Pub Date : 2020-11-16DOI: 10.1109/LCN48667.2020.9314851
Ramtin Aryan, A. Yazidi, A. Bouhoula, P. Engelstad
Policy anomalies are frequent in nowadays’s computer networks due to their increasing configuration complexity. Resolving policy anomalies usually requires network administrator intervention, which is a time-intensive and error-prone process. In this paper, we present Net Auto-Solver, a formal approach for automatic resolution of OpenFlow anomalies. The approach resorts to the concept of high-level policies to not only detect policy violations but also correct them on-the-fly. Our approach is fully automated and does not require interaction with the network administrator. Although there is a multitude of research works on detecting anomalies in SDN, research to correct those anomalies in an automatic manner is extremely scarce. At the heart of our approach, we propose two inference systems to perform corrective actions to the policy. We provide some experimental results involving real-life network configurations to show the performance of our approach. The first results are very promising.
{"title":"Net Auto-Solver: A formal approach for automatic resolution of OpenFlow anomalies","authors":"Ramtin Aryan, A. Yazidi, A. Bouhoula, P. Engelstad","doi":"10.1109/LCN48667.2020.9314851","DOIUrl":"https://doi.org/10.1109/LCN48667.2020.9314851","url":null,"abstract":"Policy anomalies are frequent in nowadays’s computer networks due to their increasing configuration complexity. Resolving policy anomalies usually requires network administrator intervention, which is a time-intensive and error-prone process. In this paper, we present Net Auto-Solver, a formal approach for automatic resolution of OpenFlow anomalies. The approach resorts to the concept of high-level policies to not only detect policy violations but also correct them on-the-fly. Our approach is fully automated and does not require interaction with the network administrator. Although there is a multitude of research works on detecting anomalies in SDN, research to correct those anomalies in an automatic manner is extremely scarce. At the heart of our approach, we propose two inference systems to perform corrective actions to the policy. We provide some experimental results involving real-life network configurations to show the performance of our approach. The first results are very promising.","PeriodicalId":245782,"journal":{"name":"2020 IEEE 45th Conference on Local Computer Networks (LCN)","volume":"2017 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115774069","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 : 2020-11-16DOI: 10.1109/LCN48667.2020.9314780
M. Al-Shaboti, Gang Chen, I. Welch
Multiple users often share their Internet of Things (IoT) devices in a smart space. However, existing IoT systems do not support IoT sharing between multiple users or take into account the security risks associated with using shared devices. We address this problem by proposing a new multi-user IoT Secure Sharing (IoTSS) system supported by a newly designed sharing policy language. Our approach treats the policies as constraints in the context of an optimisation problem to fulfil user activities using the least vulnerable devices. We show how IoT sharing can be transformed into an equivalent Integer Linear Programming (ILP) problem, which can be solved efficiently and effectively by off-the-shelf Integer ILP solvers. To study the practical feasibility of IoTSS, we have implemented a proof-of-concept proxy-based prototype for the popularly used Mozilla WebThings Gateway. We found that the proxy service can achieve policies enforcement without incurring statistically significant time overhead.
{"title":"Achieving IoT Devices Secure Sharing in Multi-User Smart Space","authors":"M. Al-Shaboti, Gang Chen, I. Welch","doi":"10.1109/LCN48667.2020.9314780","DOIUrl":"https://doi.org/10.1109/LCN48667.2020.9314780","url":null,"abstract":"Multiple users often share their Internet of Things (IoT) devices in a smart space. However, existing IoT systems do not support IoT sharing between multiple users or take into account the security risks associated with using shared devices. We address this problem by proposing a new multi-user IoT Secure Sharing (IoTSS) system supported by a newly designed sharing policy language. Our approach treats the policies as constraints in the context of an optimisation problem to fulfil user activities using the least vulnerable devices. We show how IoT sharing can be transformed into an equivalent Integer Linear Programming (ILP) problem, which can be solved efficiently and effectively by off-the-shelf Integer ILP solvers. To study the practical feasibility of IoTSS, we have implemented a proof-of-concept proxy-based prototype for the popularly used Mozilla WebThings Gateway. We found that the proxy service can achieve policies enforcement without incurring statistically significant time overhead.","PeriodicalId":245782,"journal":{"name":"2020 IEEE 45th Conference on Local Computer Networks (LCN)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114906121","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 : 2020-11-16DOI: 10.1109/LCN48667.2020.9314819
Syed Usman Jamil, M. A. Khan, S. Rehman
Smart cities enhance the quality of life for citizens by utilising cutting edge technologies such as 5G and beyond wireless communication. Internet of Everything (IoE) enables a smart city to power and monitor multiple geographically distributed IoE nodes to support a range of applications across various domains such as energy and resource management, intelligent transport systems and E-health to name a few. Due to unprecedented increase in the use of IoE technology and the volume of data it generates, there is need to develop a state-of-the-art architecture to support wide range of applications in order to manage smart city resources in an efficient and intelligent manner. In this work in progress article, we present a conceptual design to establish efficient task off-loading and resource allocation architecture for smart city environment. We first present a novel conceptual design, called conventional model for task off-loading and resource allocation. Secondly, we build upon the conventional model to introduce the intelligence for task off-loading and resource allocation problem. We further develop the specific research questions in order to design and evaluate the performance of various units within the above mentioned models to accommodate the technological advancements such as the use of Artificial Intelligence (AI) in the sixth generation (6G) wireless communication era.
{"title":"Intelligent Task Off-Loading and Resource Allocation for 6G Smart City Environment","authors":"Syed Usman Jamil, M. A. Khan, S. Rehman","doi":"10.1109/LCN48667.2020.9314819","DOIUrl":"https://doi.org/10.1109/LCN48667.2020.9314819","url":null,"abstract":"Smart cities enhance the quality of life for citizens by utilising cutting edge technologies such as 5G and beyond wireless communication. Internet of Everything (IoE) enables a smart city to power and monitor multiple geographically distributed IoE nodes to support a range of applications across various domains such as energy and resource management, intelligent transport systems and E-health to name a few. Due to unprecedented increase in the use of IoE technology and the volume of data it generates, there is need to develop a state-of-the-art architecture to support wide range of applications in order to manage smart city resources in an efficient and intelligent manner. In this work in progress article, we present a conceptual design to establish efficient task off-loading and resource allocation architecture for smart city environment. We first present a novel conceptual design, called conventional model for task off-loading and resource allocation. Secondly, we build upon the conventional model to introduce the intelligence for task off-loading and resource allocation problem. We further develop the specific research questions in order to design and evaluate the performance of various units within the above mentioned models to accommodate the technological advancements such as the use of Artificial Intelligence (AI) in the sixth generation (6G) wireless communication era.","PeriodicalId":245782,"journal":{"name":"2020 IEEE 45th Conference on Local Computer Networks (LCN)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126842360","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 : 2020-11-16DOI: 10.1109/LCN48667.2020.9314802
Sumitro Bhaumik, Sandip Chakraborty
Container resource management is non-trivial over hyperconverged platforms where the storage is shared among host servers. Therefore, the same backbone network is used by storage and regular network traffic. In this paper, we first characterize this problem by analyzing the nature of the traffic from storage workloads and its impact on the network workloads in a container-based virtualization environment. Accordingly, we develop CONtrol, a resource management approach for assuring network workloads’ performance in the presence of storage workloads. CONtrol uses a proportional-integral-derivative controller to dynamically decide the bandwidth redistribution among various workloads. Additionally, it uses a container migration strategy for balancing the workloads across different servers of a hyperconverged platform. We have implemented CONtrol over a hyperconverged platform with 5 physical servers. Thorough testing indicates that it can significantly improve the performance of various benchmark applications over a containerized hyper-converged platform.
{"title":"Managing Container QoS with Network and Storage Workloads over a Hyperconverged Platform","authors":"Sumitro Bhaumik, Sandip Chakraborty","doi":"10.1109/LCN48667.2020.9314802","DOIUrl":"https://doi.org/10.1109/LCN48667.2020.9314802","url":null,"abstract":"Container resource management is non-trivial over hyperconverged platforms where the storage is shared among host servers. Therefore, the same backbone network is used by storage and regular network traffic. In this paper, we first characterize this problem by analyzing the nature of the traffic from storage workloads and its impact on the network workloads in a container-based virtualization environment. Accordingly, we develop CONtrol, a resource management approach for assuring network workloads’ performance in the presence of storage workloads. CONtrol uses a proportional-integral-derivative controller to dynamically decide the bandwidth redistribution among various workloads. Additionally, it uses a container migration strategy for balancing the workloads across different servers of a hyperconverged platform. We have implemented CONtrol over a hyperconverged platform with 5 physical servers. Thorough testing indicates that it can significantly improve the performance of various benchmark applications over a containerized hyper-converged platform.","PeriodicalId":245782,"journal":{"name":"2020 IEEE 45th Conference on Local Computer Networks (LCN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126430611","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 : 2020-11-16DOI: 10.1109/LCN48667.2020.9314779
Ahmed Alutaibi, S. Ganti
Machine Learning research has progressed tremendously in recent years. Major fields that machine learning pushed its frontier were prediction and data modeling. In this work we evaluate the applicability of a handpicked prediction models on predicting inter-day aggregate network traffic. We chose models that work best with multi-variate feature space. They represent linear, decision trees, and neural network models. Over the years, predicting network traffic has resorted to predicting point values. This approach is not descriptive enough and naively gives a shallow conclusion about the data. We propose using a quantile loss function that predicts boundaries or prediction intervals. Our results show that linear models fared well compared to their simplicity while Long Short-Term Memory Neural Networks gave best results across all experiments.
{"title":"Network Traffic Prediction using Quantile Regression with linear, Tree, and Deep Learning Models","authors":"Ahmed Alutaibi, S. Ganti","doi":"10.1109/LCN48667.2020.9314779","DOIUrl":"https://doi.org/10.1109/LCN48667.2020.9314779","url":null,"abstract":"Machine Learning research has progressed tremendously in recent years. Major fields that machine learning pushed its frontier were prediction and data modeling. In this work we evaluate the applicability of a handpicked prediction models on predicting inter-day aggregate network traffic. We chose models that work best with multi-variate feature space. They represent linear, decision trees, and neural network models. Over the years, predicting network traffic has resorted to predicting point values. This approach is not descriptive enough and naively gives a shallow conclusion about the data. We propose using a quantile loss function that predicts boundaries or prediction intervals. Our results show that linear models fared well compared to their simplicity while Long Short-Term Memory Neural Networks gave best results across all experiments.","PeriodicalId":245782,"journal":{"name":"2020 IEEE 45th Conference on Local Computer Networks (LCN)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116633666","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 : 2020-11-16DOI: 10.1109/LCN48667.2020.9314805
Eryk Schiller, Elfat Esati, Sina Rafati Niya, B. Stiller
This work develops an integration of Blockchains (BC) with the Internet-of-Things (IoT) using a highly constrained TelosB IoT platform based on the MSP430 processor family and CC2420 IEEE 802.15.4-compliant radio interfaces. The system is evaluated in an indoor office environment focusing on overhead and energy efficiency of BC transaction (TX) transmissions.
{"title":"Blockchain on MSP430 with IEEE 802.15.4","authors":"Eryk Schiller, Elfat Esati, Sina Rafati Niya, B. Stiller","doi":"10.1109/LCN48667.2020.9314805","DOIUrl":"https://doi.org/10.1109/LCN48667.2020.9314805","url":null,"abstract":"This work develops an integration of Blockchains (BC) with the Internet-of-Things (IoT) using a highly constrained TelosB IoT platform based on the MSP430 processor family and CC2420 IEEE 802.15.4-compliant radio interfaces. The system is evaluated in an indoor office environment focusing on overhead and energy efficiency of BC transaction (TX) transmissions.","PeriodicalId":245782,"journal":{"name":"2020 IEEE 45th Conference on Local Computer Networks (LCN)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131128134","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 : 2020-11-16DOI: 10.1109/LCN48667.2020.9314830
Carlos A. Rivera A., Arash Shaghaghi, S. Kanhere
IoT devices are the target of choice for attackers, and one of the most devastating threats involving compromised IoT devices has been their exploitation as part of botnets. Here, we propose c-Shield, as a distributed and extensible solution designed to detect and respond to IoT-based bots in an enterprise network. c-Shield passively inspects network traffic associated with IoT devices over a range of different protocols and systematically analyses the URLs extracted. Compared with the existing solutions, c-Shield is designed to be capable of detecting bots using advanced evasion techniques such as Domain Name Generation Algorithms (DGA) with a high accuracy rate.
{"title":"Towards a Distributed Defence Mechanism Against IoT-based Bots","authors":"Carlos A. Rivera A., Arash Shaghaghi, S. Kanhere","doi":"10.1109/LCN48667.2020.9314830","DOIUrl":"https://doi.org/10.1109/LCN48667.2020.9314830","url":null,"abstract":"IoT devices are the target of choice for attackers, and one of the most devastating threats involving compromised IoT devices has been their exploitation as part of botnets. Here, we propose c-Shield, as a distributed and extensible solution designed to detect and respond to IoT-based bots in an enterprise network. c-Shield passively inspects network traffic associated with IoT devices over a range of different protocols and systematically analyses the URLs extracted. Compared with the existing solutions, c-Shield is designed to be capable of detecting bots using advanced evasion techniques such as Domain Name Generation Algorithms (DGA) with a high accuracy rate.","PeriodicalId":245782,"journal":{"name":"2020 IEEE 45th Conference on Local Computer Networks (LCN)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132654031","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 : 2020-11-16DOI: 10.1109/LCN48667.2020.9314774
J. Perdomo, Mårten Ericson, M. Nordberg, K. Andersson
Multi-connectivity and network densification are two solutions intended to improve performance and reliability. These solutions can improve 5G NR’s system performance especially when using high-frequency bands. This work focuses on the user equipment (UE) performance using multi-connectivity within an ultra-dense deployment in a city environment. By being connected to more than one access node simultaneously, the UE should benefit from increased reliability and performance. However, this improved performance comes at the expense of a potentially increased power consumption. Simulation results show that multi-connectivity improves performance by up to 46% and 27% in downlink and uplink resp., increases UE energy efficiency by up to 30% and improves reliability for highly mobile users by up to 37%. The price to pay is an increased UE power consumption of up to 25% and 60% for dual-connectivity and tri-connectivity resp. A multi-connectivity scheme is presented to reduce the secondary connection’s transmit power.
{"title":"User Performance in a 5G Multi-connectivity Ultra-Dense Network City Scenario","authors":"J. Perdomo, Mårten Ericson, M. Nordberg, K. Andersson","doi":"10.1109/LCN48667.2020.9314774","DOIUrl":"https://doi.org/10.1109/LCN48667.2020.9314774","url":null,"abstract":"Multi-connectivity and network densification are two solutions intended to improve performance and reliability. These solutions can improve 5G NR’s system performance especially when using high-frequency bands. This work focuses on the user equipment (UE) performance using multi-connectivity within an ultra-dense deployment in a city environment. By being connected to more than one access node simultaneously, the UE should benefit from increased reliability and performance. However, this improved performance comes at the expense of a potentially increased power consumption. Simulation results show that multi-connectivity improves performance by up to 46% and 27% in downlink and uplink resp., increases UE energy efficiency by up to 30% and improves reliability for highly mobile users by up to 37%. The price to pay is an increased UE power consumption of up to 25% and 60% for dual-connectivity and tri-connectivity resp. A multi-connectivity scheme is presented to reduce the secondary connection’s transmit power.","PeriodicalId":245782,"journal":{"name":"2020 IEEE 45th Conference on Local Computer Networks (LCN)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133765124","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 : 2020-11-16DOI: 10.1109/LCN48667.2020.9314789
Shruti Gandhi, Y. Viniotis
Inter-datacenter WANs connect geo-distributed datacenters and carry a considerable amount of traffic, generally a mix of flows. There has been little work done to provide custom guarantees depending on the nature of traffic requirements in such environments. In this paper we address this problem by proposing Vritti, an adaptable spatial-temporal system for traffic engineering in inter-datacenter WAN environments applicable to single and federated clouds. With Vritti, cloud providers can offer tailor-made guarantees to users with widely differing requirements (in terms of hard, soft or no deadlines) and traffic characteristics (in terms of known or unknown traffic volumes). We use linear programming to mathematically formulate the problem with the objective of maximizing utility. We propose two online algorithms to generate admission control, scheduling and routing decisions. Our simulations show that Vritti can effectively meet deadline transfers and provide fairness to non-deadline transfers in both single and federated cloud environments.
{"title":"Guarantees for Mix-flows in Inter-Datacenter WANs in Single and Federated Clouds","authors":"Shruti Gandhi, Y. Viniotis","doi":"10.1109/LCN48667.2020.9314789","DOIUrl":"https://doi.org/10.1109/LCN48667.2020.9314789","url":null,"abstract":"Inter-datacenter WANs connect geo-distributed datacenters and carry a considerable amount of traffic, generally a mix of flows. There has been little work done to provide custom guarantees depending on the nature of traffic requirements in such environments. In this paper we address this problem by proposing Vritti, an adaptable spatial-temporal system for traffic engineering in inter-datacenter WAN environments applicable to single and federated clouds. With Vritti, cloud providers can offer tailor-made guarantees to users with widely differing requirements (in terms of hard, soft or no deadlines) and traffic characteristics (in terms of known or unknown traffic volumes). We use linear programming to mathematically formulate the problem with the objective of maximizing utility. We propose two online algorithms to generate admission control, scheduling and routing decisions. Our simulations show that Vritti can effectively meet deadline transfers and provide fairness to non-deadline transfers in both single and federated cloud environments.","PeriodicalId":245782,"journal":{"name":"2020 IEEE 45th Conference on Local Computer Networks (LCN)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116187165","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 : 2020-11-16DOI: 10.1109/LCN48667.2020.9314773
M. Raza, M. Abolhasan, J. Lipman, N. Shariati, Wei Ni
Mission-critical machine type communication (MC-MTC) systems in which machines communicate to perform various tasks such as coordination, sensing, and actuation, require stringent requirements of ultra-reliable and low latency communications (URLLC). Edge computing being an integral part of future wireless networks, provides services that support URLLC applications. In this paper, we use the edge computing approach and present a statistical learning-based dynamic retransmission mechanism. The proposed approach meets the desired latency-reliability criterion in MC-MTC networks employing framed ALOHA. The maximum number of retransmissions Nr under a given latency-reliability constraint is learned statistically by the devices from the history of their previous transmissions and shared with the base station. Simulations are performed in MATLAB to evaluate a framed-ALOHA system’s performance in which an active device can have only one successful transmission in one round composed of (Nr + 1) frames, and the performance is compared with the diversity transmission-based framed-ALOHA.
{"title":"Statistical Learning-Based Dynamic Retransmission Mechanism for Mission Critical Communication: An Edge-Computing Approach","authors":"M. Raza, M. Abolhasan, J. Lipman, N. Shariati, Wei Ni","doi":"10.1109/LCN48667.2020.9314773","DOIUrl":"https://doi.org/10.1109/LCN48667.2020.9314773","url":null,"abstract":"Mission-critical machine type communication (MC-MTC) systems in which machines communicate to perform various tasks such as coordination, sensing, and actuation, require stringent requirements of ultra-reliable and low latency communications (URLLC). Edge computing being an integral part of future wireless networks, provides services that support URLLC applications. In this paper, we use the edge computing approach and present a statistical learning-based dynamic retransmission mechanism. The proposed approach meets the desired latency-reliability criterion in MC-MTC networks employing framed ALOHA. The maximum number of retransmissions Nr under a given latency-reliability constraint is learned statistically by the devices from the history of their previous transmissions and shared with the base station. Simulations are performed in MATLAB to evaluate a framed-ALOHA system’s performance in which an active device can have only one successful transmission in one round composed of (Nr + 1) frames, and the performance is compared with the diversity transmission-based framed-ALOHA.","PeriodicalId":245782,"journal":{"name":"2020 IEEE 45th Conference on Local Computer Networks (LCN)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121227328","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：