Pub Date : 2017-06-14DOI: 10.1109/IWQoS.2017.7969110
Li Li, Ke Xu, Dan Wang, Chunyi Peng, Kai Zheng, Haiyang Wang, Rashid Mijumbi, Xiangxiang Wang
Recent advances in high speed rails (HSRs), coupled with user demands for communication on the move, are propelling the need for acceptable quality of communication services in high speed mobility scenarios. This calls for an evaluation of how well popular voice/video call applications, such as Skype, can perform in such scenarios. This paper presents the first comprehensive measurement study on Skype voice/video calls in LTE networks on HSRs with a peak speed of 310 km/h in China. We collected 50 GB of performance data, covering a total HSR distance of 39,900 km. We study various objective performance metrics (such as RTT, sending rate, call drop rate, etc.), as well as subjective metrics such as quality of experience of the calls. We also evaluate the efficiency of Skype's algorithms regarding the level of utilization of network resources. We observed that the quality of Skype calls degrades significantly on HSRs. Moreover, it was discovered that Skype significantly under-utilizes the network resources, such as available bandwidth. We discovered that the root of these inefficiencies is the poor adaptability of Skype in many aspects, including overlay routing, rate control, state update and call termination. These findings highlight the need to develop more adaptive voice/video call services for high speed mobility scenarios.
{"title":"A measurement study on Skype voice and video calls in LTE networks on high speed rails","authors":"Li Li, Ke Xu, Dan Wang, Chunyi Peng, Kai Zheng, Haiyang Wang, Rashid Mijumbi, Xiangxiang Wang","doi":"10.1109/IWQoS.2017.7969110","DOIUrl":"https://doi.org/10.1109/IWQoS.2017.7969110","url":null,"abstract":"Recent advances in high speed rails (HSRs), coupled with user demands for communication on the move, are propelling the need for acceptable quality of communication services in high speed mobility scenarios. This calls for an evaluation of how well popular voice/video call applications, such as Skype, can perform in such scenarios. This paper presents the first comprehensive measurement study on Skype voice/video calls in LTE networks on HSRs with a peak speed of 310 km/h in China. We collected 50 GB of performance data, covering a total HSR distance of 39,900 km. We study various objective performance metrics (such as RTT, sending rate, call drop rate, etc.), as well as subjective metrics such as quality of experience of the calls. We also evaluate the efficiency of Skype's algorithms regarding the level of utilization of network resources. We observed that the quality of Skype calls degrades significantly on HSRs. Moreover, it was discovered that Skype significantly under-utilizes the network resources, such as available bandwidth. We discovered that the root of these inefficiencies is the poor adaptability of Skype in many aspects, including overlay routing, rate control, state update and call termination. These findings highlight the need to develop more adaptive voice/video call services for high speed mobility scenarios.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125494350","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 : 2017-06-14DOI: 10.1109/IWQoS.2017.7969111
Di Mu, Yunpeng Ge, M. Sha, Steve Paul, N. Ravichandra, Souma Chowdhury
Research efforts over the last few decades produced multiple wireless technologies, which are readily available to support communication between devices in various Internet of Things (IoT) applications. However, none of the existing technologies delivers optimal performance across all critical quality of service (QoS) dimensions under varying environmental conditions. Using a single wireless technology therefore cannot meet the demands of varying workloads or changing environmental conditions. This problem is exacerbated with the increasing interest in placing embedded devices on the user's body or other mobile objects in mobile IoT applications. Instead of pursuing a one-radio-fits-all approach, we design ARTPoS, an adaptive radio and transmission power selection system, which makes available multiple wireless technologies at runtime and selects the radio(s) and transmission power(s) most suitable for the current conditions and requirements. Experimental results show that ARTPoS can significantly reduce the power consumption, while maintaining desired link reliability.
{"title":"Adaptive radio and transmission power selection for Internet of Things","authors":"Di Mu, Yunpeng Ge, M. Sha, Steve Paul, N. Ravichandra, Souma Chowdhury","doi":"10.1109/IWQoS.2017.7969111","DOIUrl":"https://doi.org/10.1109/IWQoS.2017.7969111","url":null,"abstract":"Research efforts over the last few decades produced multiple wireless technologies, which are readily available to support communication between devices in various Internet of Things (IoT) applications. However, none of the existing technologies delivers optimal performance across all critical quality of service (QoS) dimensions under varying environmental conditions. Using a single wireless technology therefore cannot meet the demands of varying workloads or changing environmental conditions. This problem is exacerbated with the increasing interest in placing embedded devices on the user's body or other mobile objects in mobile IoT applications. Instead of pursuing a one-radio-fits-all approach, we design ARTPoS, an adaptive radio and transmission power selection system, which makes available multiple wireless technologies at runtime and selects the radio(s) and transmission power(s) most suitable for the current conditions and requirements. Experimental results show that ARTPoS can significantly reduce the power consumption, while maintaining desired link reliability.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121174982","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 : 2017-06-14DOI: 10.1109/IWQoS.2017.7969143
Zenan Wang, Jiao Zhang, Tao Huang, Yun-jie Liu
Network Function Virtualization has attracted attention from both academia and industry as it can help the service provider to obtain agility and flexibility in network service deployment. In general, the enterprises require their flows to pass through a specific sequence of virtual network function (VNF) that varies from service to service. In addition, for each VNF required in the coming service demands, the operator can either launch a new instance for it or assign it to an established instance. This makes the network service deployment tasks even more complicated. In this paper, we first propose a method based on min-K-cut to cluster the VNFs. With clustering results as guidance, we determine whether to launch or reuse the instance to improve utilization rate of the VNF instance. Furthermore, for purpose of decreasing link bandwidth occupation, we aggregate the instances that are deployed with VNFs from the same cluster into the same server or rack. We evaluate our approach considering the average link bandwidth occupied by every accepted demand, the instance utilization rate and the total number of served demands. The simulation shows that our approach reduces link occupation effectively, and, meanwhile, guarantees the VNF instance utilization rate advantageously.
{"title":"A clustering-based approach for Virtual Network Function Mapping and Assigning","authors":"Zenan Wang, Jiao Zhang, Tao Huang, Yun-jie Liu","doi":"10.1109/IWQoS.2017.7969143","DOIUrl":"https://doi.org/10.1109/IWQoS.2017.7969143","url":null,"abstract":"Network Function Virtualization has attracted attention from both academia and industry as it can help the service provider to obtain agility and flexibility in network service deployment. In general, the enterprises require their flows to pass through a specific sequence of virtual network function (VNF) that varies from service to service. In addition, for each VNF required in the coming service demands, the operator can either launch a new instance for it or assign it to an established instance. This makes the network service deployment tasks even more complicated. In this paper, we first propose a method based on min-K-cut to cluster the VNFs. With clustering results as guidance, we determine whether to launch or reuse the instance to improve utilization rate of the VNF instance. Furthermore, for purpose of decreasing link bandwidth occupation, we aggregate the instances that are deployed with VNFs from the same cluster into the same server or rack. We evaluate our approach considering the average link bandwidth occupied by every accepted demand, the instance utilization rate and the total number of served demands. The simulation shows that our approach reduces link occupation effectively, and, meanwhile, guarantees the VNF instance utilization rate advantageously.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116649238","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 : 2017-06-14DOI: 10.1109/IWQoS.2017.7969163
Anmin Xu, J. Bi, Baobao Zhang, Shuhe Wang, Jianping Wu
To speed up the recovery from network failures, an extensive list of methods have been proposed. Many failure-recovery methods are proposed based on tunneling or marking, which increase the packet processing burden on routers and consume extra bandwidth. With neither tunneling nor marking, existing methods guarantee recovery from any single-link failure if a detour for the failed link exists, but they generate long traffic detours that will degrade the network performance, and even increase the operational cost, which is undesirable to network operators. Therefore, in this paper, we propose a Failure Inference approach to shortening Traffic Detours named as FITD, which works in OSPF/IS-IS networks. FITD does not use explicit failure notification, and can infer which link fails based on traffic information. FITD guarantees recovery from any single-link failure if a detour for the failed link exists. In particular, for networks with symmetric link weights, FITD guarantees to generate shortest detours for any single-link failure.
{"title":"Failure Inference for shortening traffic Detours","authors":"Anmin Xu, J. Bi, Baobao Zhang, Shuhe Wang, Jianping Wu","doi":"10.1109/IWQoS.2017.7969163","DOIUrl":"https://doi.org/10.1109/IWQoS.2017.7969163","url":null,"abstract":"To speed up the recovery from network failures, an extensive list of methods have been proposed. Many failure-recovery methods are proposed based on tunneling or marking, which increase the packet processing burden on routers and consume extra bandwidth. With neither tunneling nor marking, existing methods guarantee recovery from any single-link failure if a detour for the failed link exists, but they generate long traffic detours that will degrade the network performance, and even increase the operational cost, which is undesirable to network operators. Therefore, in this paper, we propose a Failure Inference approach to shortening Traffic Detours named as FITD, which works in OSPF/IS-IS networks. FITD does not use explicit failure notification, and can infer which link fails based on traffic information. FITD guarantees recovery from any single-link failure if a detour for the failed link exists. In particular, for networks with symmetric link weights, FITD guarantees to generate shortest detours for any single-link failure.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133186961","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 : 2017-06-14DOI: 10.1109/IWQoS.2017.7969173
Wen Hu, Jiahui Huang, Zhi Wang, Peng Wang, Kun Yi, Yonggang Wen, Kaiyan Chu, Lifeng Sun
Driven by the exponentially increasing amount of mobile video traffic, caching videos closer to the end users has become an appealing solution to reduce the traffic through the backbone network while improving users' perceived quality-of-experience (e.g., better video quality and reduced service delay). This research interest has been gaining lots of momentums due to the emergence of smart Access Points (APs), which are equipped with large storage space (several GBs). To address the “small population” problem involved in the prefetching at the edge, we propose to prefetch videos to APs ahead of users' requests via tensor learning: We first adopt the weighted tensor model to mine the hidden semantic pattern to characterize both users' preference for different types of videos and the dynamic video popularity over time; Then, based on the resulting low-dimension matrixes generated by the tensor factorization, we adopt an exponential smoothing model to capture the temporal pattern to predict users' propensity to unwatched videos; Finally, based on the predicted video popularity, we proactively replicate videos from the original CDN server to the APs at the edge. Through trace-driven simulations, we show that the proposed prefetching solution can outperform the baseline algorithms: compared with the SVD-based prefetching strategy, our design achieves a better hit ratio (e.g., surpassing about 10%) and accuracy (e.g., surpassing about 15%); compared with the history based strategy, our design also have about 40% (resp. 20%) improvement in terms of hit ratio (resp. accuracy).
{"title":"MUSA: Wi-Fi AP-assisted video prefetching via Tensor Learning","authors":"Wen Hu, Jiahui Huang, Zhi Wang, Peng Wang, Kun Yi, Yonggang Wen, Kaiyan Chu, Lifeng Sun","doi":"10.1109/IWQoS.2017.7969173","DOIUrl":"https://doi.org/10.1109/IWQoS.2017.7969173","url":null,"abstract":"Driven by the exponentially increasing amount of mobile video traffic, caching videos closer to the end users has become an appealing solution to reduce the traffic through the backbone network while improving users' perceived quality-of-experience (e.g., better video quality and reduced service delay). This research interest has been gaining lots of momentums due to the emergence of smart Access Points (APs), which are equipped with large storage space (several GBs). To address the “small population” problem involved in the prefetching at the edge, we propose to prefetch videos to APs ahead of users' requests via tensor learning: We first adopt the weighted tensor model to mine the hidden semantic pattern to characterize both users' preference for different types of videos and the dynamic video popularity over time; Then, based on the resulting low-dimension matrixes generated by the tensor factorization, we adopt an exponential smoothing model to capture the temporal pattern to predict users' propensity to unwatched videos; Finally, based on the predicted video popularity, we proactively replicate videos from the original CDN server to the APs at the edge. Through trace-driven simulations, we show that the proposed prefetching solution can outperform the baseline algorithms: compared with the SVD-based prefetching strategy, our design achieves a better hit ratio (e.g., surpassing about 10%) and accuracy (e.g., surpassing about 15%); compared with the history based strategy, our design also have about 40% (resp. 20%) improvement in terms of hit ratio (resp. accuracy).","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131111488","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 : 2017-06-14DOI: 10.1109/IWQoS.2017.7969161
Xiaojie Zhou, Kun Wang, Weijia Jia, M. Guo
For better service provision and utilization of renewable energy, Internet service providers have already built their data centers in geographically distributed locations. These companies balance quality of service (QoS) revenue and power consumption by migrating virtual machines (VMs) and allocating the resource of servers adaptively. However, existing approaches model the QoS revenue by service-level agreement (SLA) violation, and ignore the network communication cost and immigration time. In this paper, we propose a reinforcement learning-based adaptive resource management algorithm, which aims to get the balance between QoS revenue and power consumption. Our algorithm does not need to assume prior distribution of resource requirements, and is robust in actual workload. It outperforms other existing approaches in three aspects: 1) The QoS revenue is directly modeled by differentiated revenue of different tasks, instead of using SLA violation. 2) For geo-distributed data centers, the time spent on VM migration and network communication cost are taken into consideration. 3) The information storage and random action selection of reinforcement learning algorithms are optimized for rapid decision making. Experiments show that our proposed algorithm is more robust than the existing algorithms. Besides, the power consumption of our algorithm is around 13.3% and 9.6% better than the existing algorithms in non-differentiated and differentiated services.
{"title":"Reinforcement learning-based adaptive resource management of differentiated services in geo-distributed data centers","authors":"Xiaojie Zhou, Kun Wang, Weijia Jia, M. Guo","doi":"10.1109/IWQoS.2017.7969161","DOIUrl":"https://doi.org/10.1109/IWQoS.2017.7969161","url":null,"abstract":"For better service provision and utilization of renewable energy, Internet service providers have already built their data centers in geographically distributed locations. These companies balance quality of service (QoS) revenue and power consumption by migrating virtual machines (VMs) and allocating the resource of servers adaptively. However, existing approaches model the QoS revenue by service-level agreement (SLA) violation, and ignore the network communication cost and immigration time. In this paper, we propose a reinforcement learning-based adaptive resource management algorithm, which aims to get the balance between QoS revenue and power consumption. Our algorithm does not need to assume prior distribution of resource requirements, and is robust in actual workload. It outperforms other existing approaches in three aspects: 1) The QoS revenue is directly modeled by differentiated revenue of different tasks, instead of using SLA violation. 2) For geo-distributed data centers, the time spent on VM migration and network communication cost are taken into consideration. 3) The information storage and random action selection of reinforcement learning algorithms are optimized for rapid decision making. Experiments show that our proposed algorithm is more robust than the existing algorithms. Besides, the power consumption of our algorithm is around 13.3% and 9.6% better than the existing algorithms in non-differentiated and differentiated services.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126478200","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 : 2017-06-01DOI: 10.1109/IWQoS.2017.7969155
Jianping Weng, Jessie Hui Wang, Jiahai Yang, Yang Yang
Anomalies of multitier services running in cloud platform can be caused by components of the same tenant or performance interference from other tenants. If the performance of a multitier service degrades, we need to find out the root causes precisely to recover the service as soon as possible. In this paper, we argue that cloud providers are in a better position than tenants to solve this problem, and the solution should be non-intrusive to tenants' services or applications. Based on these two considerations, we propose a solution for cloud providers to help tenants to localize root causes of any anomaly. We design a non-intrusive method to capture the dependency relationships of components, which improves the feasibility of root cause localization system. Our solution can find out root causes no matter they are in the same tenant as the anomaly or from other tenants. Our proposed two-step localization algorithm exploits measurement data of both application layer and underlay infrastructure and a random walk procedure to improve its accuracy. Our real-world experiments of a three-tier web application running in a small-scale cloud platform show a 38.9% improvement in mean average precision compared to current methods.
{"title":"Root cause analysis of anomalies of multitier services in public clouds","authors":"Jianping Weng, Jessie Hui Wang, Jiahai Yang, Yang Yang","doi":"10.1109/IWQoS.2017.7969155","DOIUrl":"https://doi.org/10.1109/IWQoS.2017.7969155","url":null,"abstract":"Anomalies of multitier services running in cloud platform can be caused by components of the same tenant or performance interference from other tenants. If the performance of a multitier service degrades, we need to find out the root causes precisely to recover the service as soon as possible. In this paper, we argue that cloud providers are in a better position than tenants to solve this problem, and the solution should be non-intrusive to tenants' services or applications. Based on these two considerations, we propose a solution for cloud providers to help tenants to localize root causes of any anomaly. We design a non-intrusive method to capture the dependency relationships of components, which improves the feasibility of root cause localization system. Our solution can find out root causes no matter they are in the same tenant as the anomaly or from other tenants. Our proposed two-step localization algorithm exploits measurement data of both application layer and underlay infrastructure and a random walk procedure to improve its accuracy. Our real-world experiments of a three-tier web application running in a small-scale cloud platform show a 38.9% improvement in mean average precision compared to current methods.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124290790","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 : 2017-06-01DOI: 10.1109/IWQoS.2017.7969124
Jie Zhang, W. Lou
The idea of employees leveraging their personal mobile devices for their work (Bring Your Own Device, or BYOD) is becoming increasingly popular in recent years. As BYOD users will use various digital goods (such as cloud services and mobile software) for their work and personal purposes via the same mobile devices, it brings serious security risks into both the cloud and mobile devices. Generally, the BYOD users would employ digital rights management (DRM) to control and manage the execution of digital goods. However, the security requirements for using the digital goods for work and personal tasks are very different, and conventional unified cloud-based DRM services lack the flexibility to satisfy the BYOD users' demands on diversified security levels. In this paper, we regard the security of digital goods as a metric to differentiate the DRM service into multiple grades. We propose a differentiated DRM service to increase the security flexibility of digital goods, which allows BYOD users to choose their preferred DRM grades to maximize their utility. Moreover, the differentiated DRM service can increase the benefit of service providers (SPs) even when the SPs competes with others, and thus, it becomes a dominant strategy for the SPs.
近年来，员工利用自己的个人移动设备(Bring Your Own Device，简称BYOD)工作的想法变得越来越流行。由于BYOD用户将通过同一移动设备使用各种数字产品(如云服务和移动软件)进行工作和个人用途，这给云和移动设备带来了严重的安全风险。通常，BYOD用户会采用数字版权管理(DRM)来控制和管理数字产品的执行。然而，数字产品用于工作和个人任务的安全需求有很大不同，传统的基于云的统一DRM服务缺乏灵活性，无法满足BYOD用户多样化的安全需求。本文将数字商品的安全性作为区分数字版权管理服务等级的指标。我们提出了一种差异化的DRM服务，以增加数字产品的安全灵活性，允许BYOD用户选择自己喜欢的DRM等级，以最大限度地发挥其效用。此外，差异化DRM服务在服务提供商之间的竞争中也能增加服务提供商的利益，成为服务提供商的主导策略。
{"title":"Which DRM grade could BYOD users employ? A differentiated DRM service between the cloud and mobile devices","authors":"Jie Zhang, W. Lou","doi":"10.1109/IWQoS.2017.7969124","DOIUrl":"https://doi.org/10.1109/IWQoS.2017.7969124","url":null,"abstract":"The idea of employees leveraging their personal mobile devices for their work (Bring Your Own Device, or BYOD) is becoming increasingly popular in recent years. As BYOD users will use various digital goods (such as cloud services and mobile software) for their work and personal purposes via the same mobile devices, it brings serious security risks into both the cloud and mobile devices. Generally, the BYOD users would employ digital rights management (DRM) to control and manage the execution of digital goods. However, the security requirements for using the digital goods for work and personal tasks are very different, and conventional unified cloud-based DRM services lack the flexibility to satisfy the BYOD users' demands on diversified security levels. In this paper, we regard the security of digital goods as a metric to differentiate the DRM service into multiple grades. We propose a differentiated DRM service to increase the security flexibility of digital goods, which allows BYOD users to choose their preferred DRM grades to maximize their utility. Moreover, the differentiated DRM service can increase the benefit of service providers (SPs) even when the SPs competes with others, and thus, it becomes a dominant strategy for the SPs.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121872670","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 : 2017-06-01DOI: 10.1109/IWQoS.2017.7969123
Sheng Tao, Lin Gu, Deze Zeng, Hai Jin, Kan Hu
By softwarizing traditional dedicated hardware based functions to virtualized network functions (VNFs) that can run on standard commodity servers, network function virtualization (NFV) technology promises high efficiency, flexibility and scalability. To NFV service providers, one primary concern is to maximize network throughput and reduce service time. To reach this goal, two main challenges should be tackled: 1) how to schedule the unpredictable and burst network flows; 2) how to fairly allocate resources between various flows with different resource requirements. In this paper, we are motivated to investigate a throughput maximization problem with joint consideration of fairness between multiple flows using a discrete time queuing model. By taking advantages of Lyapunov optimization techniques, we propose a low-complexity online distributed algorithm that can achieve arbitrary optimal utility with different fairness levels by tuning the fairness bias. The high efficiency of our proposal is validated by both theoretical analysis and extensive simulation studies.
网络功能虚拟化(network function virtualization, NFV)技术将传统的专用硬件功能软件化为可在标准商用服务器上运行的虚拟化网络功能(virtual network function, VNFs)，从而保证了高效率、灵活性和可扩展性。对于NFV服务提供商来说，最大限度地提高网络吞吐量和缩短服务时间是一个主要问题。为了实现这一目标，需要解决两个主要挑战:1)如何调度不可预测和突发的网络流量;2)如何在不同资源需求的各个流之间公平分配资源。在本文中，我们被激励研究一个吞吐量最大化问题，联合考虑多个流之间的公平性使用离散时间排队模型。利用李雅普诺夫优化技术，提出了一种低复杂度的在线分布式算法，该算法可以通过调整公平性偏差来实现不同公平性水平下的任意最优效用。理论分析和大量的仿真研究验证了我们的方案的高效性。
{"title":"Fairness-aware dynamic rate control and flow scheduling for network function virtualization","authors":"Sheng Tao, Lin Gu, Deze Zeng, Hai Jin, Kan Hu","doi":"10.1109/IWQoS.2017.7969123","DOIUrl":"https://doi.org/10.1109/IWQoS.2017.7969123","url":null,"abstract":"By softwarizing traditional dedicated hardware based functions to virtualized network functions (VNFs) that can run on standard commodity servers, network function virtualization (NFV) technology promises high efficiency, flexibility and scalability. To NFV service providers, one primary concern is to maximize network throughput and reduce service time. To reach this goal, two main challenges should be tackled: 1) how to schedule the unpredictable and burst network flows; 2) how to fairly allocate resources between various flows with different resource requirements. In this paper, we are motivated to investigate a throughput maximization problem with joint consideration of fairness between multiple flows using a discrete time queuing model. By taking advantages of Lyapunov optimization techniques, we propose a low-complexity online distributed algorithm that can achieve arbitrary optimal utility with different fairness levels by tuning the fairness bias. The high efficiency of our proposal is validated by both theoretical analysis and extensive simulation studies.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124437146","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 : 2017-06-01DOI: 10.1109/IWQoS.2017.7969176
K. Tanabe, Hiroki Nakayama, Tsunemasa Hayashi, K. Yamaoka
In this paper, we study a resource granularity effect on the optimal resource assignment of MME and S/P-GW in a single vEPC server. We distinguished communications of M2M devices and smartphones and modeled the vEPC server by using queueing theory. Numerical analysis under a fixed number of hardware resources of MME and S/P-GW is done for various resource granularities of the vEPC server. The evaluation results of numerical analysis showed that the vEPC-ORA method derives the optimal resource assignment in a practical calculation time.
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