Pub Date : 2019-10-01DOI: 10.23919/CNSM46954.2019.9012744
F. Valente, João Paulo Morijo, Kelen Cristiane Teixeira Vivaldini, L. Trevelin
The Internet of Things (IoT) is an environment that can be divided in three large layers: the sensor/actuator level where a wide variety of objects with different computing, sensors and communication capabilities resides, the communication layer with wireless technologies such as ZigBee, Bluetooth and emerging 6LoWPAN (e.g LoRa), and the intelligence layer, where computing analytics/decisions occur. IoT can be used for monitoring, inferring problems, decision making at a business level or actuating at the edge via IoT nodes. As the IoT sensor network grows, an enormous amount of data from multiple sources flows to the intelligence layer. In order to make decisions based on analytics over these data, the measurements need to be precise and accurate. Data fusion is an effective way to improve data quality, however, IoT environments are still evolving and the best way and location where data fusion should happen is an open problem. This paper presents one potential strategy for IoT sensor data fusion by implementing multi-sensor data fusion as microservices using a container platform built into an opensource IoT middleware based in a fog computing infrastructure which is can scale automatically as the influx of data from the IoT nodes grows. A number of data fusion tests were performed for different amounts of IoT nodes and sensor readings over ZigBee and LoRa using a specific data fusion algorithm. The results show that, the strategy can be effectively used in IoT heterogeneous environments.
{"title":"Fog-based Data Fusion for Heterogeneous IoT Sensor Networks: A Real Implementation","authors":"F. Valente, João Paulo Morijo, Kelen Cristiane Teixeira Vivaldini, L. Trevelin","doi":"10.23919/CNSM46954.2019.9012744","DOIUrl":"https://doi.org/10.23919/CNSM46954.2019.9012744","url":null,"abstract":"The Internet of Things (IoT) is an environment that can be divided in three large layers: the sensor/actuator level where a wide variety of objects with different computing, sensors and communication capabilities resides, the communication layer with wireless technologies such as ZigBee, Bluetooth and emerging 6LoWPAN (e.g LoRa), and the intelligence layer, where computing analytics/decisions occur. IoT can be used for monitoring, inferring problems, decision making at a business level or actuating at the edge via IoT nodes. As the IoT sensor network grows, an enormous amount of data from multiple sources flows to the intelligence layer. In order to make decisions based on analytics over these data, the measurements need to be precise and accurate. Data fusion is an effective way to improve data quality, however, IoT environments are still evolving and the best way and location where data fusion should happen is an open problem. This paper presents one potential strategy for IoT sensor data fusion by implementing multi-sensor data fusion as microservices using a container platform built into an opensource IoT middleware based in a fog computing infrastructure which is can scale automatically as the influx of data from the IoT nodes grows. A number of data fusion tests were performed for different amounts of IoT nodes and sensor readings over ZigBee and LoRa using a specific data fusion algorithm. The results show that, the strategy can be effectively used in IoT heterogeneous environments.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128873120","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 : 2019-10-01DOI: 10.23919/CNSM46954.2019.9012714
Theresa Enghardt, Philipp S. Tiesel, T. Zinner, A. Feldmann
Today’s end-user devices have multiple access networks available and can achieve better application performance by distributing traffic across access networks. However, matching application traffic to the most suitable access network or bundling them is non-trivial, given varying application needs and network performance characteristics. Therefore, we propose an application-informed approach for access network selection (IANS). Based on the size of a Web resource, we select the better access network in terms of latency and available downstream capacity. We implement IANS within our Socket Intents prototype and evaluate its benefits for Web page loads under a variety of network conditions and for various Web pages. IANS provides the highest speedups for scenarios with asymmetric network conditions and for scenarios with low downstream capacity. Here, IANS improves relevant Web metrics by between 500 and 1000 ms in the median, compared to using the better of the two access networks, and may also outperform MPTCP. This confirms that IANS improves application performance over using a single network and, in several scenarios, even using MPTCP.
{"title":"Informed Access Network Selection: The Benefits of Socket Intents for Web Performance","authors":"Theresa Enghardt, Philipp S. Tiesel, T. Zinner, A. Feldmann","doi":"10.23919/CNSM46954.2019.9012714","DOIUrl":"https://doi.org/10.23919/CNSM46954.2019.9012714","url":null,"abstract":"Today’s end-user devices have multiple access networks available and can achieve better application performance by distributing traffic across access networks. However, matching application traffic to the most suitable access network or bundling them is non-trivial, given varying application needs and network performance characteristics. Therefore, we propose an application-informed approach for access network selection (IANS). Based on the size of a Web resource, we select the better access network in terms of latency and available downstream capacity. We implement IANS within our Socket Intents prototype and evaluate its benefits for Web page loads under a variety of network conditions and for various Web pages. IANS provides the highest speedups for scenarios with asymmetric network conditions and for scenarios with low downstream capacity. Here, IANS improves relevant Web metrics by between 500 and 1000 ms in the median, compared to using the better of the two access networks, and may also outperform MPTCP. This confirms that IANS improves application performance over using a single network and, in several scenarios, even using MPTCP.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131654489","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 : 2019-10-01DOI: 10.23919/CNSM46954.2019.9012660
Hyundong Hwang, Young-Tak Kim
The IEEE 802.11p, IEEE 1609, and wireless access in vehicular environment (WAVE) standards are developed to be used on multi-channels in dedicated short range communication (DSRC) spectrum. While the vehicular networks will be inevitably installed in overlapped manner in metropolitan area, most research works of VANETs, however, are focused on the coordinated multichannel MAC protocol operations in a single isolated ad hoc network environment without considering overlapped vehicular network environments that include interferences from neighbor networks. In this paper, we propose a slotted TDMA Multichannel MAC (STMC-MAC) for overlapped vehicular networks (OVN) with software-defined networking-based distribution system (SDN-DS) as infrastructure. The proposed STMC-MAC guarantees reliable delivery of basic safety message (BSM) with bounded delay and scalability on OVN with SDN-DS for metropolitan area with high vehicular density. The proposed STMC-MAC provides higher scalability, reliability, and flexibility in BSM and non-BSM data exchanges at various VN-ESS topologies and different level of vehicular density. The proposed scheme had been implemented on NS-3 network simulator, and the performances of the proposed scheme are measured, analyzed, and compared with existing approaches.1
{"title":"Slotted TDMA Multichannel MAC for Overlapped Vehicular Networks with SDN-based Distributed System","authors":"Hyundong Hwang, Young-Tak Kim","doi":"10.23919/CNSM46954.2019.9012660","DOIUrl":"https://doi.org/10.23919/CNSM46954.2019.9012660","url":null,"abstract":"The IEEE 802.11p, IEEE 1609, and wireless access in vehicular environment (WAVE) standards are developed to be used on multi-channels in dedicated short range communication (DSRC) spectrum. While the vehicular networks will be inevitably installed in overlapped manner in metropolitan area, most research works of VANETs, however, are focused on the coordinated multichannel MAC protocol operations in a single isolated ad hoc network environment without considering overlapped vehicular network environments that include interferences from neighbor networks. In this paper, we propose a slotted TDMA Multichannel MAC (STMC-MAC) for overlapped vehicular networks (OVN) with software-defined networking-based distribution system (SDN-DS) as infrastructure. The proposed STMC-MAC guarantees reliable delivery of basic safety message (BSM) with bounded delay and scalability on OVN with SDN-DS for metropolitan area with high vehicular density. The proposed STMC-MAC provides higher scalability, reliability, and flexibility in BSM and non-BSM data exchanges at various VN-ESS topologies and different level of vehicular density. The proposed scheme had been implemented on NS-3 network simulator, and the performances of the proposed scheme are measured, analyzed, and compared with existing approaches.1","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130779104","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 : 2019-10-01DOI: 10.23919/CNSM46954.2019.9012691
Ali Safari Khatouni, Martino Trevisan, Danilo Giordano
Network monitoring is fundamental to understand network evolution and behavior. However, monitoring studies have the main limitation of running new experiments when the phenomenon under analysis is over e.g., congestion. To overcome this limitation, network emulation is of vital importance for network testing and research experiments either in wired and mobile networks. When it comes to mobile networks, the variety of technical characteristics, coupled with the opaque network configurations, make realistic network emulation a challenging task.In this paper, we address this issue leveraging a large scale dataset composed of 500M network latency measurements in Mobile BroadBand networks. By using this dataset, we create 51 different network latency profiles based on the Mobile BroadBand operator, the radio access technology and signal strength. These profiles are then processed to make them compatible with the tc-netem emulation tool. Finally, we show that, despite the limitation of current tc-netem emulation tool, Generative Adversarial Networks are a promising solution used to create realistic temporal emulation.We believe that this work could be the first step toward a comprehensive data-driven network emulation. For this, we make our profiles and codes available to foster further studies in these directions.
{"title":"Data-Driven Emulation of Mobile Access Networks","authors":"Ali Safari Khatouni, Martino Trevisan, Danilo Giordano","doi":"10.23919/CNSM46954.2019.9012691","DOIUrl":"https://doi.org/10.23919/CNSM46954.2019.9012691","url":null,"abstract":"Network monitoring is fundamental to understand network evolution and behavior. However, monitoring studies have the main limitation of running new experiments when the phenomenon under analysis is over e.g., congestion. To overcome this limitation, network emulation is of vital importance for network testing and research experiments either in wired and mobile networks. When it comes to mobile networks, the variety of technical characteristics, coupled with the opaque network configurations, make realistic network emulation a challenging task.In this paper, we address this issue leveraging a large scale dataset composed of 500M network latency measurements in Mobile BroadBand networks. By using this dataset, we create 51 different network latency profiles based on the Mobile BroadBand operator, the radio access technology and signal strength. These profiles are then processed to make them compatible with the tc-netem emulation tool. Finally, we show that, despite the limitation of current tc-netem emulation tool, Generative Adversarial Networks are a promising solution used to create realistic temporal emulation.We believe that this work could be the first step toward a comprehensive data-driven network emulation. For this, we make our profiles and codes available to foster further studies in these directions.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133373464","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 : 2019-10-01DOI: 10.23919/CNSM46954.2019.9012743
Moath Bagarish, Riyad Alshammari, A. N. Zincir-Heywood
Social media is an important communication medium in these days. Twitter is famous as microblogging service. It has been reported that social bots have been used in Twitter widely. In this research, we aim to understand whether bots are selective in the topics they participate or not. To this end, we explore tweets on FIFA World Cup. Our analysis indicate that there are bot activities even in tweets related to soccer (football) events but not just political topics.
{"title":"Are There Bots even in FIFA World Cup 2018 Tweets?","authors":"Moath Bagarish, Riyad Alshammari, A. N. Zincir-Heywood","doi":"10.23919/CNSM46954.2019.9012743","DOIUrl":"https://doi.org/10.23919/CNSM46954.2019.9012743","url":null,"abstract":"Social media is an important communication medium in these days. Twitter is famous as microblogging service. It has been reported that social bots have been used in Twitter widely. In this research, we aim to understand whether bots are selective in the topics they participate or not. To this end, we explore tweets on FIFA World Cup. Our analysis indicate that there are bot activities even in tweets related to soccer (football) events but not just political topics.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133385797","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 : 2019-10-01DOI: 10.23919/CNSM46954.2019.9012696
Jerico Moeyersons, Behrooz Farkiani, Bahador Bakhshi, S. A. MirHassani, T. Wauters, B. Volckaert, F. Turck
Emergency services must be able to transfer data with high priority over different networks. With 5G, slicing concepts at mobile network connections are introduced, allowing operators to divide portions of their network for specific use cases. In addition, Software-Defined Networking (SDN) principles allow to assign different Quality-of-Service (QoS) levels to different network slices.This paper proposes an SDN-based solution, executable both offline and online, that guarantees the required bandwidth for the emergency flows and maximizes the best-effort flows over the remaining bandwidth based on their priority. The offline model allows to optimize the problem for a batch of flow requests, but is computationally expensive, especially the variant where flows can be split up over parallel paths. For practical, dynamic situations, an online approach is proposed that periodically recalculates the optimal solution for all requested flows, while using shortest path routing and a greedy heuristic for bandwidth allocation for the intermediate flows.Afterwards, the offline approaches are evaluated through simulations while the online approach is validated through physical experiments with SDN switches, both in a scenario with 500 best-effort and 50 emergency flows. The results show that the offline algorithm is able to guarantee the resource allocation for the emergency flows while optimizing the best-effort flows with a sub-second execution time. As a proof-of-concept, a physical setup with Zodiac switches effectively validates the feasibility of the online approach in a realistic setup.
{"title":"Enabling Emergency Flow Prioritization in SDN Networks","authors":"Jerico Moeyersons, Behrooz Farkiani, Bahador Bakhshi, S. A. MirHassani, T. Wauters, B. Volckaert, F. Turck","doi":"10.23919/CNSM46954.2019.9012696","DOIUrl":"https://doi.org/10.23919/CNSM46954.2019.9012696","url":null,"abstract":"Emergency services must be able to transfer data with high priority over different networks. With 5G, slicing concepts at mobile network connections are introduced, allowing operators to divide portions of their network for specific use cases. In addition, Software-Defined Networking (SDN) principles allow to assign different Quality-of-Service (QoS) levels to different network slices.This paper proposes an SDN-based solution, executable both offline and online, that guarantees the required bandwidth for the emergency flows and maximizes the best-effort flows over the remaining bandwidth based on their priority. The offline model allows to optimize the problem for a batch of flow requests, but is computationally expensive, especially the variant where flows can be split up over parallel paths. For practical, dynamic situations, an online approach is proposed that periodically recalculates the optimal solution for all requested flows, while using shortest path routing and a greedy heuristic for bandwidth allocation for the intermediate flows.Afterwards, the offline approaches are evaluated through simulations while the online approach is validated through physical experiments with SDN switches, both in a scenario with 500 best-effort and 50 emergency flows. The results show that the offline algorithm is able to guarantee the resource allocation for the emergency flows while optimizing the best-effort flows with a sub-second execution time. As a proof-of-concept, a physical setup with Zodiac switches effectively validates the feasibility of the online approach in a realistic setup.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132522808","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 : 2019-10-01DOI: 10.23919/CNSM46954.2019.9012745
Mohammed Chahbar, G. Diaz, Abdulhalim Dandoush
Network Slicing (NS) is actually an ongoing standardization work, different visions and inconsistent use of terminologies are observed across Standard Developing Organizations (SDOs). In this paper, we aim at presenting and comparing most well known works about NS information models. The target is to combine major contributions from different SDOs and come out with a proposition of a unified NS model. The proposed NS model components and the way they relate to each other are then mapped to the end-to-end Management and Orchestration (MANO) reference architecture.
{"title":"Towards a Unified Network Slicing Model","authors":"Mohammed Chahbar, G. Diaz, Abdulhalim Dandoush","doi":"10.23919/CNSM46954.2019.9012745","DOIUrl":"https://doi.org/10.23919/CNSM46954.2019.9012745","url":null,"abstract":"Network Slicing (NS) is actually an ongoing standardization work, different visions and inconsistent use of terminologies are observed across Standard Developing Organizations (SDOs). In this paper, we aim at presenting and comparing most well known works about NS information models. The target is to combine major contributions from different SDOs and come out with a proposition of a unified NS model. The proposed NS model components and the way they relate to each other are then mapped to the end-to-end Management and Orchestration (MANO) reference architecture.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130027125","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 : 2019-10-01DOI: 10.23919/CNSM46954.2019.9012684
Ali Safari Khatouni, Lan Zhang, K. Aziz, Ibrahim Zincir, Nur Zincir-Heywood
The usage of Network Address Translation (NAT) devices is common among end users, organizations, and Internet Service Providers. NAT provides anonymity for users within an organization by replacing their internal IP addresses with a single external wide area network address. While such anonymity provides an added measure of security for legitimate users, it can also be taken advantage of by malicious users hiding behind NAT devices. Thus, identifying NAT devices and hosts behind them is essential to detect malicious behaviors in traffic and application usage. In this paper, we propose a machine learning based solution to detect hosts behind NAT devices by using flow level statistics (excluding IP addresses, port numbers, and application layer information) from passive traffic measurements. We capture a large dataset and perform an extensive evaluation of our proposed approach with four existing approaches from the literature. Our results show that the proposed approach could identify NAT behaviors and hosts not only with higher accuracy but also demonstrates the impact of parameter sensitivity of the proposed approach.
{"title":"Exploring NAT Detection and Host Identification Using Machine Learning","authors":"Ali Safari Khatouni, Lan Zhang, K. Aziz, Ibrahim Zincir, Nur Zincir-Heywood","doi":"10.23919/CNSM46954.2019.9012684","DOIUrl":"https://doi.org/10.23919/CNSM46954.2019.9012684","url":null,"abstract":"The usage of Network Address Translation (NAT) devices is common among end users, organizations, and Internet Service Providers. NAT provides anonymity for users within an organization by replacing their internal IP addresses with a single external wide area network address. While such anonymity provides an added measure of security for legitimate users, it can also be taken advantage of by malicious users hiding behind NAT devices. Thus, identifying NAT devices and hosts behind them is essential to detect malicious behaviors in traffic and application usage. In this paper, we propose a machine learning based solution to detect hosts behind NAT devices by using flow level statistics (excluding IP addresses, port numbers, and application layer information) from passive traffic measurements. We capture a large dataset and perform an extensive evaluation of our proposed approach with four existing approaches from the literature. Our results show that the proposed approach could identify NAT behaviors and hosts not only with higher accuracy but also demonstrates the impact of parameter sensitivity of the proposed approach.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114315759","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 : 2019-10-01DOI: 10.23919/CNSM46954.2019.9012750
Nik Sultana, A. Rao, Zihao Jin, Pardis Pashakhanloo, Henry Zhu, V. Yegneswaran, B. T. Loo
Analysing software and networks can be done using established tools, such as debuggers and packet analysers, but using established tools to analyse network software is difficult and impractical because of the sheer detail the tools present and the performance overheads they typically impose. This makes it difficult to precisely diagnose performance anomalies in network software to identify their causes (is it a DoS attack or a bug?) and determine what needs to be fixed.We present Flowdar: a practical tool for analysing software traces to produce intuitive summaries of network software behaviour by abstracting unimportant details and demultiplexing traces into different sessions’ subtraces. Flowdar can use existing state-of-the-art tracing tools for lower overhead during trace gathering for offline analysis. Using Flowdar we can drill down when diagnosing performance anomalies without getting overwhelmed in detail or burdening the system being observed.We show that Flowdar can be applied to existing real-world software and can digest complex behaviour into an intuitive visualisation.
{"title":"Trace-based Behaviour Analysis of Network Servers","authors":"Nik Sultana, A. Rao, Zihao Jin, Pardis Pashakhanloo, Henry Zhu, V. Yegneswaran, B. T. Loo","doi":"10.23919/CNSM46954.2019.9012750","DOIUrl":"https://doi.org/10.23919/CNSM46954.2019.9012750","url":null,"abstract":"Analysing software and networks can be done using established tools, such as debuggers and packet analysers, but using established tools to analyse network software is difficult and impractical because of the sheer detail the tools present and the performance overheads they typically impose. This makes it difficult to precisely diagnose performance anomalies in network software to identify their causes (is it a DoS attack or a bug?) and determine what needs to be fixed.We present Flowdar: a practical tool for analysing software traces to produce intuitive summaries of network software behaviour by abstracting unimportant details and demultiplexing traces into different sessions’ subtraces. Flowdar can use existing state-of-the-art tracing tools for lower overhead during trace gathering for offline analysis. Using Flowdar we can drill down when diagnosing performance anomalies without getting overwhelmed in detail or burdening the system being observed.We show that Flowdar can be applied to existing real-world software and can digest complex behaviour into an intuitive visualisation.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133196376","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 : 2019-10-01DOI: 10.23919/CNSM46954.2019.9012685
Takuto Kimura, Tatsuaki Kimura, A. Matsumoto, J. Okamoto
Bitrate-selection algorithms are key to improving the quality of experience (QoE) of adaptive video streaming. Although current bitrate selection algorithms maximize the QoE, video consumers are concerned with QoE and traffic-volume usage due to the pay-per-use or data-capped plans. To balance between the QoE and traffic volume, some commercial video-streaming services enable users to set the upper limit of the selectable bitrate. However, it is difficult for users to set an appropriate limit to obtain sufficient QoE. We propose BANQUET, a novel bitrate-selection algorithm that enables users to control intuitively the balance between the QoE and traffic volume. Assuming a user-set target QoE as a balancing parameter, BANQUET selects the bitrate that minimizes the traffic volume while maintaining the estimated mean opinion score (MOS) above the target QoE. BANQUET calculates the appropriate bitrate based on estimations of the throughput and butter transition. A trace-based simulation shows that BANQUET reduces the traffic volume by up to 47.0% compared to a baseline while maintaining the same average estimated MOS.
{"title":"BANQUET: Balancing Quality of Experience and Traffic Volume in Adaptive Video Streaming","authors":"Takuto Kimura, Tatsuaki Kimura, A. Matsumoto, J. Okamoto","doi":"10.23919/CNSM46954.2019.9012685","DOIUrl":"https://doi.org/10.23919/CNSM46954.2019.9012685","url":null,"abstract":"Bitrate-selection algorithms are key to improving the quality of experience (QoE) of adaptive video streaming. Although current bitrate selection algorithms maximize the QoE, video consumers are concerned with QoE and traffic-volume usage due to the pay-per-use or data-capped plans. To balance between the QoE and traffic volume, some commercial video-streaming services enable users to set the upper limit of the selectable bitrate. However, it is difficult for users to set an appropriate limit to obtain sufficient QoE. We propose BANQUET, a novel bitrate-selection algorithm that enables users to control intuitively the balance between the QoE and traffic volume. Assuming a user-set target QoE as a balancing parameter, BANQUET selects the bitrate that minimizes the traffic volume while maintaining the estimated mean opinion score (MOS) above the target QoE. BANQUET calculates the appropriate bitrate based on estimations of the throughput and butter transition. A trace-based simulation shows that BANQUET reduces the traffic volume by up to 47.0% compared to a baseline while maintaining the same average estimated MOS.","PeriodicalId":273818,"journal":{"name":"2019 15th International Conference on Network and Service Management (CNSM)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121377902","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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