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AAWAS: An Application and Workload-Aware Scheduling Technique for Efficient Task Allocation in Cloud computing Environments

AAWAS: An Application and Workload-Aware Scheduling Techniqu...

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Advancements and Key Challenges in Green Energy and computing (AKGEC), international conference on

作者： Vidhyasagar Bs M. Arvindhan J. Arunnehru H. Anwarbasha Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Amity School of Engineering & Technology Gwalior Madhya Pradesh India SRM Institute of Science and Technology Chennai India Rajalakshmi Institute of Technology Chennai India

ISBN: (数字)9798350390179

ISBN: (纸本)9798350390186

One interesting aspect of distributed systems is cloud computing. It offers its services on an as-needed, pay-per-use basis. Research challenges in cloud computing include the scheduling and balance of tasks. Scheduling tasks entails assigning them to available resources (Virtual Machines), whereas load balancing is spreading out the work over multiple available resources. We offer a job scheduling technique that takes into account anticipated demands on compute nodes. We begin by investigating the reasons for the disparity in workloads and the viability of redistributing computing resources. All of the complex simulations are run in clouds. The process consisted of two distinct parts. The simulation begins with a randomly generated workload. Second, we combine the workload prediction model with an application and workload-aware scheduling algorithm (AAWAS) [14]. We present a parallel job scheduling approach using computational node workload prediction AAWAS to simplify the AAWAS algorithm. Experimental results reveal that AAWA is superior to other algorithms in terms of minimizing makespan and optimizing resource utilization, and the proposed method is compared to FCFS, SJF, Min-Min, and EDF. To make Task scheduling in compute clouds faces various challenges due to the highly dynamic environment, such as availability, access policies, security, and reliability of computing resources. Furthermore, the collaborative nature of cloud computing projects on the internet adds complexity to task scheduling. From simulation results, it is evident that our proposed scheduler AAWAS outperforms A2C, DQN, and PPO across the board by 4.1%, 2.6%, and 3.4%, respectively. Because AAWS relies on policy for learning rather than Q-value, its superiority can be defended. Several environmental factors affect AAWAS and contribute to its consistent learning process and the high chance of accurate predictions. As a result, AAWASC may learn from experiences independently of target networks,

关键词： Cloud computing Protocols Scheduling algorithms Computational modeling Throughput Prediction algorithms Virtual machines Resource management Faces Load modeling

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A configuration analysis method of high-speed railway train-set equipment based on handle 2

A configuration analysis method of high-speed railway train-...

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2nd international conference on Artificial Intelligence and Computer Engineering, ICAICE 2021

作者： Sun, Peng Wang, Hui China Academy of Railway Sciences Institute of Computing Technology Beijing China

ISBN: (纸本)9781665421867

The industry identification analysis system is the primary technical problem in building the data acquisition capability of the railway internet of things, and the configuration analysis of complex equipment assets is the difficulty in application. According to the configuration analysis management requirements of complex equipment of the high-speed railway train-set, combined with the technical information management of the high-speed railway train-set, the corresponding handle structure of the high-speed railway train-set is given, and the distributed processing algorithm of configuration analysis of the high-speed railway train-set is designed. The high-speed analysis ability, stability and reliability of the system and method described in this paper are verified by experiments, which can meet the practical requirements of railway identification application innovation. © 2021 IEEE.

关键词： Data acquisition

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On the distributed DoS attacks targeting at the bottlenecked links: More Threatening DoS attacks than server targeting DoS attacks 21

On the distributed DoS attacks targeting at the bottlenecked...

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2nd international conference on computing, Networks and internet of Things, CNIOT 2021

作者： Akashi, Shigeo Tong, Yao Department of Information Sciences Faculty of Science and Technology Tokyo University of Science Chiba Prefecture Noda City Japan

ISBN: (纸本)9781450389693

The modern dynamic routing protocols are constructed so as to prevent any routing loops from being brought about spontaneously, because unnecessary circulation of packets on a certain network, whose destinations do not exist unnecessarily consumes the bandwidth which is assigned for the network. In the former half of this paper, we point out the fact that, if we apply dynamic routing together with static one simultaneously, another type of network traffic congestion, which resembles what is brought about by the routing loops, may happen spontaneously. In the latter half of this paper, we discuss the problem asking if this network traffic congestion can be brought about not only spontaneously but also intentionally. © 2021 Association for computing Machinery. All rights reserved.

关键词： Traffic congestion

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Research and Implementation of Secure Storage technology of Private Cloud Based on Hadoop

Research and Implementation of Secure Storage Technology of ...

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Networking, Communications and Information technology (NetCIT), international conference on

作者： Meirong Lin School of Information Engineering Hainan Vocational University of science and technology Haikou Hainan China

In recent years, with the rapid development of cloud computing industry, big data processing technology is also maturing. At the same time, the scale of domestic mobile internet market is constantly expanding, the number of users has exceeded 500 million, and it has brought a huge amount of mobile internet traffic data. Private cloud storage has become the best choice to solve the current enterprise security storage needs because of the unsafe factors such as data leakage, loss and storage instability in public cloud storage. It is an implementation of private cloud computing. Compared with public cloud, it has higher security and lower investment cost. From the current situation of mobile internet, on the one hand, the surge of mobile data traffic has brought huge operating pressure to operators, which requires them to invest more funds in network construction and upgrading. On the other hand, due to the growth of mobile data services, traditional voice messaging and other services have declined. The cloud storage system can provide massive storage capacity to solve the problem of big data storage in the smart grid. With the development of cloud computing technology, cloud security becomes more and more critical. In the cloud computing environment, users lose control over the data and computing placed in the cloud server, and are uncertain whether the data is protected and whether the computing task is executed correctly. Therefore, in the smart grid cloud storage system, the problem of data security is an urgent problem to be solved.

关键词： Computers Cloud computing distributed databases Surge protection Big Data Smart grids Servers

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A Critical Review of Detection and Prediction of Infectious Disease using IOT Sensors 2

A Critical Review of Detection and Prediction of Infectious ...

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2nd international conference on Electronics and Sustainable Communication Systems, ICESC 2021

作者： Meraj, Mohammad Alvi, Syed Ahad Murtaza Quasim, Mohammad Tabrez Haidar, Sk Wasim College of Applied Computer Sciences King Saud University Al-Muzahimiya Saudi Arabia College of Computing Information Technology University of Bisha Bisha Saudi Arabia Sultanate of Oman Oman

ISBN: (纸本)9781665428675

Detection and prediction of infectious disease is a very challenging task due to the lack of substantial evidence of the disease and its behaviours. The effective infection prevention mechanisms through IoT sensors have been explored in the various researches in recent times. Various researchers use the internet of Things (IoT) to collect real-time sensory information data for the detection and prediction of Infectious Disease. A group of sensors distributed in the workplace to detect or gathered data related to Infectious Disease is one of the major explorations of this paper. Sensors could collect the real-time data gathered in the cloud storage unit and further the user has to be intimated with the real scenario of data suggested. Behind this filtering and analytics process to execute on the gathered data and extract the data in form of user information. This paper explores the Flu, COVID-19, Zika, and H1N1, especially focus on COVID-19 as the recent pandemic. The technique as the Remote Excess of Experts thought IoT data is also the research investigation of this paper. © 2021 IEEE.

关键词： Diseases

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1D CNN Based Model for Detection of DDoS Attack

1D CNN Based Model for Detection of DDoS Attack

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Device Intelligence, computing and Communication Technologies, (DICCT), international conference on

作者： Padmavathy C Mahalakshmi A Vadivel R Rajat Kumawat Ritam Dutta Bhaskar Roy Nilanjan Dutta Computer Science and Engineering Sri Ramakrishna Engineering College Coimbatore India Computer Science and Engineering B.N.M Institute of Technology Bangalore India Computer Science and Engineering Poornima University Jaipur India Artificial Intelligence & Machine Learning Asansol Engineering College Asansol India Electronics & Comm. Engineering Asansol Engineering College Asansol India

ISBN: (数字)9798350372847

ISBN: (纸本)9798350372854

As the technology behind informatics systems has improved, the internet of Things (IoT) has grown in significance and application. IoT applications are becoming more popular as a result of the expansion of IoT enablers including smart watches, smart phones, security cameras, and smart sensors. Unfortunately, other issues have raised due to the unsecured nature of IoT devices. distributed Denial of Service (DDoS) assaults are one of the deadliest cyber-attacks as an example. The untrustworthiness of IoT systems causes a number of security issues. Protecting IoT networks from dispersed denial of service attacks has been the focus of several recent research and development efforts. The primary challenge in this area of study is creating a model that is responsive to different types of DDoS assaults while also being able to distinguish between malicious and benign traffic to prevent false positives. In this study, a Convolutional Neural Network with only one dimension is used. The suggested system is employed in both statistics and cognitive science, and it is based on the central nervous system in particular. They are modelled as mathematical functions that are structured to depict complicated interactions between inputs and outputs (dependent variables), and they are exemplified by the connectivity of brain systems from a variety of input variables to the output (dependent variables) We foresee three types of assaults in our article. All models are tested with precision, recall and F-score analysis. SVM achieved nearly 86% of precision, 95.15% of recall and 90.43% of F-score, where the projected model achieved 92.53% of precision, 97.17% of recall and 91.59% of F-score.

关键词： Support vector machines Computational modeling Brain modeling Mathematical models internet of Things Security Convolutional neural networks

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Lightweight Blockchain of Things (BCoT) Architecture for Enhanced Security: A Literature Review 2

Lightweight Blockchain of Things (BCoT) Architecture for Enh...

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2nd international conference on computing, Networking, Telecommunications and Engineering Sciences Applications, CoNTESA 2021

作者： Liu, Aofan Khatun, Mst. Surma Liu, Hanting Miraz, Mahdi H. Xiamen University Malaysia Selangor Malaysia Russian State Academy Moscow Russia

ISBN: (纸本)9781665436106

Both the internet of things (IoT) and distributed ledger technology (DLT), more commonly known as the blockchain, are two popular emerging technologies of this era. While blockchain offers strengthened security, along with other benefits, it requires peer-to-peer (P2P) nodes for its consensus process. On the contrary, IoT ecosystems inherently consist of many P2P nodes but it is highly critiqued for its lack of security measures. Therefore, the fusion of these complementary duos, known as the blockchain of things (BCoT), has become a recent research trend. While the fit is good and the benefits such consolidation can offer are obvious, a lot of challenges are yet to be addressed. Therefore, we have conducted a comprehensive literature review, covering 33 research articles, spanning over the last six years (2016-2021), to report the state-of-the-art research in this domain. We have synthesised the existing literature by comparing, contrasting, resembling as well as critically evaluating them and thus, deduced the current challenges and future research directions, particularly with regards to lightweightness. © 2021 IEEE.

关键词： internet of things

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Adaptive Response technology for Threats in Power IoT Terminals Based on Reinforcement Learning

Adaptive Response Technology for Threats in Power IoT Termin...

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Mechatronics, IoT and Industrial Informatics (ICMIII), international conference on

作者： Changhua Sun Xin Sun Yifeng Wang Hua Dai Futai Zou Mingyi Huang State Grid Zhejiang Electric Power Co. Ltd. Research Institute Hangzhou China Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350386639

ISBN: (纸本)9798350386646

The power internet of Things (IoT) terminal is an integral part of the power system and faces a complex network attack scenario. When the power system detects a network attack, it needs to generate disposal scripts to respond to the attack. Traditional network threat response technologies struggle to handle new types of network attacks, so introducing artificial intelligence algorithms to generate disposal scripts is necessary to enhance response success rates. However, power IoT terminals typically have limited computing resources and struggle to execute artificial intelligence algorithms. To address this issue, this paper proposes a power IoT threat response technology based on reinforcement learning, employing a client-server architecture. Here, the client represents the power IoT terminal requiring threat response, while the server functions as the threat disposal center within the power system. Upon receiving threat information, the threat disposal center initially processes it into the necessary response actions. Subsequently, it invokes the reinforcement learning algorithm to produce the operation sequence required by the client to respond and generates distinct disposal scripts tailored to the system environment of each power IoT terminal. These scripts are then distributed to the clients for response. After executing the disposal script, the clients compute the reinforcement learning reward value based on execution results and transmit it back to the server. The server adjusts the response action sequence based on the reward value received from the client and regenerates the disposal script. This iterative process continues until the client successfully completes the threat response. Experiments demonstrate that the power IoT threat response architecture proposed in this paper achieved a 100% response success rate in two threat response scenarios, conclusively showcasing its effectiveness in completing power IoT threat response tasks.

关键词： Mechatronics Reinforcement learning Computer architecture Malware Power systems Servers internet of Things

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Construction of Agricultural Economic Data Management and Service Platform Based on Improved Genetic Algorithm

Construction of Agricultural Economic Data Management and Se...

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Networking, Communications and Information technology (NetCIT), international conference on

作者： Qixiu Li Huaihua Polytechnic College Huaihua Hunan China

As a large agricultural country, agriculture is the foundation of China's national economy. Agricultural informatization construction is a major measure to strengthen the basic position of agriculture and promote the new agricultural scientific and technological revolution. It is of great significance to develop agricultural economy and promote the construction of a new socialist countryside. With the rise and continuous improvement of cloud computing, it has brought new inspiration to the construction of agricultural informatization. Cloud computing is the latest network information technology at present. It creates a new model of serving computing resources, storage resources and information resources under the condition of rapid network development, so that information can spread at a high speed, so that farmers can get better agricultural technology and more agricultural information resources in the shortest time, so as to greatly improve the agricultural economy. In recent years, the new cloud computing technology provides a new method and feeling for the construction of agricultural economic management information service platform. In order to realize the rapid acquisition of a variety of information resources and the sharing of information data, and improve the service level and service quality of agricultural information, taking the new IT resource model “cloud computing” as the starting point, computing and big data are distributed on computers all over the country. People can easily obtain applications, data and resources through mobile phones, computers and other services. Relying on cloud computing technology, the agricultural economic management information service platform can not only give full play to the township internet and call rate with high coverage in China, but also realize unlimited capacity storage, fast and high-speed operation and fast and efficient information transmission that cannot be realized by traditional technology without pressur

关键词： Economics Computers Cloud computing Information resources Computational modeling Information services Production

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A Combination Techniques of Intrusion Prevention and Detection for Cloud computing 2

A Combination Techniques of Intrusion Prevention and Detecti...

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2nd international conference of Modern Applications on Information and Communication technology, ICMAICT 2020

作者： Alturfi, Sabah M. Muhsen, Dena Kadhim Mohammed, Mohammed A. Aziz, Israa T. Aljshamee, Mustafa University of Kerbala Iraq University of Technology Iraq University of Mosul Iraq Al-Tuff University College Iraq

Cloud computing provides scalable, on-demand, and highly available computing services over the internet to both the public and organizations on a pay-per-use basis. It provides a variety of services such as networking, storage space, and applications. The key issue for cloud computing is ensuring the confidentiality and privacy of cloud resources and data. Enticing the user to purchase cloud services requires their trust which cannot be guaranteed unless the infrastructure is effectively protected because attacks at this level will threaten the whole system. To this end, we propose the Integrated Intrusion Prevention and Detection System (IIPDS) to prevent and detect different types of attacks to the infrastructure level of the cloud system. The proposed design uses Trusted Third Party (TTP) services and SSL/TLS protocols as intrusion prevention methods to secure the communication between the cloud provider and the user. It also uses multiple Intrusion Detection Systems (IDS) distributed over multiple cloud regions. The IDS system is capable of detecting known and unknown attacks using anomaly and rule-based (signature) intrusion detection techniques. The simulation results proved the efficiency of the system in detecting a wide range of attacks with low false positive alerts and low computational overhead. © Published under licence by IOP Publishing Ltd.

关键词： Intrusion detection

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