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Benchmarking distributed Stream Processing Frameworks for Real Time Classical Machine Learning Applications

Benchmarking Distributed Stream Processing Frameworks for Re...

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international conference on computing and networking Technology (ICCNT)

作者： Merlin Sundar Sriram Kailasam Timothy A. Gonsalves IIT Mandi Kamand India

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

As the volume of data generated is growing at an unprecedented rate, it becomes important to analyze this data in real-time. To handle the huge volume of data streaming at a high velocity, we not only require powerful machines but also means to distribute the computation involved on the multiple machines. There are several open-source distributed stream processing frameworks such as Apache {Storm, Flink, Spark} and Confluent Kafka for building real-time machine learning applications. Prior works benchmarked some of these platforms using low-level operations like filters, joins, windowed computations etc. Our work includes benchmarking these popular frameworks for their applicability to classical machine learning models: Online K-Means, Online Linear Regression and Online Logistic Regression. We study the following quantitative metrics of evaluation: throughput, latency, CPU, and memory usage. The experiments were conducted in both standalone and clusters setups to determine the scalability of the models. This study will help system designers choose the right model and the right framework, given a specific configuration on streaming data.

关键词： Machine learning Storms Logistics Clustering algorithms Machine learning algorithms Linear regression Sparks

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Data Correction Management Method Using Temporal Data in Fog computing 12

Data Correction Management Method Using Temporal Data in Fog...

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12th international conference on Mobile computing and Ubiquitous networking (ICMU)

作者： Kudo, Tsukasa Shizuoka Inst Sci & Technol Fac Informat Fukuroi Japan

ISBN: (纸本)9784907626419

With the recent development and expansion of the Internet of Things, fog computing has been proposed to solve the problem of transferring large quantities of sensor data to a cloud server. Primary processing is performed at fog nodes installed near sensors and only its results are transferred to server to be shared and used by various analytical processing. When any missing or defective data is detected, the corrected data is retransferred to the server and the related analytical processing are executed again. And, when the results of the analytical and primary processing have a relationship, such as summaries and details, the analytical processing results must be updated with maintaining consistency between them. However, to maintain consistency at all times, analytical processing must be performed with every re-transfer thereby degrading the efficiency. In this paper, I propose a method to reflect many sequential corrections in a lump while maintaining consistency by using the temporal database concept and show its effectiveness.

关键词： IoT fog computing distributed database temporal database bitemporal database transaction time

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Analysis and Visualization of Twitter Data using R

Analysis and Visualization of Twitter Data using R

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international conference on Parallel distributed and Grid computing (PDGC)

作者： Aman Sharma Rishi Rana Jaypee University of Information Technology District Solan Himachal Pradesh INDIA

ISBN: (数字)9781728171326

ISBN: (纸本)9781728171333

“Human is a social animal” this line itself explains the importance of society in one's life. Society brings stability, a medium to express thoughts. Society leads to social interaction which eventually brings thoughtful minds. Humans have the intrinsic nature of analyzing and opinionating things and persons. This keen nature of humanity has emerged as a new field of analysis that is social data analysis. The Internet has merged the world today and as a result, human social circles have expanded. There are various peculiar social networking sites available on the internet, some of them are on Facebook, Twitter, LinkedIn and many more. Each maintains accounts of billions of active users and the huge amount of data is being produced as a result of interactions over such sites. Hence analyzing this data is a tedious task. But analysis of such online social communities and predicting their behavior is of great importance for businesses and academics. In this paper, we are concentrating more on twitter. This paper aims to develop a research-based application using twitter and R-tool. We have visualized and analyzed the data using R-tool.

关键词： Social networking (online) Blogs Data mining Data visualization Sentiment analysis Handheld computers Tag clouds

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Service function chaining across openstack and kubernetes domains 19

Service function chaining across openstack and kubernetes do...

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13th ACM international conference on distributed and Event-Based Systems, DEBS 2019

作者： Kouchaksaraei, Hadi Razzaghi Karl, Holger Computer Network Group Paderborn University Germany

ISBN: (纸本)9781450367943

Remarkable advantages of Containers (CNs) over Virtual Machines (VMs) such as lower overhead and faster startup has gained the attention of Communication Service Providers (CSPs) as using CNs for providing Virtual Network Functions (VNFs) can save costs while increasing the service agility. However, as it is not feasible to realise all types of VNFs in CNs, the coexistence of VMs and CNs is proposed. To put VMs and CNs together, an orchestration framework that can chain services across distributed and heterogeneous domains is required. To this end, we implemented a framework by extending and consolidating state-of-the-art tools and technologies originated from Network Function Virtualization (NFV), Software-defined networking (SDN) and cloud computing environments. This framework chains services provisioned across Kubernetes and OpenStack domains. During the demo, we deploy a service consist of CN- and VM-based VNFs to demonstrate different features provided by our framework. © 2019 Authors.

关键词： Software defined networking

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Heterogeneous Statistical QoS Driven Collaborative Learning Based Energy Harvesting Over Full-Duplex Cognitive Radio Networks 39

Heterogeneous Statistical QoS Driven Collaborative Learning ...

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39th IEEE international conference on distributed computing Systems (ICDCS)

作者： Zhang, Xi Wang, Jingqing Texas A&M Univ Dept Elect & Comp Engn Networking & Informat Syst Lab College Stn TX 77843 USA

ISBN: (纸本)9781728125190

With the recent developments in energy harvesting (EH) technologies, mobile devices are able to support the wireless multimedia services by harvesting energy from various external sources. As one of the promising technologies to solve the energy scarcity problem, EH schemes have brought many new challenges due to the stochastic nature of the wireless channel and the harvested energy in supporting the statistical quality-of-service (QoS) provisionings. On the other hand, the full-duplex spectrum sensing (FD-SS) scheme has been designed to improve the spectrum efficiency while significantly enhancing the system performance over cognitive radio networks (CRNs). However, due to the unknown dynamics of the channel state information and the energy state information, it is challenging to design the efficient EH based power allocation policies for all the users with different operating modes while guaranteeing the statistical delay-bounded QoS constraints. To overcome the aforementioned problems, in this paper we develop the collaborative learning system model by choosing the optimal operation strategies and power allocation policies through learning from the EH process while satisfying the heterogeneous statistical delay-bounded QoS constraints over CRNs. In particular, we establish and analyze the FD-SS based EH system models over CRNs. Under the heterogeneous statistical delay-bounded QoS requirements, we formulate and solve the max-min fairness effective-capacity optimization problem for the battery-free EH based CRNs. Then, we apply the collaborative learning algorithm for deriving the optimal joint EH based mode selection and power allocation schemes. Also conducted is a set of simulations which evaluate the system performances and show that our proposed collaborative learning based EH scheme outperforms the other existing schemes under the heterogeneous statistical delay-bounded QoS constraints over CRNs.

关键词： Collaborative learning energy harvesting full duplex heterogeneous statistical delay-bounded quality of service (QoS) max-min fairness effective capacity cognitive radio networks

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Pipe-torch: Pipeline-Based distributed Deep Learning in a GPU Cluster with Heterogeneous networking 7

Pipe-torch: Pipeline-Based Distributed Deep Learning in a GP...

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7th international conference on Advanced Cloud and Big Data (CBD)

作者： Zhan, Jun Zhang, Jinghui Southeast Univ Sch Comp Sci & Engn Nanjing Peoples R China

ISBN: (纸本)9781728151410

Because training a deep neural network (DNN) takes arduous amounts of time and computation, often researchers expedite the training process via distributed parallel training on GPUs. On one hand, this lower computing-to-communication ratio makes traditional data parallelism difficult to scale, and traditional model parallelism leads to low GPU utilization. Both make it difficult to obtain a higher speedup. On the other hand, multi-GPU systems exhibit complex connectivity among GPUs. Overall, workload schedulers must consider hardware topology and workload communication requirements to allocate GPU resources for optimal execution time and improved utilization in GPU clusters with heterogeneous networking. Thus, in this paper, we introduce Pipe-torch, an improved pipeline-hybrid parallelism method (using both data and model parallelism) in a heterogeneous network environment. Ultimately, the framework's model partition algorithm aims to expedite pipeline-hybrid parallelism training between heterogeneous network-connected GPUs. Experiments with four different DNN models show that Pipe-torch averages 1.4x speedup compared to data parallelism.

关键词： distributed deep learning Pipeline-hybrid parallelism Heterogeneous network environment

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Anonymous and Coercion-Resistant distributed Electronic Voting

Anonymous and Coercion-Resistant Distributed Electronic Voti...

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international conference on computing, networking and Communications (ICNC)

作者： Ehab Zaghloul Tongtong Li Jian Ren

ISBN: (数字)9781728149059

ISBN: (纸本)9781728149066

Electronic voting (e-voting) presents a convenient and cost-effective alternative to current paper ballot-based voting. It provides many benefits such as increased voter turnout and accuracy in the decision-making process. While presenting many improvements, e-voting still faces serious security challenges that hinder its adoption. In this paper, we propose a novel remote e-voting scheme that can enhance the integrity, efficiency, and voter turnout of the election process. Our proposed work is secure and preserves the privacy of voters through secure multi-party computations performed by parties of differing allegiances. It also leverages a blockchain running smart contracts as a publicly accessible and tamper-resistant bulletin board to permanently store votes and prevent double-voting. In our security and privacy analysis, we show that our proposed scheme is secure against potential threats and provides voter anonymity. Our performance discussion shows that the proposed scheme is practical for large-scale elections.

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A Fast, Secure and distributed Consensus Mechanism for Energy Trading Among Vehicles using Hashgraph

A Fast, Secure and Distributed Consensus Mechanism for Energ...

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international conference on Information networking

作者： Gaurang Bansal Ashutosh Bhatia Department of Computer Science and Information Systems Birla Institute of Technology and Science Pilani Rajasthan

ISBN: (数字)9781728141992

ISBN: (纸本)9781728142005

Energy trading among inter vehicles (V2V) offers an efficient response to most of the problems presented by future electricity supply. V2V is often envisioned as a peer-to-peer (P2P) model of electric mercantilism for electric vehicle (EV) merchandising. With security vulnerability increasing, confidence in secured third parties is declining. Blockchain is becoming increasingly common as it provides a system for privacy conservation and efficient agreement without the need for trusted third parties. However, all operations in such a scheme are restricted by memory, time, computing capital, energy etc. and it is quite obvious that the mechanism for blockchain agreement is not sufficient to address all of them. In this paper, we present an alternative to the blockchain using Hashgraph which is scalable, fast, fault-tolerant and fair. It is efficient, inexpensive, and DoS resistant fulfilling the requirement of V2V energy trading.

关键词： Peer-to-peer computing Protocols Discharges (electric) Smart grids Load modeling Synchronization

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Optimizing the energy envelope in the Internet of Things using predictive cubic splines

Optimizing the energy envelope in the Internet of Things usi...

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Annual IEEE international conference on Sensing, Communication, and networking Workshops (SECON Workshops)

作者： Saibal Ghosh Dharma P Agrawal Center for Distributed and Mobile Computing University of Cincinnati Cincinnati OH United States

ISBN: (数字)9781728110622

ISBN: (纸本)9781728110639

The paradigm of Internet of Things (IoT) is the result of rapid advances in the development of small low powered computing devices with wireless connectivity. This has given rise to a plethora of new applications, including, but not limited to monitoring, sensing, intrusion detection and others. Due to the nature of these applications, IoT devices are often burdened with receiving and transmitting a large volume of data that is time and delay sensitive. Furthermore, since most of these devices are battery powered, a data deluge often renders parts of the network depleted of energy, causing that part to go dark. In this work, we propose an energy optimization framework based on predictive cubic splines that anticipate a sudden increase in the bandwidth and minimize energy consumed by these devices while still maintaining an optimum degree of availability and reducing bottlenecks in the data flow.

关键词： Task analysis Delays Splines (mathematics) conferences Energy consumption Interpolation Character recognition

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An Active Signaling Mechanism to Reduce Access Collisions in a distributed TDMA Based MAC Protocol for Vehicular Networks 33rd

An Active Signaling Mechanism to Reduce Access Collisions in...

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33rd international conference on Advanced Information networking and Applications, AINA-2019

作者： Boukhalfa, Fouzi Hadded, Mohamed Muhlethaler, Paul Shagdar, Oyunchimeg VEDECOM Versailles France INRIA Paris France

ISBN: (纸本)9783030150310

A Vehicular Ad-Hoc NETwork (VANET) is an emerging technology consisting in a set of vehicles, mobile devices and an infrastructure, which uses wireless transmission technologies to enable real-time communication between them. VANETs help to improve traffic safety and efficiency by enabling each vehicle to exchange information about vehicle positions, speeds and the state of the road. Due to its promising applications, this type of network has attracted a lot of attention in the research community, including those in the domain of Medium Access Control (MAC). In fact, an efficient MAC protocol design in VANETs is crucial to guarantee safety-critical message broadcasting with high reliability and minimum delay. A Time Division Multiple Access (TDMA)-based MAC protocol is advantageous in VANETs thanks to its ability to prevent the hidden node problem, and to guarantee high quality of service for real-time applications. However, time slot assignments to vehicles could suffer from the access collision problem which can frequently occur between vehicles trying to access the same time slots. This problem is mainly due to the lack of infrastructure and potentially high density of vehicles in VANETs. In this paper, we focus on the problem of access collision in the time slot assignments of the DTMAC protocol, and present an enhanced version based on active signaling (AS-DTMAC, i.e. Active Signaling-DTMAC). Extensive simulations are conducted considering various traffic densities to demonstrate the performance of AS-DTMAC. © 2020, Springer Nature Switzerland AG.

关键词： Time division multiple access

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