2018 IEEE 17th International Symposium on Network Computing and Applications (NCA)最新文献_第3页

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2018 IEEE 17th International Symposium on Network Computing and Applications (NCA) Pub Date : 2018-11-01 DOI: 10.1109/nca.2018.8548332

引用次数: 0

Data-Driven Edge Computing Resource Scheduling for Protest Crowds Incident Management 基于数据驱动的边缘计算资源调度的抗议人群事件管理

2018 IEEE 17th International Symposium on Network Computing and Applications (NCA) Pub Date : 2018-11-01 DOI: 10.1109/NCA.2018.8548069

Jon Patman, Peter Lovett, A. Banning, Annie Barnert, D. Chemodanov, P. Calyam

{"title":"Data-Driven Edge Computing Resource Scheduling for Protest Crowds Incident Management","authors":"Jon Patman, Peter Lovett, A. Banning, Annie Barnert, D. Chemodanov, P. Calyam","doi":"10.1109/NCA.2018.8548069","DOIUrl":"https://doi.org/10.1109/NCA.2018.8548069","url":null,"abstract":"Computation offloading has been shown to be a viable solution for addressing the challenges of processing compute-intensive workloads between low-power devices and nearby servers known as cloudlets. However, factors such as dynamic network conditions, concurrent user access, and limited resource availability often result in offloading decisions negatively impacting end users in terms of delay and energy consumption. To address these shortcomings, we investigate the benefits of using Machine Learning for predicting offloading costs for a facial recognition service in a series of realistic wireless experiments. We also perform a set of trace-driven simulations to emulate a multi-edge protest crowd incident case study and formulate an optimization model that minimizes the time taken for all service tasks to be completed. Because optimizing offloading schedules for such a system is a well-known NP-complete problem, we use mixed integer programming and show that our scheduling solution scales efficiently for a moderate number of user devices (10–100) with a correspondingly small number of cloudlets (1–10), a scale commonly sufficient for public safety officials in crowd incident management. Moreover, our results indicate that using Machine Learning for predicting offloading costs leads to near-optimal scheduling in 70 % of the cases we investigated and offers a 40 % gain in performance over baseline estimation techniques.","PeriodicalId":268662,"journal":{"name":"2018 IEEE 17th International Symposium on Network Computing and Applications (NCA)","volume":"484 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116029243","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: 7

Characterization and Modeling of IoT Data Traffic in the Fog of Things Paradigm 物联网数据流量在物雾范式中的表征和建模

2018 IEEE 17th International Symposium on Network Computing and Applications (NCA) Pub Date : 2018-11-01 DOI: 10.1109/NCA.2018.8548340

Ernando Batista, L. Andrade, Ramon Dias Costa, A. Andrade, G. Figueiredo, Cássio V. S. Prazeres

{"title":"Characterization and Modeling of IoT Data Traffic in the Fog of Things Paradigm","authors":"Ernando Batista, L. Andrade, Ramon Dias Costa, A. Andrade, G. Figueiredo, Cássio V. S. Prazeres","doi":"10.1109/NCA.2018.8548340","DOIUrl":"https://doi.org/10.1109/NCA.2018.8548340","url":null,"abstract":"The Internet of Things (IoT) allows for the communication of a large number of physical or virtual objects through different technologies, protocols and patterns. Several organizations have tried to predict the number of IoT devices that will be connected to the Internet by 2020. Although they have not yet to agree on an exact ‘magical’ number of such devices (in billions), we can expect this huge number of devices to be active which may pose several challenges regarding connectivity and information exchange over network infrastructures. And despite the fact that Cloud and Fog computing addresses some of these challenges, it can also create other problems due to the high demand for storage as well as high network traffic at the edge level. In this paper, we model the IoT data traffic in order to execute several experiments related to the demand for storage and network traffic. As a consequence, the results of our experiments, which have been validated in a modeling based on the Fog of Things paradigm, can be used to evaluate the impact that variation in IoT data traffic patterns has on IoT / Fog environments.","PeriodicalId":268662,"journal":{"name":"2018 IEEE 17th International Symposium on Network Computing and Applications (NCA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116728389","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: 9

Towards a Low Latency Network-Slice Resistant to Unresponsive Traffic 迈向低延迟的网络切片，抵抗无响应的流量

2018 IEEE 17th International Symposium on Network Computing and Applications (NCA) Pub Date : 2018-11-01 DOI: 10.1109/NCA.2018.8548335

Paulo Pinto, Amineh Mazandarani, Pedro Amaral, Luís Bernardo

{"title":"Towards a Low Latency Network-Slice Resistant to Unresponsive Traffic","authors":"Paulo Pinto, Amineh Mazandarani, Pedro Amaral, Luís Bernardo","doi":"10.1109/NCA.2018.8548335","DOIUrl":"https://doi.org/10.1109/NCA.2018.8548335","url":null,"abstract":"This paper studies what mechanisms a network must have to offer a very low-latency service to applications (featuring a maximum end-to-end packet delay). We assume very concrete requirements, not seen in the literature, that raise the challenge level: i) applications might be unresponsive to traffic warnings from the network; and ii) applications do not inform or require any network resources, exactly as the Internet works today (i.e., there is no admission control procedures). We present an architecture/algorithm with a minimum of state information and good scalability properties. Obviously, it is not applicable to the wide Internet. Even more, the architecture is not TCP-friendly (because control loops must be shorter than the Round Trip Time (RTT) magnitudes and oscillations, and packet losses are higher). Instead, it is appropriate to an end-to-end slice network based on a virtualization of the physical network with independent queues and line bandwidths. It is designed for interactive applications and for certain real-time ones. We use plain backpressure control supported by cooperation amongst the routers to isolate offending traffic. We are particularly concerned in situations of very high load, as they will be very common in the future. One objective is to reach a predictable network behaviour that in the limit (heavy network overload) is maintained, contrary to the current Internet. In the future, new pace-based congestion control algorithms for applications can be designed to take the most out of this type of network.","PeriodicalId":268662,"journal":{"name":"2018 IEEE 17th International Symposium on Network Computing and Applications (NCA)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132275729","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

Energy-Efficient Data Center Networks 节能数据中心网络

2018 IEEE 17th International Symposium on Network Computing and Applications (NCA) Pub Date : 2018-11-01 DOI: 10.1109/NCA.2018.8548323

J. Manjate, M. Hidell, Peter Sjödin

{"title":"Energy-Efficient Data Center Networks","authors":"J. Manjate, M. Hidell, Peter Sjödin","doi":"10.1109/NCA.2018.8548323","DOIUrl":"https://doi.org/10.1109/NCA.2018.8548323","url":null,"abstract":"Data center networks (DCNs) are designed to be scalable, resilient, and tolerant to failures. This is achieved through redundancy of network devices and links. All devices and links are always operational, consuming full energy even when underutilized. Energy-aware routing (EAR) protocols leverage network-wide information to dynamically scale up or down network energy consumption according to utilization. However, many EARs are designed for networks of devices and links that are not energy-proportional, such as ElasticTree and VMPlanner. The advent of Energy Efficient Ethernet (EEE) brings new challenges into how EAR protocols are designed. In this paper, we propose Greener, an extension of ElasticTree to leverage the energy proportionality characteristics of EEE. We integrate the EEE energy model with the ElasticTree solution. Greener is designed for K-ary Fat-Tree multi-rooted topologies, to steer flows along the most energy-efficient paths and put into sleep mode unused switches and links. Simulation experiments of Greener in DCNs of different sizes and under varying traffic loads show that it brings significant improvements in energy savings. Moreover, Greener outperforms the benchmark ElasticTree executed on EEE-based DCNs by up to 10 percentage points of energy savings.","PeriodicalId":268662,"journal":{"name":"2018 IEEE 17th International Symposium on Network Computing and Applications (NCA)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133944117","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

DBFT: Efficient Leaderless Byzantine Consensus and its Application to Blockchains DBFT:高效的无领导拜占庭共识及其在区块链中的应用

2018 IEEE 17th International Symposium on Network Computing and Applications (NCA) Pub Date : 2018-11-01 DOI: 10.1109/NCA.2018.8548057

Tyler Crain, V. Gramoli, M. Larrea, M. Raynal

{"title":"DBFT: Efficient Leaderless Byzantine Consensus and its Application to Blockchains","authors":"Tyler Crain, V. Gramoli, M. Larrea, M. Raynal","doi":"10.1109/NCA.2018.8548057","DOIUrl":"https://doi.org/10.1109/NCA.2018.8548057","url":null,"abstract":"This paper introduces a new leaderless Byzantine consensus called the Democratic Byzantine Fault Tolerance (DBFT) for blockchains. While most blockchain consensus protocols rely on a correct leader or coordinator to terminate, our algorithm can terminate even when its coordinator is faulty. The key idea is to allow processes to complete asynchronous rounds as soon as they receive a threshold of messages, instead of having to wait for a message from a coordinator that may be slow. The resulting decentralization is particularly appealing for blockchains for two reasons: (i) each node plays a similar role in the execution of the consensus, hence making the decision inherently “democratic” (ii) decentralization avoids bottlenecks by balancing the load, making the solution scalable. DBFT is deterministic, assumes partial synchrony, is resilience optimal, time optimal and does not need signatures. We first present a simple safe binary Byzantine consensus algorithm, modify it to ensure termination, and finally present an optimized reduction from multivalue consensus to binary consensus whose fast path terminates in 4 message delays.","PeriodicalId":268662,"journal":{"name":"2018 IEEE 17th International Symposium on Network Computing and Applications (NCA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123861191","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: 135

Recurrent Neural Network-Based Prediction of TCP Transmission States from Passive Measurements 基于递归神经网络的被动测量TCP传输状态预测

2018 IEEE 17th International Symposium on Network Computing and Applications (NCA) Pub Date : 2018-11-01 DOI: 10.1109/NCA.2018.8548064

D. Hagos, P. Engelstad, A. Yazidi, Ø. Kure

{"title":"Recurrent Neural Network-Based Prediction of TCP Transmission States from Passive Measurements","authors":"D. Hagos, P. Engelstad, A. Yazidi, Ø. Kure","doi":"10.1109/NCA.2018.8548064","DOIUrl":"https://doi.org/10.1109/NCA.2018.8548064","url":null,"abstract":"Long Short-Term Memory (LSTM) neural networks are a state-of-the-art techniques when it comes to sequence learning and time series prediction models. In this paper, we have used LSTM-based Recurrent Neural Networks (RNN) for building a generic prediction model for Transmission Control Protocol (TCP) connection characteristics from passive measurements. To the best of our knowledge, this is the first work that attempts to apply LSTM for demonstrating how a network operator can identify the most important system-wide TCP per-connection states of a TCP client that determine a network condition (e.g., cwnd) from passive traffic measured at an intermediate node of the network without having access to the sender. We found out that LSTM learners outperform the state-of-the-art classical machine learning prediction models. Through an extensive experimental evaluation on multiple scenarios, we demonstrate the scalability and robustness of our approach and its potential for monitoring TCP transmission states related to network congestion from passive measurements. Our results based on emulated and realistic settings suggest that Deep Learning is a promising tool for monitoring system-wide TCP states from passive measurements and we believe that the methodology presented in our paper may strengthen future research work in the computer networking community.","PeriodicalId":268662,"journal":{"name":"2018 IEEE 17th International Symposium on Network Computing and Applications (NCA)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124997360","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: 8

A Hybrid Approach to Detect DDoS Attacks Using KOAD and the Mahalanobis Distance 基于KOAD和马氏距离的混合DDoS攻击检测方法

2018 IEEE 17th International Symposium on Network Computing and Applications (NCA) Pub Date : 2018-11-01 DOI: 10.1109/NCA.2018.8548334

Salva Daneshgadeh, Thomas Kemmerich, Tarem Ahmed, N. Baykal

{"title":"A Hybrid Approach to Detect DDoS Attacks Using KOAD and the Mahalanobis Distance","authors":"Salva Daneshgadeh, Thomas Kemmerich, Tarem Ahmed, N. Baykal","doi":"10.1109/NCA.2018.8548334","DOIUrl":"https://doi.org/10.1109/NCA.2018.8548334","url":null,"abstract":"Distributed Denial of Service (DDoS) attacks continue to adversely affect internet-based services and applications. Various approaches have been proposed to detect different types of DDoS attacks. The computational and memory complexities of most algorithms, however prevent them from being employed in online manner. In this paper, we propose a novel victim-end online DDoS attack detection framework based on the celebrated Kernel-based Online Anomaly Detection (KOAD) algorithm and the Mahalanobis distance. We have employed the KOAD algorithm to adaptively model the normal behavior of network traffic, and then constructed the normal and abnormal datasets based on the results of KOAD. Subsequently, the Mahalanobis distance metric was calculated between datapoints of the abnormal and normal subsets. Finally, the chi-square test was used on the Mahalanobis distance values to segregate the DDoS attack datapoints from the normal ones. We have validated our algorithm on simulated DDoS scenarios, as well as real baseline data from a company operating in cyber security. Our results have revealed that our proposed hybrid approach boosts the performance of sole KOAD algorithm and Mahalanobis distance in detecting DDoS traffic in terms of both false positive and detection rates.","PeriodicalId":268662,"journal":{"name":"2018 IEEE 17th International Symposium on Network Computing and Applications (NCA)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124122170","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

Modeling System-Level Power Consumption Profiles Using RAPL 使用RAPL建模系统级功耗配置文件

2018 IEEE 17th International Symposium on Network Computing and Applications (NCA) Pub Date : 2018-11-01 DOI: 10.1109/NCA.2018.8548281

James Phung, Young Choon Lee, Albert Y. Zomaya

引用次数: 3

A Formal Treatment of Efficient Byzantine Routing Against Fully Byzantine Adversary 针对完全拜占庭对手的有效拜占庭路由的形式化处理

2018 IEEE 17th International Symposium on Network Computing and Applications (NCA) Pub Date : 2018-11-01 DOI: 10.1109/NCA.2018.8548163

Siddhant Goenka, Sisi Duan, Haibin Zhang

引用次数: 0