Pub Date : 2024-02-01DOI: 10.23919/JCN.2023.000063
Jimena Andrade-Hoz;Jose M. Alcaraz-Calero;Qi Wang
The next generation of network capabilities coupled with artificial intelligence (AI) can provide innovative solutions for network control and self-optimisation. Network control demands a detailed knowledge of the network components to enforce the correct control rules. To this end, an immense number of metrics related to devices, flows, network rules, etc. can be used to describe the state of the network and to gain insights about which rule to enforce depending on the context. However, selection of the most relevant metrics often proves challenging and there is no readily available tool that can facilitate the dataset extraction and labelling for AI model training. This research work therefore first develops an analysis of the most relevant metrics in terms of network control to create a training dataset for future AI development purposes. It then presents a new architecture to allow the extraction of these metrics from a 5G network with a novel dataset visualisation and labelling tool to help perform the exploratory analysis and the labelling process of the resultant dataset. It is expected that the proposed architecture and its associated tools would significantly speed up the training process, which is crucial for the data-driven approach in developing AI-based network control capabilities.
{"title":"NetLabeller: Architecture with data extraction and labelling framework for beyond 5G networks","authors":"Jimena Andrade-Hoz;Jose M. Alcaraz-Calero;Qi Wang","doi":"10.23919/JCN.2023.000063","DOIUrl":"https://doi.org/10.23919/JCN.2023.000063","url":null,"abstract":"The next generation of network capabilities coupled with artificial intelligence (AI) can provide innovative solutions for network control and self-optimisation. Network control demands a detailed knowledge of the network components to enforce the correct control rules. To this end, an immense number of metrics related to devices, flows, network rules, etc. can be used to describe the state of the network and to gain insights about which rule to enforce depending on the context. However, selection of the most relevant metrics often proves challenging and there is no readily available tool that can facilitate the dataset extraction and labelling for AI model training. This research work therefore first develops an analysis of the most relevant metrics in terms of network control to create a training dataset for future AI development purposes. It then presents a new architecture to allow the extraction of these metrics from a 5G network with a novel dataset visualisation and labelling tool to help perform the exploratory analysis and the labelling process of the resultant dataset. It is expected that the proposed architecture and its associated tools would significantly speed up the training process, which is crucial for the data-driven approach in developing AI-based network control capabilities.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10459140","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140031620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.23919/JCN.2023.000054
Ruisi Wu;Wen-Kang Jia
The packet forwarding engine (PFE), a vital component of high-performance switches and routers, plays a pivotal role in rapidly selecting the appropriate output port for tens of thousands of packets. The performance of the PFE hinges on the efficacy of the group membership algorithm. In this research, we present a hybrid approach called caching scalar-pair and vectors routing and forwarding (CSVRF), which comprises virtual output port bitmap caching (VOPBC) and fractional-N SVRF, designed to address significant multicast forwarding challenges such as scalability. We achieve this through the implementation of content address memory (CAM). Within the CSVRF framework, we introduce an innovative virtual output port bitmap cache table, which encompasses the most frequently occurring combinations of output port bitmaps (OPB). Furthermore, we divide the larger scalar-pair into N subgroups to enhance the reusability of prime resources. We validate our findings using Matlab-based mathematical models and simulations. Our results demonstrate significant decreases in both memory space usage and forwarding latency. Our approach assures minimized memory consumption, faster processing, and robust scalability in high port-density settings.
{"title":"A popularity-based caching strategy for improved efficiency in SVRF-based multicast control-planes","authors":"Ruisi Wu;Wen-Kang Jia","doi":"10.23919/JCN.2023.000054","DOIUrl":"https://doi.org/10.23919/JCN.2023.000054","url":null,"abstract":"The packet forwarding engine (PFE), a vital component of high-performance switches and routers, plays a pivotal role in rapidly selecting the appropriate output port for tens of thousands of packets. The performance of the PFE hinges on the efficacy of the group membership algorithm. In this research, we present a hybrid approach called caching scalar-pair and vectors routing and forwarding (CSVRF), which comprises virtual output port bitmap caching (VOPBC) and fractional-N SVRF, designed to address significant multicast forwarding challenges such as scalability. We achieve this through the implementation of content address memory (CAM). Within the CSVRF framework, we introduce an innovative virtual output port bitmap cache table, which encompasses the most frequently occurring combinations of output port bitmaps (OPB). Furthermore, we divide the larger scalar-pair into N subgroups to enhance the reusability of prime resources. We validate our findings using Matlab-based mathematical models and simulations. Our results demonstrate significant decreases in both memory space usage and forwarding latency. Our approach assures minimized memory consumption, faster processing, and robust scalability in high port-density settings.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10459134","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140031680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.23919/JCN.2024.000009
{"title":"Information for authors","authors":"","doi":"10.23919/JCN.2024.000009","DOIUrl":"https://doi.org/10.23919/JCN.2024.000009","url":null,"abstract":"","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10459128","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140031682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.23919/JCN.2024.000001
Ibrahim Ghareeb;Osama Al-Shalali
This paper studies the statistical analysis of cascaded Nakagami-m fading channels that are arbitrarily correlated and not necessarily identically distributed. The probability density function (PDF), cumulative distribution function (CDF), and the nth moment for the product of N correlated Nakagami-m random variables (RVs) are derived and presented in exact form expressions using the Meijer's G function. The cascaded channels are assumed to have flat and slow fading with arbitrarily non-identical fading severity parameters. Using these results, the impact of channel correlation and fading severity parameters are investigated for the cascaded Nakagami-m channels. Furthermore, performance analysis addressed by outage probability (OP), average channel capacity, and average bit error probability (BEP) for coherently detected binary PSK and FSK signals are derived. As a consequence of the versatility of Nakagami-m distribution, the derived expressions can compromise the statistics of other useful multivariate distributions such as One-sided Gaussian distribution with m = 1/2 and Rayleigh distribution with m = 1. To the best of the authors' knowledge, the derived expressions are novel and have not been reported in the literature. To aid and verify the theoretical analysis, numerical results authenticated by Monte Carlo simulation are presented.
本文研究了任意相关且不一定同分布的级联中上-m 渐变信道的统计分析。利用 Meijer's G 函数推导出了 N 个相关 Nakagami-m 随机变量（RV）乘积的概率密度函数（PDF）、累积分布函数（CDF）和第 n 矩，并以精确形式表达出来。级联信道被假定为具有任意非相同衰减严重性参数的平缓衰减。利用这些结果，研究了级联中上-m 信道的信道相关性和衰落严重性参数的影响。此外，还得出了相干检测二进制 PSK 和 FSK 信号的中断概率 (OP)、平均信道容量和平均误码概率 (BEP) 等性能分析。由于中神-m 分布的多功能性，推导出的表达式可以折中其他有用的多元分布的统计量，如 m = 1/2 的单边高斯分布和 m = 1 的瑞利分布。据作者所知，推导出的表达式是新颖的，在文献中从未报道过。为了帮助和验证理论分析，本文介绍了经蒙特卡罗模拟验证的数值结果。
{"title":"Statistical analysis of cascaded Nakagami-m fading channels with generalized correlation","authors":"Ibrahim Ghareeb;Osama Al-Shalali","doi":"10.23919/JCN.2024.000001","DOIUrl":"https://doi.org/10.23919/JCN.2024.000001","url":null,"abstract":"This paper studies the statistical analysis of cascaded Nakagami-m fading channels that are arbitrarily correlated and not necessarily identically distributed. The probability density function (PDF), cumulative distribution function (CDF), and the nth moment for the product of N correlated Nakagami-m random variables (RVs) are derived and presented in exact form expressions using the Meijer's G function. The cascaded channels are assumed to have flat and slow fading with arbitrarily non-identical fading severity parameters. Using these results, the impact of channel correlation and fading severity parameters are investigated for the cascaded Nakagami-m channels. Furthermore, performance analysis addressed by outage probability (OP), average channel capacity, and average bit error probability (BEP) for coherently detected binary PSK and FSK signals are derived. As a consequence of the versatility of Nakagami-m distribution, the derived expressions can compromise the statistics of other useful multivariate distributions such as One-sided Gaussian distribution with m = 1/2 and Rayleigh distribution with m = 1. To the best of the authors' knowledge, the derived expressions are novel and have not been reported in the literature. To aid and verify the theoretical analysis, numerical results authenticated by Monte Carlo simulation are presented.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10459136","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140031708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.23919/JCN.2024.000003
Feng Yuan;Zeyu Hu;Zhiyuan Jiang
In this paper, we adopt the fluid limits approach to analyze the age of information (AoI) in a wireless multi-access network where users share the channel and transmissions are unreliable. We prove the convergence of the AoI occupancy measure to the fluid limit, represented by a partial differential equation (PDE). Furthermore, we demonstrate the global convergence to the equilibrium of the PDE, i.e., the stationary AoI distribution. Within this framework, we first consider the case of i.i.d. channel conditions and generate-at-will statuses for users. We demonstrate that a previously established AoI lower bound in the literature is asymptotically accurate, and a straightforward threshold-based access policy can be asymptotically optimal. Next, we consider the case where the channel states are time-varying, i.e., the Gilbert-Elliott channel model. We assume partial channel state information (CSI) is available due to channel probing singals. Theoretical analysis reveals that only a fraction of CSI is required to approach the optimal performance. Additionally, we numerically evaluate the performance of the proposed policy and the existing Whittle's index policy under time-varying channels. Simulation results demonstrate that the proposed policy outperforms the Whittle's index policy since the latter cannot adapt to time-varying channels.
{"title":"Analyzing age of information in multiaccess networks with time-varying channels: A fluid limits approach","authors":"Feng Yuan;Zeyu Hu;Zhiyuan Jiang","doi":"10.23919/JCN.2024.000003","DOIUrl":"https://doi.org/10.23919/JCN.2024.000003","url":null,"abstract":"In this paper, we adopt the fluid limits approach to analyze the age of information (AoI) in a wireless multi-access network where users share the channel and transmissions are unreliable. We prove the convergence of the AoI occupancy measure to the fluid limit, represented by a partial differential equation (PDE). Furthermore, we demonstrate the global convergence to the equilibrium of the PDE, i.e., the stationary AoI distribution. Within this framework, we first consider the case of i.i.d. channel conditions and generate-at-will statuses for users. We demonstrate that a previously established AoI lower bound in the literature is asymptotically accurate, and a straightforward threshold-based access policy can be asymptotically optimal. Next, we consider the case where the channel states are time-varying, i.e., the Gilbert-Elliott channel model. We assume partial channel state information (CSI) is available due to channel probing singals. Theoretical analysis reveals that only a fraction of CSI is required to approach the optimal performance. Additionally, we numerically evaluate the performance of the proposed policy and the existing Whittle's index policy under time-varying channels. Simulation results demonstrate that the proposed policy outperforms the Whittle's index policy since the latter cannot adapt to time-varying channels.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10459132","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140031706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The future integration of software-defined network (SDN) with the service-oriented architecture (SOA) paradigm requires new solutions to ensure the quality of service (QoS) according to the users' requirements. The paper presents a user experience-centric approach to traffic engineering and QoS/quality of experience (QoE) support for service-oriented software-defined network (SOSDN) architecture. This approach is to enable end-to-end QoS across the networking and computing domain by monitoring and agreeing on the dynamic state of their functioning. The proposed SOSDN is based on improved traffic engineering techniques, such as adaptive prioritization of services, server selection, and QoS/QoE-based routing. The developed adaptive service prioritization algorithm automatically changes the priority of flows in the network operation mode by the SDN controller for individual users under the concluded service level agreements (SLA) contract. We proposed a mathematical model of correlation of user satisfaction level by QoE score with technical QoS parameters. This model is based on the normalized value of the integral additive QoS criterion. Accordingly, ensuring the ordered user-centric QoS/QoE is carried out by means of proposed multi-criteria adaptive routing of data flows, the metric of which is based on the integral additive QoS criterion. The simulation results showed that, in contrast to known practical solutions, the integrated use of the proposed method of adaptive multi-criteria routing and prioritization of data flows provides a high level of QoE required by users in the SOSDN paradigm.
{"title":"Traffic engineering and QoS/QoE supporting techniques for emerging service-oriented software-defined network","authors":"Mykola Beshley;Natalia Kryvinska;Halyna Beshley;Oleksiy Panchenko;Mykhailo Medvetskyi","doi":"10.23919/JCN.2023.000065","DOIUrl":"https://doi.org/10.23919/JCN.2023.000065","url":null,"abstract":"The future integration of software-defined network (SDN) with the service-oriented architecture (SOA) paradigm requires new solutions to ensure the quality of service (QoS) according to the users' requirements. The paper presents a user experience-centric approach to traffic engineering and QoS/quality of experience (QoE) support for service-oriented software-defined network (SOSDN) architecture. This approach is to enable end-to-end QoS across the networking and computing domain by monitoring and agreeing on the dynamic state of their functioning. The proposed SOSDN is based on improved traffic engineering techniques, such as adaptive prioritization of services, server selection, and QoS/QoE-based routing. The developed adaptive service prioritization algorithm automatically changes the priority of flows in the network operation mode by the SDN controller for individual users under the concluded service level agreements (SLA) contract. We proposed a mathematical model of correlation of user satisfaction level by QoE score with technical QoS parameters. This model is based on the normalized value of the integral additive QoS criterion. Accordingly, ensuring the ordered user-centric QoS/QoE is carried out by means of proposed multi-criteria adaptive routing of data flows, the metric of which is based on the integral additive QoS criterion. The simulation results showed that, in contrast to known practical solutions, the integrated use of the proposed method of adaptive multi-criteria routing and prioritization of data flows provides a high level of QoE required by users in the SOSDN paradigm.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10459131","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140031619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.23919/JCN.2023.000067
Love Allen Chijioke Ahakonye;Gabriel Chukwunonso Amaizu;Cosmas Ifeanyi Nwakanma;Jae Min Lee;Dong-Seong Kim
The domain name system (DNS) has evolved into an essential component of network communications, as well as a critical component of critical industrial systems (CIS) and Supervisory Control and Data Acquisition (SCADA) network connection. DNS over HTTPS (DoH) encapsulating DNS within hypertext transfer protocol secure (HTTPS) does not eliminate network access exploitation. This paper proposes a hybrid deep learning model for the early classification of encoded network traffic into one of the two classes: DoH and NonDoH. They can be malicious, benign, or zero-day attacks. The proposed scheme incorporates the swiftness of the convolutional neural network (CNN) in extracting useful information and the ease of long short-term memory (LSTM) in learning long-term dependencies. The simulation results showed that the proposed approach accurately classifies the encoded network traffic as DoH or NonDoH and characterizes the traffic as benign, zero-day, or malicious. The proposed robust hybrid deep learning model had high accuracy and precision of 99.28%, recall of 99.75%, and AUC of 0.9975 at a minimal training and testing time of 745s and 0.000324 s, respectively. In addition to outperforming other compared contemporary algorithms and existing techniques, the proposed technique significantly detects all attack types. This study also investigated the impact of the SMOTE technique as a tool for data balancing. To further validate the reliability of the proposed scheme, an industrial control system SCADA (ICS-SCADA) dataset, in addition to two (2) other cyber-security datasets (NSL-KDD and CICDS2017), were evaluated. Mathews correlation coefficient (MCC) was employed to validate the model performance, confirming the applicability of the proposed model in a critical industrial system such as SCADA.
{"title":"Classification and characterization of encoded traffic in SCADA network using hybrid deep learning scheme","authors":"Love Allen Chijioke Ahakonye;Gabriel Chukwunonso Amaizu;Cosmas Ifeanyi Nwakanma;Jae Min Lee;Dong-Seong Kim","doi":"10.23919/JCN.2023.000067","DOIUrl":"https://doi.org/10.23919/JCN.2023.000067","url":null,"abstract":"The domain name system (DNS) has evolved into an essential component of network communications, as well as a critical component of critical industrial systems (CIS) and Supervisory Control and Data Acquisition (SCADA) network connection. DNS over HTTPS (DoH) encapsulating DNS within hypertext transfer protocol secure (HTTPS) does not eliminate network access exploitation. This paper proposes a hybrid deep learning model for the early classification of encoded network traffic into one of the two classes: DoH and NonDoH. They can be malicious, benign, or zero-day attacks. The proposed scheme incorporates the swiftness of the convolutional neural network (CNN) in extracting useful information and the ease of long short-term memory (LSTM) in learning long-term dependencies. The simulation results showed that the proposed approach accurately classifies the encoded network traffic as DoH or NonDoH and characterizes the traffic as benign, zero-day, or malicious. The proposed robust hybrid deep learning model had high accuracy and precision of 99.28%, recall of 99.75%, and AUC of 0.9975 at a minimal training and testing time of 745s and 0.000324 s, respectively. In addition to outperforming other compared contemporary algorithms and existing techniques, the proposed technique significantly detects all attack types. This study also investigated the impact of the SMOTE technique as a tool for data balancing. To further validate the reliability of the proposed scheme, an industrial control system SCADA (ICS-SCADA) dataset, in addition to two (2) other cyber-security datasets (NSL-KDD and CICDS2017), were evaluated. Mathews correlation coefficient (MCC) was employed to validate the model performance, confirming the applicability of the proposed model in a critical industrial system such as SCADA.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10459137","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140031681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.23919/JCN.2024.000010
{"title":"Copyright transfer form","authors":"","doi":"10.23919/JCN.2024.000010","DOIUrl":"https://doi.org/10.23919/JCN.2024.000010","url":null,"abstract":"","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10459130","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140031618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.23919/JCN.2023.000062
Raghu Thekke Veedu;Kiran Manjappa
This study aims to give an edge to public safety applications over commercial applications in an underlay cellular-assisted device-to-device (D2D) communication. The proposed framework introduces two frameworks: Cluster-based many-to-many resource allocation and resource sharing framework (CMMRARS) and constant time power control algorithm (CTPCA). The RB assigned to a CUE can share with multiple DUE pairs, and the DUE pairs can also use RB assigned to multiple CUEs under the many-to-many strategy. The CMMRARS framework is responsible for resource allocation and resource sharing and accordingly, it is further divided into three sub-problems. The CTPCA framework is divided into two subproblems and used to find optimal power for cellular users and D2D transmitters to avoid cross-tier and co-tier interference. The K-means clustering algorithm is employed to form application-specific clusters, and it ensures that more cellular users fall into the public safety clusters so that the D2D users will get more resource-sharing options. Cellular users use a weighted bipartite graph to form a priority list of D2D users for resource sharing. The main objective of the proposed work is to enhance the system's sum rate by simultaneously reusing the same resource by multiple D2D pairs and safeguarding the Quality of Services provided to all kinds of network users. A theoretical justification is presented to ensure that the proposed frameworks terminate after a certain number of runs and congregate to a consistent matching. Simulation results show that the proposed method influences the overall system's sum rate and provides a preference for public safety applications over commercial applications.
{"title":"An efficient application based many-to-many resource allocation and sharing with power optimization for D2D communication — A clustered approach","authors":"Raghu Thekke Veedu;Kiran Manjappa","doi":"10.23919/JCN.2023.000062","DOIUrl":"https://doi.org/10.23919/JCN.2023.000062","url":null,"abstract":"This study aims to give an edge to public safety applications over commercial applications in an underlay cellular-assisted device-to-device (D2D) communication. The proposed framework introduces two frameworks: Cluster-based many-to-many resource allocation and resource sharing framework (CMMRARS) and constant time power control algorithm (CTPCA). The RB assigned to a CUE can share with multiple DUE pairs, and the DUE pairs can also use RB assigned to multiple CUEs under the many-to-many strategy. The CMMRARS framework is responsible for resource allocation and resource sharing and accordingly, it is further divided into three sub-problems. The CTPCA framework is divided into two subproblems and used to find optimal power for cellular users and D2D transmitters to avoid cross-tier and co-tier interference. The K-means clustering algorithm is employed to form application-specific clusters, and it ensures that more cellular users fall into the public safety clusters so that the D2D users will get more resource-sharing options. Cellular users use a weighted bipartite graph to form a priority list of D2D users for resource sharing. The main objective of the proposed work is to enhance the system's sum rate by simultaneously reusing the same resource by multiple D2D pairs and safeguarding the Quality of Services provided to all kinds of network users. A theoretical justification is presented to ensure that the proposed frameworks terminate after a certain number of runs and congregate to a consistent matching. Simulation results show that the proposed method influences the overall system's sum rate and provides a preference for public safety applications over commercial applications.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10459141","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140031709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.23919/JCN.2023.000051
Mir Muhammad Suleman Sarwar;Afaq Muhammad;Wang-Cheol Song
This paper presents an intent-based networking (IBN) system for the orchestration of OpenStack-based clouds and overlay networks between multiple clouds. Clouds need to communicate with other clouds for various reasons such as reducing latency and overcoming single points of failure. An overlay network provides connectivity between multiple Clouds for communication. Moreover, there can be several paths of communication between a source and a destination cloud in the overlay network. A machine learning model can be used to proactively select the best path for efficient network performance. Communication between the source and destination can then be established over the selected path. Communication in such type of a scenario requires complex networking configurations. IBN provides a closed-loop and Intelligent system for cloud to cloud communication. To this end, IBN abstracts complex networking and cloud configurations by receiving an intent from a user, translating the intent, generating complex configurations for the intent, and deploying the configurations, thereby assuring the intent. Therefore, the IBN that is presented here has three major features: (1) It can deploy an OpenStack cloud at a target machine, (2) it can deploy GENEVE tunnels between different clouds that form an overlay network, and (3) it can then leverage the advantages of machine learning to find the best path for communication between any two clouds. As machine learning is an essential component of the intelligent IBN system, two linear and three non-linear models were tested. RNN, LSTM, and GRU models were employed for non-linear modeling. Linear regression and SVR models were employed for linear modeling. Overall all the non-linear models outperformed the linear model with an 81% R 2 score, exhibiting similar performance. Linear models also showed similar performance but with lower accuracy. The testbed contains an overlay network of 11 GENEVE tunnels between 7 OpenStack-based clouds deployed in Malaysia, Korea, Pakistan, and Cambodia at TEIN.
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