{"title":"Resource-Aware Service Prioritization in a Slice-Supportive 5G Core Control Plane for Improved Resilience and Sustenance","authors":"Supriya Kumari, Shwetha Vittal, Antony Franklin A","doi":"10.1109/CCNC51664.2024.10454708","DOIUrl":"https://doi.org/10.1109/CCNC51664.2024.10454708","url":null,"abstract":"Providing resilient and sustained service is quite challenging in the Service Based Architecture of distributed 5G Core (5GC) as multiple Network Functions (NFs) are involved to help serve the various User Service Requests (USRs) arriving in the control plane. In this regard, the continuous monitoring of individual NFs in a Closed Loop Automation (CLA) is a need of hour to keep up the robust and resilient functioning of the 5GC overall. Any unforeseen situations like the sudden failure, overload, or congestion of the NFs of the 5GC can drop the critical USRs unnecessarily. This paper proposes the proactive monitoring of the NFs of the 5GC in the control plane and utilizes it to intelligently schedule and serve the frequently arriving USRs and prioritize the critical slice service requests. Specifically, the Ford-Fulkerson algorithm popularly known as the Max-Flow problem solver is leveraged to proactively assess the NFs' performance and availability and use it effectively to serve critical service requests arriving during unexpected situations of failure and overloads. Our experiments based on the 3GPP-compliant 5G testbed show that, with the proposed solution, the native 5GC can serve 20% more predominant USRs, and the slice-supportive 5GC can serve 33% more massive Machine Type Communications (mMTC) slice USRs, and 47% more ultra Reliable Low Latency Communications (uRLLC) slice USRs while handling their respective peak traffic.","PeriodicalId":518411,"journal":{"name":"2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)","volume":"3 6","pages":"113-120"},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531631","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":"Proposal of Differential Privacy Anonymization for IoT Applications Using MQTT Broker","authors":"Kentaro Morise, Tokimasa Toyohara, Hiroaki Nishi","doi":"10.1109/CCNC51664.2024.10454877","DOIUrl":"https://doi.org/10.1109/CCNC51664.2024.10454877","url":null,"abstract":"IoT applications require secure communication methods that protect personal information contained in communication data. This study focuses on MQTT, a low-cost protocol used for IoT communication, and proposes a mechanism to anonymize communication data between IoT and clients. MQTT is a publish-subscribe model of communication where a broker handles many-to-many communications among clients. Due to the concentration of communications on the broker, it is efficient to anonymize data there. Therefore, the proposed mechanism performs differential privacy anonymization of communication data on the MQTT broker. We also propose a mechanism to anonymize data according to anonymization criteria required by senders and receivers using topic names and user properties, which are features of MQTT. We implemented the proposed mechanism in an FPGA-based MQTT broker and confirmed that it achieves the same throughput and low latency as regular MQTT communication and satisfies IoT applications such as power control and automated driving that require sub-millisecond latency.","PeriodicalId":518411,"journal":{"name":"2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)","volume":"94 7","pages":"634-635"},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531653","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":"Word Embedding with Emotionally Relevant Keyword Search for Context Detection from Smart Home Voice Commands","authors":"Brent Anderson, Razib Iqbal","doi":"10.1109/CCNC51664.2024.10454678","DOIUrl":"https://doi.org/10.1109/CCNC51664.2024.10454678","url":null,"abstract":"Voice-enabled virtual assistants have received widespread popularity in smart homes. Adding a context detection feature in voice conversations with virtual assistants can offer a more personalized experience in smart homes such that it maintains awareness of the ongoing conversation and responds appropriately. In this paper, we present a novel word embedding with emotionally relevant keyword search (WERKS) approach for context detection. This WERKS approach makes use of a combination of emotion detection, keyword search, and word embedding for context detection from voice commands and short conversations with virtual assistants. The TPOT classifier was applied over RAVDESS and a custom data set to obtain experimental results, which demonstrated a 15 and 12 percent increase in prediction accuracy of our defined contexts.","PeriodicalId":518411,"journal":{"name":"2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)","volume":"64 9","pages":"594-595"},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531826","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}
Xing-fa Liu, Wei Yu, Cheng Qian, David W. Griffith, N. Golmie
{"title":"Deep Reinforcement Learning for Channel State Information Prediction in Internet of Vehicles","authors":"Xing-fa Liu, Wei Yu, Cheng Qian, David W. Griffith, N. Golmie","doi":"10.1109/CCNC51664.2024.10454739","DOIUrl":"https://doi.org/10.1109/CCNC51664.2024.10454739","url":null,"abstract":"In this paper, we address the issue of Channel State Information (CSI) prediction of the Internet of Vehicles (loV) system, which is a highly dynamic network environment. We propose a deep reinforcement learning-based approach to predict CSI with historical data and video footage captured by smart cameras. Specifically, we use a Conventional Neural Network (CNN) to extract unique environmental characteristics, which will be sent to a Recurrent Neural Network (RNN)-based learning model so that the future CSI can be predicted. Our approach also considers the heterogeneous nature of IoV communication environments by adopting transfer learning to reduce the training cost when applying our approach to different IoV scenarios. We assess the efficacy of our proposed approach using our designed IoV simulation platform. The experimental results confirm that our approach can accurately predict CSI by using historically generated data.","PeriodicalId":518411,"journal":{"name":"2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)","volume":"66 7","pages":"388-391"},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531969","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":"Accelerating Feedback Control for QoE Fairness in Adaptive Video Streaming Over ICN","authors":"Rei Nakagawa, S. Ohzahata, Ryo Yamamoto","doi":"10.1109/CCNC51664.2024.10454865","DOIUrl":"https://doi.org/10.1109/CCNC51664.2024.10454865","url":null,"abstract":"Today, information centric networking enables adaptive video streaming clients to further improve QoE by applying flexible content-based control. However, an adaptive bitrate algorithm makes a client occupy the bottleneck link at excessively high bitrate, reducing the QoE fairness to other clients sharing the bottleneck link. Then, we propose fairAccel, a method of accelerating bitrate-based feedback control for achieving QoE fairness. fairAccel assigns more bandwidth to clients selecting the lower bitrate while suppressing content requests from clients selecting the highest bitrate on the bottleneck link. In addition, to further improve QoE fairness, fairAccel exploits the symmetric routing of ICN content request / response and applies bidirectional feedback control to the content request / response path. Thus, fairAccel accelerates feedback control by mitigating router queues under control of suppressing content requests before excessive traffic is delivered to the response path. Through simulation experiments, fairAccel improves the average bitrate and further improves QoE fairness for representative ABR algorithms.","PeriodicalId":518411,"journal":{"name":"2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)","volume":"87 11","pages":"98-106"},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531662","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}
Masahiro Takigawa, Ryochi Kataoka, I. Kanno, Yoji Kishi
{"title":"Antenna Design for Robust Millimeter Wave LoS-MIMO Link in Mobile Analog Repeater Achieving Low Latency and High Capacity","authors":"Masahiro Takigawa, Ryochi Kataoka, I. Kanno, Yoji Kishi","doi":"10.1109/CCNC51664.2024.10454777","DOIUrl":"https://doi.org/10.1109/CCNC51664.2024.10454777","url":null,"abstract":"This paper proposes an antenna design suitable for a mobile analog repeater with frequency-to-spatial multiplexing do-main conversion (FSMDC) among access and backhaul link. The relaying scheme with FSMDC, which we had proposed, converts wider band frequency multiplexing in access link into spatial multiplexing for the backhaul link only with analog circuits, and it achieves low latency and high capacity in millimeter wave spectrum. However, the typical scenario where the millimeter wave repeater is operated is LoS environment, and spatial multiplexing (i.e. LoS-MIMO) gain is not secured due to its dependency to the communication distance. For the robustness, the proposed antenna design is optimized by applying cost functions, that can achieve better channel capacity of FSMDC at any communication distance, as the fitness in genetic algorithm. The simulation results show its robustness to the communication distance of the LoS MIMO Links.","PeriodicalId":518411,"journal":{"name":"2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)","volume":"87 6","pages":"912-917"},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531881","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":"Predicting Downlink Retransmissions in 5G Networks Using Deep Learning","authors":"S. Bouk, Babatunji Omoniwa, Sachin Shetty","doi":"10.1109/CCNC51664.2024.10454769","DOIUrl":"https://doi.org/10.1109/CCNC51664.2024.10454769","url":null,"abstract":"5G networks are expected to provide high-speed, low-latency, and reliable connectivity to support various applications such as autonomous vehicles, smart cities, and the Internet of Things (IoT). However, the performance of 5G networks can be affected by several factors such as interference, congestion, signal attenuation, or attacks, which can lead to packet loss and retransmissions. Retransmissions in the network may be seen as an essential measure to improve network reliability, but a high retransmission rate may indicate issues that can help network operators mitigate possible service disruptions or threats to network users. A deep learning-based approach has been proposed to predict downlink retransmissions in 5G networks, achieving as much as 5%- 15% improvement over traditional prediction algorithms.","PeriodicalId":518411,"journal":{"name":"2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)","volume":"79 11","pages":"1056-1057"},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531894","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":"Towards Transparency in Email Security","authors":"Ronald Petrlic, David Stiegler","doi":"10.1109/CCNC51664.2024.10454854","DOIUrl":"https://doi.org/10.1109/CCNC51664.2024.10454854","url":null,"abstract":"There is no transparency in email security today. Neither senders of emails know beforehand how well the email transport is protected, nor receivers know after reception of an email how well the email was protected during transport. We make use of a solution that provides transparency towards the senders of emails and extend the solution by providing transparency towards recipients as well. We present an Outlook plugin that provides the feedback to the recipient.","PeriodicalId":518411,"journal":{"name":"2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)","volume":"10 3","pages":"1046-1047"},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531627","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":"A Study on Semi-Reliable Communications for Real-Time Data Stream Services","authors":"Kotaro Uchida, Mikiya Yoshida, Hiroyuki Koga","doi":"10.1109/CCNC51664.2024.10454725","DOIUrl":"https://doi.org/10.1109/CCNC51664.2024.10454725","url":null,"abstract":"Internet of Things (loT) services that provide stream-oriented communications have become increasingly popular, and the demand for such services is expected to grow in the future. For example, data stream services used in automated driving and connected cars require low latency and real-time communication, but it is also essential to reduce loss rates as much as possible to provide high-quality services. Therefore, we propose a semi-reliable communication scheme to provide real-time communication with low latency and loss rates by using Forward Error Correction (FEC) technique at relay routers in networks, and show its effectiveness.","PeriodicalId":518411,"journal":{"name":"2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)","volume":"110 1","pages":"1086-1087"},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531646","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":"ReVo: A Hybrid Consensus Protocol for Blockchain in the Internet of Things through Reputation and Voting Mechanisms","authors":"Shivam Barke, Gautam Srivastava","doi":"10.1109/CCNC51664.2024.10454776","DOIUrl":"https://doi.org/10.1109/CCNC51664.2024.10454776","url":null,"abstract":"In the realm of the Internet of Things (IoT), in-tegrating blockchain technology has brought about significant enhancements in security and transparency. Nevertheless, the union of these two domains grapples with persistent challenges in performance and scalability. A dilemma confronts developers and researchers: the intricate interplay between security, scalability, and performance in various consensus protocols tailored for implementing blockchain within loT ecosystems. This research paper proposes an innovative consensus protocol to tackle these challenges while striking an optimal equilibrium among these tripartite factors. Central to this proposal is introducing a hybrid architectural framework that bridges the world of loT devices and cloud service providers via distinct regional entities, all united in the objective of consensus through a novel voting mechanism hinged on reputationbased mechanisms. The core of this voting mechanism is a dynamic ensemble of nodes, each endowed with unique roles - encompassing ordinary nodes, verifiers, and assemblers. The protocol employs a random selection mechanism through a verifiable random function (VRF) to designate assem-blers, ensuring a level playing field. At the heart of the reputation model lies an analysis of region-specific traffic patterns, granting privileges to nodes that demonstrate trustworthy behaviour and high rates of request fulfillment. Extending this framework is an incentive mechanism designed to maintain the network's organic and dynamic allocation of roles. Simulation results benchmarked against Ethereum provide results of the ReVo consensus protocol for latency and transaction throughput. This paper also analyses the protocol working through a novel use case of Taxi Providers and Taxi Ride Consumer Services. Index Terms-Blockchain, Consensus Algorithm, Reputation, Internet Of things, Hybrid blockchain, Voting.","PeriodicalId":518411,"journal":{"name":"2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)","volume":"15 4","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531790","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}