Proceedings of the International Conference on Research in Adaptive and Convergent Systems最新文献

Migration Selection Method using two Factors based LSTM in Micro DataCenter 基于双因素LSTM的微数据中心迁移选择方法

Proceedings of the International Conference on Research in Adaptive and Convergent Systems Pub Date : 2020-10-13 DOI: 10.1145/3400286.3418280

Su June Lee, J. An, Younghwan Kim

{"title":"Migration Selection Method using two Factors based LSTM in Micro DataCenter","authors":"Su June Lee, J. An, Younghwan Kim","doi":"10.1145/3400286.3418280","DOIUrl":"https://doi.org/10.1145/3400286.3418280","url":null,"abstract":"In recent years, cloud service has been used in many field. In particular, a micro datacenter based on edge computing has been used to overcome the limitations of latency and bandwidth of cloud network architecture. Micro datacentre is small-scaled to reduce environmental constraints and minimize the complexity of fieldwork. Since there are not enough computing resources when compared with existing datacentre, efficient operation methods of services are being researched. Migration is used as a way to duplicate services and load balance services. However, migration is executed when the workload was overloading, delay may occur. This paper propose novel method MSFL(Migration Selection Method using two Factors based LSTM) that provides service availability by predicting power values based on past resource utilization rates and Long Short-Term Memory(LSTM) and pre-selecting migration target based on the relationship between servers and workloads, and values predicted. This method calculates the power consumption of servers and workloads by collecting the utilization of workload resource(CPU, Memory, Network, Disk I/O). The collected power consumption is an input value of LSTM to predict future workload is defined by analyzing the resource utilization of the workload and the server, the weight of the LSTM result is calculated using the two factors. Finally, the target of migration is selected.","PeriodicalId":326100,"journal":{"name":"Proceedings of the International Conference on Research in Adaptive and Convergent Systems","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132239547","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}

引用次数: 0

An Automated Machine Learning Platform for Non-experts 面向非专家的自动化机器学习平台

Proceedings of the International Conference on Research in Adaptive and Convergent Systems Pub Date : 2020-10-13 DOI: 10.1145/3400286.3418276

Jin Han, Ki Sun Park, K. Lee

引用次数: 2

On Matching Log Analysis to Source Code: A Systematic Mapping Study 匹配日志分析对源代码的系统映射研究

Proceedings of the International Conference on Research in Adaptive and Convergent Systems Pub Date : 2020-10-13 DOI: 10.1145/3400286.3418262

Vincent Bushong, Russell Sanders, Jacob Curtis, Mark Du, T. Cerný, Karel Frajták, Miroslav Bures, Pavel Tisnovsky, Dongwan Shin

引用次数: 7

A Machine-Learning-based Data Classifier to Reduce the Write Amplification in SSDs 一种基于机器学习的数据分类器以减少ssd中的写放大

Proceedings of the International Conference on Research in Adaptive and Convergent Systems Pub Date : 2020-10-13 DOI: 10.1145/3400286.3418239

Yi-Ying Lu, Chin-Hsien Wu, Ya-Shu Chen

{"title":"A Machine-Learning-based Data Classifier to Reduce the Write Amplification in SSDs","authors":"Yi-Ying Lu, Chin-Hsien Wu, Ya-Shu Chen","doi":"10.1145/3400286.3418239","DOIUrl":"https://doi.org/10.1145/3400286.3418239","url":null,"abstract":"Solid-state drives (SSDs) that consist of flash memory have the advantages of non-volatility, fast speed, shock resistance, low-power consumption, and small size. Two critical characteristics of flash memory are that it does not support in-place updates, and it must write data in units of a page and erase data in units of a block. Due to the two characteristics, when a block is selected as a victim block to erase, we need to copy the remaining valid pages from the victim block to another free block and the additional copy overhead is called write amplification (WA). Therefore, how to reduce the write amplification (WA) is a crucial issue for SSDs. By performing data classification, it is effective to concentrate the invalid pages in specific blocks and decrease the distribution of invalid pages in the flash memory. The advantage is that we can reduce the write amplification due to the valid pages copied. In the paper, we will propose a machine-learning-based data classifier to classify the written data. Data with similar characteristics will be eventually written in the same group of data blocks in flash memory. Through such a design, it can improve the performance of SSDs by concentrating the invalid pages in the same block and reduce the write amplification.","PeriodicalId":326100,"journal":{"name":"Proceedings of the International Conference on Research in Adaptive and Convergent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128869117","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}

引用次数: 2

Motion Mode Recognition for Traffic Safety in Campus Guiding Application 运动模式识别在校园交通安全引导中的应用

Proceedings of the International Conference on Research in Adaptive and Convergent Systems Pub Date : 2020-10-13 DOI: 10.1145/3400286.3418246

Rukang Yan, Zhan Gao, Lianbing Xu, Lei Cai, Zhengtao Xiang, Yufeng Chen

引用次数: 1

Developing IoT Applications Using Spiking Neural Networks Framework 使用峰值神经网络框架开发物联网应用

Proceedings of the International Conference on Research in Adaptive and Convergent Systems Pub Date : 2020-10-13 DOI: 10.1145/3400286.3418271

Seoyeon Kim, Jaehyeok Jeong, Jaehee Kim, Young-Sun Yun, Bongjae Kim, Jinmang Jung

引用次数: 1

EDAroid

Proceedings of the International Conference on Research in Adaptive and Convergent Systems Pub Date : 2020-10-13 DOI: 10.1145/3400286.3418266

Heejin Kim, Kyuho Kim, Jiman Hong, Jun-Young Heo, Joongjin Kook

引用次数: 2

Evading a Machine Learning-based Intrusion Detection System through Adversarial Perturbations 基于机器学习的入侵检测系统对抗性扰动的规避

Proceedings of the International Conference on Research in Adaptive and Convergent Systems Pub Date : 2020-10-13 DOI: 10.1145/3400286.3418252

T. Fladby, H. Haugerud, S. Nichele, Kyrre M. Begnum, A. Yazidi

{"title":"Evading a Machine Learning-based Intrusion Detection System through Adversarial Perturbations","authors":"T. Fladby, H. Haugerud, S. Nichele, Kyrre M. Begnum, A. Yazidi","doi":"10.1145/3400286.3418252","DOIUrl":"https://doi.org/10.1145/3400286.3418252","url":null,"abstract":"Machine-learning based Intrusion Detection and Prevention Systems provide significant value to organizations because they can efficiently detect previously unseen variations of known threats, new threats related to known malware or even zero-day malware, unrelated to any other known threats. However, while such systems prove invaluable to security personnel, researchers have observed that data subject to inspection by behavioral analysis can be perturbed in order to evade detection. We investigated the use of adversarial techniques for adapting the communication patterns between botnet malware and control unit in order to evaluate the robustness of an existing Network Behavioral Analysis solution. We implemented a packet parser that let us extract and edit certain properties of network flows and automated an approach for conducting a grey-box testing scheme of Stratosphere Linux IPS. As part of our implementation, we provided several techniques for providing perturbation to network flow parameters, including a Simultaneous Perturbation Stochastic Approximation method, which was able to produce sufficiently perturbed network flow patterns while adhering to an underlying objective function. Our results showed that network flow parameters could indeed be perturbed to ultimately enable evasion of intrusion detection based on the detection models that were used with the Intrusion Detection System. Additionally, we demonstrated that it was possible to combine evading detection with techniques for optimization problems that aimed to minimize the magnitude of perturbation to network flows, effectively enabling adaptive network flow behavior.","PeriodicalId":326100,"journal":{"name":"Proceedings of the International Conference on Research in Adaptive and Convergent Systems","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124682926","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}

引用次数: 3

Design and Implementation of Analytical Load Balancing between Distributed Collaborative Container Platforms 分布式协同容器平台分析式负载均衡的设计与实现

Proceedings of the International Conference on Research in Adaptive and Convergent Systems Pub Date : 2020-10-13 DOI: 10.1145/3400286.3418277

Jae-Seung Han, J. An, Younghwan Kim

{"title":"Design and Implementation of Analytical Load Balancing between Distributed Collaborative Container Platforms","authors":"Jae-Seung Han, J. An, Younghwan Kim","doi":"10.1145/3400286.3418277","DOIUrl":"https://doi.org/10.1145/3400286.3418277","url":null,"abstract":"Container-based Micro Service technology has problems with the limitations of resource expansion and the inability to move services between container platforms to respond to growing user traffic. For this reason, distributed collaborative container plat-form(DCCP) technology has emerged that provides the expansion and availability of services and enables collaboration among locally distributed container platforms. DCCP is an essential technology to overcome the limitations of existing stand-alone container platforms by maximizing flexible expansion of resources and service mobility through collaboration between distributed platforms. In this paper, the inter-platform traffic load balancing technology is proposed to construct DDCP. The proposed technology analyzes the user's traffic, identifies the user's geographic location information, and calculates scores for each distributed platform. The scoring method calculates the geographical score based on the platform's geographical location information and the user's geographical location, and calculates the resource score by analyzing the platform's resource status. Transport traffic through the calculated geographical scores and resource scores to the platform that holds the highest scores. The proposed technology provides analytical load balancing technology that addresses the non-efficient problem of randomly dispersing loads on existing independent platforms by load balancing according to the location and resource status of the platform.","PeriodicalId":326100,"journal":{"name":"Proceedings of the International Conference on Research in Adaptive and Convergent Systems","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129129179","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}

引用次数: 0

An Extrinsic Depth Camera Calibration Method for Narrow Field of View Color Camera 窄视场彩色相机的外部深度相机标定方法

Proceedings of the International Conference on Research in Adaptive and Convergent Systems Pub Date : 2020-10-13 DOI: 10.1145/3400286.3418251

C. Shih, Hao-Yu Chen

引用次数: 0