Pub Date : 2019-11-01DOI: 10.1109/CloudNet47604.2019.9064114
Kamil Tokmakov, M. Sarker, Jörg Domaschka, S. Wesner
Virtualisation first and cloud computing later has led to a consolidation of workload in data centres that also comprises latency-sensitive application domains such as High Performance Computing and telecommunication. These types of applications require strict latency guarantees to maintain their Quality of Service. In virtualised environments with their churn, this demands for adaptability and flexibility to satisfy. At the same time, the mere scale of the infrastructures favours commodity (Ethernet) over specialised (Infiniband) hardware. For that purpose, this paper introduces a novel traffic management algorithm that combines Rate-limited Strict Priority and Deficit round-robin for latency-aware and fair scheduling respectively. In addition, we present an implementation of this algorithm on the bmv2 P4 software switch by evaluating it against standard priority-based and best-effort scheduling.
{"title":"A Case for Data Centre Traffic Management on Software Programmable Ethernet Switches","authors":"Kamil Tokmakov, M. Sarker, Jörg Domaschka, S. Wesner","doi":"10.1109/CloudNet47604.2019.9064114","DOIUrl":"https://doi.org/10.1109/CloudNet47604.2019.9064114","url":null,"abstract":"Virtualisation first and cloud computing later has led to a consolidation of workload in data centres that also comprises latency-sensitive application domains such as High Performance Computing and telecommunication. These types of applications require strict latency guarantees to maintain their Quality of Service. In virtualised environments with their churn, this demands for adaptability and flexibility to satisfy. At the same time, the mere scale of the infrastructures favours commodity (Ethernet) over specialised (Infiniband) hardware. For that purpose, this paper introduces a novel traffic management algorithm that combines Rate-limited Strict Priority and Deficit round-robin for latency-aware and fair scheduling respectively. In addition, we present an implementation of this algorithm on the bmv2 P4 software switch by evaluating it against standard priority-based and best-effort scheduling.","PeriodicalId":340890,"journal":{"name":"2019 IEEE 8th International Conference on Cloud Networking (CloudNet)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129437190","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 : 2019-11-01DOI: 10.1109/CloudNet47604.2019.9064144
P. Ribeiro, R. Prior, S. Crisóstomo
We propose MCOFS a secure cloud storage system for Android that combines the use of multiple public cloud providers with cryptography and redundancy mechanisms to ensure the confidentiality and availability of files even if one of the providers becomes hostile or suffers catastrophic data loss. Experimental results show that, while there is a performance penalty in comparison to the plain use of a single provider, it is small enough and a fair price to pay for the added guarantees.
{"title":"Secure File Storage for Android Devices on Public Clouds","authors":"P. Ribeiro, R. Prior, S. Crisóstomo","doi":"10.1109/CloudNet47604.2019.9064144","DOIUrl":"https://doi.org/10.1109/CloudNet47604.2019.9064144","url":null,"abstract":"We propose MCOFS a secure cloud storage system for Android that combines the use of multiple public cloud providers with cryptography and redundancy mechanisms to ensure the confidentiality and availability of files even if one of the providers becomes hostile or suffers catastrophic data loss. Experimental results show that, while there is a performance penalty in comparison to the plain use of a single provider, it is small enough and a fair price to pay for the added guarantees.","PeriodicalId":340890,"journal":{"name":"2019 IEEE 8th International Conference on Cloud Networking (CloudNet)","volume":"63 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116381985","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 : 2019-11-01DOI: 10.1109/CloudNet47604.2019.9064125
Carlos Melo, J. Dantas, Ronierison Maciel, Paulo Pereira, Eder Quesado, P. Maciel
This paper proposes and evaluates availability models for blockchain provisioning over cloud computing infrastructures as well as their respective deployment expenses in order to establish a cost × benefit relationship. To demonstrate these models' feasibility, we provide two case studies considering blockchain provisioning over a baseline architecture, and three other alternative redundant environments.
{"title":"Blockchain provisioning over private cloud computing environments: Availability modeling and cost requirements","authors":"Carlos Melo, J. Dantas, Ronierison Maciel, Paulo Pereira, Eder Quesado, P. Maciel","doi":"10.1109/CloudNet47604.2019.9064125","DOIUrl":"https://doi.org/10.1109/CloudNet47604.2019.9064125","url":null,"abstract":"This paper proposes and evaluates availability models for blockchain provisioning over cloud computing infrastructures as well as their respective deployment expenses in order to establish a cost × benefit relationship. To demonstrate these models' feasibility, we provide two case studies considering blockchain provisioning over a baseline architecture, and three other alternative redundant environments.","PeriodicalId":340890,"journal":{"name":"2019 IEEE 8th International Conference on Cloud Networking (CloudNet)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124752778","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 : 2019-11-01DOI: 10.1109/CloudNet47604.2019.9064135
Zhaoxia Sun, P. Du, A. Nakao, L. Zhong, R. Onishi
With the development of IoT and 5G networks, the demand for the next-generation intelligent transportation system has been growing at a rapid pace. Dynamic mapping has been considered one of the key technologies to reduce traffic accidents and congestion in the intelligent transportation system. However, as the number of vehicles keeps growing, a huge volume of mapping traffic may overload the central cloud, leading to serious performance degradation. In this paper, we propose and prototype a CUPS (control and user plane separation)-based edge computing architecture for the dynamic mapping and quantify its benefits by prototyping. There are a couple of merits of our proposal: (i) we can mitigate the overhead of the networks and central cloud because we only need to abstract and send global dynamic mapping information from the edge servers to the central cloud; (ii) we can reduce the response latency since the dynamic mapping traffic can be isolated from other data traffic by being generated and distributed from a local edge server that is deployed closer to the vehicles than the central server in cloud. The capabilities of our system have been quantified. The experimental results have shown our system achieves throughput improvement by more than four times, and response latency reduction by 67.8% compared to the conventional central cloud-based approach. Although these results are still obtained from the preliminary evaluations using our prototype system, we believe that our proposed architecture gives insight into how we utilize CUPS and edge computing to enable efficient dynamic mapping applications.
{"title":"Building Dynamic Mapping with CUPS for Next Generation Automotive Edge Computing","authors":"Zhaoxia Sun, P. Du, A. Nakao, L. Zhong, R. Onishi","doi":"10.1109/CloudNet47604.2019.9064135","DOIUrl":"https://doi.org/10.1109/CloudNet47604.2019.9064135","url":null,"abstract":"With the development of IoT and 5G networks, the demand for the next-generation intelligent transportation system has been growing at a rapid pace. Dynamic mapping has been considered one of the key technologies to reduce traffic accidents and congestion in the intelligent transportation system. However, as the number of vehicles keeps growing, a huge volume of mapping traffic may overload the central cloud, leading to serious performance degradation. In this paper, we propose and prototype a CUPS (control and user plane separation)-based edge computing architecture for the dynamic mapping and quantify its benefits by prototyping. There are a couple of merits of our proposal: (i) we can mitigate the overhead of the networks and central cloud because we only need to abstract and send global dynamic mapping information from the edge servers to the central cloud; (ii) we can reduce the response latency since the dynamic mapping traffic can be isolated from other data traffic by being generated and distributed from a local edge server that is deployed closer to the vehicles than the central server in cloud. The capabilities of our system have been quantified. The experimental results have shown our system achieves throughput improvement by more than four times, and response latency reduction by 67.8% compared to the conventional central cloud-based approach. Although these results are still obtained from the preliminary evaluations using our prototype system, we believe that our proposed architecture gives insight into how we utilize CUPS and edge computing to enable efficient dynamic mapping applications.","PeriodicalId":340890,"journal":{"name":"2019 IEEE 8th International Conference on Cloud Networking (CloudNet)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130815516","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 : 2019-11-01DOI: 10.1109/CloudNet47604.2019.9064139
J. H. Corrêa, Epaminondas A. Sousa Junior, I. Fonseca, Vivek Nigam, M. Ribeiro, R. Villaça
Distributed Denial-of-Service (DDoS) is becoming an even more complex problem with the migration of these services and applications to shared and centralized cloud infrastructures. Application layer Denial-of-Service attacks (ADDoS) is an special type of DDoS attacks, and the main problem in mitigating these attacks is because attacker requests are similar to legitimate clients. This paper proposes to use the scalability feature of cloud infrastructure as a defense from high-rate DDoS attacks, and selectivity defense to mitigate low-rate ADDoS attacks. Experiments are conducted in an OpenStack cloud environment to show that the combined use of selectivity and autoscaling can be used as a defense against low- and high-rate DDoS attacks.
{"title":"Selectivity and Autoscaling as Complementary Defenses for DDoS Protection to Cloud Services","authors":"J. H. Corrêa, Epaminondas A. Sousa Junior, I. Fonseca, Vivek Nigam, M. Ribeiro, R. Villaça","doi":"10.1109/CloudNet47604.2019.9064139","DOIUrl":"https://doi.org/10.1109/CloudNet47604.2019.9064139","url":null,"abstract":"Distributed Denial-of-Service (DDoS) is becoming an even more complex problem with the migration of these services and applications to shared and centralized cloud infrastructures. Application layer Denial-of-Service attacks (ADDoS) is an special type of DDoS attacks, and the main problem in mitigating these attacks is because attacker requests are similar to legitimate clients. This paper proposes to use the scalability feature of cloud infrastructure as a defense from high-rate DDoS attacks, and selectivity defense to mitigate low-rate ADDoS attacks. Experiments are conducted in an OpenStack cloud environment to show that the combined use of selectivity and autoscaling can be used as a defense against low- and high-rate DDoS attacks.","PeriodicalId":340890,"journal":{"name":"2019 IEEE 8th International Conference on Cloud Networking (CloudNet)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131137029","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 : 2019-11-01DOI: 10.1109/CloudNet47604.2019.9064067
Geymerson S. Ramos, Rian G. S. Pinheiro, Andre L. L. Aquino
This paper presents a new mathematical multi-objective formulation for the allocation of users in base stations of the evolved packet system architecture, with 5G applications that use software-defined networking. The model minimizes (i) communication cost between base stations and data centers; (ii) handover occurrences; (iii) the communication cost between users and base stations subject to user's bandwidth requirements. The proposed formulation is demonstrated in a simulation with data collected from a user's GPS and base station coordinates. It is verified in the results that the allocations considered the shortest distance, handover average, and network bandwidth availability, as established by our mathematical model.
{"title":"Optimizing 5G Networks Processes With Software Defined Networks","authors":"Geymerson S. Ramos, Rian G. S. Pinheiro, Andre L. L. Aquino","doi":"10.1109/CloudNet47604.2019.9064067","DOIUrl":"https://doi.org/10.1109/CloudNet47604.2019.9064067","url":null,"abstract":"This paper presents a new mathematical multi-objective formulation for the allocation of users in base stations of the evolved packet system architecture, with 5G applications that use software-defined networking. The model minimizes (i) communication cost between base stations and data centers; (ii) handover occurrences; (iii) the communication cost between users and base stations subject to user's bandwidth requirements. The proposed formulation is demonstrated in a simulation with data collected from a user's GPS and base station coordinates. It is verified in the results that the allocations considered the shortest distance, handover average, and network bandwidth availability, as established by our mathematical model.","PeriodicalId":340890,"journal":{"name":"2019 IEEE 8th International Conference on Cloud Networking (CloudNet)","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129573666","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 : 2019-11-01DOI: 10.1109/CloudNet47604.2019.9064118
Vítor Pereira, Miguel Rocha, Pedro Sousa
Internet Service Providers (ISPs) and dedicated inter-Data Center Wide Area Networks have been exploring Software-Defined Networking (SDN) features to achieve a high utilization of the available resources. This work proposes a scalable hybrid IP/SDN routing model, and optimization procedures fostered by Evolutionary Computation algorithms, to achieve near optimal network resources utilization under changing traffic requirements.
{"title":"Hybrid IP/SDN Routing for Inter-Data Center Communications","authors":"Vítor Pereira, Miguel Rocha, Pedro Sousa","doi":"10.1109/CloudNet47604.2019.9064118","DOIUrl":"https://doi.org/10.1109/CloudNet47604.2019.9064118","url":null,"abstract":"Internet Service Providers (ISPs) and dedicated inter-Data Center Wide Area Networks have been exploring Software-Defined Networking (SDN) features to achieve a high utilization of the available resources. This work proposes a scalable hybrid IP/SDN routing model, and optimization procedures fostered by Evolutionary Computation algorithms, to achieve near optimal network resources utilization under changing traffic requirements.","PeriodicalId":340890,"journal":{"name":"2019 IEEE 8th International Conference on Cloud Networking (CloudNet)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128872842","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 : 2019-11-01DOI: 10.1109/CloudNet47604.2019.9064048
Márk Szalay, P. Mátray, László Toka
In the era of cloud services, there is a strong desire to improve the elasticity and reliability of applications in the cloud. The standard way of achieving these goals is to decouple the life-cycle of important application states from the life-cycle of individual application instances: states, and data in general, are written to and read from cloud databases, deployed close to the application code. The high performance requirements on the application impose strict latency limits on these storage solutions for state access. Cloud database instances are therefore distributed on multiple hosts in order to strive to ensure data locality for all functions. However, the shared nature of certain states, and the inevitable dynamics of the application workload necessarily lead to inter-host data access within the data center (or even across data centers, if the application requires a multi-data center setup). In order to minimize the inter-host communication due to state externalization, we propose an advanced cloud scheduling algorithm that places functions' states across the hosts of a data center. We create a model for the state placement with the aim of minimizing state access latency, and we prove that it is a complex problem. We therefore propose heuristics for fast and efficient placement methods and we evaluate those across realistic scenarios. We show that our approximations are close to the optimal placement, and in large-scale settings the algorithms take only a few minutes to yield good placement results.
{"title":"Minimizing state access delay for cloud-native network functions","authors":"Márk Szalay, P. Mátray, László Toka","doi":"10.1109/CloudNet47604.2019.9064048","DOIUrl":"https://doi.org/10.1109/CloudNet47604.2019.9064048","url":null,"abstract":"In the era of cloud services, there is a strong desire to improve the elasticity and reliability of applications in the cloud. The standard way of achieving these goals is to decouple the life-cycle of important application states from the life-cycle of individual application instances: states, and data in general, are written to and read from cloud databases, deployed close to the application code. The high performance requirements on the application impose strict latency limits on these storage solutions for state access. Cloud database instances are therefore distributed on multiple hosts in order to strive to ensure data locality for all functions. However, the shared nature of certain states, and the inevitable dynamics of the application workload necessarily lead to inter-host data access within the data center (or even across data centers, if the application requires a multi-data center setup). In order to minimize the inter-host communication due to state externalization, we propose an advanced cloud scheduling algorithm that places functions' states across the hosts of a data center. We create a model for the state placement with the aim of minimizing state access latency, and we prove that it is a complex problem. We therefore propose heuristics for fast and efficient placement methods and we evaluate those across realistic scenarios. We show that our approximations are close to the optimal placement, and in large-scale settings the algorithms take only a few minutes to yield good placement results.","PeriodicalId":340890,"journal":{"name":"2019 IEEE 8th International Conference on Cloud Networking (CloudNet)","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116324504","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 : 2019-11-01DOI: 10.1109/CloudNet47604.2019.9064148
Yipeng Wang, Tong Yang, Ren Wang, T. Tai
Heavy hitter detection is a key task for networking traffic profiling, which can be used for various purposes such as Denial of Service (DoS) attack detection, Quality of Service (QoS) scheduling, load balancing, and flow size based routing, etc. Over the years, many efforts have been made on designing data structures and algorithms to achieve fast and memory-efficient inline profiling in cloud networks. Traditional heavy hitter detection methods, however, yield an innate and nonadjustable profiling accuracy (i.e., false positive or false negative) once the data structure is initialized. Users have no runtime feedback information nor control on the profiling accuracy, which could be an important factor for their usages. In this paper, we propose and evaluate a novel dynamic and memory-efficient heavy hitter detection algorithm, called Dynamic sketch. Dynamic sketch performs runtime accuracy monitoring and provides feedback to users via a sampling based method. It also self-adjusts the accuracy at runtime to satisfy the target given by the user. We implemented Dynamic sketch and our evaluations show that Dynamic sketch is able to report profiling accuracy with only a minimal 2% performance overhead. In addition, Dynamic sketch is 2.35 × faster than the state-of-the-art hash table based heavy hitter detector and achieves more than 2× memory efficiency than the state-of-the-art sketch based implementation.
{"title":"Dynamic Sketch: Efficient and Adjustable Heavy Hitter Detection for Software Packet Processing","authors":"Yipeng Wang, Tong Yang, Ren Wang, T. Tai","doi":"10.1109/CloudNet47604.2019.9064148","DOIUrl":"https://doi.org/10.1109/CloudNet47604.2019.9064148","url":null,"abstract":"Heavy hitter detection is a key task for networking traffic profiling, which can be used for various purposes such as Denial of Service (DoS) attack detection, Quality of Service (QoS) scheduling, load balancing, and flow size based routing, etc. Over the years, many efforts have been made on designing data structures and algorithms to achieve fast and memory-efficient inline profiling in cloud networks. Traditional heavy hitter detection methods, however, yield an innate and nonadjustable profiling accuracy (i.e., false positive or false negative) once the data structure is initialized. Users have no runtime feedback information nor control on the profiling accuracy, which could be an important factor for their usages. In this paper, we propose and evaluate a novel dynamic and memory-efficient heavy hitter detection algorithm, called Dynamic sketch. Dynamic sketch performs runtime accuracy monitoring and provides feedback to users via a sampling based method. It also self-adjusts the accuracy at runtime to satisfy the target given by the user. We implemented Dynamic sketch and our evaluations show that Dynamic sketch is able to report profiling accuracy with only a minimal 2% performance overhead. In addition, Dynamic sketch is 2.35 × faster than the state-of-the-art hash table based heavy hitter detector and achieves more than 2× memory efficiency than the state-of-the-art sketch based implementation.","PeriodicalId":340890,"journal":{"name":"2019 IEEE 8th International Conference on Cloud Networking (CloudNet)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115160981","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 : 2019-11-01DOI: 10.1109/CloudNet47604.2019.9064113
A. Soltani, B. Akbari, N. Mokari
With 5G networks on the horizon, providing immense radio access rate, mobile core networks will face an extremely heavy load to accommodate the users' requests. Employing Content Delivery Networks inside Mobile Networks (Telco-CDNs) is one of the promising solutions to alleviate the extra load and avoid congestion in the mobile core networks. Our goal is to exploit the users' profiles in cache replacement policies in order to improve their Quality of Experience (QoE). By using the information readily available in Mobile Network Operators (MNOs) such as user locations and their content preference, we propose a novel cache replacement strategy incorporating the users' profile information. We evaluate the proposed method compared to de-facto policies. Furthermore, we demonstrate that in scenarios involving moving users, our approach shows better performance with up to 23% more traffic saving relative to traditional methods. Finally, we investigate our method's sensitivity to profile accuracy and demonstrate its capabilities despite possible errors in profile estimations.
{"title":"User Profile-based Caching in 5G Telco-CDNs","authors":"A. Soltani, B. Akbari, N. Mokari","doi":"10.1109/CloudNet47604.2019.9064113","DOIUrl":"https://doi.org/10.1109/CloudNet47604.2019.9064113","url":null,"abstract":"With 5G networks on the horizon, providing immense radio access rate, mobile core networks will face an extremely heavy load to accommodate the users' requests. Employing Content Delivery Networks inside Mobile Networks (Telco-CDNs) is one of the promising solutions to alleviate the extra load and avoid congestion in the mobile core networks. Our goal is to exploit the users' profiles in cache replacement policies in order to improve their Quality of Experience (QoE). By using the information readily available in Mobile Network Operators (MNOs) such as user locations and their content preference, we propose a novel cache replacement strategy incorporating the users' profile information. We evaluate the proposed method compared to de-facto policies. Furthermore, we demonstrate that in scenarios involving moving users, our approach shows better performance with up to 23% more traffic saving relative to traditional methods. Finally, we investigate our method's sensitivity to profile accuracy and demonstrate its capabilities despite possible errors in profile estimations.","PeriodicalId":340890,"journal":{"name":"2019 IEEE 8th International Conference on Cloud Networking (CloudNet)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116439355","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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