2015 IEEE 34th Symposium on Reliable Distributed Systems Workshop (SRDSW)最新文献

Architectural Support for DevOps in a Neo-Metropolis BDaaS Platform 新城BDaaS平台中DevOps的体系结构支持

2015 IEEE 34th Symposium on Reliable Distributed Systems Workshop (SRDSW) Pub Date : 2015-09-28 DOI: 10.1109/SRDSW.2015.14

Hong-Mei Chen, R. Kazman, Serge Haziyev, Valentyn Kropov, Dmitri Chtchourov

引用次数: 21

On the Use of Mobile GPU for Accelerating Malware Detection Using Trace Analysis 基于跟踪分析的移动GPU加速恶意软件检测

2015 IEEE 34th Symposium on Reliable Distributed Systems Workshop (SRDSW) Pub Date : 2015-09-28 DOI: 10.1109/SRDSW.2015.18

Manel Abdellatif, C. Talhi, A. Hamou-Lhadj, M. Dagenais

{"title":"On the Use of Mobile GPU for Accelerating Malware Detection Using Trace Analysis","authors":"Manel Abdellatif, C. Talhi, A. Hamou-Lhadj, M. Dagenais","doi":"10.1109/SRDSW.2015.18","DOIUrl":"https://doi.org/10.1109/SRDSW.2015.18","url":null,"abstract":"Malware detection on mobile phones involves analysing and matching large amount of data streams against a set of known malware signatures. Unfortunately, as the number of threats grows continuously, the number of malware signatures grows proportionally. This is time consuming and leads to expensive computation costs, especially for mobile devices where memory, power and computation capabilities are limited. As the security threat level is getting worse, parallel computation capabilities for mobile phones is getting better with the evolution of mobile graphical processing units (GPUs). In this paper, we discuss how we can benefit from the evolving parallel processing capabilities of mobile devices in order to accelerate malware detection on Android mobile phones. We have designed and implemented a parallel host-based anti-malware for mobile devices that exploits the computation capabilities of mobile GPUs. A series of computation and memory optimization techniques are proposed to increase the detection throughput. The results suggest that mobile graphic cards can be used effectively to accelerate malware detection for mobile phones.","PeriodicalId":415692,"journal":{"name":"2015 IEEE 34th Symposium on Reliable Distributed Systems Workshop (SRDSW)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121739807","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: 4

Secure Dissemination of Video Data in Vehicle-to-Vehicle Systems 车对车系统中视频数据的安全传播

2015 IEEE 34th Symposium on Reliable Distributed Systems Workshop (SRDSW) Pub Date : 2015-09-28 DOI: 10.1109/SRDSW.2015.22

Chenyang Qu, D. Ulybyshev, B. Bhargava, R. Ranchal, L. Lilien

引用次数: 6

Building Secure Applications Using Pattern-Based Design Fragments 使用基于模式的设计片段构建安全的应用程序

2015 IEEE 34th Symposium on Reliable Distributed Systems Workshop (SRDSW) Pub Date : 2015-09-28 DOI: 10.1109/SRDSW.2015.12

Paul Rimba, Liming Zhu, Xiwei Xu, Daniel W. Sun

引用次数: 2

Impact of Initial Target Position on Performance of UAV Surveillance Using Opportunistic Resource Utilization Networks 初始目标位置对机会资源利用网络无人机监视性能的影响

2015 IEEE 34th Symposium on Reliable Distributed Systems Workshop (SRDSW) Pub Date : 2015-09-28 DOI: 10.1109/SRDSW.2015.11

L. Lilien, L. B. Othmane, Pelin Angin, B. Bhargava, Raed M. Salih, A. DeCarlo

引用次数: 7

SMS Botnet Detection for Android Devices through Intent Capture and Modeling 基于意图捕获和建模的Android设备短信僵尸网络检测

2015 IEEE 34th Symposium on Reliable Distributed Systems Workshop (SRDSW) Pub Date : 2015-09-28 DOI: 10.1109/SRDSW.2015.21

Erik Johnson, I. Traoré

引用次数: 11

Exactly-Once Quantity Transfer 精确一次数量转移

2015 IEEE 34th Symposium on Reliable Distributed Systems Workshop (SRDSW) Pub Date : 2015-09-28 DOI: 10.1109/SRDSW.2015.10

Ali Shoker, Paulo Sérgio Almeida, Carlos Baquero

{"title":"Exactly-Once Quantity Transfer","authors":"Ali Shoker, Paulo Sérgio Almeida, Carlos Baquero","doi":"10.1109/SRDSW.2015.10","DOIUrl":"https://doi.org/10.1109/SRDSW.2015.10","url":null,"abstract":"Strongly consistent systems supporting distributed transactions can be prone to high latency and do not tolerate partitions. The present trend of using weaker forms of consistency, to achieve high availability, poses notable challenges in writing applications due to the lack of linearizability, e.g., to ensure global invariants, or perform mutator operations on a distributed datatype. This paper addresses a specific problem: the exactly-once transfer of a \"quantity\" from one node to another on an unreliable network (coping with message duplication, loss, or reordering) and without any form of global synchronization. This allows preserving a global property (the sum of quantities remains unchanged) without requiring global linearizability and only through using pairwise interactions between nodes, therefore allowing partitions in the system. We present the novel quantity-transfer algorithm while focusing on a specific use-case: a redistribution protocol to keep the quantities in a set of nodes balanced, in particular, averaging a shared real number across nodes. Since this is a work in progress, we briefly discuss the correctness of the protocol, and we leave potential extensions and empirical evaluations for future work.","PeriodicalId":415692,"journal":{"name":"2015 IEEE 34th Symposium on Reliable Distributed Systems Workshop (SRDSW)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132542361","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

A Client-Based Replication Protocol for Multiversion Cloud File Storage 基于客户端的多版本云文件存储复制协议

2015 IEEE 34th Symposium on Reliable Distributed Systems Workshop (SRDSW) Pub Date : 2015-09-28 DOI: 10.1109/SRDSW.2015.17

Mamoru Ohara, S. Fukumoto

{"title":"A Client-Based Replication Protocol for Multiversion Cloud File Storage","authors":"Mamoru Ohara, S. Fukumoto","doi":"10.1109/SRDSW.2015.17","DOIUrl":"https://doi.org/10.1109/SRDSW.2015.17","url":null,"abstract":"In recent years, data replication have received attention in terms of tolerance for large-scale disasters. Also, file versioning features, by which more than one version of a file can be maintained, have been commercially available in some storage services. For providing file versioning with limited storage resources, it is essential to divide the resources among versions in accordance with the varied needs of numerous users. In this paper, we focus on applications in which newer versions of a file are more likely to be requested, which may be true in the case of many subscription services. We propose a new distributed data replication protocol supporting the file versioning feature. In order to eliminate a single point of failure, replica nodes themselves do not know about which nodes hold the newest version, instead, clients dynamically search the nodes having the required version in read/write operations. We also construct an analytical model that can derive an optimal allocation of the resources when the total number of replica nodes in a system and the distribution of the frequency of read requests for each version are given. In addition, we present some numerical examples obtained by simulations to show the good scalability and dependability of our system by assuming some realistic parameters.","PeriodicalId":415692,"journal":{"name":"2015 IEEE 34th Symposium on Reliable Distributed Systems Workshop (SRDSW)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122002557","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: 1

Hard Drive Failure Prediction Using Big Data 基于大数据的硬盘故障预测

2015 IEEE 34th Symposium on Reliable Distributed Systems Workshop (SRDSW) Pub Date : 2015-09-28 DOI: 10.1109/SRDSW.2015.15

Wenjun Yang, Dianming Hu, Yuliang Liu, Shuhao Wang, Tianming Jiang

{"title":"Hard Drive Failure Prediction Using Big Data","authors":"Wenjun Yang, Dianming Hu, Yuliang Liu, Shuhao Wang, Tianming Jiang","doi":"10.1109/SRDSW.2015.15","DOIUrl":"https://doi.org/10.1109/SRDSW.2015.15","url":null,"abstract":"We design a general framework named Hdoctor for hard drive failure prediction. Hdoctor leverages the power of big data to achieve a significant improvement comparing to all previous researches that used sophisticated machine learning algorithms. Hdoctor exhibits a series of engineering innovations: (1) constructing time dependent features to characterize the Self-Monitoring, Analysis and Reporting Technology (SMART) value transitions during disk failures, (2) combining features to enable the model to learn the correlation among different SMART attributes, (3) regarding circumstance data such as cluster workload, temperature, humidity, location as related features. Meanwhile, Hdoctor collects/labels samples and updates model automatically, and works well for all kinds of disk failure prediction in our intelligent data center. In this work, we use Hdoctor to collect 74,477,717 training records from our clusters involving 220,022 disks. By training a simple and scalable model, our system achieves a detection rate of 97.82%, with a false alarm rate (FAR) of 0.3%, which hugely outperforms all previous algorithms. In addition, Hdoctor is an excellent indicator for how to predict different hardware failures efficiently under various circumstances.","PeriodicalId":415692,"journal":{"name":"2015 IEEE 34th Symposium on Reliable Distributed Systems Workshop (SRDSW)","volume":"11 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116114743","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: 34

Selective Hearing: An Approach to Distributed, Eventually Consistent Edge Computation 选择性听力:一种分布式，最终一致的边缘计算方法

2015 IEEE 34th Symposium on Reliable Distributed Systems Workshop (SRDSW) Pub Date : 2015-09-28 DOI: 10.1109/SRDSW.2015.9

Christopher S. Meiklejohn, P. V. Roy

引用次数: 10