{"title":"Organic 6G Continuum Architecture: A Uniform Control Plane Across Devices, Radio, and Core","authors":"Marius Corici;Fabian Eichhorn;Thomas Magedanz","doi":"10.1109/LNET.2023.3338363","DOIUrl":"https://doi.org/10.1109/LNET.2023.3338363","url":null,"abstract":"6G visionaries propose uniform control plane operations across connected devices, radio, and core networks. We introduce an advanced, organic 6G continuum concept and architecture, extending the core network’s control plane to encompass near-real-time radio control and user equipment via a novel Web-based services functionality split. This design, when compared with the 5G Service Based Architecture, showcases a reduction in complexity and an increase in flexibility.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"6 1","pages":"11-15"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10336892","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140042930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Exact Solution of the Full RMSA Problem in Elastic Optical Networks","authors":"Fabio David;José F. de Rezende;Valmir C. Barbosa","doi":"10.1109/LNET.2023.3337041","DOIUrl":"10.1109/LNET.2023.3337041","url":null,"abstract":"Exact solutions of the Routing, Modulation, and Spectrum Allocation (RMSA) problem in Elastic Optical Networks (EONs), so that the number of admitted demands is maximized while those of regenerators and frequency slots used are minimized, require a complex ILP formulation taking into account frequency-slot continuity and contiguity. We introduce the first such formulation, ending a hiatus of some years since the last ILP formulation for a much simpler RMSA variation was introduced. By exploiting a number of problem and solver specificities, we use the NSFNET topology to illustrate the practicality and importance of obtaining exact solutions.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"6 1","pages":"55-59"},"PeriodicalIF":0.0,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139340081","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}
{"title":"Modeling Super-Lightweight Cellular Traffic Prediction via Multiservice and Multimodal Feature Fusion Network","authors":"Yingqi Li;Mingxiang Hao;Xiaochuan Sun;Haijun Zhang","doi":"10.1109/LNET.2023.3329744","DOIUrl":"10.1109/LNET.2023.3329744","url":null,"abstract":"Cellular Traffic Prediction has proven to be a key enabler towards automatic network management. However, to pursue performance improvement, the existing studies mainly focus on developing complex deep neural network models, which suffer from extensive computation cost and large model size inevitably. Such models are quite difficult to be deployed on resource-constrained devices. In this letter, we propose a multiservice and multimodal feature fusion network for super-lightweight cellular network traffic prediction, namely \u0000<inline-formula> <tex-math>$m^{2}FFNet$ </tex-math></inline-formula>\u0000, to address the issue. Briefly speaking, such a network consists of a duel feature extraction channel based on grouped 3D convolution for capturing multiservice feature and multimodal feature (yielded from wavelet transform decomposition), respectively. Simulation results demonstrate that our proposal can achieve comparable prediction accuracy as the state-of-the-art deep learning methods, meanwhile obtaining much less computation burden with rather few model size.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"6 1","pages":"16-20"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134889870","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}
Sonu Rathi;Jorge F. Schmidt;Udo Schilcher;Siddhartha S. Borkotoky
{"title":"Energy-Aware Relaying in Dense LoRa Networks With Heterogeneous Batteries","authors":"Sonu Rathi;Jorge F. Schmidt;Udo Schilcher;Siddhartha S. Borkotoky","doi":"10.1109/LNET.2023.3329030","DOIUrl":"10.1109/LNET.2023.3329030","url":null,"abstract":"We propose a relaying scheme for a LoRa network’s uplink, where some end devices (EDs) overhear and relay messages from other EDs. The scheme’s salient feature is that it allows the EDs to adjust their relaying behavior according to their energy status, such that EDs with higher energy reserves perform more forwarding. This prevents early depletion of batteries at the low-energy forwarders, while still achieving high reliability levels. The network is divided into tiers. Any ED in a given tier can relay message from any other ED in certain other tier; this eliminates the need for complicated relay-selection procedures. No synchronization requirement is imposed on the EDs. We demonstrate large reductions in the loss rate with just 10% of the EDs acting as relays, operating within 1% duty cycle.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"6 1","pages":"41-45"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135362165","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}
{"title":"Energy Sustainability in Dense Radio Access Networks via High Altitude Platform Stations","authors":"Maryam Salamatmoghadasi;Amir Mehrabian;Halim Yanikomeroglus","doi":"10.1109/LNET.2023.3328918","DOIUrl":"10.1109/LNET.2023.3328918","url":null,"abstract":"The growing demand for radio access networks (RANs) driven by advanced wireless technology and the ever-increasing mobile traffic, faces significant energy consumption challenges that threaten sustainability. To address this, an architecture referring to the vertical heterogeneous network (vHetNet) has recently been proposed. Our study seeks to enhance network operations in terms of energy efficiency and sustainability by examining a vHetNet configuration, comprising a high altitude platform station (HAPS) acting as a super macro base station (SMBS), along with a macro base station (MBS) and a set of small base stations (SBSs) in a densely populated area. By intelligently managing SBSs’ sleep mode and employing HAPS’s potentials and additional capacity, our approach aims to minimize vHetNet energy consumption. The proposed method dynamically determines which SBSs to switch off based on the traffic load of SBSs, MBS, and HAPS. This innovative approach offers a flexible and promising solution to enhance network sustainability, energy efficiency, and capacity utilization without compromising the user quality-of-service (QoS). We show that our proposed method offers a scalable solution with comparable performance to exhaustive search (ES) as the optimal solution in terms of energy efficiency. Furthermore, incorporating HAPS, significantly improves grid power consumption, compared to having no offloading, reducing it by 30% for a large number of SBSs.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"6 1","pages":"21-25"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135362157","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}
{"title":"Task Offloading and Approximate Computing in Solar Powered IoT Networks","authors":"Junfei Zhan;Jiayi Wu;Tengjiao He;Kwan-Wu Chin","doi":"10.1109/LNET.2023.3328893","DOIUrl":"10.1109/LNET.2023.3328893","url":null,"abstract":"This letter considers approximate computing and task offloading in a solar powered Internet of Things (IoT) network. Specifically, it addresses the novel problem of minimizing the energy consumption of IoT devices by either offloading their tasks or executing these tasks in approximate mode. To this end, this letter outlines a novel mixed integer linear program (MILP) that computes the minimum total energy required to execute tasks. It optimizes four key factors: (i) task offloading decision of devices, (ii) use of approximate computing by devices, (iii) channel allocation, and (iv) virtual machine (VM) assignment. Further, it outlines a novel solution that determines these factors using channel gain and energy arrival estimates obtained from digital twins (DTs). The results show that our DT-based solution uses at most 1.62x more energy than MILP.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"6 1","pages":"26-30"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135263191","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}
{"title":"Intrusion Detection System for MIL-STD-1553 Based on Convolutional Neural Networks With Binary Images and Adaptive Quantization","authors":"Gianmarco Baldini;Kandeepan Sithamparanathan","doi":"10.1109/LNET.2023.3324508","DOIUrl":"10.1109/LNET.2023.3324508","url":null,"abstract":"This letter proposes an Intrusion Detection System (IDS) for the MIL-STD-1553 serial bus protocol, which is used in the aerospace systems. This letter proposes a novel encoding scheme to transform all the traffic data of MIL-STD-1553 including header, payload and time of packet transmission to binary images, which are given as an input to a Convolutional Neural Network (CNN). The encoding scheme is based on a quantization parameter \u0000<inline-formula> <tex-math>$Q_{b}$ </tex-math></inline-formula>\u0000, which must be tuned to support the optimal attack detection performance of the algorithm. Then, this letter proposes a pre-processing adaptive step before the application of CNN to select the optimal value of \u0000<inline-formula> <tex-math>$Q_{b}$ </tex-math></inline-formula>\u0000. The proposed approach is applied on a recently published cybersecurity data set of MIL-STD-1553 traffic, where it achieves a detection accuracy of 99.31%.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"6 1","pages":"50-54"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136301723","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}