Pub Date : 2022-10-01DOI: 10.1109/FNWF55208.2022.00046
Amine Boukhtouta, Taous Madi, M. Pourzandi, H. Alameddine
The convergence of Telecommunication and industry operational networks towards cloud native applications has enabled the idea to integrate protection layers to harden security posture and management of cloud native based deployments. In this paper, we propose a data-driven approach to support detection of anomalies in cloud native application based on a graph neural network. The essence of the profiling relies on capturing interactions between different perspectives in cloud native applications through a network dependency graph and transforming it to a computational graph neural network. The latter is used to profile different deployed assets like micro-service types, workloads' namespaces, worker machines, management and orchestration machines as well as clusters. As a first phase of the profiling, we consider a fine-grained profiling on microservice types with an emphasis on network traffic indicators. These indicators are collected on distributed Kubernetes (K8S) deployment premises. Experimental results shows good trade-off in terms of accuracy and recall with respect to micro-service types profiling (around 96%). In addition, we used predictions entropy scores to infer anomalies in testing data. These scores allow to segregate between benign and anomalous graphs, where we identified 19 out of 23 anomalies. Moreover, by using entropy scores, we can conduct a root cause analysis to infer problematic micro-services.
{"title":"Cloud Native Applications Profiling using a Graph Neural Networks Approach","authors":"Amine Boukhtouta, Taous Madi, M. Pourzandi, H. Alameddine","doi":"10.1109/FNWF55208.2022.00046","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00046","url":null,"abstract":"The convergence of Telecommunication and industry operational networks towards cloud native applications has enabled the idea to integrate protection layers to harden security posture and management of cloud native based deployments. In this paper, we propose a data-driven approach to support detection of anomalies in cloud native application based on a graph neural network. The essence of the profiling relies on capturing interactions between different perspectives in cloud native applications through a network dependency graph and transforming it to a computational graph neural network. The latter is used to profile different deployed assets like micro-service types, workloads' namespaces, worker machines, management and orchestration machines as well as clusters. As a first phase of the profiling, we consider a fine-grained profiling on microservice types with an emphasis on network traffic indicators. These indicators are collected on distributed Kubernetes (K8S) deployment premises. Experimental results shows good trade-off in terms of accuracy and recall with respect to micro-service types profiling (around 96%). In addition, we used predictions entropy scores to infer anomalies in testing data. These scores allow to segregate between benign and anomalous graphs, where we identified 19 out of 23 anomalies. Moreover, by using entropy scores, we can conduct a root cause analysis to infer problematic micro-services.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":"418 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123447137","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 : 2022-10-01DOI: 10.1109/FNWF55208.2022.00032
H. Kholidy, A. Karam, Jeffrey H. Reed, Yusuf Elazzazi
Network slicing is a key feature of 5G that enables network operators to physically segregate traffic on different radio networks, slice a single network, or combine the capacity of multiple networks and slice the pooled resources. In this paper, we study the network slice-related emergence topics such as slice orchestration, resource federation, and network slice trust and security. Moreover, we introduce our new 5G testbed that helps researchers and students to showcase, test, and validate their 5G services, prototypes, and algorithms on. We test and validate the testbed using two real-time experiments namely (1) Monitoring the violations of the SLA for different performance metrics such as CPU, memory utilization, and network bandwidth, and (2) red team/blue team exercise using Metasploit, Ksniff, and Snort.
{"title":"An Experimental 5G Testbed for Secure Network Slicing Evaluation","authors":"H. Kholidy, A. Karam, Jeffrey H. Reed, Yusuf Elazzazi","doi":"10.1109/FNWF55208.2022.00032","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00032","url":null,"abstract":"Network slicing is a key feature of 5G that enables network operators to physically segregate traffic on different radio networks, slice a single network, or combine the capacity of multiple networks and slice the pooled resources. In this paper, we study the network slice-related emergence topics such as slice orchestration, resource federation, and network slice trust and security. Moreover, we introduce our new 5G testbed that helps researchers and students to showcase, test, and validate their 5G services, prototypes, and algorithms on. We test and validate the testbed using two real-time experiments namely (1) Monitoring the violations of the SLA for different performance metrics such as CPU, memory utilization, and network bandwidth, and (2) red team/blue team exercise using Metasploit, Ksniff, and Snort.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122910108","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 : 2022-10-01DOI: 10.1109/FNWF55208.2022.00014
Sandesh Dhawaskar Sathyanarayana, Murugan Sankaradas, S. Chakradhar
5G-LAN is an enterprise local area network (LAN) that leverages 5G technology for wireless connectivity instead of WiFi. 5G technology is unique: it uses network slicing to distinguish customers in the same traffic class using new QoS technologies in the RF domain. This unique ability is not supported by most enterprise LANs, which rely primarily on DiffServ-like technologies that distinguish among traffic classes rather than customers. We first show that this mismatch in QoS between the 5G network and the LAN affects the accuracy of insights from the LAN-resident analytics applications. We systematically analyze the root causes of the QoS mismatch and propose a first-of-a-kind 5G-LAN orchestrator (5GLoR). 5GLoR is a middleware that applications can use to preserve the QoS of their 5G data streams through the enterprise LAN. In most cases, the loss of QoS is not due to the oversubscription of LAN switches but primarily due to the inefficient assignment of 5G data to queues at ingress and egress ports. 5GLoR periodically analyzes the status of these queues, provides suitable DSCP identifiers to the application, and installs relevant switch re-write rules (to change DSCP identifiers between switches) to continuously preserve the QoS of the 5G data through the LAN. 5GLoR improves the RTP frame level delay and inter-frame delay by 212% and 122%, respectively, for the WebRTC application. Additionally, with 5GLoR, the accuracy of two example applications (face detection and recognition) improved by 33%, while the latency was reduced by about 25%. Our experiments show that the performance (accuracy and latency) of applications on a 5G-LAN performs well with the proposed 5GLoR compared to the same applications on MEC. This is significant because 5G-LAN offers an order of magnitude more computing, networking, and storage resources to the applications than the resource-constrained MEC, and mature enterprise technologies can be used to deploy, manage, and update IoT applications.
{"title":"5GLoR: 5G LAN Orchestration for enterprise IoT applications","authors":"Sandesh Dhawaskar Sathyanarayana, Murugan Sankaradas, S. Chakradhar","doi":"10.1109/FNWF55208.2022.00014","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00014","url":null,"abstract":"5G-LAN is an enterprise local area network (LAN) that leverages 5G technology for wireless connectivity instead of WiFi. 5G technology is unique: it uses network slicing to distinguish customers in the same traffic class using new QoS technologies in the RF domain. This unique ability is not supported by most enterprise LANs, which rely primarily on DiffServ-like technologies that distinguish among traffic classes rather than customers. We first show that this mismatch in QoS between the 5G network and the LAN affects the accuracy of insights from the LAN-resident analytics applications. We systematically analyze the root causes of the QoS mismatch and propose a first-of-a-kind 5G-LAN orchestrator (5GLoR). 5GLoR is a middleware that applications can use to preserve the QoS of their 5G data streams through the enterprise LAN. In most cases, the loss of QoS is not due to the oversubscription of LAN switches but primarily due to the inefficient assignment of 5G data to queues at ingress and egress ports. 5GLoR periodically analyzes the status of these queues, provides suitable DSCP identifiers to the application, and installs relevant switch re-write rules (to change DSCP identifiers between switches) to continuously preserve the QoS of the 5G data through the LAN. 5GLoR improves the RTP frame level delay and inter-frame delay by 212% and 122%, respectively, for the WebRTC application. Additionally, with 5GLoR, the accuracy of two example applications (face detection and recognition) improved by 33%, while the latency was reduced by about 25%. Our experiments show that the performance (accuracy and latency) of applications on a 5G-LAN performs well with the proposed 5GLoR compared to the same applications on MEC. This is significant because 5G-LAN offers an order of magnitude more computing, networking, and storage resources to the applications than the resource-constrained MEC, and mature enterprise technologies can be used to deploy, manage, and update IoT applications.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117264162","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 : 2022-10-01DOI: 10.1109/FNWF55208.2022.00023
Jaya Lakshmi Ravipudi, M. Brandt-Pearce
The effects of crosstalk and fragmentation cause unnecessary blocking in space-division multiplexing-based elastic optical networks. A routing, modulation, core, and spectrum allocation (RMCSA) algorithm is proposed in this paper using a novel score function that balances the crosstalk and fragmentation. Reduced blocking and fragmentation levels are observed when compared with the benchmark algorithms.
{"title":"A Score Function Heuristic for Crosstalk- and Fragmentation-Aware Dynamic Routing, Modulation, Core, and Spectrum Allocation in SDM-EONs","authors":"Jaya Lakshmi Ravipudi, M. Brandt-Pearce","doi":"10.1109/FNWF55208.2022.00023","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00023","url":null,"abstract":"The effects of crosstalk and fragmentation cause unnecessary blocking in space-division multiplexing-based elastic optical networks. A routing, modulation, core, and spectrum allocation (RMCSA) algorithm is proposed in this paper using a novel score function that balances the crosstalk and fragmentation. Reduced blocking and fragmentation levels are observed when compared with the benchmark algorithms.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114333588","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 : 2022-10-01DOI: 10.1109/FNWF55208.2022.00122
Sokratis Barmpounakis, A. Georgakopoulos, P. Vlacheas, P. Demestichas
It is a key challenge and obligation for future networks to deliver high-quality wireless for enabling novel services and application to flourish for the benefit of humans on a personal level, for society as a whole, as well as for business and innovation. The dynamics, as well as the heterogeneity of the foreseen 6G system in terms of communication technologies, frequencies used, management frameworks, etc. make the need for flexibility of utmost importance. Although several steps are being made to this direction, flexible networks, capable of dynamically adapting to changes, (re)configuring themselves, exploiting highly dynamic resources in terms of availability in a three- dimensional network space is still a challenge from different perspectives. This paper identifies the key challenges, technical enablers, as well as current efforts towards the realization of the 3D, flexible 6G “network of networks” concept.
{"title":"Towards 3D Flexible 6G Networks: Status, Challenges and Technical Enablers","authors":"Sokratis Barmpounakis, A. Georgakopoulos, P. Vlacheas, P. Demestichas","doi":"10.1109/FNWF55208.2022.00122","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00122","url":null,"abstract":"It is a key challenge and obligation for future networks to deliver high-quality wireless for enabling novel services and application to flourish for the benefit of humans on a personal level, for society as a whole, as well as for business and innovation. The dynamics, as well as the heterogeneity of the foreseen 6G system in terms of communication technologies, frequencies used, management frameworks, etc. make the need for flexibility of utmost importance. Although several steps are being made to this direction, flexible networks, capable of dynamically adapting to changes, (re)configuring themselves, exploiting highly dynamic resources in terms of availability in a three- dimensional network space is still a challenge from different perspectives. This paper identifies the key challenges, technical enablers, as well as current efforts towards the realization of the 3D, flexible 6G “network of networks” concept.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126587514","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 : 2022-10-01DOI: 10.1109/FNWF55208.2022.00086
Jack Brassil
We describe a prototype of Science Traffic as a Service (STAAS), a decentralized, cooperative system to collect, filter and distribute a diverse collection of real and synthetic data traffic to the global experimental research testbed user community. Available on-demand to networking experimenters through a web dashboard, the tool promises to elevate traffic selection and distribution to a first class experimental instrumentation resource. We believe the alternatives to providing this service on large-scale federated testbeds are increasingly unworkable for experimenters. As backbone networks increasingly deploy 100–1000 Gbps communications links we are moving beyond the point where experimenters can reasonably be asked to independently, safely, and efficiently create test traffic that provides the realism that their investigations will demand. We seek to deploy our prototype at campuses and testbeds attached to the emerging FABRIC mid-scale networking research infrastructure. We describe prototype design, operation and implementation, and how it is integrated with existing campus networking infrastructure. We explain how remote experimenters will request and acquire network traffic to study. We detail our process for forwarding campus traffic onto the experimental testbed, while striving to preserve both the timing integrity of the flows and the data privacy of their payloads.†
{"title":"Network Traffic as a Federated Testbed Service","authors":"Jack Brassil","doi":"10.1109/FNWF55208.2022.00086","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00086","url":null,"abstract":"We describe a prototype of Science Traffic as a Service (STAAS), a decentralized, cooperative system to collect, filter and distribute a diverse collection of real and synthetic data traffic to the global experimental research testbed user community. Available on-demand to networking experimenters through a web dashboard, the tool promises to elevate traffic selection and distribution to a first class experimental instrumentation resource. We believe the alternatives to providing this service on large-scale federated testbeds are increasingly unworkable for experimenters. As backbone networks increasingly deploy 100–1000 Gbps communications links we are moving beyond the point where experimenters can reasonably be asked to independently, safely, and efficiently create test traffic that provides the realism that their investigations will demand. We seek to deploy our prototype at campuses and testbeds attached to the emerging FABRIC mid-scale networking research infrastructure. We describe prototype design, operation and implementation, and how it is integrated with existing campus networking infrastructure. We explain how remote experimenters will request and acquire network traffic to study. We detail our process for forwarding campus traffic onto the experimental testbed, while striving to preserve both the timing integrity of the flows and the data privacy of their payloads.†","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121349658","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 : 2022-10-01DOI: 10.1109/FNWF55208.2022.00100
Nina Slamnik-Kriještorac, W. Vandenberghe, Rakshith Kusumakar, Karel Kural, M. Klepper, G. Kakes, L. Velde, J. Márquez-Barja
A big challenge of autonomous mobility is guaranteeing safety in all possible extreme and unexpected scenarios. For the last 25 years, the sector therefore focused on improving the automation functions. Nevertheless, autonomous mobility is still not part of daily life. The 5G-Blueprint project follows an alternative approach: direct control teleoperation. This concept relies on 5G connectivity to remove the physical coupling between the human driver or sailor and the controlled vehicle or vessel. This way, automation and teleoperation can be combined as complementary technologies, assigning them to different segments of a single trajectory, realizing driverless mobility in a safe, scalable, and cost-efficient manner. However, this mode of operation brings demanding connectivity requirements, such as high uplink bandwidth, low latency and ultra-reliability at the same time, for which the potential of 5G needs to be studied and explored. In this paper, we present our performance validation strategies to pursue 5G-enhanced teleoperation in real-life environment (e.g., public roads, busy sea ports), including some initial results that we collected during the in-country piloting phase.
{"title":"Performance Validation Strategies for 5G-enhanced Transport & Logistics: The 5G-Blueprint Approach","authors":"Nina Slamnik-Kriještorac, W. Vandenberghe, Rakshith Kusumakar, Karel Kural, M. Klepper, G. Kakes, L. Velde, J. Márquez-Barja","doi":"10.1109/FNWF55208.2022.00100","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00100","url":null,"abstract":"A big challenge of autonomous mobility is guaranteeing safety in all possible extreme and unexpected scenarios. For the last 25 years, the sector therefore focused on improving the automation functions. Nevertheless, autonomous mobility is still not part of daily life. The 5G-Blueprint project follows an alternative approach: direct control teleoperation. This concept relies on 5G connectivity to remove the physical coupling between the human driver or sailor and the controlled vehicle or vessel. This way, automation and teleoperation can be combined as complementary technologies, assigning them to different segments of a single trajectory, realizing driverless mobility in a safe, scalable, and cost-efficient manner. However, this mode of operation brings demanding connectivity requirements, such as high uplink bandwidth, low latency and ultra-reliability at the same time, for which the potential of 5G needs to be studied and explored. In this paper, we present our performance validation strategies to pursue 5G-enhanced teleoperation in real-life environment (e.g., public roads, busy sea ports), including some initial results that we collected during the in-country piloting phase.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132964312","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 : 2022-10-01DOI: 10.1109/FNWF55208.2022.00104
Haibin Zhang, Y. Toh, Iñaki Martín Soroa, D. Morris, Marie-Pauline Roukens
The use of real-time video-audio and vital patient data significantly improves the effectiveness of remote assessment in emergencies, compared with the current audio-only pre-hospital communications. This was found during recently completed 5G trials, involving ambulance professionals. The aim of the trials was to investigate how 5G-enabled video-audio and vital patient data monitoring can benefit remote patient assessment and what are the potential implementation constraints. An indoor 5G standalone network was used for the trials, with measured round-trip time as low as 7 ms. With the trials, it was verified that the decision making was quicker and more accurate when the remotely based Chief Medical Officer of an ambulance service received real-time video-audio complimented with vital patient data (for example electrocardiogram) from the paramedic. This meant that the pre-hospital triage significantly improved accelerating patient treatment and avoiding unnecessary conveyance to the hospital. Recommendations are also given addressing the observed implementation constraints.
{"title":"Pre-hospital Triage Improvement for Ambulances via 5G Video and Vital Data Communication","authors":"Haibin Zhang, Y. Toh, Iñaki Martín Soroa, D. Morris, Marie-Pauline Roukens","doi":"10.1109/FNWF55208.2022.00104","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00104","url":null,"abstract":"The use of real-time video-audio and vital patient data significantly improves the effectiveness of remote assessment in emergencies, compared with the current audio-only pre-hospital communications. This was found during recently completed 5G trials, involving ambulance professionals. The aim of the trials was to investigate how 5G-enabled video-audio and vital patient data monitoring can benefit remote patient assessment and what are the potential implementation constraints. An indoor 5G standalone network was used for the trials, with measured round-trip time as low as 7 ms. With the trials, it was verified that the decision making was quicker and more accurate when the remotely based Chief Medical Officer of an ambulance service received real-time video-audio complimented with vital patient data (for example electrocardiogram) from the paramedic. This meant that the pre-hospital triage significantly improved accelerating patient treatment and avoiding unnecessary conveyance to the hospital. Recommendations are also given addressing the observed implementation constraints.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130435652","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 : 2022-10-01DOI: 10.1109/FNWF55208.2022.00085
Ravi Potluri, Kristen Young, Jin Yang
Efficient management of network slices requires an integrated approach considering multiple aspects of the network as well as a dynamic approach that uses the feedback from the network to optimize decision-making. In this paper, we propose the concept of multi-stage control in 5G wireless networks. We also discuss the architecture for management and execution of multi-stage control, using polymorphic algorithms running at the right level of network granularity. The relationship of polymorphic algorithm execution with respect to industry standards such as O-RAN and 3GPP standards is also discussed.
{"title":"Multi-Stage, Dynamic Control of Wireless Network Slices with Polymorphic Algorithms","authors":"Ravi Potluri, Kristen Young, Jin Yang","doi":"10.1109/FNWF55208.2022.00085","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00085","url":null,"abstract":"Efficient management of network slices requires an integrated approach considering multiple aspects of the network as well as a dynamic approach that uses the feedback from the network to optimize decision-making. In this paper, we propose the concept of multi-stage control in 5G wireless networks. We also discuss the architecture for management and execution of multi-stage control, using polymorphic algorithms running at the right level of network granularity. The relationship of polymorphic algorithm execution with respect to industry standards such as O-RAN and 3GPP standards is also discussed.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134589191","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 : 2022-10-01DOI: 10.1109/FNWF55208.2022.00053
Taisho Sasada, Yuzo Taenaka, Y. Kadobayashi
Spatio-temporal data is useful for various applications such as urban planning, epidemiology, and natural disasters, but causes exposure of private information, such as home/workplace addresses, because it involves people's trajec-tories. Local Differential Privacy (LDP) based processing is a promising technology for removing sensitive information from spatio-temporal data. A LDP-based processing adds a certain amount of noise to make each piece of data indistinguishable while keeping its intrinsic value. However, LDP is vulnerable to data amplification. When a data store receives data from any device, the data store only appends the received data to existing data. This allows anyone to inject any amount of data into the data and manipulate the trend of the whole data. To tackle this problem, we design a data collection method enabling a data store to collect statistical trends of data from every device irrespective of the data volume. We utilize an Oblivious Transfer (OT) protocol that performs a packet sampling at the reception side, the data store. This sampling enables the collection of statistical trends but requires adjusting LDP processing because the amount of noise is determined by the assumption that the data store receives every piece of LDP-processed data. We then propose an adjustment method for LDP-based process based on the Euclidean algorithm. We conducted qualitative and experimental overhead analysis and showed that the proposed method decouples the relationship between statistical trend and data volume. We also show the processing load can be acceptable on small devices such as smartphones and loT.
{"title":"Decoupling Statistical Trends from Data Volume on LDP-Based Spatio-Temporal Data Collection","authors":"Taisho Sasada, Yuzo Taenaka, Y. Kadobayashi","doi":"10.1109/FNWF55208.2022.00053","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00053","url":null,"abstract":"Spatio-temporal data is useful for various applications such as urban planning, epidemiology, and natural disasters, but causes exposure of private information, such as home/workplace addresses, because it involves people's trajec-tories. Local Differential Privacy (LDP) based processing is a promising technology for removing sensitive information from spatio-temporal data. A LDP-based processing adds a certain amount of noise to make each piece of data indistinguishable while keeping its intrinsic value. However, LDP is vulnerable to data amplification. When a data store receives data from any device, the data store only appends the received data to existing data. This allows anyone to inject any amount of data into the data and manipulate the trend of the whole data. To tackle this problem, we design a data collection method enabling a data store to collect statistical trends of data from every device irrespective of the data volume. We utilize an Oblivious Transfer (OT) protocol that performs a packet sampling at the reception side, the data store. This sampling enables the collection of statistical trends but requires adjusting LDP processing because the amount of noise is determined by the assumption that the data store receives every piece of LDP-processed data. We then propose an adjustment method for LDP-based process based on the Euclidean algorithm. We conducted qualitative and experimental overhead analysis and showed that the proposed method decouples the relationship between statistical trend and data volume. We also show the processing load can be acceptable on small devices such as smartphones and loT.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128115396","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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