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the Influence-Maximizing Node Selection Algorithm Based on Local Isolated Centrality in Large-scale networks Implemented by distributed Graph computing

The Influence-Maximizing Node Selection Algorithm Based on L...

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IEEE international conference on High Performance computing and Communications (HPCC)

作者： Piaoyang Chen Rong Lei Mingsen Deng School of Information Guizhou University of Finance and Economics Guiyang China

Identifying influence-maximizing (IM) nodes is an effective strategy for designing efficient communication networks or contain the spreading of information for rumors and epidemics with limited budgets. With the growing of the sizes of the social networks, finding solutions to the problem of intfuence − maximizing vertices becomes more and more challenging. Tra-ditionally, the number of users finally affected was the focus. However, the information diffusion speed was becoming a bottle-neck of IM problems. In this paper, we proposed a locality-aware vertex selection strategy based on local isolation centrality (LIC), while the information diffusion experiments used the Independent Cascade (IC) model. the computing scheme was implemented by a distributed graph computing framework. the superiority of the LIC algorithm was confirmed by evaluated on three real-world datasets. It was indistinguishable from algorithms such as K-shell, H-index, degree centrality (DC), local centrality (LC), and VoteRank at the diffusion cascade scale. But it showed better superiority in diffusion speed. More importantly, by comparing LIC with the VoteRank algorithm, which was the closest algorithm on diffusion speed to that of LIC, the huge advantage of the LIC algorithm in terms of time cost was found. We believe that the locality-aware LIC algorithm was more suitable for the influence-maximization problem in very large-scale social networks.

关键词： Epidemics Costs Social networking (online) Computational modeling Communication networks Integrated circuit modeling

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Review on Zero Trust Architecture Apply In Enterprise Next Generation Firewall

Review on Zero Trust Architecture Apply In Enterprise Next G...

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international conference on Information Technology (INCIT)

作者： thana Sarkorn Krishna Chimmanee College of Digital Innovation Technology Rangsit University Thailand

ISBN: (数字)9798350366303

ISBN: (纸本)9798350366310

the modern cybersecurity threat landscape requires a paradigm change in network defense strategies. Zero Trust Architecture (ZTA), that significant difference from traditional security models, by limiting the total trust tacit within an organization’s network. this paper presents a literature review on the comprehensive application of Zero Trust principles within Next Generation Firewall (NGFW) devices by integrating the improved ZTA and NGFW to provide durable security controls thorough and continuously updated. this is necessary to mitigate and prevent the complexity of cyber threats. the article will examine key elements of the ZTA, including user authentication. Subdivision and implementation of least privileged access within existing NGFW devices are also discussed. Case studies and current progress are discussed to demonstrate the practical benefits and challenges of this integration. the results show that integrating the ZTA architecture with NGFW devices not only strengthens security measures but also enhances security. It also provides a scalable and adaptable solution for modern organizations facing complex and persistent cyber threats.

关键词： Industries Technological innovation Limiting Firewalls (computing) Reviews Organizations Market research Zero Trust Information technology Next generation networking

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Compute and Network Aware VM Scheduling using Reinforcement Learning in Cloud

Compute and Network Aware VM Scheduling using Reinforcement ...

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international conference for Convergence of Technology (I2CT)

作者： Suyash Kamat Surabhi Naik Sagar Kanamadi Shrinidhi Alur Narayan D G Somashekar Patil KLE Technological University Hubballi India

Cloud computing has been used widely to provide a variety of services which include servers, databases, storage, networking, software, analytics, and intelligence. Scalability is increased and upfront IT infrastructure costs are lowered. In some scenarios, VMs are used extensively for an extended period of time which leads to higher infrastructure costs. Effective virtual machine (VM) management is necessary to make the most out of cloud infrastructures in terms of performance and cost. For scheduling VM effectively we have considered network and compute parameters. Machine learning algorithms are used to predict the best host for the VM placement. We have used reinforcement learning which further uses reward and penalty methods to schedule the VMs, and a methodology is proposed that consists of modules such as Scheduling Module, Host Detection Module, Learning Agent Module, and Consolidation Module. Resource utilization needs to be predicted in order for the system to learn and perform better. the reinforcement-learning-based and ARIMA-based Models are used for better understanding and result analysis. Further, on the basis of three parameters service level agreement violations, energy consumption, and the number of hosts shutdowns, the Reinforcement Learning, and the ARIMA-based Model are compared. the presented Reinforcement Learning Model, which integrates the Enhanced Max-Min algorithm to schedule the VMs and host load prediction, provides the best results by lowering energy usage and service level agreement violations.

关键词： Cloud computing Schedules Costs Processor scheduling Reinforcement learning Minimax techniques Predictive models

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A Community-Driven Approach to Democratize Access to Satellite Ground Stations 21

A Community-Driven Approach to Democratize Access to Satelli...

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27th ACM Annual international conference on Mobile computing and networking (MobiCom)

作者： Singh, Vaibhav Prabhakara, Akarsh Zhang, Diana Yagan, Osman Kumar, Swarun Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9781450383424

Should you decide to launch a nano-satellite today in Low-Earth Orbit (LEO), the cost of renting ground station communication infrastructure is likely to significantly exceed your launch costs. While space launch costs have lowered significantly with innovative launch vehicles, private players, and smaller payloads, access to ground infrastructure remains a luxury. this is especially true for smaller LEO satellites that are only visible at any location for a few tens of minutes a day and whose signals are extremely weak, necessitating bulky and expensive ground station infrastructure. In this paper, we present a community-driven distributed reception paradigm for LEO satellite signals where signals received on many tiny handheld receivers (not necessarily deployed on rooftops but also indoors) are coherently combined to recover the desired signal. this is made possible by employing new synchronization and receiver orientation techniques that study satellite trajectories and leverage the presence of other ambient signals. We compare our results with a large commercial receiver deployed on a rooftop and show a 8 dB SNR increase both indoors and outdoors using 8 receivers, costing $38 per RF frontend.

关键词： LEO Satellites Ground stations Synchronization Coherent Combination low-cost distributed Systems

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Hybrid Multiple Cryptography for Data Encryption

Hybrid Multiple Cryptography for Data Encryption

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international conference on Communication and Electronics Systems (ICCES)

作者： M. Anuradha Sathyapriya Loganathan G. Suseela Mercy Paul Selvan M. Nalini Chitra Devi D Dept of CSE S.A.Engineering College Computing Technologies Faculty of Engineering and Technology SRM Institute of Science and Technology Dept of Networking and Communications School of Computing College of Engineering and Technology SRM Institute of Science and Technology CSE Department Sathyabama Institute of Science & Technology Dept of CSE S.A. Engineering College

Since the information technology revolution, cryptography has been essential for protecting sensitive information and communication. A plethora of algorithms have been developed to safeguard data and protect data integrity, with the goal of improving data security and protection. Modern cryptography is based on a variety of encryption techniques, namely Hybrid cryptography and multiple cryptography. Hybrid cryptography combines asymmetric key and symmetric key encryption to combine the strengths of both. Multiple cryptography is the process of encrypting a previously encrypted message one or more times, each time using the same or a different symmetric or asymmetric algorithm. the study proposes an approach that seeks to incorporate both hybrid and multiple cryptography as a way to combine all of their benefits while also minimizing the drawbacks that each technique has on its own to provide an additional layer of security. Although these techniques have all contributed to data protection, not all of them have been successful in providing a high level of security as they have shown a propensity for being targeted and exploited over time. this research project implements a cryptosystem based on Hybrid Multiple Cryptography (HMC) which is a novel scheme for data encryption that offers a greater level of security for sending data in an Android messaging application, in order to showcase the system's security capabilities in real time.

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A Comparative Analysis on three Duplication Elements in Copy-Move Forgery using PatchMatch-Based Detection Method

A Comparative Analysis on Three Duplication Elements in Copy...

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international conference on Software Engineering and Computer Systems (ICSECS)

作者： Nur Izzati Nor Azaimi Nor Bakiah Abd Warif Nor-Syahidatul N Ismail Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Johor Malaysia Faculty of Computer Science and Information Technology Centre for Information Security Research Universiti Tun Hussein Onn Malaysia Johor Malaysia Department of Computer System and Networking Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah Pekan Pahang Malaysia

Image forgery is the alteration of a digital image to hide some of the important and useful information. Copy-move forgery (CMF) is one of the most difficult to detect because the copied part of the image has the same characteristics as the original image. Most of the existing datasets only highlight additional attacks in the copied part. Since there are no categories of duplication elements in the datasets, this research analyzed three categories of duplication elements in CMF which are animals, food and non-living things using DEFACTO and CoMo3Dataset. the analysis is performed on PatchMatch-based detection method and the results show that the method able to maintain at least 83% for all duplication elements in both DEFACTO and CoMo3Dataset. Furthermore, the method is able to detect a minimum 92% score for the food category in both datasets.

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the Effect of Plastic Bag Ban Policy towards Waste Complaints in Jakarta through JAKI and Qlue 8

The Effect of Plastic Bag Ban Policy towards Waste Complaint...

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8th international conference on ICT for Smart Society, ICISS 2021

作者： Feliren, Vicky Nugraha, Yudhistira Nasution, Bahrul Ilmi Febria Finola, Clarissa Kanggrawan, Juan I. Suherman, Alex L. Jakarta Smart City Department of Communication Informatics and Statistics Jakarta Indonesia Jakarta Smart City School of Computing Telkom University Bandung Jakarta Indonesia Directorate of Research and Community Service Telkom University Bandung Indonesia

ISBN: (纸本)9781665416979

Plastic bag ban policy has been implemented in Jakarta since July 1st, 2020. However, it is still unclear the impact of this policy on Jakarta to reduce waste. the public complaint can be used as a proxy to see how the public responds to the waste reports distributed in Jakarta. this research aims to look at the plastic bag ban policy's significance towards waste complaints through two applications that citizens used to report, JAKI and Qlue. In this study, non-parametric hypothesis testing was performed since the data are not normally distributed. the result shows that North Jakarta did not show any significant differences in the waste reports after the plastic bag ban policy. On the other hand, the rest of the districts show a considerable difference. © 2021 IEEE.

关键词： Normal distribution

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Sentiment Analysis on Indonesia-English Code-Mixed Data

Sentiment Analysis on Indonesia-English Code-Mixed Data

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international conference for Convergence of Technology (I2CT)

作者： Hilal Ramadhan Utomo Ade Romadhony School of Computing Telkom University Bandung Indonesia

Social media users nowadays tend to use code-mixed language to express their opinion. the users of social media has exponentially risen in some countries like Indonesia, it has given rise to large volumes of code-mixed data, in which users use more than one language in a single text. Data with code-mixed is often noisy and most importantly, the monolingual model usually does not work well on it. this has been a challenge for Natural Language Processing (NLP) for processing and analyzing the data. In this work, we conduct experiment of sentiment analysis on English-Indonesian code-mixed data. the approach that is by utilizing a multilingual pre-trained model, mBERT. By analyzing the sentiment analysis models’ predictions, we may assess how effectively the model can adjust to the implicit noises inherent in code-mixed data. the classification model’s performance was tested using batch size and epochs parameters to discover and obtain the highest accuracy. the experimental result shows that the highest accuracy we obtained from the mBERT model that is trained with our dataset obtained was 76%, with 16 batch size and epochs used 7.

关键词： Sentiment analysis Analytical models Social networking (online) Sociology Predictive models Market research Data models

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DRL Model for distributed Agent-based IoT on Multi-Access Edge computing for Accident Forecast

DRL Model for Distributed Agent-based IoT on Multi-Access Ed...

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Big Data, Cloud computing, Data Science & Engineering (BCD)

作者： Jongho Seol Jongyeop Kim Abhilash Kancharla Department of Information Technology Middle Georgia State University Macon GA U.S.A Department of Information Technology Georgia Southern University Statesboro GA U.S.A Department of Computer Science The University of Tampa Tampa FL U.S.A

this paper introduces a state-of-the-art Deep Reinforcement Learning (DRL) model designed for IoT devices in Multi-Access Edge computing (MEC), with a focus on urban accident prediction. the Edge server serves as a central hub, collecting reinforcement learning data from distributed IoT devices and distributing custom deep learning models for reinforcement learning back to these devices, all within the network. the study also addresses privacy concerns by combining Differential Privacy (DP) with Federated Learning (FL) in DRL within MEC environments. DRL combines deep learning and reinforcement learning principles, enabling wireless IoT devices to optimize actions for maximum rewards in their environments. the surge in IoT devices in networks not only generates massive data but also raises privacy concerns. Differential Privacy, rooted in Google's FL technology, safeguards data privacy. IoT devices utilize DRL and FL to improve learning efficiency and uphold privacy policies. the paper outlines how wireless IoT devices accumulate traceable data tables through reinforcement learning within a Grid-world framework. Within the MEC architecture, Edge servers efficiently execute deep neural networks tailored for reinforcement learning data and distribute results to other IoT devices upon request. this paper presents a tailored DRL model for MEC and a federated DRL framework for maintaining differential privacy while handling shared data generated through deep learning in Edge servers.

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Direct GPU Compilation and Execution for Host Applications with OpenMP Parallelism 8

Direct GPU Compilation and Execution for Host Applications w...

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8th IEEE/ACM Annual Workshop on the LLVM Compiler Infrastructure in HPC, LLVM-HPC 2022

作者： Tian, Shilei Huber, Joseph Parasyris, Konstantinos Chapman, Barbara Doerfert, Johannes Stony Brook University Department of Computer Science Stony Brook United States Advanced Micro Devices Austin United States Lawrence Livermore National Laboratory Center for Applied Scientific Computing Livermore United States

ISBN: (纸本)9781665475587

Currently, offloading to accelerators requires users to identify which regions are to be executed on the device, what memory needs to be transferred, and how synchronization is to be resolved. On top of these manual tasks, many standard (C/C++ library) functions, such as file I/O or memory manipulation, cannot be directly executed on the device and need to be worked around by the user explicitly. this makes it challenging to port programs in the first place and hinders developers from testing features on the GPU and within the GPU compilation pipeline. Existing tests and test suites for the host are effectively unusable for accelerators and need to be manually ported to provide the same benefits for the devices as they do on the host. In this paper, we propose a direct GPU compilation scheme that leverages the portable target offloading interface provided by LLVM/OpenMP. Utilizing this infrastructure allows us to compile an existing host application for the GPU and execute it there with only a minimal wrapper layer for the user code, command line arguments, and a compiler provided GPU implementation of C/C++ standard library functions. the C/C++ library functions are partially implemented for direct device execution and otherwise fallback to remote procedure call (RPC) to call host functions transparently. Our proposed prototype will allow users to quickly compile for, and test on, the GPU without explicitly handling kernel launches, data mapping, or host-device synchronization. We evaluate our implementation using three proxy applications with host OpenMP parallelism and three microbenchmarks to test the correctness of our prototype GPU compilation. © 2022 IEEE.

关键词： Graphics processing unit

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