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SardineDB: A distributed Database on the Edge of the Network 5th

SardineDB: A Distributed Database on the Edge of the Network

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5th Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) international Joint conference on Web and Big Data

作者： Dong, Min Zhong, Haozhao Sun, Boyu Bi, Sheng Cai, Yi South China Univ Technol Sch Comp Sci & Engn Guangzhou 510006 Guangdong Peoples R China Minist Educ Key Lab Big Data & Intelligent Robot Guangzhou 510006 Guangdong Peoples R China South China Univ Technol Sch Software Engn Guangzhou 510006 Guangdong Peoples R China

ISBN: (纸本)9783030858995;9783030858988

In the past few years, the number of sensors is rapidly increasing on the edge of the network. IoT(internet of things) devices play not only data producers but also data consumers. It is valuable to deploy a distributed database on the edge of the network. However, flash memory is the mainstream storage medium on the edge, which is different from cloud environment. Flash memory can wear out through repeated writes while large amount of data are written on the edge per day. thus, in this paper, SardineDB is presented, which is a decentralized distributed database optimized for edge. the engine of SardineDB is Sardine-Core, which is a flash-optimized key-value separation storage based on LevelDB. SardineCore has low GC (garbage collection) burden, which can be used to low the write amplification and improve the write performance on the edge. From evaluation results, the write performance and random read performance of SardineDB have great advantages compared with existing distributed databases on the edge. As a result, SardineDB is very suitable for edge because it has high write performance, low GC burden and low write amplification.

关键词： IOT Edge computing LevelDB distributed database Sensor Flash memory

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Performance Analysis of Load Balancing Algorithms in Amazon Cloud 5th

Performance Analysis of Load Balancing Algorithms in Amazon ...

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5th international conference on Microelectronics, computing and Communication Systems, MCCS 2020

作者： Kumari, Ragini Jha, Vijay Kumar Department of Computer Science and Engineering Birla Institute of Technology Mesra Ranchi Jharkhand India

ISBN: (纸本)9789811602740

Cloud computing has vast impact in the field of parallel and distributed computing systems today. It enables a massive number of users to access virtualized hardware and software infrastructures with the help of the internet. Consequently, it produces huge traffic into cloud servers. the abrupt growth of this load leads to serious challenges for load balancer of cloud to work out efficiently. the function of load balancer is to distribute the heavy load on servers in cloud environment to obtain maximum utilization of resources by achieving maximum throughput and minimum response time. Various researches have been done to implement better load balancing algorithms to minimize load on servers, but all existing research work in this direction have been developed as an analytical approach in which performance analysis of load balancing algorithms have been performed or compared by creating servers in their systems. the future analysis of this research has been left to implement the load balancing algorithms in real environments. this paper demonstrates the performance analysis of two most popular load balancing algorithms i.e. Round Robin and Least Connections in Amazon Web Service cloud in real-time with the help of performance measuring tool Apache JMeter. © 2021, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cloud computing

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Hybrid CNN-GRU Framework with Integrated Pre-trained Language Transformer for SMS Phishing Detection 5

Hybrid CNN-GRU Framework with Integrated Pre-trained Languag...

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5th international conference on Future Networks and distributed Systems: the Premier conference on Smart Next Generation Networking Technologies, ICFNDS 2021

作者： Ulfath, Rubaiath E Alqahtani, Hamed Hammoudeh, Mohammad Sarker, Iqbal H. Department of Computer Science and Engineering Chittagong University of Engineering and Technology Chittagong4349 Bangladesh King Khalid University College of Computer Science Abha62529 Saudi Arabia Department of Computing & Math Manchester Metropolitan University Manchester United Kingdom

ISBN: (纸本)9781450387347

Smartphones are prone to SMS phishing due to the rapid growth in the availability of smart mobile technologies driven by internet connections. Also, detecting phishing SMS is a challenging task due to the unstructured nature of SMS text data with non-linear complex correlations. In this concern, considering the recent advancements in the domain of cybersecurity, we have proposed a hybrid deep learning framework that extracts robust features from SMS texts followed by an automatic detection of Phishing SMS. Due to combining the potential capability of individual models into one hybrid framework, it has outperformed various other individual machine learning and deep learning models. the proposed Phishing Detection framework is an effective hybrid combination of pretrained transformer model, MPNet (Masked and Permuted Language Modeling), with supervised ConvNets (CNN) and Bi-directional Gated Recurrent Units (GRU). It is intended to successfully detect unstructured short phishing text messages that contain complex patterns. © 2021 ACM.

关键词： Deep learning

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GWO Based Task Allocation for Load Balancing in Containerized Cloud 5

GWO Based Task Allocation for Load Balancing in Containerize...

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5th international conference on Inventive Computation Technologies (ICICT)

作者： Patel, Dimple Patra, Manoj Kumar Sahoo, Bibhudatta Natl Inst Technol Dept Comp Sci & Engn Rourkela India

ISBN: (纸本)9781728146850

On-demand provisioning of computing services such as analytics, intelligence, networking, storage, and servers, etc. over the internet is the main function of cloud computing. Several servers are connected in a distributed manner over the internet to execute tasks. Recently, container technology has gained enormous popularity as it can improve overall application performance by providing OS-level virtualization in cloud computing systems. Based on the resources available on server, a server can accommodate more than one container running on it. the process of distributing the incoming requests or user tasks among all available servers in such a way that all the servers will have almost equal workload is called load balancing. In this paper, we proposed a Grey Wolf Optimization(GWO) based technique for load distribution in the containerized cloud and also to reduce the makespan. We have compared our results with the Genetic algorithm and Particle Swarm Optimization(PSO) based algorithm. the experimental result indicate that the GWO based technique is performing better in terms of load balancing and also having reduced makespan.

关键词： Cloud computing Resource Allocation Load Balancing Container Task Scheduling Grey Wolf Optimization

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distributed Edge computing to Assist LPWAN: Fog-MEC Model 21

Distributed Edge Computing to Assist LPWAN: Fog-MEC Model

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Proceedings of the 5th international conference on Future Networks and distributed Systems

作者： Mona Mahmoud Abdelhamied Ashraf Ateya Ammar Muthanna Adel Zaghloul Ruslan Kirichek Andrey Koucheryavy Zagazig University Egypt Electronics and Communications Engineering Zagazig University Egypt and The Bonch-Bruevich Saint Petersburg State University of Telecommunications Russian Federation The Bonch-Bruevich Saint Petersburg State University of Telecommunications Russia Electronics and Communications Engineering Zagazig University Egypt Electronics and Communications Engineering The Bonch-Bruevich Saint Petersburg State University of Telecommunications Russia

ISBN: (纸本)9781450387347

Low power wide area network (LPWAN) is one of the main internet of things (IoT) networks that is widely used for the outdoor-IoT applications. A main feature with such networks is the long-range coverage that enables the dense deployment over such networks. However, the introduction of massive number of IoT devices puts many constraints and limitations on the design and development of such networks. A promising solution for a part of such challenges is the introduction of distributed computing technology to enable this massive number of deployed devices. this work considers such deployment of heterogeneous forms of distributed computing units to assist the design and development of LPWAN networks for dense deployed applications. Two main forms of the distributed computing are considered in this work; multiple access edge computing (MEC), and fog computing. the integration of fog and MEC units is introduced in a way that achieves higher latency, energy, and availability efficiency. A proof-of-concept of the developed model is introduced for dense deployment scenarios. the developed fog-MEC model is evaluated for LPWAN for heterogeneous simulation scenarios, and the simulation results validate the developed model.

关键词： Fog

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Analysis of Computer Network Information Security under the Background of Big Data 5

Analysis of Computer Network Information Security under the ...

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5th international conference on Smart Grid and Electrical Automation (ICSGEA)

作者： Xie Peng Zhang Hongmei Cui Lijie Hu Ying Equipment Management & UAN Engn Coll Air Force Engn Xian 710051 Peoples R China Xian Railway Technician Inst Xian 710038 Peoples R China

ISBN: (数字)9781728182780

ISBN: (纸本)9781728182780

In today's society, under the comprehensive arrival of the internet era, the rapid development of technology has facilitated people's production and life, but it is also a "double-edged sword", making people's personal information and other data subject to a greater threat of abuse. the unique features of big data technology, such as massive storage, parallel computing and efficient query, have created a breakthrough opportunity for the key technologies of large-scale network security situational awareness. On the basis of big data acquisition, preprocessing, distributed computing and mining and analysis, the big data analysis platform provides information security assurance services to the information system. this paper will discuss the security situational awareness in large-scale network environment and the promotion of big data technology in security perception.

关键词： Big Data Network Security Situation Awareness Parallel computing

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Detecting distributed Denial of Service Attacks in internet of things Networks Using Machine Learning in Fog computing

Detecting Distributed Denial of Service Attacks in Internet ...

引用

international conference on Engineering technology and their Applications (IICETA)

作者： Karrar Falih Hassan Mehdi Ebady Manaa College of Information Technology University of Babylon Babylon Iraq

ISBN: (数字)9781665472159

ISBN: (纸本)9781665472166

the number of internet of things (IoT) devices and the data produced by these devices have increased dramatically in recent years. IoT networks have benefited from the arrival of 5G, which aims to link more devices quickly and reliably. However, many of these devices are unsecured, leaving the internet open to assault. Since IoT devices are resource-restricted, attackers may simply mount a larger and more complex DDoS assault using IoT devices. Entropy-based detection is technique proposed by other researchers, and it has a high sensitivity and a good degree of reliability. In this paper, authors propose an entropy-based framework with the machine learning algorithms to optimize the detection result. the proposed system consists of three parts: the first part is to create a sliding time window to calculate the entropy, and the second is using the Euclidean distance to make early detection possible during the DDoS but not after the collapse. the third part is the use of machine learning algorithms (KNN and SVM), to improve the accuracy of the results in early detection. the results showed that the proposed system is able to increase the accuracy from 98.6% to 100%, and efficiently detect attacks in real-time for (ICMP, TCP, UDP, HTTP and DNS) DDoS attacks.

关键词： Support vector machines Machine learning algorithms Euclidean distance Denial-of-service attack Real-time systems Entropy internet of things

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the Impact of Quantum computing on Security in Emerging Technologies 2021

The Impact of Quantum Computing on Security in Emerging Tech...

引用

the 5th international conference on Future Networks & distributed Systems

作者： Abdelrahman Abuarqoub Simak Abuarqoub Ahmad Alzu'bi Ammar Muthanna Cardiff School of Technologies Cardiff Metropolitan University UK Faculty of Engineering and Technology Liverpool John Moores University United Kingdom Department of Computer Science Jordan University of Science and Technology Jordan Department of Telecommunication Networks and Data Transmission The Bonch-Bruevich Saint-Petersburg State University of Telecommunications Russian Federation

ISBN: (纸本)9781450387347

Quantum computing is rapidly shifting from high-tech lab to mainstream commercial use in the next few years, representing the next breakthrough in modern ICT. It is motivated by quantum computer's ability to perform computational tasks with efficiencies that are not possible with classical computers. Quantum computing technology has a lasting potential impact on society and broad implications on many aspects of our lives. Although quantum computing has several advantages, it threatens the security of current cryptographic techniques. It is expected that quantum computers will be able to solve the key distribution problem and break every single cryptography and authentication algorithm based on asymmetric cryptography. New emerging technologies such as the internet of things, blockchain, autonomous vehicles, 5G, artificial intelligence and robotics all rely on cryptography for their secure operation. therefore, the realisation of quantum computing will pose significant challenges to the current progress and future development of these technologies. In this paper, the quantum technology preliminaries are discussed. the possible impact of quantum technologies on emerging technologies is investigated. Finally, some of the currently available quantum-safe cryptosystems devoted to protecting computer systems in the quantum era are discussed.

关键词： Security Challenges Quantum computing Asymmetric Cryptography Emerging Technologies

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Improving SMEs Knowledge and Performance With Cloud computing CSF Approach : Systematic Literature Review 5

Improving SMEs Knowledge and Performance With Cloud Computin...

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5th international conference on Information Management and technology (ICIMTech)

作者： Hartono, Indra Kusumadi Inayatulloh Alianto, Hendra Bina Nusantara Univ Informat Syst Dept Sch Informat Syst Jakarta 11480 Indonesia

ISBN: (纸本)9781728170718

Information technology in particular the internet has changed the company's business processes to improve their performance. the availability of the internet opens up opportunities for companies to get relatively inexpensive resources without space and time limits, one of which is the use of cloud computing to support the company's business processes. Various types of companies have used cloud computing to run their businesses, one of which is SMEs. this paper aims to find out the success factors for using cloud computing for SMEs. A systematic literature review was conducted on 45 journal articles to get the results. the inspected journal paper were available from 2008 to 2018 and displayed 14 success aspects for cloud computing for SMEs. the main factor is organizational support to implementation cloud computing. this research only talks about the use of service cloud computing in Small Medium Enterprise. It is expected that future research will discuss other issues related to the application of cloud computing in Small Medium Enterprises.

关键词： cloud computing SMEs SLR CSF

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Challenges in Scholarly Communication and Scientific Publication – Present Scenario and Opportunities through Blockchain Solutions 21

Challenges in Scholarly Communication and Scientific Publica...

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Proceedings of the 5th international conference on Future Networks and distributed Systems

作者： Eashwar Sivakumar Paras Chawla Geetha Ganesan Electronics and Communication Engineering Chandigarh University India Advanced Computing Research Society India

ISBN: (纸本)9781450387347

the internet is flooded with predatory, cloned and hijacked journals. Even the senior researchers fall pray to these dubious publications. Blockchain being transparent, decentralized and immutable in nature has great potential in scientific publication industry. We found that certain blockchain based frameworks for journal publication are being developed. In this paper we have listed the opportunities through blockchain technology so as to disrupt the scientific publication houses. We have also compared the existing blockchain based frameworks and open research problems to tackle limitations faced in traditional scholarly communication and scientific publication. Development in the area of consensus algorithm, adopting Management Principles such as Business Process Management (BPM) and Lean Six Sigma (LSS), Smart Contract, verifying the genuinity of publication, reviewer selection process are the identified problems that can help scientific publication industry to be sustainable.

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