{"title":"sd - wan中基于邻域中心性的交换机-控制器分配算法","authors":"Isaiah O. Adebayo, M. Adigun, P. Mudali","doi":"10.1109/icABCD59051.2023.10220485","DOIUrl":null,"url":null,"abstract":"The advent of artificial intelligence and big data makes it nearly impossible for large scale networks to be managed manually. To this end, software-defined networking (SDN) was introduced to provide network operators with the infrastructure for achieving greater flexibility and fine-grained control over networks. However, a critical issue to consider when incorporating SDN technology over large-scale networks like wide area networks (WANs) is the allocation of switches to controllers. In this paper, we address the switch-to-controller allocation problem that considers the heterogeneity of controller capacities. Specifically, we propose two neighbourhood centrality-based algorithms for addressing the problem with the aim of minimizing switch-to-controller latency. We also introduce a weighted centrality function that enables fair distribution of load across capacitated controllers. The proposed algorithms utilize centrality-based measures and heuristics to determine the ideal switch-to-controller allocations that consider the propagating capacity of suitable controller nodes. We evaluate the performance of the proposed algorithms on the internet2 topology. The results show that considering the heterogeneity of controller capacities reduces load imbalance significantly. Moreover, by limiting the exploration of the local centrality for each node to a maximum of two-step neighbours the complexity of the proposed algorithm is reduced. Thus, making it suitable for implementation in real-world SD-WANs.","PeriodicalId":51314,"journal":{"name":"Big Data","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2023-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Neighbourhood Centality Based Algorithms for Switch-to-Controller Allocation in SD-WANs\",\"authors\":\"Isaiah O. Adebayo, M. Adigun, P. Mudali\",\"doi\":\"10.1109/icABCD59051.2023.10220485\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The advent of artificial intelligence and big data makes it nearly impossible for large scale networks to be managed manually. To this end, software-defined networking (SDN) was introduced to provide network operators with the infrastructure for achieving greater flexibility and fine-grained control over networks. However, a critical issue to consider when incorporating SDN technology over large-scale networks like wide area networks (WANs) is the allocation of switches to controllers. In this paper, we address the switch-to-controller allocation problem that considers the heterogeneity of controller capacities. Specifically, we propose two neighbourhood centrality-based algorithms for addressing the problem with the aim of minimizing switch-to-controller latency. We also introduce a weighted centrality function that enables fair distribution of load across capacitated controllers. The proposed algorithms utilize centrality-based measures and heuristics to determine the ideal switch-to-controller allocations that consider the propagating capacity of suitable controller nodes. We evaluate the performance of the proposed algorithms on the internet2 topology. The results show that considering the heterogeneity of controller capacities reduces load imbalance significantly. Moreover, by limiting the exploration of the local centrality for each node to a maximum of two-step neighbours the complexity of the proposed algorithm is reduced. Thus, making it suitable for implementation in real-world SD-WANs.\",\"PeriodicalId\":51314,\"journal\":{\"name\":\"Big Data\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2023-08-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Big Data\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1109/icABCD59051.2023.10220485\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Big Data","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1109/icABCD59051.2023.10220485","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Neighbourhood Centality Based Algorithms for Switch-to-Controller Allocation in SD-WANs
The advent of artificial intelligence and big data makes it nearly impossible for large scale networks to be managed manually. To this end, software-defined networking (SDN) was introduced to provide network operators with the infrastructure for achieving greater flexibility and fine-grained control over networks. However, a critical issue to consider when incorporating SDN technology over large-scale networks like wide area networks (WANs) is the allocation of switches to controllers. In this paper, we address the switch-to-controller allocation problem that considers the heterogeneity of controller capacities. Specifically, we propose two neighbourhood centrality-based algorithms for addressing the problem with the aim of minimizing switch-to-controller latency. We also introduce a weighted centrality function that enables fair distribution of load across capacitated controllers. The proposed algorithms utilize centrality-based measures and heuristics to determine the ideal switch-to-controller allocations that consider the propagating capacity of suitable controller nodes. We evaluate the performance of the proposed algorithms on the internet2 topology. The results show that considering the heterogeneity of controller capacities reduces load imbalance significantly. Moreover, by limiting the exploration of the local centrality for each node to a maximum of two-step neighbours the complexity of the proposed algorithm is reduced. Thus, making it suitable for implementation in real-world SD-WANs.
Big DataCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
9.10
自引率
2.20%
发文量
60
期刊介绍:
Big Data is the leading peer-reviewed journal covering the challenges and opportunities in collecting, analyzing, and disseminating vast amounts of data. The Journal addresses questions surrounding this powerful and growing field of data science and facilitates the efforts of researchers, business managers, analysts, developers, data scientists, physicists, statisticians, infrastructure developers, academics, and policymakers to improve operations, profitability, and communications within their businesses and institutions.
Spanning a broad array of disciplines focusing on novel big data technologies, policies, and innovations, the Journal brings together the community to address current challenges and enforce effective efforts to organize, store, disseminate, protect, manipulate, and, most importantly, find the most effective strategies to make this incredible amount of information work to benefit society, industry, academia, and government.
Big Data coverage includes:
Big data industry standards,
New technologies being developed specifically for big data,
Data acquisition, cleaning, distribution, and best practices,
Data protection, privacy, and policy,
Business interests from research to product,
The changing role of business intelligence,
Visualization and design principles of big data infrastructures,
Physical interfaces and robotics,
Social networking advantages for Facebook, Twitter, Amazon, Google, etc,
Opportunities around big data and how companies can harness it to their advantage.