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distributed Novelty Detection at the Edge for IoT Network Security 21st

Distributed Novelty Detection at the Edge for IoT Network Se...

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21st international conference on Computational Science and Its applications (ICCSA)

作者： Puhl, Luis Cassales, Guilherme Weigert Guardia, Helio Crestana Senger, Hermes Univ Fed Sao Carlos Sao Carlos Brazil

ISBN: (纸本)9783030869700;9783030869694

The ongoing implementation of the Internet of Things (IoT) is sharply increasing the number and variety of small devices on edge networks. Likewise, the attack opportunities for hostile agents also increases, requiring more effort from network administrators and strategies to detect and react to those threats. For a network security system to operate in the context of edge and IoT, it has to comply with processing, storage, and energy requirements alongside traditional requirements for stream and network analysis like accuracy and scalability. Using a previously defined architecture (IDSA-IoT), we address the construction and evaluation of a support mechanism for distributed Network Intrusion Detection Systems based on the MINAS Data Stream Novelty Detection algorithm. We discuss the algorithm steps, how it can be deployed in a distributed environment, the impacts on the accuracy and evaluate performance and scalability using a cluster of constrained devices commonly found in IoT scenarios. The obtained results show a negligible accuracy loss in the distributed version but also a small reduction in the execution time using low profile devices. Although not efficient, the parallel version showed to be viable as the proposed granularity provides equivalent accuracy and viable response times.

关键词： Novelty detection Intrusion detection Data streams distributed system Edge computing Internet of Things

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Profile-Guided parallel Task Extraction and Execution for Domain Specific Heterogeneous SoC

Profile-Guided Parallel Task Extraction and Execution for Do...

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IEEE international conference on Big Data and Cloud Computing (BdCloud)

作者： Liangliang Chang Joshua Mack Benjamin Willis Xing Chen John Brunhaver Ali Akoglu Chaitali Chakrabarti The School of Electrical Computer and Energy Engineering Arizona State University USA Electrical and Computer Engineering Department The University of Arizona USA

In this study, we introduce a methodology for automatically transforming user applications in the radar and communication domain written in $\boldsymbol{\mathrm{C}/\mathrm{C}++}$ based on dynamic profiling to a parallel representation targeted for a heterogeneous SoC. We present our approach for instrumenting the user application binary during the compilation process with barrier synchronization primitives that enable runtime system schedule and execute independent tasks concurrently over the available compute resources. We demonstrate the capabilities of our integrated compile time and runtime flow through task-level parallel and functionally correct execution of real-life applications. We perform validation of our integrated system by executing four distinct applications each carrying various degrees of task level parallelism over the Xeon-based multi-core homogeneous processor. We use the proposed compilation and code transformation methodology to re-target each application for execution on a heterogeneous SoC composed of three ARM cores and one FFT accelerator that is emulated on the Xilinx Zynq Ultra $\mathbf{Scale}+$ platform. We demonstrate our runtime's ability to process application binary, dispatch independent tasks over the available compute resources of the emulated SoC on the Zynq FPGA based on three different scheduling heuristics. Finally we demonstrate execution of each application individually with task level parallelism on the Zynq FPGA and execution of workload scenarios composed of multiple instances of the same application as well as mixture of two distinct applications to demonstrate ability to realize both application and task level parallel execution. Our integrated approach offers a path forward for application developers to take full advantage of the target SoC without requiring users to become hardware and parallel programming experts.

关键词： Schedules Runtime Processor scheduling parallel programming parallel processing Hardware Radar applications

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Cognitive Twins for Predictive Maintenance and Security in IoT Software Systems

Cognitive Twins for Predictive Maintenance and Security in I...

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Mobile Networks and Wireless Communications (ICMNWC), IEEE international conference on

作者： B. Venkata Swamy Pareshwar Prasad Barmola Senthil Thangavel S. Kaliappan Hardik Patel Girish Abhyankar Department of Chemistry B V Raju Institute of Technology Medak India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun India Distributed Systems Cloud Solutions & Machine Learning Expert Paypal Inc California USA Division of Research and Development Lovely Professional University Phagwara India Department of Electronics & Communication Engineering Faculty of Engineering and Technology Parul institute of Engineering and Technology Parul University Post Limda India Faculty of Law Symbiosis Law School Symbiosis International (Deemed University) Pune India

ISBN: (数字)9798331528348

ISBN: (纸本)9798331528355

The increasing complexity and interconnectedness of Internet of Things (IoT) software systems necessitate the development of intelligent solutions for predictive maintenance and security. Conventional techniques often fail to provide real-time insights and proactive responses due to the diverse and dynamic nature of IoT environments. To address these challenges, cognitive technologies offer promising avenues for enhancing the operational efficiency and security of IoT networks. This paper introduces Cognitive Twins, an AI-driven framework designed to optimize predictive maintenance and strengthen security in IoT software systems. Cognitive Twins leverage advanced machine learning models and real-time data streams to create dynamic digital replicas of IoT devices and software components. The framework employs a combination of deep learning-based anomaly detection, reinforcement learning for proactive maintenance scheduling, and natural language processing (NLP) for automated security log analysis. By continuously learning from device interactions and evolving threat patterns, Cognitive Twins predict potential failures and detect security threats before they occur, enabling real-time decision-making and automated responses. Cognitive Twins were evaluated on a large-scale IoT network, consisting of 500 nodes across multiple application domains. The framework achieved a predictive maintenance accuracy of 96.8%, reducing downtime by 35% compared to traditional models. In security applications, Cognitive Twins identified cyber threats with a detection rate of 98.3%, lowering the false positive rate to 1.5%.

关键词： Biological system modeling Decision making Reinforcement learning Software systems Real-time systems Natural language processing Maintenance Internet of Things Security Predictive maintenance

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Empowering Smart Homes with Fog Computing for IoT Connectivity

Empowering Smart Homes with Fog Computing for IoT Connectivi...

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Decision Aid Sciences and Application (DASA), international conference on

作者： Amjed Abbas Ahmed Ali Hamza Najim Ali Jafer Mahdi Khattab M. Ali Alheeti Nurhizam Safie Mohd Satar Aisha Hassan Abdallah Hashim Faculty of Information Science and Technology Center for Cyber Security Universiti Kebangsaan Malaysia Bangi Malaysia Department of Computer Techniques Engineering Imam AIKadhum College (IKC) Baghdad Iraq Department of Computer Technical Engineering Imam Al-Kadhum College (IKC) Al-Diwaniyah Iraq Department of Scientific Affairs AI-Zahraa University for Women Bangi Malaysia Computer Networking Systems Department College of Computer and Information Technology University of Anbar Anbar Iraq Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia (UKM) Bangi Malaysia Department of Electrical and Computer Engineering Faculty of Engineering International Islamic University Malaysia Selangor Malaysia

ISBN: (数字)9798350369106

ISBN: (纸本)9798350369113

Innovative grid technology leverages Information and Communication Technology (ICT) to enhance energy efficiency and mitigate losses. This paper introduces a “novel three-tier hierarchical framework for smart homes within the Internet of Things (IoT)” ecosystem, addressing the current shortage of intelligent solutions that underutilize IoT advantages. Our framework's primary objective is to elevate smart homes to the microgrid level, enabling the seamless integration from the microgrid's renewable distributed energy sources and attaining maximum energy efficiency. In addition to traditional data processing, we propose the application of fog computing in smart homes. Through a rigorous simulation using real smart meter datasets, our study demonstrates that fog computing, mainly when using predictive filtering, may drastically cut down on the amount of data being sent and the load on the home's network. This innovation holds immense potential for revolutionizing energy management and resource allocation in the context of smart homes, thus contributing to a sustainable and efficient future. This research represents a critical step towards harnessing the power of IoT and fog computing in smart grids and homes, offering a promising path towards more intelligent, eco-friendly, and energy-efficient living spaces.

关键词： Renewable energy sources Smart homes Microgrids Data processing Energy efficiency Smart grids Information and communication technology Internet of Things Optimization Edge computing

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Real-Time Task Scheduling and Resource Scheduling in Fog Computing using Deep Learning techniques

Real-Time Task Scheduling and Resource Scheduling in Fog Com...

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distributed Computing and Electrical Circuits and Electronics (ICDCECE), IEEE international conference on

作者： Vivek Ranjan Lalit Sharma Department of CS Noida Institute of Engineering and Technology Greater Noida India Department of Computer Science and Engineering Galgotias University Greater Noida India

Cloud capabilities may now be accessed from the network's edge thanks to fog computing. In order to fulfill the needs of organizations that have particularly high standards for the quality of the services they provide, it is essential to choose the most suitable site for the execution of applications. So, a cloud service has to have a dependable task scheduling system in order to establish in which geographic zone a certain piece of information may be put into action. We provide two different schedulers that are able to maximize work scheduling by using the resources of cloud computing and fog computing respectively. Both planners are grounded on nonlinear mathematical programming as their primary methodology. When deciding which processors should be assigned a certain work, the schedulers do not use any rules that have already been established; rather, they take into consideration a range of characteristics, such as availability and performance, when making their choices. The recommended algorithms usually perform much better than the scheduling problem that are already in use, such as the Randomised and Round Robins approaches, without sacrificing the quality of the service provided, as shown by the numerical solution. This research aims to enhance the total effectiveness of execution of tasks in IoT systems by consciously selecting certain real-time activities to carry out at the fog layer. This is done with the intention of increasing overall efficiency. We present a way for scheduling activities in a cloud-fog computing environment that takes use of fuzzy logic to split up work between the cloud and fog layers. This approach can be found in our paper "A Technique for Creating Schedules in a Cloud-Fog Computing Environment. The approach selects appropriate processing units to carry out the designated tasks in the fog nodes that include homogeneous devices, taking into consideration the requirements of the job (such as compute, storage, and bandwidth), as well as

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Towards Agent-based Simulation of the parallel Trading Market of Pharmaceuticals

Towards Agent-based Simulation of the Parallel Trading Marke...

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IEEE international conference on Big Data and Cloud Computing (BdCloud)

作者： Ruhollah Jamali Sanja Lazarova-Molnar The Maersk Mc-Kinney Moller Institute University of Southern Denmark Odense Denmark Institute AIFB Karlsruhe Institute of Technology Karlsruhe Germany

Pharmaceutical parallel trade is a legal trade in European countries, where traders can buy medicinal products in one country and sell them in other countries to make a profit. In the pharmaceutical parallel trade market, players such as manufacturers, wholesalers, parallel traders, pharmacies, and hospitals are involved. Studying and analyzing this market is of significant interest to economists and players involved. Agent-based modeling offers a robust algorithmic framework to analyze macroeconomic phenomena through micro-founded models. As an initial step in using agent-based modeling for the parallel trade of pharmaceuticals, we consider a simplified pharmaceutical trading market inspired by available game theory models. In this paper, we developed and elaborated the implementation of an agent-based model for the pharmaceutical trade market and employed it to run multiple scenarios that are impossible to analyze through game-theoretic models. Subsequently, we demonstrated how an agent-based model could be utilized to analyze the market from an economic perspective and how players in this market can recruit this model in their business decisions.

关键词： Analytical models Law Hospitals Biological system modeling Europe Agent-based modeling Macroeconomics

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DROAllocator: A Dynamic Resource-Aware Operator Allocation Framework in distributed Streaming processing 17th

DROAllocator: A Dynamic Resource-Aware Operator Allocation ...

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17th IFIP WG 10.3 international conference on Network and parallel Computing, NPC 2020

作者： Liu, Fan Jin, Zongze Mu, Weimin Zhu, Weilin Zhang, Yun Wang, Weiping Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783030794774

With the rapid development of Internet services and the Internet of Things (IoT), many studies focus on operator allocation to enhance the DSPAs’ (data stream processing applications) performance and resource utilization. However, the existing approaches ignore the dynamic changes of the node resources to allocate the operator instances to guarantee the performance, which increasing the number of migration leads to the waste of resources and the instability. To address these issues, we propose a framework named DROAllocator to select the appropriate nodes to allocate the operator instances. By capturing the change tendency of the node resources and the operator performance, our allocation mechanism decreases the number of migration to enhance the performance. The experimental results show the DROAllocator not only decrease the number of migrations to allocate the operator instances to ensure the end-to-end throughput and the latency, but also enhance the resource utilization. © 2021, IFIP international Federation for Information processing.

关键词： Internet of things

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Comparative analysis of different symmetric encryption techniques based on computation time 6

Comparative analysis of different symmetric encryption techn...

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6th international conference on parallel, distributed and Grid Computing, PDGC 2020

作者： Agnihotri, Nishant Sharma, Aman Kumar Himachal Pradesh University Computer Science Department Shimla India

ISBN: (纸本)9781728171326

Lately the trend of the internet is taking a front seat for different applications. Organizations are collecting and processing and then sharing the data using the internet. Sharing using public network will invite various security lapses in the data. Security will remain the maj or thrust in the area for providing enough level of security for the data. Encryption is the best way to provide security for the data. There are two different types of approaches for ensuring data security. These techniques are symmetric and asymmetric. The symmetric technique includes different approaches with variation in the time and space complexity. In this research paper five different techniques of the symmetric approaches are compared for three different length strings. AES is the best performing in all the three cases. The time comparison for the AES with different techniques is comparatively better than the other four techniques like IDEA, RC6, Two Fish, MARS. © 2020 IEEE.

关键词： Fish

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Acceleration of Radiofrequency Ablation Process for Liver Cancer Using GPU 28

Acceleration of Radiofrequency Ablation Process for Liver Ca...

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28th Euromicro international conference on parallel, distributed and Network-Based processing (PDP)

作者： Schepke, Claudio Miletto, Marcelo Cogo Fed Univ Pampa UNIPAMPA Lab Estudos Avancados LEA Campus Alegrete BR-97546550 Alegrete Brazil Fed Univ Rio Grande Sul UFRGS Grp Proc Paralelo & Distribuido GPPD Campus Vale BR-91509900 Porto Alegre RS Brazil

ISBN: (纸本)9781728165820

Computational simulation is a technique used in several research areas. In medicine, the Radiofrequency Ablation Finite Element Method (RAFEM) application was developed to simulate the RadioFrequency Ablation (RFA) process, which is a medical procedure to treat hepatic cancer. This application presents a high computational time to perform a simulation, taking up to 20 hours for simulation while the RFA procedure itself lasts from four to six minutes. Some efforts have already been carried out to obtain better performance for the application. However, none of them considered the use of GPUs, which is an architecture that can be used to accelerate finite element method applications. This work aims to propose a parallelization approach to explore ways to obtain better performance for the application through the use of GPUs to reduce the execution time under a few minutes. We adopted an iterative development process to coordinate and to generate parallel versions of the code. Through this process allied to the use of GPU-accelerated code libraries, it was possible to create different versions of the application, adding improvements to each one. The results obtained with the best version showed a reduction of the computation time by up to 18 times. Therefore, this improvement makes the use of RAFEM application more feasible in health treatment by reducing the waiting time for the results.

关键词： Graphics processing unit

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parallel Deployment of VNFs in Service Function Chain: Benefit or Not?

Parallel Deployment of VNFs in Service Function Chain: Benef...

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IEEE international conference on Big Data and Cloud Computing (BdCloud)

作者： Kaiwen Ning Hao Wang Zhiheng Zhang Zhou Xu Xiaowei Shu School of Software Engineering Dalian University of Technology China

Network Function Virtualization (NFV) technology facilitates flexible and fast service provisioning by deploying network functions in wished positions and chaining order as Service Function Chain (SFC). Empirically, if the processing inside some Virtual Network Functions (VNFs) does not relate to each other, parallel chaining them can further improve the performance, such as reducing the end-to-end hops of SFCs. However, it is often ignored that parallel deploy VNFs will also introduce additional VNFs to replicate, distribute, and merge data. This will add hops and increase resource consumption. Will parallel deployment of VNFs in SFCs necessarily bring benefits? Regarding multiple parallel forms of an SFC, which one is the best? Further, how does the service process of the NFV network affect the parallel decisions of VNFs? In this paper, we design an NFV orchestrator, DP-NFVO, to maximize the revenue of NFV Service Providers and provide quantitative insights into the impact of parallel VNFs deploy-ment. Precisely, we first refine existing VNF parallelism rules and discuss the impact of VNF parallelism on latency and resource consumption, and analyze the optimal form of parallelism for SFCs. Second, we decompose the service request process in NFV networks into multiple stages and provide a joint model of VNF parallelism and deployment. Further, we design a VNF online deployment and parallelism decision policy for DP-NFVO based on Proximal Policy Optimization (PPO) to maximize revenue. Finally, we demonstrate the effectiveness and adaptability of DP-NFVO on parallel processing and the requests service process with extensive experiments.

关键词： Adaptation models Service function chaining parallel processing Network function virtualization Delays Optimization

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