defined Networking." Journal of Computational and Theoretical Nanoscience 16, no. 10 (October 1, 2019): 4236–41. http://dx.doi.org/10.1166/jctn.2019.8506.

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Анотація:
In today’s era Software Defined Networking (SDN) has accumulated popularity in both the Industry and Academia. SDN is massively facilitated by different sectors, there is an abundant amount of work going on in the studies where SDN is required. Improving the load balancing in SDN plays an important role in solving the problem in the specific domain. Since 2009, publications in this field are getting doubled approximately, it takes a short time for bibliometric analysis. This paper facilitates the comprehensive survey on “SDN Load Balancing” for the fixed frame of timeline. 530 publications related to the Load Balancing in SDN were scrutinized based on the database of Scopus. This paper investigated the publications of research on multiple parameters: 1. Publishing patterns e.g., Authors and affiliations 2. Keywords to examine the specific domain 3. Analysis of keywords 4. Citation patterns 5. Several publications. Lastly, it examines the survey of literature based on the quantifiable structures of SDN load balancing on several perspectives. The suggested analytical study will act as an influential instrument for substantial discussion of impending research schemes.
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4

Wahanani, Henni Endah, Mohammad Idhom, and Eka Prakarsa Mandyartha. "LOAD BALANCING TOPOLOGI BIPARTITE PADA JARINGAN SDN." Prosiding Seminar Nasional Informatika Bela Negara 2 (November 25, 2021): 7–10. http://dx.doi.org/10.33005/santika.v2i0.77.

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Анотація:
Layanan teknologi telah berkembang dengan keandalan yang tinggi, oleh karena itu diperlukan sebuah konsep sistem kendali terpusat untuk mengatur perangkat jaringan pada sebuah infrastruktur jaringan yang disebut SDN (Software Defined Network), dengan memisahkan antara sistem kontrol (control plane) dan sistem forwarding (data plane). Pengontrol dapat memberikan kontrol terpusat dengan menginstal aturan penerusan dalam bidang data, dan switch melakukan operasi yang berbeda pada paket sesuai dengan aturan ini. Cara komunikasi antara perangkat dan controller menggunakan sebuah protokol yang disebut dengan Openflow. Untuk mendukung SDN diperlukannya sebuah metode untuk mendistribusikan trafik jaringan komputer secara seimbang agar trafik jaringan komputer berjalan secara maksimal, metode itu adalah load balancing. Dalam penelitian ini melakukan ujicoba load balancing topologi bipartite di ujicoba pada 3 paket yaitu UDP Flow, DNS, dan Telnet dengan parameter yang diuji adalah delay dan packet rate dengan mengirimkan 1000 paket dengan ukuran setiap paket 100Kb selama 60s dengan background trafik setiap link 100 Mbit/s. Hasil dari pengujian delay yang terkecil terdapat pada paket DNS topologi 1 dengan 11,382 ms, dan packet rate terbesar pada paket telnet dengan 92,02 pkt/s.
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5

Shrivastava, Gourav, Praveen Kaushik, and R. K.Pateriya. "Load balancing strategies in software defined networks." International Journal of Engineering & Technology 7, no. 3 (August 22, 2018): 1854. http://dx.doi.org/10.14419/ijet.v7i3.14017.

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Анотація:
In the past few years, network requirements have been changing frequently as the amount of data traffic increasing exponentially so it is difficult to utilize the full capacity of network resources. Software Defined Networking (SDN) is emerging as a new networking technology which decouples the control plane from the data plane in the network devices. Separation of control and data plane allows a network administrator a better control over network management and also enables new development through network programmability. Presently Open-Flow is the most popular SDN protocol which provides communication between network devices and controller. In this paper, the Round Robin algorithm is compared with the Dynamic load balancing algorithm using the OpenFlow protocol in SDN under varying load conditions of TCP and UDP traffic. Experimental analysis shows that the dynamic load balancing strategy works better than the Round Robin load balancing.
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6

Kaliuzhnyi, Oleksandr. "METHOD FOR ORGANIZING MULTIPATH ROUTING IN SDN NETWORKS." Scientific review, no. 7(60)2019 (January 10, 2019): 18–28. http://dx.doi.org/10.26886/scientificreview.2311-4517.7(60)2019.2.

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Анотація:
In this work we propose a method for organizing multipath routing for SDN networks. It have two main parts. The fisrt one is a routing method based on modified wave algorithm for finding paths, and second one is load balancing method based on ECMP algorithm. Combination of these methods can optimize using of network resources and provide a more optimal load balancing of network. The basis of routing algorithm is the search and use partially-overlapping routes. The basis of load balancing algorithm is equal distribution network load between all found routes. A comparative analysis with an existing algorithms for routing and load balancing was conducted and the advantages of this development are presented.
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7

Semong, Thabo, Thabiso Maupong, Stephen Anokye, Kefalotse Kehulakae, Setso Dimakatso, Gabanthone Boipelo, and Seth Sarefo. "Intelligent Load Balancing Techniques in Software Defined Networks: A Survey." Electronics 9, no. 7 (July 3, 2020): 1091. http://dx.doi.org/10.3390/electronics9071091.

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Анотація:
In the current technology driven era, the use of devices that connect to the internet has increased significantly. Consequently, there has been a significant increase in internet traffic. Some of the challenges that arise from the increased traffic include, but are not limited to, multiple clients on a single server (which can result in denial of service (DoS)), difficulty in network scalability, and poor service availability. One of the solutions proposed in literature, to mitigate these, is the use of multiple servers with a load balancer. Despite their common use, load balancers, have shown to have some disadvantages, like being vendor specific and non-programmable. To address these disadvantages and improve internet traffic, there has been a paradigm shift which resulted in the introduction of software defined networking (SDN). SDN allows for load balancers that are programmable and provides the flexibility for one to design and implement own load balancing strategies. In this survey, we highlight the key elements of SDN and OpenFlow technology and their effect on load balancing. We provide an overview of the various load balancing schemes in SDN. The overview is based on research challenges, existing solutions, and we give possible future research directions. A summary of emulators/mathematical tools commonly used in the design of intelligent load balancing SDN algorithms is provided. Finally, we outline the performance metrics used to evaluate the algorithms.
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8

Данешманд, Б., and Л. А. Ту. "STUDY AND REVIEW OF SDN-BASED LOAD BALANCING MECHANISMS IN 5G / IMT-2020." ВЕСТНИК ВОРОНЕЖСКОГО ГОСУДАРСТВЕННОГО ТЕХНИЧЕСКОГО УНИВЕРСИТЕТА, no. 1 (March 14, 2022): 102–11. http://dx.doi.org/10.36622/vstu.2022.18.1.012.

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Анотація:
Ожидается, что рост числа мобильных устройств и потребность в пользовательских данных к 2030 году окажут беспрецедентное давление на текущую мобильную сеть. У будущих мобильных сетей должно быть несколько требований в отношении объема данных, задержки, качества обслуживания и опыта, мобильности, спектра и энергоэффективности. Поэтому в последнее время начались усилия по созданию более эффективных решений для мобильных сетей. С этой целью балансировка нагрузки привлекла большое внимание как многообещающее решение для более эффективного использования ресурсов, повышения производительности системы и снижения эксплуатационных расходов. Это эффективный способ сбалансировать трафик и уменьшить перегрузку в гетерогенных сетях в будущих сетях 5G / IMT-2020. Балансировка нагрузки - одна из наиболее важных задач, необходимых для максимального повышения производительности, масштабируемости и надежности сети. В настоящее время с появлением программно-конфигурируемых сетей (SDN) балансировка нагрузки для SDN стала важной проблемой в будущей сети 5G / IMT-2020. SDN позволяет использовать программируемые балансировщики нагрузки и обеспечивает гибкость для разработки и реализации стратегий балансировки нагрузки. В этом обзоре мы выделяем методы балансировки нагрузки на основе сетей SDN и предполагаемые требования к балансировке нагрузки в сетях 5G The growing number of mobile devices and the demand for user data by 2030 are expected to put pressure on the current mobile network in an unprecedented way. Future mobile networks must have several requirements regarding data amount, latency, quality of service and experience, mobility, spectrum, and energy efficiency. Therefore, efforts have recently begun for more efficient mobile network solutions. To this end, load balancing has attracted much attention as a promising solution for greater resource utilization, improved system performance, and reduced operating costs. This is an effective way to balance traffic and reduce congestion in heterogeneous networks in future 5G/IMT-2020 networks. Load Balancing is one of the most critical tasks required to maximize network performance, scalability, and robustness. Nowadays, with the emergence of Software-Defined Networking (SDN), Load Balancing for SDN has become a significant issue in future network 5G/IMT-2020. SDN allows for programmable load balancers and provides the flexibility to design and implement load balancing strategies. In this survey, we highlight the methods of load balancing based on SDN networks and prospective load balancing requirements on 5G networks
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9

Chen, Junyan, Yong Wang, Xuefeng Huang, Xiaolan Xie, Hongmei Zhang, and Xiaoye Lu. "ALBLP: Adaptive Load-Balancing Architecture Based on Link-State Prediction in Software-Defined Networking." Wireless Communications and Mobile Computing 2022 (February 12, 2022): 1–16. http://dx.doi.org/10.1155/2022/8354150.

Повний текст джерела
Анотація:
Load-balancing optimization in software-defined networking (SDN) has been researched for a long time. Researchers have proposed many solutions to the load-balancing problem but have rarely considered the impact of transmission delay between controllers and switches under high-load network conditions. In this paper, we propose an adaptive load-balancing architecture based on link-state prediction (ALBLP) in SDN that can solve the influence of transmission delay between controllers and switches on network load balancing. ALBLP constructs the prediction model of the network link status, adopts the long-term and short-term memory neural network (LSTM) algorithm to predict the network link-state value, and then uses the predicted value as the Dijkstra weight to calculate the optimal path between network hosts. The proposed architecture can adaptively optimize network load balancing and avoid the empty window period, in which the switch flow table does not exist by actively issuing the flow table. Under the network architecture, we collect the data set of the network link-state by simulating the GÉANT network, and we verify the effectiveness of the proposed algorithm. The experiment results show that the ALBLP proposed in this paper can optimize load balancing in SDN and solve the problem of transmission delay between controllers and switches. It has a maximum load-balancing improvement of 23.7% and 11.7% in comparison with the traditional Open Shortest Path First (OSPF) algorithm and the reinforcement learning method based on Q-Learning.
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10

Joshi, Prof Swati, Arnab Dutta, Neeraj Chavan, Gaurav Dhus, and Pratik Bharsakle. "Enhancing Traffic Management and Load Balancing in SDN." IJARCCE 6, no. 4 (April 30, 2014): 794–99. http://dx.doi.org/10.17148/ijarcce.2017.64148.

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Більше джерел

Дисертації з теми "Load balancing in SDN"

1

Warsama, Ahmed. "Traffic Engineering with SDN : Optimising traffic Load-Balancing with OpenFlow". Thesis, Mittuniversitetet, Institutionen för informationssystem och –teknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-39385.

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Анотація:
The advent of trends such as virtualization, cloud computing, IoT and BYOD has increased the traffic loads on modern enterprise and data-center networks. As the requirements on today’s networks increase, newer designs and solutions have sprout forth. Software-Defined Networking was developed to cater to the needs of modern networks and to improve traffic handling among other things. This study focuses on the ways SDN, specifically the OpenFlow standard, can be used to load-balance and increase the network throughput, in comparison to traditional methods such as Equal-Cost Load-Balancing. This was done by creating a test environment with the network emulator Mininet, and by creating load-balancing programs. The load-balancers were created using the OpenFlow protocol. These programs were used together with the Floodlight controller and were compared in the same environment. The results showed that the bandwidth load-balancer outperformed the Equal-Cost Load-Balancer.
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2

Wang, Xuan. "A Load Balancing Algorithm for Flow Management in Hybrid-SDN Networks." Thesis, University of South Dakota, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10937380.

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Анотація:

Hybrid Software Defined Network(Hybrid-SDN) is the most popular topic in recent years, with related development and deployment of vendors of software and hardware. HybridSDN has the capabilities of most advantaged technology and features with the network current on use in public. However, the Hybrid-SDN does not have the highest performance which is the pure SDN network architecture. It is necessary for researchers understand the differences between legacy network, SDN and Hybrid-SDN, through the numeric comparison of performances by simulations. Also, as the cooperation part between the legacy nodes and SDN nodes in Hybrid-SDN network architecture, load balancing algorithm played an important role. There are lots of load balancing algorithm comes out since the network architecture first time constructed. But the different between load balancing algorithms are not clear. It is necessary for researchers know is there existing difference between load balancing algorithms. Also, particular for Hybrid-SDN network architecture, the messed up environment of different type of devices, the current existing load balancing algorithm did not considering all the cases may affect the network. The solution for the problem is to design a load balancing algorithm which particular focusing on Hybrid-SDN environment. To explain the differences of these framework and design the load balancing algorithm, we studied different network architectures and load balancing algorithms, evaluated them by simulation results. The main work included the following tasks:

• Simulated three network architectures. • Simulated two common load balancing algorithms. • Designed a load balancing algorithm for flow management focus on Hybrid-SDN

The simulation results of three network architectures provided the clearly differences between these architectures, which approve the Hybrid-SDN has a big performance promotion with Legacy Network. The results of two load balancing algorithms showed there existing difference between load balancing algorithms, so that, it is necessary to have a load balancing algorithm particular focusing on Hybrid-SDN. And both analysis and simulation results dedicated that our proposed load balancing algorithm can perform efficiently for Hybrid-SDN network architecture.

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3

Marciniak, Petr. "Vyvažování zátěže v sítích OpenFlow." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2013. http://www.nusl.cz/ntk/nusl-236205.

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Анотація:
The aim of this thesis is to develop a load balancing tool for OpenFlow networks. Software-defined networking (SDN) principles are introduced (OpenFlow protocol used as an example) and compared to the legacy routing and switching technology. Openflow is the first protocol/API enabling communication between the control and infrastructure planes of the software-defined networking model. Key features of the protocol are described and several OpenFlow controllers are introduced. Current best practices in computer networks load balancing are discussed as well. The load balancing application development process is described including the test laboratory setups - Mininet (SW) and OFELIA (HW). The application test results are evaluated and possible further enhancements to the program are discussed.
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4

Sehery, Wile Ali. "OneSwitch Data Center Architecture." Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/94376.

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Анотація:
In the last two-decades data center networks have evolved to become a key element in improving levels of productivity and competitiveness for different types of organizations. Traditionally data center networks have been constructed with 3 layers of switches, Edge, Aggregation, and Core. Although this Three-Tier architecture has worked well in the past, it poses a number of challenges for current and future data centers. Data centers today have evolved to support dynamic resources such as virtual machines and storage volumes from any physical location within the data center. This has led to highly volatile and unpredictable traffic patterns. Also The emergence of "Big Data" applications that exchange large volumes of information have created large persistent flows that need to coexist with other traffic flows. The Three-Tier architecture and current routing schemes are no longer sufficient for achieving high bandwidth utilization. Data center networks should be built in a way where they can adequately support virtualization and cloud computing technologies. Data center networks should provide services such as, simplified provisioning, workload mobility, dynamic routing and load balancing, equidistant bandwidth and latency. As data center networks have evolved the Three-Tier architecture has proven to be a challenge not only in terms of complexity and cost, but it also falls short of supporting many new data center applications. In this work we propose OneSwitch: A switch architecture for the data center. OneSwitch is backward compatible with current Ethernet standards and uses an OpenFlow central controller, a Location Database, a DHCP Server, and a Routing Service to build an Ethernet fabric that appears as one switch to end devices. This allows the data center to use switches in scale-out topologies to support hosts in a plug and play manner as well as provide much needed services such as dynamic load balancing, intelligent routing, seamless mobility, equidistant bandwidth and latency.
PHD
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5

Nguyen, Van-Giang. "Towards SDN/NFV-based Mobile Packet Core : Benefits, Challenges, and Potential Solutions." Licentiate thesis, Karlstads universitet, Institutionen för matematik och datavetenskap (from 2013), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-67132.

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Анотація:
In mobile networks, the mobile core plays a crucial role in providing connectivity between mobile user devices and external packet data networks such as the Internet. Through the years, along with the dramatical changes in radio access networks, the mobile core has also been evolved from being a circuit-based analog telephony system in its first generation (1G) to become a purely packet-based network called the Evolved Packet Core (EPC) in the current generation (4G). In recent years, the explosion of mobile data traffic and devices and the advent of new services have led to the investigation of the next generation of mobile networks, i.e., 5G. A wide range of technologies has been proposed as candidates for the development of 5G. Among other technology candidates, Software Defined Networking (SDN) and Network Function Virtualization (NFV) have been widely considered to be key enablers for the network architecture of 5G, especially the mobile packet core (MPC) network. This thesis aims at identifying benefits and challenges of introducing SDN and NFV to re-achitect the current MPC network architecture towards 5G and addressing some of the challenges. To this end, we conduct a comprehensive literature review of the state-of-the-art work leveraging SDN and NFV to re-design the 4G EPC architecture. Through this survey work, several research questions for future work have been identified and we contribute to address two of them in this thesis. Firstly, since most of the current works focus on unicast services, we propose an SDN/NFV-based MPC architecture for providing multicast and broadcast services. Our numerical results show that the proposed architecture can reduce the total signaling cost compared to the traditional architecture. Secondly, we address the question regarding the scalability of the control plane. We take the Mobility Management Entity (MME) - one of the EPC key control plane entities - as a case study. In our work, the MME is deployed as a cluster of multiple virtual instances (vMMEs) and a front-end load balancer. We focus on investigating different approaches to achieve better load balancing among these vMMEs, which in turn improves scalability. Our experimental results suggest that carefully selected load balancing algorithms can significantly reduce the control plane latency.
In mobile networks, the mobile core plays a crucial role in providing connectivity between mobile user devices and external packet data networks such as the Internet. After more than three decades, the mobile core has been gradually evolved through four generations and is called the Evolved Packet Core (EPC) in the current generation (4G). In recent years, the explosion of mobile data traffic and devices and the advent of new services have led to the investigation of the next generation of mobile networks, i.e., 5G. Among other technology candidates, Software Defined Networking (SDN) and Network Function Virtualization (NFV) have been widely considered to be key enablers for the network architecture of 5G, especially the mobile packet core (MPC) network. This thesis aims at identifying benefits and challenges of introducing SDN and NFV to re-achitect the current MPC architecture towards 5G and addressing some of the challenges. To this end, we conduct a comprehensive survey of the existing SDN/NFV-based MPC architectures. Through this survey work, several research questions for future work have been identified and we contribute to address two of the research questions. Firstly, we propose an SDN/NFV-based MPC architecture for providing multicast and broadcast services. Secondly, we tackle the scalability problem of the Mobility Management Entity (MME) - one of the EPC key control plane entities. In particular, we investigate different approaches to achieve better load balancing among virtual MMEs in a virtual and distributed MME design, which in turn improves scalability.
HITS, 4707
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6

Aravinthan, Gopalasingham. "SDN based service oriented control approach for future radio access networks." Thesis, Evry, Institut national des télécommunications, 2017. http://www.theses.fr/2017TELE0013.

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Анотація:
Le SDN (Software-Defined Networking) émerge comme une nouvelle architecture pour la programmation des réseaux. A l'origine, l'idée du SDN est de déplacer le plan de contrôle à l'extérieur des équipements, et de permettre ainsi un contrôle déporté de l'ensemble depuis une entité logicielle logique nommée "contrôleur". Le principal avantage d'une telle approche est de centraliser donc toute l'intelligence de gestion du réseau dans le contrôleur, qui s'appuie pour cela sur des protocoles standard et assure par ce biais la reprogrammation de la totalité de la partie du réseau sous son contrôle. L'évolution technologique vers le SDN est toujours en cours dans des scénarios de déploiement programmable et flexible des réseaux mobiles. Le NFV (Network Function Virtualization) est le processus de déplacement ou de migration des fonctions réseau d'un équipement dédié de réseau vers des serveurs génériques dans le Cloud. Les SDN et NFV sont deux technologies étroitement liées qui sont souvent utilisées ensemble. Le couplage fort entre les plans de contrôle et de données, ainsi que les limitations en matière de passage à l'échelle et de flexibilité, font que la virtualisation des réseaux mobiles actuels nécessite non seulement l'utilisation du Cloud Computing mais aussi les récentes innovations telles que SDN et NFV pour pouvoir permettre un déploiement à la demande des services réseaux (Network-as-a-Service) aux utilisateurs. Les lignes de recherche globales de cette thèse s'inscrivent dans deux principaux cas d'utilisation. Ces cas d'utilisation, bien qu'appelés de la "prochaine génération de réseaux mobiles", sont le "Telco" et le "Vertical", qui apparaissent ici couplés, les deux étant traditionnellement complètement séparés. Dans les cas d'utilisation de "télécommunications", nous exploitons les avantages de SDN pour avoir un cadre de contrôle flexible pour les réseaux d'auto-organisation (SON) et la division de traitement dynamique des utilisateurs. Dans le cas d'utilisation de "verticale", nous appliquons divers avantages du protocole SDN et OpenFlow pour utiliser efficacement les ressources radio du réseau de backhaul dans le système de communication train-sol. Notre cadre d'étude du SDN, en général, peut être une solution efficace et alternative pour la gestion RAN (Radio Access Network), c'est-à-dire pour des objectives comme l'optimisation des ressources radio, l'optimisation du réseau, la gestion de la mobilité et l'équilibrage de la charge, peuvent être atteint avec ce cadre. Grâce à l'analyse et l'expérimentation concrète des SDN et NFV pour le RAN, nous montrons que les solutions proposées dans ce travail peuvent apporter un faisceau d'avantages évidents aux réseaux mobiles tels que la flexibilité, la programmabilité, la gestion unifiée et la mise en œuvre de nouveaux services
Software-Defined Networking (SDN) has emerged as a new intelligent architecture for network programmability. The primary idea behind SDN is to move the control-plane outside the switches and enable external control of data-plane through a logical software entity called controller. Such approach benefits mobile network management by brining complete intelligence to the logically centralized controller. Network Function Virtualization (NFV) is the process of relocating or migrating network functions from dedicated hardware to generic servers. SDN and NFV are two closely related technologies that are often used together. The traditional mobile network architecture due to its strongest coupling between control and data planes along with limitations in scalability and flexibility requires the usage of cloud computing along with the recent revolutionary approaches in networking such as SDN and NFV to have an architecture that deploys on demand "Network-as-a-Service" for users. The global research focus of this thesis falls in to two main use cases of next generation mobile networks such as Telco and Vertical. In the telco use cases, we exploit the advantages of SDN to have flexible control framework for both Self-Organizing Networks (SON) and dynamic user processing split. In vertical use case, we apply various advantages of SDN and OpenFlow protocol to efficiently utilize the scare radio resources of wireless backhaul network in the train-to-ground communication system. Our SDN framework in general can be an efficient and alternative solution for RAN management i.e. Radio Optimization, Network Optimization, Mobility Management and Load Balancing can be achieved with such framework. Through analysis and experimentation of SDN frameworks for RAN, we shows that the proposed solutions can bring set of advantages to wireless networks such as flexibility, programmability, unified management, and enables new services
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7

Кузнєцов, Ярослав Іванович. "Спосіб балансування навантаження в масштабних програмноконфігурованих мережах". Master's thesis, КПІ ім. Ігоря Сікорського, 2020. https://ela.kpi.ua/handle/123456789/34050.

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Анотація:
Робота складається із вступу, трьох розділів та одного додатку. Загальний обсяг роботи: 69 аркуші основного тексту, 41 ілюстрація, 6 таблиць. При підготовці використовувалася література з 38 різних джерел. Актуальність. Дедалі більшу популярність набуває стрімінгові сервіси, зростає кількість мережевих сервісів та абонентів мережі, що потребують забезпечення якості обслуговування. Традиційні мережі наближаються до своєї межі ефективності. Альтернативою традиційним мережам є централізована архітектура SDN. Ідея технології SDN не є новою, проте активне впровадження технології припадає лише на останні 15 років. Однією із важливих задач при організації мережі є задача балансування трафіку, що включає в собі маршрутизацію та забезпечення якості обслуговування. Використання нової технології вимагає розробки нових алгоритмів та протоколів, або адаптації традиційних, задача балансування трафіку є актуальною. Мета і завдання дослідження. Метою магістерської роботи є розроблення методу, що дозволить маршрутизувати трафік по оптимальним шляхам, уникаючи високої затримки та забезпечення більш рівномірного завантаження мережі шляхом балансування трафіку, з використанням можливостей програмно-конфігурованих мереж. Для досягнення мети дослідження поставлено і вирішено такі завдання: • дослідження структури та принципів побудови програмноконфігурованих мереж; • дослідження методів масштабування програмно-конфігурованих мереж; • дослідження методів забезпечення якості обслуговування в класичних та програмно-конфігурованих мережах; • Дослідження методів маршрутизації в програмно-конфігурованих мережах; • Дослідження методів рішення задач багатокритеріальної оптимізації; • Pозробка методу балансування трафіку в програмно-конфігурованих мережах; • Розробка програмного модулю на основі розробленого методу; • Ілюстрація роботи моделі та аналіз отриманих результатів. Об’єкт дослідження – процес пошуку оптимального шляху між вузлами в програмно-конфігурованих мережах. Предмет дослідження – методи маршрутизації та визначення оптимальності маршруту в програмно-конфігурованих мережах. Методи досліджень. Для досягнення поставлених в магістерській роботі задач, використано методи теорії графів, методи моделювання, методи вирішення задач багатокритеріальної організації. Проведене дослідження дає можливість використання розробленої моделі в SDN мережах в якості застосунку контролера та виконувати емуляцію роботи мережі для прогнозування трафіку та завантаженості компонентів мережі. Особистий внесок здобувача. Магістерське дослідження є самостійно виконаною роботою, в якій відображено особистий авторський підхід та особисто отримані теоретичні та прикладні результати, що відносяться до вирішення задачі маршрутизації та контролю трафіку в SDN мережах. Формулювання мети та завдань дослідження проводилось спільно з науковим керівником. Практична цінність. Отримані результати можуть використовуватися у майбутніх дослідженнях за напрямками: • вдосконалення методів маршрутизації; • аналіз та прогнозування трафіку в SDN; • балансування навантаження в SDN мережах.
Current work consists of receipt, three sections and one application. Total amount of work: 69 pages of the main text, 41 illustrations, 6 tables. By preparation a literature from 38 different sources was used. Topic Relevance. The increasing popularity acquires streaming services, the number of network services and subscribers of network grows that need ensuring quality of service. Traditional networks come nearer to the limit of efficiency. An alternative to traditional networks is the centralized architecture of SDN. The idea of SDN technology is not new, however active implementation of technology falls only on the last 15 years. The problem of balancing of traffic is one of important tasks at the organization of network that includes in itself routing and ensuring quality of service. Use of new technology demands development of new algorithms and protocols, or adaptation traditional, the problem of balancing of traffic is relevant. Research goal. The research goal of the master's thesis is development of a method that will allow to route traffic on optimal ways, avoiding a high delay and ensuring more uniform loading of network by balancing of traffic, with use of opportunities of software defined networks. For achievement of the goal of a research it is put and solved the following tasks: • Research of structure and the principles of construction software defined networks; • Researches of methods scaling software defined networks; • Researches of methods of ensuring quality of service in classical and software defined networks; • Researches of methods of routing in software defined networks; • Researches of methods of solving problems of multicriterial optimization; • Development of a method of balancing of traffic in software defined networks; • Development of the program module on the basis of the developed method; • Illustration of work of model and the analysis of the received results. Object of research – Process of search of an optimal way between nodes in software defined networks. Subject of research – Methods of routing and determination of optimality of a route in software defined networks. Methods of research. For achievement of the tasks set in the master's thesis, it is used methods of the theory of graphs, modeling methods, methods of the solution of tasks of the multicriteria organization. The conducted research gives the chance of use of the developed model in SDN networks as an application of the controller and to carry out emulation of network functioning for forecasting of traffic and load of components of network. Scientific contribution. The master research is independently done work in which it is reflected personal author's approach and personally received theoretical and applied results relating to the solution of a problem of routing and control of traffic in SDN networks. A formulation of the purpose and tasks the research was conducted together with the research supervisor. Practical value of obtained results. The received results can be used in future researches on the directions: • to improvement of methods of routing; • the analysis and forecasting of traffic in SDN; • balancing of loading in SDN networks.
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8

Carpa, Radu. "Energy Efficient Traffic Engineering in Software Defined Networks." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSEN065/document.

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Ce travail a pour but d'améliorer l'efficacité énergétique des réseaux de cœur en éteignant un sous-ensemble de liens par une approche SDN (Software Defined Network). Nous nous différencions des nombreux travaux de ce domaine par une réactivité accrue aux variations des conditions réseaux. Cela a été rendu possible grâce à une complexité calculatoire réduite et une attention particulière au surcoût induit par les échanges de données. Pour valider les solutions proposées, nous les avons testées sur une plateforme spécialement construite à cet effet.Dans la première partie de cette thèse, nous présentons l'architecture logicielle ``SegmenT Routing based Energy Efficient Traffic Engineering'' (STREETE). Le cœur de la solution repose sur un re-routage dynamique du trafic en fonction de la charge du réseau dans le but d'éteindre certains liens peu utilisés. Cette solution utilise des algorithmes de graphes dynamiques pour réduire la complexité calculatoire et atteindre des temps de calcul de l'ordre des millisecondes sur un réseau de 50 nœuds. Nos solutions ont aussi été validées sur une plateforme de test comprenant le contrôleur SDN ONOS et des commutateurs OpenFlow. Nous comparons nos algorithmes aux solutions optimales obtenues grâce à des techniques de programmation linéaires en nombres entiers et montrons que le nombre de liens allumés peut être efficacement réduit pour diminuer la consommation électrique tout en évitant de surcharger le réseau.Dans la deuxième partie de cette thèse, nous cherchons à améliorer la performance de STREETE dans le cas d’une forte charge, qui ne peut pas être écoulée par le réseau si des algorithmes de routages à plus courts chemins sont utilisés. Nous analysons des méthodes d'équilibrage de charge pour obtenir un placement presque optimal des flux dans le réseau.Dans la dernière partie, nous évaluons la combinaison des deux techniques proposées précédemment : STREETE avec équilibrage de charge. Ensuite, nous utilisons notre plateforme de test pour analyser l'impact de re-routages fréquents sur les flux TCP. Cela nous permet de donner des indications sur des améliorations à prendre en compte afin d'éviter des instabilités causées par des basculements incontrôlés des flux réseau entre des chemins alternatifs. Nous croyons à l'importance de fournir des résultats reproductibles à la communauté scientifique. Ainsi, une grande partie des résultats présentés dans cette thèse peuvent être facilement reproduits à l'aide des instructions et logiciels fournis
This work seeks to improve the energy efficiency of backbone networks by automatically managing the paths of network flows to reduce the over-provisioning. Compared to numerous works in this field, we stand out by focusing on low computational complexity and smooth deployment of the proposed solution in the context of Software Defined Networks (SDN). To ensure that we meet these requirements, we validate the proposed solutions on a network testbed built for this purpose. Moreover, we believe that it is indispensable for the research community in computer science to improve the reproducibility of experiments. Thus, one can reproduce most of the results presented in this thesis by following a couple of simple steps. In the first part of this thesis, we present a framework for putting links and line cards into sleep mode during off-peak periods and rapidly bringing them back on when more network capacity is needed. The solution, which we term ``SegmenT Routing based Energy Efficient Traffic Engineering'' (STREETE), was implemented using state-of-art dynamic graph algorithms. STREETE achieves execution times of tens of milliseconds on a 50-node network. The approach was also validated on a testbed using the ONOS SDN controller along with OpenFlow switches. We compared our algorithm against optimal solutions obtained via a Mixed Integer Linear Programming (MILP) model to demonstrate that it can effectively prevent network congestion, avoid turning-on unneeded links, and provide excellent energy-efficiency. The second part of this thesis studies solutions for maximizing the utilization of existing components to extend the STREETE framework to workloads that are not very well handled by its original form. This includes the high network loads that cannot be routed through the network without a fine-grained management of the flows. In this part, we diverge from the shortest path routing, which is traditionally used in computer networks, and perform a particular load balancing of the network flows. In the last part of this thesis, we combine STREETE with the proposed load balancing technique and evaluate the performance of this combination both regarding turned-off links and in its ability to keep the network out of congestion. After that, we use our network testbed to evaluate the impact of our solutions on the TCP flows and provide an intuition about the additional constraints that must be considered to avoid instabilities due to traffic oscillations between multiple paths
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9

Burrows, Richard B. P. "Dynamic load balancing." Thesis, University of Oxford, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.363886.

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10

Nagel, Lars. "Randomised load balancing." Thesis, Durham University, 2011. http://etheses.dur.ac.uk/3207/.

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Due to the increased use of parallel processing in networks and multi-core architectures, it is important to have load balancing strategies that are highly efficient and adaptable to specific requirements. Randomised protocols in particular are useful in situations in which it is costly to gather and update information about the load distribution (e.g. in networks). For the mathematical analysis randomised load balancing schemes are modelled by balls-into-bins games, where balls represent tasks and bins computers. If m balls are allocated to n bins and every ball chooses one bin at random, the gap between maximum and average load is known to grow with the number of balls m. Surprisingly, this is not the case in the multiple-choice process in which each ball chooses d > 1 bins and allocates itself to the least loaded. Berenbrink et al. proved that then the gap remains ln ln(n) / ln(d). This thesis analyses generalisations and variations of the multiple-choice process. For a scenario in which batches of balls are allocated in parallel, it is shown that the gap between maximum and average load is still independent of m. Furthermore, we look into a process in which only predetermined subsets of bins can be chosen by a ball. Assuming that the number and composition of the subsets can change with every ball, we examine under which circumstances the maximum load is one. Finally, we consider a generalisation of the basic process allowing the bins to have different capacities. Adapting the probabilities of the bins, it is shown how the load can be balanced over the bins according to their capacities.
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Книги з теми "Load balancing in SDN"

1

Membrey, Peter, David Hows, and Eelco Plugge. Practical Load Balancing. Berkeley, CA: Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-3681-8.

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2

Server load balancing. Beijing ; Sebastopol, Calif: O'Reilly, 2001.

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3

Windows server 2003: Clustering & load balancing. New York: McGraw-Hill/Osborne, 2003.

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4

Load Balancing Servers, Firewalls, and Caches. New York: John Wiley & Sons, Ltd., 2002.

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5

W, Wah Benjamin, ed. Load balancing: An automated learning approach. River Edge, NJ: World Scientific Pub., 1995.

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6

Tumuluri, Chaitanya. Locality-conscious load balancing: Connectionist architectural support. Ithaca, N.Y: Cornell Theory Center, Cornell University, 1996.

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7

Delisle, Pierre. A load balancing facility for distributed systems. Toronto: University of Toronto, Dept. of Computer Science, 1989.

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8

Salhi, Abdellah. Load-balancing in flood-fill configured applications. Edinburgh: University of Edinburgh. Department of Business Studies, 1995.

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9

Biswas, R. Load balancing sequences of unstructured adaptive grids. [Moffett Field, Calif.]: Research Institute for Advanced Computer Science, NASA Ames Research Center, 1997.

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10

Membrey, Peter. Practical Load Balancing: Ride the Performance Tiger. Berkeley, CA: Apress, 2012.

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Частини книг з теми "Load balancing in SDN"

1

Ma, Ziyi, Xiaoqiang Di, Yuming Jiang, Huilin Jiang, and Huamin Yang. "Delay-Constrained Load Balancing in the SDN." In Communications in Computer and Information Science, 124–34. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-5937-8_14.

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2

Vani, K. A., J. Prathima Mabel, and K. N. Rama Mohan Babu. "A Switch-Prioritized Load-Balancing Technique in SDN." In Data Analytics and Learning, 39–49. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2514-4_4.

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3

Sun, Xiangshan, Zhiping Jia, Mengying Zhao, and Zhiyong Zhang. "Multipath Load Balancing in SDN/OSPF Hybrid Network." In Lecture Notes in Computer Science, 93–100. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47099-3_8.

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4

Ajeeth, B., and V. Muthumanikandan. "Hybrid Load Balancing Approach for SDN-Enabled M2M Networks." In Lecture Notes on Data Engineering and Communications Technologies, 305–14. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-1002-1_32.

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5

Li, Jingbo, Li Ma, Yingxun Fu, Dongchao Ma, and Ailing Xiao. "Load Balancing in Heterogeneous Network with SDN: A Survey." In Communications in Computer and Information Science, 250–61. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-8174-5_19.

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6

Priyadarsini, Madhukrishna, and Padmalochan Bera. "An SDN Implemented Adaptive Load Balancing Scheme for Mobile Networks." In Lecture Notes in Computer Science, 127–39. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94876-4_8.

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7

Ahmad, Ijaz, Suneth Namal Karunarathna, Mika Ylianttila, and Andrei Gurtov. "Load Balancing in Software Defined Mobile Networks." In Software Defined Mobile Networks (SDMN), 225–45. Chichester, UK: John Wiley & Sons, Ltd, 2015. http://dx.doi.org/10.1002/9781118900253.ch13.

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8

Sun, Weitao, Ji-wu Shu, and Weimin Zheng. "Storage Virtualization System with Load Balancing for SAN." In Grid and Cooperative Computing - GCC 2004 Workshops, 254–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30207-0_32.

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9

Zhu, Runshui, Hua Wang, Yanqing Gao, Shanwen Yi, and Fangjin Zhu. "Energy Saving and Load Balancing for SDN Based on Multi-objective Particle Swarm Optimization." In Algorithms and Architectures for Parallel Processing, 176–89. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27137-8_14.

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10

Semong, Thabo, and Kun Xie. "Efficient Load Balancing and Multicasting for Uncertain-Source SDN: Real-Time Link-Cost Monitoring." In Advances in Intelligent Systems and Computing, 178–87. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91186-1_19.

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Тези доповідей конференцій з теми "Load balancing in SDN"

1

Olaya, Marlon Esteban, Ivan Bernal, and David Mejia. "Application for load balancing in SDN." In 2016 8th Euro American Conference on Telematics and Information Systems (EATIS). IEEE, 2016. http://dx.doi.org/10.1109/eatis.2016.7520102.

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2

Aguilar, Leonardo, and Daniel Macêdo Batista. "Effectiveness of Implementing Load Balancing via SDN." In XXXVII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/sbrc_estendido.2019.7796.

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Анотація:
Software-Defined Networking (SDN) is an architecture that allows the creation, management and customization of the network through programmable switches and centralized controllers via a well-defined protocol. Despite the wide dissemination of general advantages in using SDN, it is always important to evaluate the real advantages considering specific network applications. In line with this, the purpose of this work is to analyze the effectiveness of using SDN for load balancing by developing a balancer, made available as free software, that can execute three different algorithms, giving to the administrator the possibility to choose, at run time, which will be used as well as their configurations, and the possibility to implement new algorithms.
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3

Qilin, Mao, and Shen Weikang. "A Load Balancing Method Based on SDN." In 2015 Seventh International Conference on Measuring Technology and Mechatronics Automation (ICMTMA). IEEE, 2015. http://dx.doi.org/10.1109/icmtma.2015.13.

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4

Singh, Abhishek, Mayank Tiwray, Raj Kumar, and Rachita Misra. "Load Balancing among Wide-Area SDN Controllers." In 2016 International Conference on Information Technology (ICIT). IEEE, 2016. http://dx.doi.org/10.1109/icit.2016.032.

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5

Sufiev, Hadar, and Yoram Haddad. "A dynamic load balancing architecture for SDN." In 2016 IEEE International Conference on the Science of Electrical Engineering (ICSEE). IEEE, 2016. http://dx.doi.org/10.1109/icsee.2016.7806104.

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6

Li, Lin, and Qiaozhi Xu. "Load balancing researches in SDN: A survey." In 2017 7th IEEE International Conference on Electronics Information and Emergency Communication (ICEIEC). IEEE, 2017. http://dx.doi.org/10.1109/iceiec.2017.8076592.

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7

Aly, Wael Hosny Fouad. "Controller Adaptive Load Balancing for SDN Networks." In 2019 Eleventh International Conference on Ubiquitous and Future Networks (ICUFN). IEEE, 2019. http://dx.doi.org/10.1109/icufn.2019.8805922.

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8

Selvi, Hakan, Gurkan Gur, and Fatih Alagoz. "Cooperative load balancing for hierarchical SDN controllers." In 2016 IEEE 17th International Conference on High Performance Switching and Routing (HPSR). IEEE, 2016. http://dx.doi.org/10.1109/hpsr.2016.7525646.

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9

Jerome, Austin, Murat Yuksel, Syed Hassan Ahmed, and Mostafa Bassiouni. "SDN-based load balancing for multi-path TCP." In 2018 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). IEEE, 2018. http://dx.doi.org/10.1109/infcomw.2018.8406943.

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Giri, Nupur, Vikas Kukreja, Dinesh Panchi, Jatin Sajnani, and Hitesh Seedani. "Performance Evaluation of Load Balancing Algorithms for SDN." In 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA). IEEE, 2018. http://dx.doi.org/10.1109/iccubea.2018.8697762.

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Звіти організацій з теми "Load balancing in SDN"

1

Hendrickson, B., and R. Leland. Multidimensional spectral load balancing. Office of Scientific and Technical Information (OSTI), January 1993. http://dx.doi.org/10.2172/6691328.

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2

Volz, B., S. Gonczi, T. Lemon, and R. Stevens. DHC Load Balancing Algorithm. RFC Editor, February 2001. http://dx.doi.org/10.17487/rfc3074.

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3

Pearce, Olga Tkachyshyn. Load Balancing Scientific Applications. Office of Scientific and Technical Information (OSTI), December 2014. http://dx.doi.org/10.2172/1178404.

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4

Heirich, Alan, and Stephen Taylor. A Parabolic Load Balancing Method. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada442993.

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5

Gabler, Jason. Better Bonded Ethernet Load Balancing. Office of Scientific and Technical Information (OSTI), September 2006. http://dx.doi.org/10.2172/883778.

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6

Filsfils, C., P. Mohapatra, and C. Pignataro. Load-Balancing for Mesh Softwires. RFC Editor, August 2009. http://dx.doi.org/10.17487/rfc5640.

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7

Brisco, T. DNS Support for Load Balancing. RFC Editor, April 1995. http://dx.doi.org/10.17487/rfc1794.

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8

Heirich, Alan. Scalable Load Balancing by Diffusion. Fort Belvoir, VA: Defense Technical Information Center, October 1994. http://dx.doi.org/10.21236/ada448706.

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9

Bershad, Brian. Load Balancing with Maitre d'. Fort Belvoir, VA: Defense Technical Information Center, December 1985. http://dx.doi.org/10.21236/ada185092.

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10

Cai, Y., H. Ou, S. Vallepalli, M. Mishra, S. Venaas, and A. Green. PIM Designated Router Load Balancing. RFC Editor, April 2020. http://dx.doi.org/10.17487/rfc8775.

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