Pub Date : 2022-10-05DOI: 10.1109/nof55974.2022.9942638
{"title":"Proceedings of the 2022 13th International Conference on the Network of the Future (NoF 2022)","authors":"","doi":"10.1109/nof55974.2022.9942638","DOIUrl":"https://doi.org/10.1109/nof55974.2022.9942638","url":null,"abstract":"","PeriodicalId":223811,"journal":{"name":"2022 13th International Conference on Network of the Future (NoF)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122003466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-05DOI: 10.1109/NoF55974.2022.9942486
E. Paolini, F. Civerchia, L. D. Marinis, L. Valcarenghi, Luca Maggiani, N. Andriolli
The benefits introduced by novel network technologies such as 5G and beyond, including low latency and support for billions of devices, have the potential to transform the lives of people. However, the features promised by these new technologies have also attracted malicious actors, with various motivations for attacking the network infrastructure, from cybercrime-based frauds to political goals. Thus, to enable the full potential of the emerging network technologies, it is necessary to take into accounts these attacks and develop tailored countermeasures. One future direction in mitigating the risks of potential attacks is the automatic classification of malicious packets, with the possibility to drop them if classified in the attack category. Hence, in this context, we propose a solution based on Neural Networks (NNs) to automatically classify packets into two classes, i.e., benign and attack, directly in the Radio Access Network (RAN), specifically inspecting packets when they are relayed at the next generation eNB (gNB)-Central Unit (CU) level. Since NNs can be computationally intensive algorithms, potentially increasing the latency of the network, we decide to leverage Photonic-Aware Neural Network (PANN), photonic accelerators able to perform NN computations in the analog optical domain and with time-of-flight latency. We devised two different PANN architectures, considering different photonic constraints. The classification performance of the two architectures has been assessed on the CICIDS-2017 dataset and compared with electronic counterparts. Results proved that the F1-score loss due to underlying hardware constraints is negligible, paving the way for PANN applications in next generation networks.
{"title":"Photonic-aware Neural Networks for Packet Classification in Beyond 5G Networks","authors":"E. Paolini, F. Civerchia, L. D. Marinis, L. Valcarenghi, Luca Maggiani, N. Andriolli","doi":"10.1109/NoF55974.2022.9942486","DOIUrl":"https://doi.org/10.1109/NoF55974.2022.9942486","url":null,"abstract":"The benefits introduced by novel network technologies such as 5G and beyond, including low latency and support for billions of devices, have the potential to transform the lives of people. However, the features promised by these new technologies have also attracted malicious actors, with various motivations for attacking the network infrastructure, from cybercrime-based frauds to political goals. Thus, to enable the full potential of the emerging network technologies, it is necessary to take into accounts these attacks and develop tailored countermeasures. One future direction in mitigating the risks of potential attacks is the automatic classification of malicious packets, with the possibility to drop them if classified in the attack category. Hence, in this context, we propose a solution based on Neural Networks (NNs) to automatically classify packets into two classes, i.e., benign and attack, directly in the Radio Access Network (RAN), specifically inspecting packets when they are relayed at the next generation eNB (gNB)-Central Unit (CU) level. Since NNs can be computationally intensive algorithms, potentially increasing the latency of the network, we decide to leverage Photonic-Aware Neural Network (PANN), photonic accelerators able to perform NN computations in the analog optical domain and with time-of-flight latency. We devised two different PANN architectures, considering different photonic constraints. The classification performance of the two architectures has been assessed on the CICIDS-2017 dataset and compared with electronic counterparts. Results proved that the F1-score loss due to underlying hardware constraints is negligible, paving the way for PANN applications in next generation networks.","PeriodicalId":223811,"journal":{"name":"2022 13th International Conference on Network of the Future (NoF)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134343396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-05DOI: 10.1109/NoF55974.2022.9942644
U. Tupakula, K. Karmakar, V. Varadharajan, Ben Collins
In this paper we present techniques for enhancing the security of south bound infrastructure in SDN which includes OpenFlow switches and end hosts. In particular, the proposed security techniques have three main goals: (i) validation and secure configuration of flow rules in the OpenFlow switches by trusted SDN controller in the domain; (ii) securing the flows from the end hosts; and (iii) detecting attacks on the switches by malicious entities in the SDN domain. We have implemented the proposed security techniques as an application for ONOS SDN controller. We have also validated our application by detecting various OpenFlow switch specific attacks such as malicious flow rule insertions and modifications in the switches over a mininet emulated network.
{"title":"Implementation of Techniques for Enhancing Security of Southbound Infrastructure in SDN","authors":"U. Tupakula, K. Karmakar, V. Varadharajan, Ben Collins","doi":"10.1109/NoF55974.2022.9942644","DOIUrl":"https://doi.org/10.1109/NoF55974.2022.9942644","url":null,"abstract":"In this paper we present techniques for enhancing the security of south bound infrastructure in SDN which includes OpenFlow switches and end hosts. In particular, the proposed security techniques have three main goals: (i) validation and secure configuration of flow rules in the OpenFlow switches by trusted SDN controller in the domain; (ii) securing the flows from the end hosts; and (iii) detecting attacks on the switches by malicious entities in the SDN domain. We have implemented the proposed security techniques as an application for ONOS SDN controller. We have also validated our application by detecting various OpenFlow switch specific attacks such as malicious flow rule insertions and modifications in the switches over a mininet emulated network.","PeriodicalId":223811,"journal":{"name":"2022 13th International Conference on Network of the Future (NoF)","volume":"51 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133205114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-05DOI: 10.1109/NoF55974.2022.9942471
D. Rossi, Giacomo Tontini, D. Borsatti, F. Callegati
In this demo proposal, we aim at demonstrating the integration of the management of the 5G connectivity and the related quality of service with the communication needs of the assets of an Industry 4.0 manufacturing scenario.
在本演示提案中，我们旨在展示5G连接管理和相关服务质量与工业4.0制造场景中资产通信需求的集成。
{"title":"Integration of 5G connectivity with the Asset Administration Shell in Industry 4.0","authors":"D. Rossi, Giacomo Tontini, D. Borsatti, F. Callegati","doi":"10.1109/NoF55974.2022.9942471","DOIUrl":"https://doi.org/10.1109/NoF55974.2022.9942471","url":null,"abstract":"In this demo proposal, we aim at demonstrating the integration of the management of the 5G connectivity and the related quality of service with the communication needs of the assets of an Industry 4.0 manufacturing scenario.","PeriodicalId":223811,"journal":{"name":"2022 13th International Conference on Network of the Future (NoF)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133422123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fifth-generation (5G) mobile networks aspire to deliver exceptionally high data rates with ultra-reliable and low-latency connectivity. With the growing popularity of mobile Internet and the increased bandwidth requirements of mobile applications, user Quality of Experience (QoE) is becoming increasingly critical. 5G networks demand predicting the real-time bandwidth of a channel to satisfy the QoE for bandwidth-savvy applications such as video streaming/conferencing, vir-tual/augmented/mixed reality, and autonomous driving. If future bandwidth can be forecast in advance, the bandwidthhungry applications may utilize the estimates to adapt their data transmission rates and dramatically enhance user QoE. By analyzing a publicly available 5G dataset comprised of the channel, context, and cell-related metrics with throughput information, existing work has used Long Short Term Memory (LSTM) based mechanisms to predict future bandwidth. We applied the Transformer-based model, namely ‘Informer,’ to the 5G dataset and found significant improvement of about 95% error decrease for bandwidth prediction. In addition, we combined some new feature analysis approaches (LASSO and Random Forest with new hyper-parameters) in addition to the the existing Random Forest with Informer to find out the most accurate prediction approach.
{"title":"Bandwidth Prediction in 5G Mobile Networks Using Informer","authors":"Tahmina Azmin, mohamadreza ahmadinejad, Nashid Shahriar","doi":"10.1109/NoF55974.2022.9942521","DOIUrl":"https://doi.org/10.1109/NoF55974.2022.9942521","url":null,"abstract":"Fifth-generation (5G) mobile networks aspire to deliver exceptionally high data rates with ultra-reliable and low-latency connectivity. With the growing popularity of mobile Internet and the increased bandwidth requirements of mobile applications, user Quality of Experience (QoE) is becoming increasingly critical. 5G networks demand predicting the real-time bandwidth of a channel to satisfy the QoE for bandwidth-savvy applications such as video streaming/conferencing, vir-tual/augmented/mixed reality, and autonomous driving. If future bandwidth can be forecast in advance, the bandwidthhungry applications may utilize the estimates to adapt their data transmission rates and dramatically enhance user QoE. By analyzing a publicly available 5G dataset comprised of the channel, context, and cell-related metrics with throughput information, existing work has used Long Short Term Memory (LSTM) based mechanisms to predict future bandwidth. We applied the Transformer-based model, namely ‘Informer,’ to the 5G dataset and found significant improvement of about 95% error decrease for bandwidth prediction. In addition, we combined some new feature analysis approaches (LASSO and Random Forest with new hyper-parameters) in addition to the the existing Random Forest with Informer to find out the most accurate prediction approach.","PeriodicalId":223811,"journal":{"name":"2022 13th International Conference on Network of the Future (NoF)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128808526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-05DOI: 10.1109/NoF55974.2022.9942599
Siamak Azadiabad, F. Khendek, M. Toeroe
Network Function Virtualization (NFV) defines a dynamic environment to deploy Virtual Network Functions (VNF) as constituents of Network Services (NS) that provide specific network functionalities. A VNF is composed of at least one VNF Component (VNFC) and zero, or more Internal Virtual Links (IntVL). The availability of an NS depends on the availability of the composing VNF functionalities. In turn these depend on the underlying resources, their placement constraints, policies, and their number, which change over time as required by the varying workload. Accordingly, the availability and failure rate of a VNF instance may vary over time. That is, it may be different for the different VNF scaling levels. In this paper, we investigate the parameters affecting the availability and the failure rate of a VNF instance, and we propose methods to calculate for such dynamic cases the guaranteed minimum availability and the guaranteed maximum failure rate for a VNF instance considering a given infrastructure.
{"title":"Availability and Failure Rate of VNF Instances: Impacting Parameters and Calculation Methods","authors":"Siamak Azadiabad, F. Khendek, M. Toeroe","doi":"10.1109/NoF55974.2022.9942599","DOIUrl":"https://doi.org/10.1109/NoF55974.2022.9942599","url":null,"abstract":"Network Function Virtualization (NFV) defines a dynamic environment to deploy Virtual Network Functions (VNF) as constituents of Network Services (NS) that provide specific network functionalities. A VNF is composed of at least one VNF Component (VNFC) and zero, or more Internal Virtual Links (IntVL). The availability of an NS depends on the availability of the composing VNF functionalities. In turn these depend on the underlying resources, their placement constraints, policies, and their number, which change over time as required by the varying workload. Accordingly, the availability and failure rate of a VNF instance may vary over time. That is, it may be different for the different VNF scaling levels. In this paper, we investigate the parameters affecting the availability and the failure rate of a VNF instance, and we propose methods to calculate for such dynamic cases the guaranteed minimum availability and the guaranteed maximum failure rate for a VNF instance considering a given infrastructure.","PeriodicalId":223811,"journal":{"name":"2022 13th International Conference on Network of the Future (NoF)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134615218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-05DOI: 10.1109/NoF55974.2022.9942578
Lylia Alouache, S. Yassa, Abdelouhab Ahfir
The Software Defined Networking (SDN) paradigm consist of decoupling the control from the data plane. Recently, the adoption of the SDN paradigm as the basic architecture for Vehicular networks (SDVN) coupled with the 5G promises to accelerate the Intelligent Transport Services and smart cities deployment. However, it raises many challenges generated mainly by the dynamic nature of the vehicular network and the centralized aspect of the control plane. The distributed control plane has been identified as suitable architecture for such environment. Hence, this study focuses on the SDVN Controller Placement Problem (CPP). Previously, several researches addressed this problem in the context of wired networks by considering primary metrics such as control path latency and controller capacity. In this paper, we propose to adopt a multi-objective optimization approach to elect the nodes designated as controllers. The election is done by considering different conflicting metrics: number of controllers, latency, load balancing metric and a key metric in distributed system, i.e: clock offset between the controllers and the vehicular network nodes for controllers synchronization. The multi-objective genetic algorithm is used to solve this multi-objective optimization problem and create a compromise controllers placement solution. Two topology models have been considered to evaluate the performances. The analysis of the simulation results shows the feasibility of our algorithm. The simulation gives promising results in both scenarios.
{"title":"A Multi-objective Optimization Approach for SDVN Controllers Placement Problem","authors":"Lylia Alouache, S. Yassa, Abdelouhab Ahfir","doi":"10.1109/NoF55974.2022.9942578","DOIUrl":"https://doi.org/10.1109/NoF55974.2022.9942578","url":null,"abstract":"The Software Defined Networking (SDN) paradigm consist of decoupling the control from the data plane. Recently, the adoption of the SDN paradigm as the basic architecture for Vehicular networks (SDVN) coupled with the 5G promises to accelerate the Intelligent Transport Services and smart cities deployment. However, it raises many challenges generated mainly by the dynamic nature of the vehicular network and the centralized aspect of the control plane. The distributed control plane has been identified as suitable architecture for such environment. Hence, this study focuses on the SDVN Controller Placement Problem (CPP). Previously, several researches addressed this problem in the context of wired networks by considering primary metrics such as control path latency and controller capacity. In this paper, we propose to adopt a multi-objective optimization approach to elect the nodes designated as controllers. The election is done by considering different conflicting metrics: number of controllers, latency, load balancing metric and a key metric in distributed system, i.e: clock offset between the controllers and the vehicular network nodes for controllers synchronization. The multi-objective genetic algorithm is used to solve this multi-objective optimization problem and create a compromise controllers placement solution. Two topology models have been considered to evaluate the performances. The analysis of the simulation results shows the feasibility of our algorithm. The simulation gives promising results in both scenarios.","PeriodicalId":223811,"journal":{"name":"2022 13th International Conference on Network of the Future (NoF)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122486952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-05DOI: 10.1109/NoF55974.2022.9942573
Mu Yuan, N. Freris
In this paper, we consider the problem of online task dispatching and scheduling in a system of devices that may possess energy harvesting capabilities. The objective is twofold, namely to maximize the cumulative weight of tasks that can be completed before their deadlines and to minimize the total energy consumption. Our proposed solution, termed ELISE, operates in an online fashion in that for each newly arriving task it decides between three alternatives (execute before another previously scheduled task, replace an existing task, or place in the waiting line) so as to meet the objectives. We analyze the complexity of ELISE and further provide performance guarantees in terms of bounds on the gap to optimality with regards to the two objectives. Extensive simulations attest to superior aggregate weight, energy consumption, guarantee ratio, and energy consumption per task, over baseline algorithms.
{"title":"Energy-aware online task dispatching and scheduling for edge systems with energy harvesting","authors":"Mu Yuan, N. Freris","doi":"10.1109/NoF55974.2022.9942573","DOIUrl":"https://doi.org/10.1109/NoF55974.2022.9942573","url":null,"abstract":"In this paper, we consider the problem of online task dispatching and scheduling in a system of devices that may possess energy harvesting capabilities. The objective is twofold, namely to maximize the cumulative weight of tasks that can be completed before their deadlines and to minimize the total energy consumption. Our proposed solution, termed ELISE, operates in an online fashion in that for each newly arriving task it decides between three alternatives (execute before another previously scheduled task, replace an existing task, or place in the waiting line) so as to meet the objectives. We analyze the complexity of ELISE and further provide performance guarantees in terms of bounds on the gap to optimality with regards to the two objectives. Extensive simulations attest to superior aggregate weight, energy consumption, guarantee ratio, and energy consumption per task, over baseline algorithms.","PeriodicalId":223811,"journal":{"name":"2022 13th International Conference on Network of the Future (NoF)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131503973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-05DOI: 10.1109/NoF55974.2022.9942580
Sabri Khamari, Rachedi Abdennour, T. Ahmed, M. Mosbah
Edge computing empowers service providers to deploy smart vehicles applications that require high throughput and extremely low latency. In this context, optimal Edge servers' placement becomes more difficult since it requires addressing several interrelated requirements at the same time, such as delay, deployment cost, and energy consumption. This paper studies optimal Edge server placement for energy efficiency. The proposed approach, called Green Optimal Edge Server Placement (GOESP), models the placement problem using integer linear programming to address the trade-off between latency, energy, and deployment cost while considering Edge servers' capacity and expected vehicle's traffic on the road. GOESP minimizes the energy consumption by minimizing the number of deployed Edge servers while meeting end-to-end communication latency and avoiding servers' overloading. We evaluate the efficiency of our approach mathematically and through simulations utilizing real-world traffic extracted from open data of Bordeaux city, France. The results demonstrate that our technique outperforms other methods in terms of energy efficiency and guarantees latency and workload balancing requirements.
{"title":"Green Edge Servers Placement for Intelligent Transport Systems","authors":"Sabri Khamari, Rachedi Abdennour, T. Ahmed, M. Mosbah","doi":"10.1109/NoF55974.2022.9942580","DOIUrl":"https://doi.org/10.1109/NoF55974.2022.9942580","url":null,"abstract":"Edge computing empowers service providers to deploy smart vehicles applications that require high throughput and extremely low latency. In this context, optimal Edge servers' placement becomes more difficult since it requires addressing several interrelated requirements at the same time, such as delay, deployment cost, and energy consumption. This paper studies optimal Edge server placement for energy efficiency. The proposed approach, called Green Optimal Edge Server Placement (GOESP), models the placement problem using integer linear programming to address the trade-off between latency, energy, and deployment cost while considering Edge servers' capacity and expected vehicle's traffic on the road. GOESP minimizes the energy consumption by minimizing the number of deployed Edge servers while meeting end-to-end communication latency and avoiding servers' overloading. We evaluate the efficiency of our approach mathematically and through simulations utilizing real-world traffic extracted from open data of Bordeaux city, France. The results demonstrate that our technique outperforms other methods in terms of energy efficiency and guarantees latency and workload balancing requirements.","PeriodicalId":223811,"journal":{"name":"2022 13th International Conference on Network of the Future (NoF)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130679617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-05DOI: 10.1109/NoF55974.2022.9942601
Souryendu Das, Wei Lian, Stavros Kalafatis, P. Lazaridis
Networking affects our daily interaction with the digital world. Advancements in Smart Device technology have led to the need for faster, more power-efficient, and error-free networks. Networking protocols, such as TCP and UDP, were originally designed without these new requirements and now face significant challenges in adapting to those goals i.e., efficiently handling congestion delays in switching networks, increasing production costs, and higher packet losses. In this paper, we propose the Smart Switch Dynamic Delay Algorithm (SSDDA) which takes into consideration multiple factors including link utilization, application-level throughput (goodput), packet loss, and queuing delay of the TCP/UDP link. The application is in datacenter switches where the switching could be moved from centralized controller to decentralized data path and programmable smart switches. Continuous feedback from the network enables SSDDA to estimate delay and modify packet flows for optimal performance. Simulation results using NS3 in a fat tree topology are carried out validating the algorithmic benefits of SSDDA.
{"title":"A Dynamic Algorithm for Optimization of Network Traffic through Smart Network Switch Data Flow Management","authors":"Souryendu Das, Wei Lian, Stavros Kalafatis, P. Lazaridis","doi":"10.1109/NoF55974.2022.9942601","DOIUrl":"https://doi.org/10.1109/NoF55974.2022.9942601","url":null,"abstract":"Networking affects our daily interaction with the digital world. Advancements in Smart Device technology have led to the need for faster, more power-efficient, and error-free networks. Networking protocols, such as TCP and UDP, were originally designed without these new requirements and now face significant challenges in adapting to those goals i.e., efficiently handling congestion delays in switching networks, increasing production costs, and higher packet losses. In this paper, we propose the Smart Switch Dynamic Delay Algorithm (SSDDA) which takes into consideration multiple factors including link utilization, application-level throughput (goodput), packet loss, and queuing delay of the TCP/UDP link. The application is in datacenter switches where the switching could be moved from centralized controller to decentralized data path and programmable smart switches. Continuous feedback from the network enables SSDDA to estimate delay and modify packet flows for optimal performance. Simulation results using NS3 in a fat tree topology are carried out validating the algorithmic benefits of SSDDA.","PeriodicalId":223811,"journal":{"name":"2022 13th International Conference on Network of the Future (NoF)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122397725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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