Pub Date : 2021-10-01DOI: 10.1109/NaNA53684.2021.00014
Yanwen Liu, Wei Su, Lizhuang Tan
Deadline-aware Transport Protocol (DTP) is a new QUIC-based transmission protocol that provides deliver-before-deadline service. Single-path DTP is not conducive to flow fairness and does not make full use of bandwidth. Compared with single-path DTP, the decision space and the solving difficulty of multipath DTP (MPDTP) scheduling are larger. In this paper, we propose a near-optimal scheduling algorithm Tetris for MPDTP. Tetris is a block scheduler based on stream characteristics at the transmission layer. We have verified its feasibility on the simulator under the deployed heterogeneous path of different network environment. The results show that our scheduling algorithm allows data blocks to be delivered before the delivery time as much as possible. The transmission completion time has been increased by 19.53% on average, and the transmission delay of all blocks have been reduced by 11.27%.
{"title":"Tetris: Near-optimal Scheduling for Multi-path Deadline-aware Transport Protocol","authors":"Yanwen Liu, Wei Su, Lizhuang Tan","doi":"10.1109/NaNA53684.2021.00014","DOIUrl":"https://doi.org/10.1109/NaNA53684.2021.00014","url":null,"abstract":"Deadline-aware Transport Protocol (DTP) is a new QUIC-based transmission protocol that provides deliver-before-deadline service. Single-path DTP is not conducive to flow fairness and does not make full use of bandwidth. Compared with single-path DTP, the decision space and the solving difficulty of multipath DTP (MPDTP) scheduling are larger. In this paper, we propose a near-optimal scheduling algorithm Tetris for MPDTP. Tetris is a block scheduler based on stream characteristics at the transmission layer. We have verified its feasibility on the simulator under the deployed heterogeneous path of different network environment. The results show that our scheduling algorithm allows data blocks to be delivered before the delivery time as much as possible. The transmission completion time has been increased by 19.53% on average, and the transmission delay of all blocks have been reduced by 11.27%.","PeriodicalId":414672,"journal":{"name":"2021 International Conference on Networking and Network Applications (NaNA)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127626886","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 : 2021-10-01DOI: 10.1109/NaNA53684.2021.00016
Shiyi Zou, Ling-ge Jiang, Pingping Ji, Chen He, Di He, Guorong Zhang
In this letter, a beam selection algorithm is put forward for beamspace high altitude platform massive multiple-input multiple-output (HAP-MIMO) systems. Specifically, the algorithm is subject to the maximization of match degree between the beams and users, which is constructed by exploiting statistical channel state information (CSI). The beam selection is partitioned into two parts. In the first part, we obtain a reduced-dimensional dominant beam set consisting of each user’s most preferred beams according to the match degree. In the second part, we formulate the selection of optimal beams from the dominant beam set as an assignment problem that can be solved by Kuhn-Munkres algorithm. Numerical results demonstrate the performance enhancement of the proposed algorithm with respect to energy efficiency.
{"title":"Beam Selection Algorithm for Beamspace HAP-MIMO Systems Based on Statistical CSI","authors":"Shiyi Zou, Ling-ge Jiang, Pingping Ji, Chen He, Di He, Guorong Zhang","doi":"10.1109/NaNA53684.2021.00016","DOIUrl":"https://doi.org/10.1109/NaNA53684.2021.00016","url":null,"abstract":"In this letter, a beam selection algorithm is put forward for beamspace high altitude platform massive multiple-input multiple-output (HAP-MIMO) systems. Specifically, the algorithm is subject to the maximization of match degree between the beams and users, which is constructed by exploiting statistical channel state information (CSI). The beam selection is partitioned into two parts. In the first part, we obtain a reduced-dimensional dominant beam set consisting of each user’s most preferred beams according to the match degree. In the second part, we formulate the selection of optimal beams from the dominant beam set as an assignment problem that can be solved by Kuhn-Munkres algorithm. Numerical results demonstrate the performance enhancement of the proposed algorithm with respect to energy efficiency.","PeriodicalId":414672,"journal":{"name":"2021 International Conference on Networking and Network Applications (NaNA)","volume":"1443 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127443524","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 : 2021-10-01DOI: 10.1109/NaNA53684.2021.00057
Guorong Zhang, Ling-ge Jiang, Pingping Ji, Shiyi Zou, Chen He, Di He
In this paper, we propose a new user grouping scheme for the high altitude platform (HAP) massive Multiple-Input Multiple-Output (MIMO) systems based on statistical-eigenmode (SE). It has been proved that SE makes a major contribution to signal power for HAPs. Then, a Fubini-Study distance based modified K-means (FS-MKM) user grouping method is proposed aiming at reducing intra-group interference and improving system performance. The proposed modified K-means algorithm improves the initial points selection of the original K-means algorithm. The Fubini-Study distance is obtained based on the SEs of different users. Simulation results confirm that the proposed user grouping algorithm yields significant performance enhancement.
{"title":"A Modified K-means User Grouping Design for HAP Massive MIMO Systems","authors":"Guorong Zhang, Ling-ge Jiang, Pingping Ji, Shiyi Zou, Chen He, Di He","doi":"10.1109/NaNA53684.2021.00057","DOIUrl":"https://doi.org/10.1109/NaNA53684.2021.00057","url":null,"abstract":"In this paper, we propose a new user grouping scheme for the high altitude platform (HAP) massive Multiple-Input Multiple-Output (MIMO) systems based on statistical-eigenmode (SE). It has been proved that SE makes a major contribution to signal power for HAPs. Then, a Fubini-Study distance based modified K-means (FS-MKM) user grouping method is proposed aiming at reducing intra-group interference and improving system performance. The proposed modified K-means algorithm improves the initial points selection of the original K-means algorithm. The Fubini-Study distance is obtained based on the SEs of different users. Simulation results confirm that the proposed user grouping algorithm yields significant performance enhancement.","PeriodicalId":414672,"journal":{"name":"2021 International Conference on Networking and Network Applications (NaNA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116689568","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 : 2021-10-01DOI: 10.1109/NaNA53684.2021.00026
Alibek Nurgaliyev, Hua Wang
This article provides an unbiased comparison of the most popular and commonly used algorithms in the field of data encryption. The capacity to secure data from various attacks, as well as the elapsed time and efficiency of data encryption, are the main features that distinguish encryption algorithms. We compared the most prevalent symmetric encryption algorithms, including DES, 3DES, Blowfish, MARS, and AES, in this study. Each algorithm was compared by processing data blocks of various sizes to estimate encryption and decryption speeds and compare entropy. The given comparison takes into account the behavior and performance of the algorithms while utilizing varied data loads because the main objective is to execute these algorithms with various settings. We also looked at characteristics including flexibility, key extension possibilities, potential attacks, entropy, and security vulnerability of the algorithms, all of which affect the cryptosystem’s efficiency.
{"title":"Comparative study of symmetric cryptographic algorithms","authors":"Alibek Nurgaliyev, Hua Wang","doi":"10.1109/NaNA53684.2021.00026","DOIUrl":"https://doi.org/10.1109/NaNA53684.2021.00026","url":null,"abstract":"This article provides an unbiased comparison of the most popular and commonly used algorithms in the field of data encryption. The capacity to secure data from various attacks, as well as the elapsed time and efficiency of data encryption, are the main features that distinguish encryption algorithms. We compared the most prevalent symmetric encryption algorithms, including DES, 3DES, Blowfish, MARS, and AES, in this study. Each algorithm was compared by processing data blocks of various sizes to estimate encryption and decryption speeds and compare entropy. The given comparison takes into account the behavior and performance of the algorithms while utilizing varied data loads because the main objective is to execute these algorithms with various settings. We also looked at characteristics including flexibility, key extension possibilities, potential attacks, entropy, and security vulnerability of the algorithms, all of which affect the cryptosystem’s efficiency.","PeriodicalId":414672,"journal":{"name":"2021 International Conference on Networking and Network Applications (NaNA)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121567965","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}
In statistical queries work, such as frequency estimation, the untrusted data collector could as an honest-but-curious (HbC) or malicious adversary to learn true values. Local differential privacy(LDP) protocols have been applied against the untrusted third party in data collecting. Nevertheless, excessive noise of LDP will reduce data utility, thus affecting the results of statistical queries. Therefore, it is significant to research the trade-off between privacy and utility. In this paper, we first measure the privacy loss by observing the maximum posterior confidence of the adversary (data collector). Then, through theoretical analysis and comparison we obtain the most suitable utility measure that is Wasserstein distance. Based on these, we introduce an originality framework for privacy-utility tradeoff framework, finding that this system conforms to the Pareto optimality state and formalizing a payoff function to find optimal equilibrium point under Pareto efficiency. Finally, we illustrate the efficacy of our system model by the Adult dataset from the UCI machine learning repository.
{"title":"The Trade-off Between Privacy and Utility in Local Differential Privacy","authors":"Mengqian Li, Youliang Tian, Junpeng Zhang, Dandan Fan, Dongmei Zhao","doi":"10.1109/NaNA53684.2021.00071","DOIUrl":"https://doi.org/10.1109/NaNA53684.2021.00071","url":null,"abstract":"In statistical queries work, such as frequency estimation, the untrusted data collector could as an honest-but-curious (HbC) or malicious adversary to learn true values. Local differential privacy(LDP) protocols have been applied against the untrusted third party in data collecting. Nevertheless, excessive noise of LDP will reduce data utility, thus affecting the results of statistical queries. Therefore, it is significant to research the trade-off between privacy and utility. In this paper, we first measure the privacy loss by observing the maximum posterior confidence of the adversary (data collector). Then, through theoretical analysis and comparison we obtain the most suitable utility measure that is Wasserstein distance. Based on these, we introduce an originality framework for privacy-utility tradeoff framework, finding that this system conforms to the Pareto optimality state and formalizing a payoff function to find optimal equilibrium point under Pareto efficiency. Finally, we illustrate the efficacy of our system model by the Adult dataset from the UCI machine learning repository.","PeriodicalId":414672,"journal":{"name":"2021 International Conference on Networking and Network Applications (NaNA)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121349315","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 : 2021-10-01DOI: 10.1109/NaNA53684.2021.00056
Sugang Ma, Zixian Zhang, Lei Zhang, Yanping Chen, Xiaobao Yang, Lei Pu, Z. Hou
In an effort to the problem of insufficient tracking performance of the Fully-convolutional Siamese network (SiamFC) in complex scenarios, a dual attention mechanism object tracking algorithm based on the Fully-convolutional Siamese network is proposed to improve the generalization capability of the tracker by ameliorating the robustness of the template characteristics. Firstly, a global context attention module is appended after the backbone network of SiamFC to ameliorate the power of original feature extraction from two dimensions of spatial and channel. Then, a coordinate attention module is introduced to augment the capability of feature extraction in the channel dimension. Finally, the model of the proposed algorithm is trained on the Got-10k dataset. Five related algorithms are tested on the OTB2015 dataset, the results of experiments manifest that our algorithm outperforms the baseline trackers, the success and precision rate of the proposed algorithm are improved by 3.3% and 6.3%. The average tracking speed is 145FPS, which can demand the requirement of real-time tracking.
{"title":"Dual attention mechanism object tracking algorithm based on Fully-convolutional Siamese network","authors":"Sugang Ma, Zixian Zhang, Lei Zhang, Yanping Chen, Xiaobao Yang, Lei Pu, Z. Hou","doi":"10.1109/NaNA53684.2021.00056","DOIUrl":"https://doi.org/10.1109/NaNA53684.2021.00056","url":null,"abstract":"In an effort to the problem of insufficient tracking performance of the Fully-convolutional Siamese network (SiamFC) in complex scenarios, a dual attention mechanism object tracking algorithm based on the Fully-convolutional Siamese network is proposed to improve the generalization capability of the tracker by ameliorating the robustness of the template characteristics. Firstly, a global context attention module is appended after the backbone network of SiamFC to ameliorate the power of original feature extraction from two dimensions of spatial and channel. Then, a coordinate attention module is introduced to augment the capability of feature extraction in the channel dimension. Finally, the model of the proposed algorithm is trained on the Got-10k dataset. Five related algorithms are tested on the OTB2015 dataset, the results of experiments manifest that our algorithm outperforms the baseline trackers, the success and precision rate of the proposed algorithm are improved by 3.3% and 6.3%. The average tracking speed is 145FPS, which can demand the requirement of real-time tracking.","PeriodicalId":414672,"journal":{"name":"2021 International Conference on Networking and Network Applications (NaNA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115009769","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 : 2021-10-01DOI: 10.1109/NaNA53684.2021.00092
Lei Zhu, Ziheng Zhang, Xinhong Hei, Yichuan Wang, Ziliang Yang, Feixiong Hu, Ping He
With the development of computer technology, lots of enterprises had begun to build a data platform, and the data and its services already paly the import role in enterprises. However, the guarantee the data security is the primary task of platform, and data access control, especially the fine-grained access control model, had become an important means to enhance the security of platform. In this paper, we propose a data access permission configuration method based on rules and FP-growth. Specifically, FP-Growth algorithm is first used to obtain the frequent items and the association relations of data, which can be transformed into the enumerable permission configuration items. Then, the correspondence and frequency of data items are calculated to acquire the frequent items, the permission configuration acting on the data table columns is obtained according to the frequency of used data items. By filtering the strong association relation, the data items that are more closely related in the association relation and the corresponding data item values are finally obtained, and they are converted into the permission configuration that acts on the rows of the data table. The proposed method has been tested and verified to meet business needs, and the performance consumption is below the threshold. Moreover, it is feasible to utilize classical data mining algorithms to generate permission configuration, which has begun to apply the Blueking Data Platform.
{"title":"A permission generation and configuration method based on Rules and FP-Growth algorithm","authors":"Lei Zhu, Ziheng Zhang, Xinhong Hei, Yichuan Wang, Ziliang Yang, Feixiong Hu, Ping He","doi":"10.1109/NaNA53684.2021.00092","DOIUrl":"https://doi.org/10.1109/NaNA53684.2021.00092","url":null,"abstract":"With the development of computer technology, lots of enterprises had begun to build a data platform, and the data and its services already paly the import role in enterprises. However, the guarantee the data security is the primary task of platform, and data access control, especially the fine-grained access control model, had become an important means to enhance the security of platform. In this paper, we propose a data access permission configuration method based on rules and FP-growth. Specifically, FP-Growth algorithm is first used to obtain the frequent items and the association relations of data, which can be transformed into the enumerable permission configuration items. Then, the correspondence and frequency of data items are calculated to acquire the frequent items, the permission configuration acting on the data table columns is obtained according to the frequency of used data items. By filtering the strong association relation, the data items that are more closely related in the association relation and the corresponding data item values are finally obtained, and they are converted into the permission configuration that acts on the rows of the data table. The proposed method has been tested and verified to meet business needs, and the performance consumption is below the threshold. Moreover, it is feasible to utilize classical data mining algorithms to generate permission configuration, which has begun to apply the Blueking Data Platform.","PeriodicalId":414672,"journal":{"name":"2021 International Conference on Networking and Network Applications (NaNA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117009880","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 : 2021-10-01DOI: 10.1109/NaNA53684.2021.00009
Wendi Sun, Xiaoying Liu, Kechen Zheng, Yang Xu, Jia Liu
Motivated by the dilemma in the multi-channel spectrum sensing by the multi-antenna user, this paper focuses on the scheme of spectrum sensing and energy harvesting to coordinate the time scheduling and energy management in the cognitive radio networks (CRNs), where a secondary transmitter (ST) exploits spectrum holes to transmit data through multichannel. To improve spectrum utilization efficiency, we investigate how the ST selects channels for sensing based on the residual energy, and adjusts the time scheduling of energy harvesting and data transmission with respect to the sensing results. To address this problem, we propose an adaptive scheme concerning spectrum sensing, channel selection, energy harvesting, and data transmission (SCED) for the ST. Moreover, we formulate the optimization of spectrum utilization efficiency as a Markov decision process (MDP) problem, which is challenging due to the system space and action space. Furthermore, we solve the MDP problem by a proposed value iteration algorithm. Numerical results show that the spectrum utilization efficiency under the SCED scheme is better than that under other schemes.
{"title":"Spectrum Utilization Improvement for Multi-Channel Cognitive Radio Networks with Energy Harvesting","authors":"Wendi Sun, Xiaoying Liu, Kechen Zheng, Yang Xu, Jia Liu","doi":"10.1109/NaNA53684.2021.00009","DOIUrl":"https://doi.org/10.1109/NaNA53684.2021.00009","url":null,"abstract":"Motivated by the dilemma in the multi-channel spectrum sensing by the multi-antenna user, this paper focuses on the scheme of spectrum sensing and energy harvesting to coordinate the time scheduling and energy management in the cognitive radio networks (CRNs), where a secondary transmitter (ST) exploits spectrum holes to transmit data through multichannel. To improve spectrum utilization efficiency, we investigate how the ST selects channels for sensing based on the residual energy, and adjusts the time scheduling of energy harvesting and data transmission with respect to the sensing results. To address this problem, we propose an adaptive scheme concerning spectrum sensing, channel selection, energy harvesting, and data transmission (SCED) for the ST. Moreover, we formulate the optimization of spectrum utilization efficiency as a Markov decision process (MDP) problem, which is challenging due to the system space and action space. Furthermore, we solve the MDP problem by a proposed value iteration algorithm. Numerical results show that the spectrum utilization efficiency under the SCED scheme is better than that under other schemes.","PeriodicalId":414672,"journal":{"name":"2021 International Conference on Networking and Network Applications (NaNA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126667398","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 : 2021-10-01DOI: 10.1109/NaNA53684.2021.00033
Ran Pang, Hui Li, Yuefeng Ji, Guangquan Wang, Chang Cao
In the Computing power network, based on the tidal characteristic of computing power nodes, with the goal of reducing the overall network energy consumption, the classification between tidal computing power nodes and non-tidal computing power nodes is proposed. This paper also proposes a new anycast routing algorithm with weighted wakeup routing penalty for tidal computing power nodes in sleep state. The simulation results show that the proposed anycast routing algorithm with tidal node classification and wake-up penalty weighted can effectively reduce energy consumption under the premise of meeting the service delay requirements.
{"title":"Energy-saving mechanism based on tidal characteristic in computing power network","authors":"Ran Pang, Hui Li, Yuefeng Ji, Guangquan Wang, Chang Cao","doi":"10.1109/NaNA53684.2021.00033","DOIUrl":"https://doi.org/10.1109/NaNA53684.2021.00033","url":null,"abstract":"In the Computing power network, based on the tidal characteristic of computing power nodes, with the goal of reducing the overall network energy consumption, the classification between tidal computing power nodes and non-tidal computing power nodes is proposed. This paper also proposes a new anycast routing algorithm with weighted wakeup routing penalty for tidal computing power nodes in sleep state. The simulation results show that the proposed anycast routing algorithm with tidal node classification and wake-up penalty weighted can effectively reduce energy consumption under the premise of meeting the service delay requirements.","PeriodicalId":414672,"journal":{"name":"2021 International Conference on Networking and Network Applications (NaNA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125451604","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}
System administrators need to monitor various metrics (network traffic, NTP offset, etc.) of their internal services in real-time as a way to determine whether anomalies occur in the system. Traditional Spectral Residual (SR) anomaly detection methods do not take into account the interference of certain human factors (e.g., changes in personal preferences) in certain scenarios, i.e., concept drift. In these scenarios, the accuracy of anomaly detection is bound to be affected. In order to guarantee the availability and stability of network services, we propose an intelligent and pervasive anomaly detection strategy, CD-SR. First, we use the traditional SR model and the SVM method to train the time series that have not drifted to determine the threshold value. Then, to solve the problem of the pervasiveness of application scenarios, we use a drift detection model to find the time series where concept drift occurs. Finally, the sequence where the concept drift occurs is imported into the drift adaptation model to complete the replacement of the old and new concepts, the data is processed in real-time, and the replaced data is detected again in the detection model for anomalies. In the experimental stage, we obtained several data metrics using the cloud platform system built by Openstack, and by comparing several mainstream anomaly detection algorithms, our method obtained superior results.
{"title":"CD-SR: A Real-time Anomaly Detection Framework for Continuous Concept Drift","authors":"Zhongyi Ding, Shujie Yang, Zhaoyang Liu, Tengchao Ma, Zichen Feng, Mingze Wang","doi":"10.1109/NaNA53684.2021.00040","DOIUrl":"https://doi.org/10.1109/NaNA53684.2021.00040","url":null,"abstract":"System administrators need to monitor various metrics (network traffic, NTP offset, etc.) of their internal services in real-time as a way to determine whether anomalies occur in the system. Traditional Spectral Residual (SR) anomaly detection methods do not take into account the interference of certain human factors (e.g., changes in personal preferences) in certain scenarios, i.e., concept drift. In these scenarios, the accuracy of anomaly detection is bound to be affected. In order to guarantee the availability and stability of network services, we propose an intelligent and pervasive anomaly detection strategy, CD-SR. First, we use the traditional SR model and the SVM method to train the time series that have not drifted to determine the threshold value. Then, to solve the problem of the pervasiveness of application scenarios, we use a drift detection model to find the time series where concept drift occurs. Finally, the sequence where the concept drift occurs is imported into the drift adaptation model to complete the replacement of the old and new concepts, the data is processed in real-time, and the replaced data is detected again in the detection model for anomalies. In the experimental stage, we obtained several data metrics using the cloud platform system built by Openstack, and by comparing several mainstream anomaly detection algorithms, our method obtained superior results.","PeriodicalId":414672,"journal":{"name":"2021 International Conference on Networking and Network Applications (NaNA)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125079718","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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