Pub Date : 2017-06-01DOI: 10.1109/IWQoS.2017.7969168
Yatong Chen, Huangxun Chen, Shuo Yang, Xiaofeng Gao, Fan Wu
In the past decade, with the rapid development of wireless communication and sensor technology, ubiquitous smartphones equipped with increasingly rich sensors have more powerful computing and sensing abilities. Thus, mobile crowdsensing has received extensive attentions from both industry and academia. Recently, plenty of mobile crowdsensing applications come forth, such as indoor positioning, environment monitoring, transportation, and so on. However, most existing mobile crowdsensing systems lack of vast user bases, and thus urgently need appropriate incentive mechanisms to attract mobile users to guarantee the service quality. In this paper, we propose to incorporate sensing platform and social network applications, which already have large user bases to build a three-layer network model. Thus, we can publicize the sensing platform promptly in large scale, and provide long-term guarantee of data sources. Based on a three-layer network model, we design incentive mechanisms for both intermediaries and the crowdsensing platform, and provide a solution to cope with the problem of user overlapping among intermediaries. We indicate the properties of our proposed incentive mechanisms, including incentive compatibility, individual rationality, and efficiency.
{"title":"Jump-start crowdsensing: A three-layer incentive framework for mobile crowdsensing","authors":"Yatong Chen, Huangxun Chen, Shuo Yang, Xiaofeng Gao, Fan Wu","doi":"10.1109/IWQoS.2017.7969168","DOIUrl":"https://doi.org/10.1109/IWQoS.2017.7969168","url":null,"abstract":"In the past decade, with the rapid development of wireless communication and sensor technology, ubiquitous smartphones equipped with increasingly rich sensors have more powerful computing and sensing abilities. Thus, mobile crowdsensing has received extensive attentions from both industry and academia. Recently, plenty of mobile crowdsensing applications come forth, such as indoor positioning, environment monitoring, transportation, and so on. However, most existing mobile crowdsensing systems lack of vast user bases, and thus urgently need appropriate incentive mechanisms to attract mobile users to guarantee the service quality. In this paper, we propose to incorporate sensing platform and social network applications, which already have large user bases to build a three-layer network model. Thus, we can publicize the sensing platform promptly in large scale, and provide long-term guarantee of data sources. Based on a three-layer network model, we design incentive mechanisms for both intermediaries and the crowdsensing platform, and provide a solution to cope with the problem of user overlapping among intermediaries. We indicate the properties of our proposed incentive mechanisms, including incentive compatibility, individual rationality, and efficiency.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"507 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":"123422870","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.2017.7969175
Ruichu Cai, Feng Xie, Wei Chen, Z. Hao
Understanding the causality behind the observational data is of great importance to a lot of real world applications, e.g., the improvement of Quality of Service. Non-Gaussianity has been exploited in numerous causal discovery methods for observational linear acyclic data. Transforming non-Gaussianity into indirect metrics is a conventional solution employed by existing methods, although this usually results in unreliable estimations or locally optimal solutions. In this work, we employs the excess kurtosis, a direct measure of non-Gaussianity, to establish a causal discovery method for linear non-Gaussian acyclic data. Firstly, we theoretically prove that an exogenous variable has the largest excess kurtosis when disturbance variables follow independent and identically distributions. Secondly, based on this property of exogenous variables, we propose an efficient exogenous variable identification algorithm, and develop a causal discovery method. Extensive experiment results verify the effectiveness and efficiency of the proposed approach.
{"title":"An efficient kurtosis-based causal discovery method for linear non-Gaussian acyclic data","authors":"Ruichu Cai, Feng Xie, Wei Chen, Z. Hao","doi":"10.1109/IWQoS.2017.7969175","DOIUrl":"https://doi.org/10.1109/IWQoS.2017.7969175","url":null,"abstract":"Understanding the causality behind the observational data is of great importance to a lot of real world applications, e.g., the improvement of Quality of Service. Non-Gaussianity has been exploited in numerous causal discovery methods for observational linear acyclic data. Transforming non-Gaussianity into indirect metrics is a conventional solution employed by existing methods, although this usually results in unreliable estimations or locally optimal solutions. In this work, we employs the excess kurtosis, a direct measure of non-Gaussianity, to establish a causal discovery method for linear non-Gaussian acyclic data. Firstly, we theoretically prove that an exogenous variable has the largest excess kurtosis when disturbance variables follow independent and identically distributions. Secondly, based on this property of exogenous variables, we propose an efficient exogenous variable identification algorithm, and develop a causal discovery method. Extensive experiment results verify the effectiveness and efficiency of the proposed approach.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"26 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":"133498918","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.2017.7969164
Xinchang Zhang, Yinglong Wang, Jianwei Zhang, Lu Wang, Yanling Zhao
Packet loss rate is an important consideration in the Quality of Service (QoS) measurement for a packet-switched network. The software-defined networking (SDN) technique can conveniently monitor flow statistics. However, the packet loss rate of a link or path cannot be directly measured by inquiring the statistics of an ongoing flow at the starting and ending points because it is impossible to accurately compute and control pairwise sampling moments. In this paper, we propose a two-way link-level packet loss measurement solution for software-defined networks. We solve the flow statistics sampling problem mentioned above by inquiring the statistics of a terminated probe flow. We propose a ring-based packet loss probe structure, which contains every measured directed link once and only once. The proposed probe structure effectively avoids the mutual interference between different probe flows, and thereby improves probe accuracy. The ring is implemented based on the flexible flow match capability of SDN. We further study an optimization problem of ring-based packet loss probe structure that strives to minimize the maximum delay of rings. This optimization problem is very complex, and we approximately solve it using a top-down-top graph partition method. A packet loss positioning method, based on flow statistic inquiries and the symmetry design of the probe ring, is also proposed herein.
{"title":"A two-way link loss measurement approach for software-defined networks","authors":"Xinchang Zhang, Yinglong Wang, Jianwei Zhang, Lu Wang, Yanling Zhao","doi":"10.1109/IWQoS.2017.7969164","DOIUrl":"https://doi.org/10.1109/IWQoS.2017.7969164","url":null,"abstract":"Packet loss rate is an important consideration in the Quality of Service (QoS) measurement for a packet-switched network. The software-defined networking (SDN) technique can conveniently monitor flow statistics. However, the packet loss rate of a link or path cannot be directly measured by inquiring the statistics of an ongoing flow at the starting and ending points because it is impossible to accurately compute and control pairwise sampling moments. In this paper, we propose a two-way link-level packet loss measurement solution for software-defined networks. We solve the flow statistics sampling problem mentioned above by inquiring the statistics of a terminated probe flow. We propose a ring-based packet loss probe structure, which contains every measured directed link once and only once. The proposed probe structure effectively avoids the mutual interference between different probe flows, and thereby improves probe accuracy. The ring is implemented based on the flexible flow match capability of SDN. We further study an optimization problem of ring-based packet loss probe structure that strives to minimize the maximum delay of rings. This optimization problem is very complex, and we approximately solve it using a top-down-top graph partition method. A packet loss positioning method, based on flow statistic inquiries and the symmetry design of the probe ring, is also proposed herein.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"45 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":"115182501","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.2017.7969137
Lailong Luo, Deke Guo, Jia Xu, Xueshan Luo
The topology of data centers changes dynamically due to link malpositions, hardware failures or software crushes. However, many topology enabled protocols or applications must know the current topology of data center precisely, which triggers the topology calibration problem. Topology calibration needs to deduce the different nodes and links between two given topologies effectively. Based on the existing method, deriving the different nodes is relatively simple, since they can be uniquely identified by their IP or MAC addresses. On the contrary, picking the different links from the massive links can be costly. Therefore, we envision a method to locate the different links with respect to the following rationales: 1) efficient, the caused storage cost or communication overhead should be low; 2) without priori knowledge, there is no support information, thus the different links should be decoded inversely. However, the existing strategies based on Bloom filter, Hash table, or Search trees fail to achieve the two rationales simultaneously. Thus, we propose graph filter, a space-efficient data structure to represent and deduce the different links in an invertible manner. To this end, the associated encoding, subtracting and decoding algorithms are proposed. The simulations highlight the strength of graph filter reasonably.
{"title":"Topology calibration in data centers","authors":"Lailong Luo, Deke Guo, Jia Xu, Xueshan Luo","doi":"10.1109/IWQoS.2017.7969137","DOIUrl":"https://doi.org/10.1109/IWQoS.2017.7969137","url":null,"abstract":"The topology of data centers changes dynamically due to link malpositions, hardware failures or software crushes. However, many topology enabled protocols or applications must know the current topology of data center precisely, which triggers the topology calibration problem. Topology calibration needs to deduce the different nodes and links between two given topologies effectively. Based on the existing method, deriving the different nodes is relatively simple, since they can be uniquely identified by their IP or MAC addresses. On the contrary, picking the different links from the massive links can be costly. Therefore, we envision a method to locate the different links with respect to the following rationales: 1) efficient, the caused storage cost or communication overhead should be low; 2) without priori knowledge, there is no support information, thus the different links should be decoded inversely. However, the existing strategies based on Bloom filter, Hash table, or Search trees fail to achieve the two rationales simultaneously. Thus, we propose graph filter, a space-efficient data structure to represent and deduce the different links in an invertible manner. To this end, the associated encoding, subtracting and decoding algorithms are proposed. The simulations highlight the strength of graph filter reasonably.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"16 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":"127151849","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.2017.7969125
Jianyuan Lu, Ying Wan, Yang Li, Chuwen Zhang, Huichen Dai, Yi Wang, Gong Zhang, B. Liu
The network link speed is increasing at an alarming rate, which requires all network functions on routers/switches to keep pace. Bloom filter is a widely-used membership check data structure in network applications. It also faces the urgent demand of improving the performance in membership check speed. To this end, this paper proposes a new Bloom filter variant called Ultra-Fast Bloom Filters, by leveraging the SIMD techniques. We make three improvements for the UFBF to accelerate the membership check speed. First, we develop a novel hash computation algorithm which can compute multiple hash functions in parallel with the use of SIMD instructions. Second, we change a Bloom filter's bit-test process from sequential to parallel. Third, we increase the cache efficiency of membership check by encoding an element's information to a small block which can easily fit into a cache-line. Both theoretical analysis and extensive simulations show that the UFBF greatly exceeds the state-of-the-art Bloom filter variants on membership check speed.
{"title":"Ultra-Fast Bloom Filters using SIMD techniques","authors":"Jianyuan Lu, Ying Wan, Yang Li, Chuwen Zhang, Huichen Dai, Yi Wang, Gong Zhang, B. Liu","doi":"10.1109/IWQoS.2017.7969125","DOIUrl":"https://doi.org/10.1109/IWQoS.2017.7969125","url":null,"abstract":"The network link speed is increasing at an alarming rate, which requires all network functions on routers/switches to keep pace. Bloom filter is a widely-used membership check data structure in network applications. It also faces the urgent demand of improving the performance in membership check speed. To this end, this paper proposes a new Bloom filter variant called Ultra-Fast Bloom Filters, by leveraging the SIMD techniques. We make three improvements for the UFBF to accelerate the membership check speed. First, we develop a novel hash computation algorithm which can compute multiple hash functions in parallel with the use of SIMD instructions. Second, we change a Bloom filter's bit-test process from sequential to parallel. Third, we increase the cache efficiency of membership check by encoding an element's information to a small block which can easily fit into a cache-line. Both theoretical analysis and extensive simulations show that the UFBF greatly exceeds the state-of-the-art Bloom filter variants on membership check speed.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"18 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":"133497541","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.2017.7969177
Zhiyuan Peng, Ranga Reddy Pallelra, Haiyang Wang
Recent years have witnessed a growing popularity of file synchronization systems. In this paper, we take a first step towards the understandings of a new Peer-to-Peer file synchronization system, Resilio Sync. Our real-world measurement identifies its unique features and reveals its potential fairness issues
{"title":"On the measurement of P2P file synchronization: Resilio Sync as a case study","authors":"Zhiyuan Peng, Ranga Reddy Pallelra, Haiyang Wang","doi":"10.1109/IWQoS.2017.7969177","DOIUrl":"https://doi.org/10.1109/IWQoS.2017.7969177","url":null,"abstract":"Recent years have witnessed a growing popularity of file synchronization systems. In this paper, we take a first step towards the understandings of a new Peer-to-Peer file synchronization system, Resilio Sync. Our real-world measurement identifies its unique features and reveals its potential fairness issues","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128722399","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.2017.7969118
You Zhou, Yian Zhou, Shigang Chen, Youlin Zhang
Per-flow counting for big network data streams is a fundamental problem in various network applications such as traffic monitoring, load balancing, capacity planning, etc. Traditional research focused on designing compact data structures to estimate flow sizes from the beginning of the data stream (i.e., landmark window model). However, for many applications, the most recent elements of a stream are more significant than those arrived long time ago, which gives rise to the sliding window model. In this paper, we consider per-flow counting over the sliding window model, and propose two novel solutions, ACE and S-ACE. Instead of allocating a separate data structure for each flow, both solutions utilize the counter sharing idea to reduce memory footprint, so they can be implemented in on-chip SRAMs in modern routers to keep up with the line speed. ACE has to reset the sliding window periodically to give precise estimates, while S-ACE based on a novel segment design can achieve persistently accurate estimates. Our extensive simulations as well as experimental evaluations based on real network traffic trace demonstrate that S-ACE can achieve fast processing speed and high measurement accuracy even with a very tight memory.
{"title":"Per-flow counting for big network data stream over sliding windows","authors":"You Zhou, Yian Zhou, Shigang Chen, Youlin Zhang","doi":"10.1109/IWQoS.2017.7969118","DOIUrl":"https://doi.org/10.1109/IWQoS.2017.7969118","url":null,"abstract":"Per-flow counting for big network data streams is a fundamental problem in various network applications such as traffic monitoring, load balancing, capacity planning, etc. Traditional research focused on designing compact data structures to estimate flow sizes from the beginning of the data stream (i.e., landmark window model). However, for many applications, the most recent elements of a stream are more significant than those arrived long time ago, which gives rise to the sliding window model. In this paper, we consider per-flow counting over the sliding window model, and propose two novel solutions, ACE and S-ACE. Instead of allocating a separate data structure for each flow, both solutions utilize the counter sharing idea to reduce memory footprint, so they can be implemented in on-chip SRAMs in modern routers to keep up with the line speed. ACE has to reset the sliding window periodically to give precise estimates, while S-ACE based on a novel segment design can achieve persistently accurate estimates. Our extensive simulations as well as experimental evaluations based on real network traffic trace demonstrate that S-ACE can achieve fast processing speed and high measurement accuracy even with a very tight memory.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"11 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":"123818515","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.2017.7969160
Yu Xu, Jianguo Yao, H. Jacobsen, Haibing Guan
Cloud applications can achieve similar performance with diverse multi-resource configurations, allowing cloud service providers to benefit from optimal resource allocation for reducing their operation cost. This paper aims to solve the problem of multi-resource negotiation with considerations of both the service-level agreement (SLA) and the cost efficiency. The performance and resource demand are usually application-dependent, making the optimization problem complicated, especially when the dimension of multi-resource configuration is large. To this end, we use reinforcement learning to solve the optimization problem of multi-resource configuration with simultaneous optimization of the learning efficiency and performance guarantee. The developed prototype named SmartYARN is extended Apache YARN equipped with our learning algorithm which can enable cloud applications to negotiate multiple resources cost-effectively. The extensive evaluations show that SmartYARN performs well in reducing the cost of resource usage while maintaining compliance with the SLA constraints of cloud service simultaneously.
{"title":"Cost-efficient negotiation over multiple resources with reinforcement learning","authors":"Yu Xu, Jianguo Yao, H. Jacobsen, Haibing Guan","doi":"10.1109/IWQoS.2017.7969160","DOIUrl":"https://doi.org/10.1109/IWQoS.2017.7969160","url":null,"abstract":"Cloud applications can achieve similar performance with diverse multi-resource configurations, allowing cloud service providers to benefit from optimal resource allocation for reducing their operation cost. This paper aims to solve the problem of multi-resource negotiation with considerations of both the service-level agreement (SLA) and the cost efficiency. The performance and resource demand are usually application-dependent, making the optimization problem complicated, especially when the dimension of multi-resource configuration is large. To this end, we use reinforcement learning to solve the optimization problem of multi-resource configuration with simultaneous optimization of the learning efficiency and performance guarantee. The developed prototype named SmartYARN is extended Apache YARN equipped with our learning algorithm which can enable cloud applications to negotiate multiple resources cost-effectively. The extensive evaluations show that SmartYARN performs well in reducing the cost of resource usage while maintaining compliance with the SLA constraints of cloud service simultaneously.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130501867","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.2017.7969126
Itamar Cohen, Gabriel Scalosub
Scheduling and managing queues with bounded buffers are among the most fundamental problems in computer networking. Traditionally, it is often assumed that all the properties of each packet are known immediately upon arrival. However, as traffic becomes increasingly heterogeneous and complex, such assumptions are in many cases invalid. In particular, in various scenarios information about packet characteristics becomes available only after the packet has undergone some initial processing. In this work, we study the problem of managing queues with limited knowledge. We start by showing lower bounds on the competitive ratio of any algorithm in such settings. Next, we use the insight obtained from these bounds to identify several algorithmic concepts appropriate for the problem, and use these guidelines to design a concrete algorithmic framework. We analyze the performance of our proposed algorithm, and further show how it can be implemented in various settings, which differ by the type and nature of the unknown information. We further validate our results and algorithmic approach by a simulation study that provides further insights as to our algorithmic design principles in face of limited knowledge.
{"title":"Queueing in the mist: Buffering and scheduling with limited knowledge","authors":"Itamar Cohen, Gabriel Scalosub","doi":"10.1109/IWQoS.2017.7969126","DOIUrl":"https://doi.org/10.1109/IWQoS.2017.7969126","url":null,"abstract":"Scheduling and managing queues with bounded buffers are among the most fundamental problems in computer networking. Traditionally, it is often assumed that all the properties of each packet are known immediately upon arrival. However, as traffic becomes increasingly heterogeneous and complex, such assumptions are in many cases invalid. In particular, in various scenarios information about packet characteristics becomes available only after the packet has undergone some initial processing. In this work, we study the problem of managing queues with limited knowledge. We start by showing lower bounds on the competitive ratio of any algorithm in such settings. Next, we use the insight obtained from these bounds to identify several algorithmic concepts appropriate for the problem, and use these guidelines to design a concrete algorithmic framework. We analyze the performance of our proposed algorithm, and further show how it can be implemented in various settings, which differ by the type and nature of the unknown information. We further validate our results and algorithmic approach by a simulation study that provides further insights as to our algorithmic design principles in face of limited knowledge.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"43 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":"124203295","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.2017.7969150
Xiaoli Zhang, Qi Li, Jianping Wu, Jiahai Yang
Network Function Virtualization (NFV) is an emerging technology to enable network functions (NFs) outsourcing on cloud so as to reduce the costs of deploying and maintaining NFs. However, NF outsourcing poses a serious gap between the expected service function chains (SFCs) and the real enforcement because SFC deployment and management on cloud is invisible to NF customers (i.e., enterprises). In this paper, we propose verifiable SFC, i.e., vSFC, the first scheme that allows an enterprise to accurately verify the correct enforcement of SFC in realtime. In particular, different from the-state-of-the-art network function verification schemes, vSFC is generic and agile, which can be deployed on various clouds, while not requiring modifications to any NFs on cloud. vSFC detects a wide range of SFC violations including forwarding path incompliance, flow dropping, and packet injection attacks. To demonstrate the feasibility and performance of vSFC, we implement a vSFC prototype built on top of KVM and conduct experiments with real traces. Our experiment results show that vSFC detects various SFC violations with a negligible overhead.
NFV (Network Function Virtualization)是一种新兴的网络功能外包技术，旨在将网络功能外包到云端，从而降低网络功能的部署和维护成本。然而，由于服务功能链在云上的部署和管理对NF客户(即企业)来说是不可见的，因此NF外包在预期的服务功能链(SFC)和实际执行之间造成了严重的差距。在本文中，我们提出了可验证的SFC，即vSFC，这是第一个允许企业实时准确验证正确执行SFC的方案。特别是vSFC不同于目前最先进的网络功能验证方案，它具有通用性和敏捷性，可以部署在各种云中，而不需要在云中修改任何NFs。vSFC可以检测广泛的SFC违规行为，包括转发路径不符合、流丢弃和包注入攻击。为了证明vSFC的可行性和性能，我们在KVM上实现了一个vSFC原型，并进行了真实痕迹的实验。我们的实验结果表明，vSFC以可以忽略不计的开销检测各种SFC违规。
{"title":"Generic and agile service function chain verification on cloud","authors":"Xiaoli Zhang, Qi Li, Jianping Wu, Jiahai Yang","doi":"10.1109/IWQoS.2017.7969150","DOIUrl":"https://doi.org/10.1109/IWQoS.2017.7969150","url":null,"abstract":"Network Function Virtualization (NFV) is an emerging technology to enable network functions (NFs) outsourcing on cloud so as to reduce the costs of deploying and maintaining NFs. However, NF outsourcing poses a serious gap between the expected service function chains (SFCs) and the real enforcement because SFC deployment and management on cloud is invisible to NF customers (i.e., enterprises). In this paper, we propose verifiable SFC, i.e., vSFC, the first scheme that allows an enterprise to accurately verify the correct enforcement of SFC in realtime. In particular, different from the-state-of-the-art network function verification schemes, vSFC is generic and agile, which can be deployed on various clouds, while not requiring modifications to any NFs on cloud. vSFC detects a wide range of SFC violations including forwarding path incompliance, flow dropping, and packet injection attacks. To demonstrate the feasibility and performance of vSFC, we implement a vSFC prototype built on top of KVM and conduct experiments with real traces. Our experiment results show that vSFC detects various SFC violations with a negligible overhead.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"9 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":"114346395","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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