Pub Date : 2018-06-01DOI: 10.1109/IWQoS.2018.8624135
Xue Leng, Kaiyu Hou, Yan Chen, Kai Bu, Libin Song
SDN-based cloud has the merit of allowing more flexibility in network management, however, the security of network accessing and the correctness of network configuration in SDN-based cloud have not been effectively addressed yet. In this paper, SDNKeeper, a generic and fine-grained policy enforcement system in SDN-based cloud is proposed, which can defend against unauthorized attacks and avoid network resource misconfiguration. With the usage of SDNKeeper, numerous flexible network management policies can be created by administrators, which give administrators the discretionary room on controlling the network resources. To be specific, SDNKeeper can reject any unauthorized network access request at Northbound Interface (NBI), which located between application plane and control plane. Moreover, compared with other traditional policy-based access control systems, SDNKeeper is totally application-transparent and lightweight, which is easy to implement, deploy and runtime configure. Based on the prototype implementation and evaluation, we conclude that SDNKeeper can perform access control accurately with negligible computation overhead whilst the throughput degradation is still within the acceptable range.
{"title":"SDNKeeper: Lightweight Resource Protection and Management System for SDN-Based Cloud","authors":"Xue Leng, Kaiyu Hou, Yan Chen, Kai Bu, Libin Song","doi":"10.1109/IWQoS.2018.8624135","DOIUrl":"https://doi.org/10.1109/IWQoS.2018.8624135","url":null,"abstract":"SDN-based cloud has the merit of allowing more flexibility in network management, however, the security of network accessing and the correctness of network configuration in SDN-based cloud have not been effectively addressed yet. In this paper, SDNKeeper, a generic and fine-grained policy enforcement system in SDN-based cloud is proposed, which can defend against unauthorized attacks and avoid network resource misconfiguration. With the usage of SDNKeeper, numerous flexible network management policies can be created by administrators, which give administrators the discretionary room on controlling the network resources. To be specific, SDNKeeper can reject any unauthorized network access request at Northbound Interface (NBI), which located between application plane and control plane. Moreover, compared with other traditional policy-based access control systems, SDNKeeper is totally application-transparent and lightweight, which is easy to implement, deploy and runtime configure. Based on the prototype implementation and evaluation, we conclude that SDNKeeper can perform access control accurately with negligible computation overhead whilst the throughput degradation is still within the acceptable range.","PeriodicalId":222290,"journal":{"name":"2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129921135","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 : 2018-06-01DOI: 10.1109/IWQoS.2018.8624123
Xiaohui Wei, Yuanyuan Liu, Shang Gao, Xingwang Wang
With increasing real-time and resource-intensive requirements, approximate computing is widely adopted to improve the performance of query processing over data streams. However, existing works concentrate on simple queries with single-step operations, such as point or join queries. There are a large number of nested queries with selection or filtering operations before aggregation. In this poster, we focus on approximate nested stream queries. We first propose a novel approximate model, SCM-sketches, that makes two-stage approximation for nested query answering with guaranteed errors. In the first stage for nested filtering operations, we use the sampling method to compress the arriving data. Then in the second stage, a sketch is used for further aggregation or join operations. We also theoretically analyze the effect of error propagation on approximate errors. Compared with existing sketch-based methods, experiment results with real-life datasets verify the effectiveness of SCM-sketches.
{"title":"Energy-Aware Allocation of Approximate Query Processing Over Data Streams with Error Guarantee","authors":"Xiaohui Wei, Yuanyuan Liu, Shang Gao, Xingwang Wang","doi":"10.1109/IWQoS.2018.8624123","DOIUrl":"https://doi.org/10.1109/IWQoS.2018.8624123","url":null,"abstract":"With increasing real-time and resource-intensive requirements, approximate computing is widely adopted to improve the performance of query processing over data streams. However, existing works concentrate on simple queries with single-step operations, such as point or join queries. There are a large number of nested queries with selection or filtering operations before aggregation. In this poster, we focus on approximate nested stream queries. We first propose a novel approximate model, SCM-sketches, that makes two-stage approximation for nested query answering with guaranteed errors. In the first stage for nested filtering operations, we use the sampling method to compress the arriving data. Then in the second stage, a sketch is used for further aggregation or join operations. We also theoretically analyze the effect of error propagation on approximate errors. Compared with existing sketch-based methods, experiment results with real-life datasets verify the effectiveness of SCM-sketches.","PeriodicalId":222290,"journal":{"name":"2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134225280","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 : 2018-06-01DOI: 10.1109/IWQoS.2018.8624180
Qingyu Shi, F. Wang, D. Feng, Weibin Xie
In datacenter networks, multipath exists to facilitate parallel data transmission. Taking deployment challenges into account, some optimized alternatives (e.g. CLOVE, Hermes) to ECMP balance load at the virtual edge or hosts. However inaccuracies of congestion detection and reaction exist in these solutions. They either detect congestion through ECN and coarse-grained RTT measurements or are congestion-oblivious. These congestion feedbacks are not sufficient enough to indicate the accurate congestion status under asymmetry. And when rerouting events occur on multiple paths, ACKs with congestion feedback of other paths can improperly influence the current sending rate. Therefore, we explore how to balance load by solving above inaccuracy problems while ensuring good adaptation to commodity switches and existing network protocols. We propose ALB, an adaptive load-balancing mechanism based on accurate congestion feedback running at end hosts, which is resilient to asymmetry. ALB leverage a latency-based congestion detection to precisely route flowlets to lighter load paths, and an ACK correction method to avoid inaccurate flow rate adjustment. In large-scale simulations ALB achieves up to 7% and 40% better flow completion time (FCT) than CONGA and CLOVE-ECN under asymmetry.
{"title":"ALB: Adaptive Load Balancing Based on Accurate Congestion Feedback for Asymmetric Topologies","authors":"Qingyu Shi, F. Wang, D. Feng, Weibin Xie","doi":"10.1109/IWQoS.2018.8624180","DOIUrl":"https://doi.org/10.1109/IWQoS.2018.8624180","url":null,"abstract":"In datacenter networks, multipath exists to facilitate parallel data transmission. Taking deployment challenges into account, some optimized alternatives (e.g. CLOVE, Hermes) to ECMP balance load at the virtual edge or hosts. However inaccuracies of congestion detection and reaction exist in these solutions. They either detect congestion through ECN and coarse-grained RTT measurements or are congestion-oblivious. These congestion feedbacks are not sufficient enough to indicate the accurate congestion status under asymmetry. And when rerouting events occur on multiple paths, ACKs with congestion feedback of other paths can improperly influence the current sending rate. Therefore, we explore how to balance load by solving above inaccuracy problems while ensuring good adaptation to commodity switches and existing network protocols. We propose ALB, an adaptive load-balancing mechanism based on accurate congestion feedback running at end hosts, which is resilient to asymmetry. ALB leverage a latency-based congestion detection to precisely route flowlets to lighter load paths, and an ACK correction method to avoid inaccurate flow rate adjustment. In large-scale simulations ALB achieves up to 7% and 40% better flow completion time (FCT) than CONGA and CLOVE-ECN under asymmetry.","PeriodicalId":222290,"journal":{"name":"2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125426798","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 : 2018-06-01DOI: 10.1109/IWQoS.2018.8624151
Chen Sun, J. Bi, Zili Meng, Xiao Zhang, Hongxin Hu
Network Function Virtualization (NFV) together with Software Defined Networking (SDN) offers the potential for enhancing service delivery flexibility and reducing overall costs. Based on the capability of dynamic creation and destruction of network function (NF) instances, NFV provides great elasticity in NF control, such as NF scaling out, scaling in, load balancing, etc. To realize NFV elasticity control, network traffic flows need to be redistributed across NF instances. However, deciding which flows are suitable for migration is a critical problem for efficient NFV elasticity control. In this paper, we propose to build an innovative flow migration controller, OFM Controller, to achieve optimized flow migration for NFV elasticity control. We identify the trigger conditions and control goals for different situations, and carefully design models and algorithms to address three major challenges including buffer overflow avoidance, migration cost calculation, and effective flow selection for migration. We implement the OFM Controller on top of NFV and SDN environments. Our evaluation results show that OFM Controller is efficient to support optimized flow migration in NFV elasticity control.
{"title":"OFM: Optimized Flow Migration for NFV Elasticity Control","authors":"Chen Sun, J. Bi, Zili Meng, Xiao Zhang, Hongxin Hu","doi":"10.1109/IWQoS.2018.8624151","DOIUrl":"https://doi.org/10.1109/IWQoS.2018.8624151","url":null,"abstract":"Network Function Virtualization (NFV) together with Software Defined Networking (SDN) offers the potential for enhancing service delivery flexibility and reducing overall costs. Based on the capability of dynamic creation and destruction of network function (NF) instances, NFV provides great elasticity in NF control, such as NF scaling out, scaling in, load balancing, etc. To realize NFV elasticity control, network traffic flows need to be redistributed across NF instances. However, deciding which flows are suitable for migration is a critical problem for efficient NFV elasticity control. In this paper, we propose to build an innovative flow migration controller, OFM Controller, to achieve optimized flow migration for NFV elasticity control. We identify the trigger conditions and control goals for different situations, and carefully design models and algorithms to address three major challenges including buffer overflow avoidance, migration cost calculation, and effective flow selection for migration. We implement the OFM Controller on top of NFV and SDN environments. Our evaluation results show that OFM Controller is efficient to support optimized flow migration in NFV elasticity control.","PeriodicalId":222290,"journal":{"name":"2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)","volume":"52 s37","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120839401","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 : 2018-06-01DOI: 10.1109/IWQoS.2018.8624161
A. Erfanian, F. Tashtarian, M. Moghaddam
HTTP adaptive streaming (HAS) is quickly becoming the dominant video delivery technique for adaptive streaming over the Internet. Still considered as its primary challenges are determining the optimal rate adaptation and improving both the quality of experience (QoE) and QoE-fairness. Recent studies have shown that techniques providing a comprehensive and central view of the network resources can lead to greater gains in performance. By leveraging software defined networking (SDN), the current study proposes an SDN-based approach to maximize QoE metrics and QoE-fairness in AVC-based HTTP adaptive streaming. The proposed approach determines both the optimal adaptation and data paths for delivering the requested video files from HTTP-media servers to DASH clients. In fact, the proposed approach, which includes a set of application modules, is centrally executed by an SND controller in a time slot fashion. We formulate the problem as a mixed integer linear programming (MILP) optimization model in such a way that it applies defined policies, e.g. setting priorities for clients in obtaining video quality. We conduct experiments by emulating the proposed framework in Mininet using Floodlight as the SDN controller. In terms of improving QoE-fairness and QoE metrics, the effectiveness of the proposed approach is validated by a comparison with different approaches.
{"title":"On Maximizing QoE in AVC-Based HTTP Adaptive Streaming: An SDN Approach","authors":"A. Erfanian, F. Tashtarian, M. Moghaddam","doi":"10.1109/IWQoS.2018.8624161","DOIUrl":"https://doi.org/10.1109/IWQoS.2018.8624161","url":null,"abstract":"HTTP adaptive streaming (HAS) is quickly becoming the dominant video delivery technique for adaptive streaming over the Internet. Still considered as its primary challenges are determining the optimal rate adaptation and improving both the quality of experience (QoE) and QoE-fairness. Recent studies have shown that techniques providing a comprehensive and central view of the network resources can lead to greater gains in performance. By leveraging software defined networking (SDN), the current study proposes an SDN-based approach to maximize QoE metrics and QoE-fairness in AVC-based HTTP adaptive streaming. The proposed approach determines both the optimal adaptation and data paths for delivering the requested video files from HTTP-media servers to DASH clients. In fact, the proposed approach, which includes a set of application modules, is centrally executed by an SND controller in a time slot fashion. We formulate the problem as a mixed integer linear programming (MILP) optimization model in such a way that it applies defined policies, e.g. setting priorities for clients in obtaining video quality. We conduct experiments by emulating the proposed framework in Mininet using Floodlight as the SDN controller. In terms of improving QoE-fairness and QoE metrics, the effectiveness of the proposed approach is validated by a comparison with different approaches.","PeriodicalId":222290,"journal":{"name":"2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128015437","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 : 2018-06-01DOI: 10.1109/IWQoS.2018.8624131
Omotayo Oshiga, Xiaowen Chu, Y. Leung, J. Ng
Many indoor localization systems rely on a set of reference anchors with known positions. A target's location is estimated from a set of distances between the target and its surrounding anchors, and hence the selection of anchors affects the localization accuracy. However, it remains a challenge to select the best set of anchors. In this paper, we study how to appropriately make use of the surrounding anchors for localizing a target. We first construct different candidate anchor clusters by selecting different number of anchors with the strongest received signals. Then for each candidate cluster, we propose a weighted min-max algorithm to provide a location estimation. Finally, we introduce a weighted geometric dilution of precision (w-GDOP) algorithm that combines the estimations from multiple clusters by quantifying their estimation accuracy. We evaluate the performance of our solution through simulations and real-world experiments. Our results show that the proposed anchor selection scheme and localization algorithm significantly improve the localization accuracy in large indoor environments.
{"title":"Anchor Selection for Localization in Large Indoor Venues","authors":"Omotayo Oshiga, Xiaowen Chu, Y. Leung, J. Ng","doi":"10.1109/IWQoS.2018.8624131","DOIUrl":"https://doi.org/10.1109/IWQoS.2018.8624131","url":null,"abstract":"Many indoor localization systems rely on a set of reference anchors with known positions. A target's location is estimated from a set of distances between the target and its surrounding anchors, and hence the selection of anchors affects the localization accuracy. However, it remains a challenge to select the best set of anchors. In this paper, we study how to appropriately make use of the surrounding anchors for localizing a target. We first construct different candidate anchor clusters by selecting different number of anchors with the strongest received signals. Then for each candidate cluster, we propose a weighted min-max algorithm to provide a location estimation. Finally, we introduce a weighted geometric dilution of precision (w-GDOP) algorithm that combines the estimations from multiple clusters by quantifying their estimation accuracy. We evaluate the performance of our solution through simulations and real-world experiments. Our results show that the proposed anchor selection scheme and localization algorithm significantly improve the localization accuracy in large indoor environments.","PeriodicalId":222290,"journal":{"name":"2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130603226","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 : 2018-06-01DOI: 10.1109/IWQoS.2018.8624166
Yiming Zeng, Pengzhan Zhou, Ji Liu, Yuanyuan Yang
This paper studies a data gathering problem in a wireless sensor network containing multiple private residual subnetworks. The interaction between the wireless sensor network operator and the owners of residual sub-networks is modeled by a Stackelberg game, which forms a novel framework for jointly analyzing the pricing, gathering data, and planning routes. It is shown that the game has a unique Stackelberg equilibrium at which the wireless sensor network operator sets prices to minimize total cost, while owners of residual sub-networks respond accordingly to maximize their utilities subject to their bandwidth constraints. An algorithm and theoretical analyses are provided for the corresponding strategies of the operator and owners, and validated by extensive simulations. It is demonstrated that the algorithm achieves lower network cost compared with existing data gathering strategies.
{"title":"A Stackelberg Game Framework for Mobile Data Gathering in Leasing Residential Sensor Networks","authors":"Yiming Zeng, Pengzhan Zhou, Ji Liu, Yuanyuan Yang","doi":"10.1109/IWQoS.2018.8624166","DOIUrl":"https://doi.org/10.1109/IWQoS.2018.8624166","url":null,"abstract":"This paper studies a data gathering problem in a wireless sensor network containing multiple private residual subnetworks. The interaction between the wireless sensor network operator and the owners of residual sub-networks is modeled by a Stackelberg game, which forms a novel framework for jointly analyzing the pricing, gathering data, and planning routes. It is shown that the game has a unique Stackelberg equilibrium at which the wireless sensor network operator sets prices to minimize total cost, while owners of residual sub-networks respond accordingly to maximize their utilities subject to their bandwidth constraints. An algorithm and theoretical analyses are provided for the corresponding strategies of the operator and owners, and validated by extensive simulations. It is demonstrated that the algorithm achieves lower network cost compared with existing data gathering strategies.","PeriodicalId":222290,"journal":{"name":"2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134418004","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 : 2018-06-01DOI: 10.1109/IWQoS.2018.8624185
Juan Li, Jie Wu, Yanmin Zhu
With the increasingly wide adoption of crowdsensing services, we can leverage the crowd to obtain labeled data instances for training machine learning models. In this paper, we focus on the critical problem that which data instances should be collected to maximize the performance of the trained model under the budget limit. Solving this problem is nontrivial because of the unclear relationship between the performance of the trained model and the data collection process, NP-hardness of the problem and the online arrival of workers. To overcome these challenges, we first propose a crowdsensing framework with multiple rounds of data collecting and model training. The framework is based on the stream-based batch-mode active learning. According to the framework, we come up with a novel data utility model to measure the contribution of a data batch to the performance of the learning model. The data utility model combines uncertainty and weighted density to measure the contribution of one instance. Finally, we propose an online algorithm to select a data batch in each round. The algorithm achieves fairness, computational efficiency and a competitive ratio 0.1218 when the ratio of the largest contribution of one data instance to the optimal offline total data utility is infinitely small. Through evaluations based on a real data set, we demonstrate the efficiency of our data utility model and our online algorithm.
{"title":"Data Utility Maximization When Leveraging Crowdsensing in Machine Learning","authors":"Juan Li, Jie Wu, Yanmin Zhu","doi":"10.1109/IWQoS.2018.8624185","DOIUrl":"https://doi.org/10.1109/IWQoS.2018.8624185","url":null,"abstract":"With the increasingly wide adoption of crowdsensing services, we can leverage the crowd to obtain labeled data instances for training machine learning models. In this paper, we focus on the critical problem that which data instances should be collected to maximize the performance of the trained model under the budget limit. Solving this problem is nontrivial because of the unclear relationship between the performance of the trained model and the data collection process, NP-hardness of the problem and the online arrival of workers. To overcome these challenges, we first propose a crowdsensing framework with multiple rounds of data collecting and model training. The framework is based on the stream-based batch-mode active learning. According to the framework, we come up with a novel data utility model to measure the contribution of a data batch to the performance of the learning model. The data utility model combines uncertainty and weighted density to measure the contribution of one instance. Finally, we propose an online algorithm to select a data batch in each round. The algorithm achieves fairness, computational efficiency and a competitive ratio 0.1218 when the ratio of the largest contribution of one data instance to the optimal offline total data utility is infinitely small. Through evaluations based on a real data set, we demonstrate the efficiency of our data utility model and our online algorithm.","PeriodicalId":222290,"journal":{"name":"2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124316912","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 : 2018-06-01DOI: 10.1109/IWQoS.2018.8624188
Chuwen Zhang, Yong Feng, Haoyu Song, Ying Wan, Wenquan Xu, Yilun Wang, Huichen Dai, Y. Li, B. Lin
Software-based IP route lookup is one of the key components in Software Defined Networks. To address challenges on density, power and cost, Commodity CPU is preferred over other platforms to run lookup algorithms. As network functions become richer and more dynamic, route updates are more frequent. Unfortunately, previous works put less effort on fast incremental updates. On the other hand, The cache in CPU could be a performance limiter due to its small size, which requires algorithm designers to give high priority on storage efficiency in addition to time complexity. In this paper, we propose a new route lookup algorithm, OBMA, which improves update performance and storage efficiency while maintaining high lookup speed. The extensive experiments over real-word traces show that OBMA reduces the memory footprint to just 4.52 bytes/prefix, supports update speed up to 7.2 M/s which is 12.5 times faster than the state-of-the-art algorithm Poptrie. Besides, OBMA achieves up to 195.87 Mpps lookup speed with a single thread. Tests on comprehensive performance of lookup and update show that OBMA can sustain high lookup speed with update speed increasing.
{"title":"OBMA: Minimizing Bitmap Data Structure with Fast and Uninterrupted Update Processing","authors":"Chuwen Zhang, Yong Feng, Haoyu Song, Ying Wan, Wenquan Xu, Yilun Wang, Huichen Dai, Y. Li, B. Lin","doi":"10.1109/IWQoS.2018.8624188","DOIUrl":"https://doi.org/10.1109/IWQoS.2018.8624188","url":null,"abstract":"Software-based IP route lookup is one of the key components in Software Defined Networks. To address challenges on density, power and cost, Commodity CPU is preferred over other platforms to run lookup algorithms. As network functions become richer and more dynamic, route updates are more frequent. Unfortunately, previous works put less effort on fast incremental updates. On the other hand, The cache in CPU could be a performance limiter due to its small size, which requires algorithm designers to give high priority on storage efficiency in addition to time complexity. In this paper, we propose a new route lookup algorithm, OBMA, which improves update performance and storage efficiency while maintaining high lookup speed. The extensive experiments over real-word traces show that OBMA reduces the memory footprint to just 4.52 bytes/prefix, supports update speed up to 7.2 M/s which is 12.5 times faster than the state-of-the-art algorithm Poptrie. Besides, OBMA achieves up to 195.87 Mpps lookup speed with a single thread. Tests on comprehensive performance of lookup and update show that OBMA can sustain high lookup speed with update speed increasing.","PeriodicalId":222290,"journal":{"name":"2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130046133","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 : 2018-06-01DOI: 10.1109/IWQoS.2018.8624130
Hao Wang, Haoyun Shen, P. Wieder, R. Yahyapour
For many application scenarios, interconnected data centers provide high service flexibility, reduce response time, and facilitate timely data backup. Many data center system parameters might have variant impact on the interconnection performance. Despite many studies on data center network performance, there exist few analytical work that reveal insightful knowledge with wide range of system parameters as input, especially focusing on data center interconnects (DCI). This paper creates analytical models for representative data center network architectures and provides the performance calculus aiming to apply for data center interconnects. By parameterising the number of devices, the arriving traffics, the switch link capacities, and the traffic locality, we derive the relationship among the DCI bandwidth, inter-DC latency, and these parameters. Based on this, further discussion and numerical examples investigate and evaluate the modelling and calculus from multiple angles and show the possibility how this calculus assists DC/DCI design and operation.
{"title":"A Data Center Interconnects Calculus","authors":"Hao Wang, Haoyun Shen, P. Wieder, R. Yahyapour","doi":"10.1109/IWQoS.2018.8624130","DOIUrl":"https://doi.org/10.1109/IWQoS.2018.8624130","url":null,"abstract":"For many application scenarios, interconnected data centers provide high service flexibility, reduce response time, and facilitate timely data backup. Many data center system parameters might have variant impact on the interconnection performance. Despite many studies on data center network performance, there exist few analytical work that reveal insightful knowledge with wide range of system parameters as input, especially focusing on data center interconnects (DCI). This paper creates analytical models for representative data center network architectures and provides the performance calculus aiming to apply for data center interconnects. By parameterising the number of devices, the arriving traffics, the switch link capacities, and the traffic locality, we derive the relationship among the DCI bandwidth, inter-DC latency, and these parameters. Based on this, further discussion and numerical examples investigate and evaluate the modelling and calculus from multiple angles and show the possibility how this calculus assists DC/DCI design and operation.","PeriodicalId":222290,"journal":{"name":"2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116745106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：