The Internet of Things (IoT) is a breakthrough technology that interconnects and empowers numerous smart devices allowing them to communicate, collect, and exchange data. The most challenging issue in IoT networks is ...
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ISBN:
(纸本)9798350369458;9798350369441
The Internet of Things (IoT) is a breakthrough technology that interconnects and empowers numerous smart devices allowing them to communicate, collect, and exchange data. The most challenging issue in IoT networks is securing exchanged data. Virtual Private Networks (VPNs) have a significant impact on ensuring security within IoT systems. So implementing a VPN-based solution can bring multiple security values to IoT systems, especially for exchanged data. However, most VPN-based solutions rely on a single central server responsible for managing all VPN connections. This presents a major problem when the number of managed VPNs increases because it will lead to the performance deterioration of the VPN server and can even lead to a single point of failure problem. We propose in this paper a distributed VPN-based solution that relies on distributed fog nodes playing the role of VPN servers. To determine the VPN server responsible for a specific communication, a fully decentralized and efficient search is guaranteed within the fog nodes through the utilization of the DHT-based Chord protocol. To enforce security and immutability, blockchain is used to verify the different criteria of a new requester to join a specific VPN. The performance evaluations have shown that our solution is efficient in terms of cost, time, and complexity.
This paper summarizes state-of-the-art results on data series processing with the emphasis on parallel and distributed data series indexes that exploit the computational power of modern computing platforms. The paper ...
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ISBN:
(纸本)9783031516429;9783031516436
This paper summarizes state-of-the-art results on data series processing with the emphasis on parallel and distributed data series indexes that exploit the computational power of modern computing platforms. The paper comprises a summary of the tutorial the author delivered at the 15th internationalconference on Management of Digital EcoSystems (MEDES'23).
Matching theory has been efficiently applied in fog computing networks (FCNs) to design distributed task offloading algorithms in the presence of selfishness and rationale of fog nodes. Given the dynamic nature of fog...
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ISBN:
(纸本)9798350349955;9798350349948
Matching theory has been efficiently applied in fog computing networks (FCNs) to design distributed task offloading algorithms in the presence of selfishness and rationale of fog nodes. Given the dynamic nature of fog computing environment, it is challenging to obtain the stable matching since the preference relations of two sides of matching game is unknown a prior. To address this challenge, this paper proposes RE-MATCH, a framework for parallel computation offloading in dynamic fog computing networks (FCNs). RE. MATCH is based on the matching theory and Thompson Sampling (TS) empowered Multi-Armed Bandit (MAR) learning to deal with the inherent challenges allowing task nodes with needed computation tasks to estimate the informed preference relations of helper nodes with available computing resource quickly and accurately. Extensive simulation results demonstrate the potential advantages of the TS based learning over the epsilon-greedy and upper confidence bound (UCB) based baselines.
Due to the complexity of the structure of doubly-fed induction generator (DFIG), it is difficult to conduct real-time simulation. For this reason, this paper designs an embeddable parallel digital image IP of DFIG bas...
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Due to the complexity of the structure of doubly-fed induction generator (DFIG), it is difficult to conduct real-time simulation. For this reason, this paper designs an embeddable parallel digital image IP of DFIG based on field programmable logic array (FPGA) to realize efficient electromagnetic simulation of DFIG. First, this paper proposes a virtual capacitor equivalent method for induction machine equivalent "T" circuit decoupling;Secondly, based on the principle of data independence and parallelism within the time step, a parallel algorithm for the internal components of DFIG is proposed;Finally, the FPGA-DFIG digital image constructed in this paper is connected to the RT-LAB/power grid, and hardware experiments are carried out under three working conditions: steady state, voltage sag and DC side fault. The experimental results are compared with the simulation results of DFIG grid connected system built in MATLAB/Simulink environment to verify the effectiveness and rapidity of the methods and models proposed in this paper.(C) 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the 2nd international Joint conference on Energy and Environmental Engineering, CoEEE, 2022.
In order to overcome the problems of high intrusion rate and low encryption depth of traditional cloud computing security research methods, this paper proposes a new cloud computing security research method based on V...
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Identifying Community structures is a fundamental problem in graph analysis. To detect communities in massive contemporary graphs, researchers have extensively explored shared- and distributed-memory parallel algorith...
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ISBN:
(纸本)9798350363074;9798350363081
Identifying Community structures is a fundamental problem in graph analysis. To detect communities in massive contemporary graphs, researchers have extensively explored shared- and distributed-memory parallel algorithms for several methods including Louvain Modularity Optimization and Label Propagation. The widely used Infomap algorithm based on Map Equation Framework (MEF) is known to provide better quality results than other approaches. However, research on parallel community detection using MEF or Infomap is extremely sparse when compared to other methods. We present a comprehensive characterization of Infomap and some of its known parallel implementations to facilitate research into parallel algorithms based on MEF. Most implementations take simple parallelization approaches, leaving strategies used to parallelize similar algorithms such as Louvain untouched. We highlight the scalability limitations of current implementations and implement and evaluate optimizations for MEF based parallel community detection that achieved up to 119% improvement on the overall speedup across the tested datasets.
grid-based simulations of hot fusion plasmas are often severely limited by computational and memory resources;the grids live in four- to six-dimensional space and thus suffer the curse of dimensionality. However, high...
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Modern computing environments are evolving towards the compute continuum paradigm, which promises to manage the heterogeneity and dynamism of geographically spread computing resources, supporting the execution of dist...
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ISBN:
(纸本)9783031506833;9783031506840
Modern computing environments are evolving towards the compute continuum paradigm, which promises to manage the heterogeneity and dynamism of geographically spread computing resources, supporting the execution of distributed and pervasive applications. As a complete understanding of all the implications and challenges posed by this new paradigm is still far, we give an overview of the key features and concepts of the compute continuum and discuss the most relevant research opportunities we envision in the field.
As the power Internet of Things (IoT) system accelerates, the IoT end devices within the power grid show an explosive growth, and generate massive electricity consumption data. While the diverse encryption technologie...
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With the growing complexity of modern internet networks, we introduce a distributed, asynchronous, and scalable algorithm tailored for determining the centrality and importance of various levels of the global internet...
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ISBN:
(纸本)9798350395679;9798350395662
With the growing complexity of modern internet networks, we introduce a distributed, asynchronous, and scalable algorithm tailored for determining the centrality and importance of various levels of the global internet network topology at a massive scale. By utilizing triangle formations and neighborhood densities in these complex networks, our algorithm provides valuable insights into the structural importance of individual nodes and the intricate relationships among interconnected entities. Focusing on the global internet's prime components routers, IP addresses, and Autonomous Systems - the algorithm provides a scalable solution extending to the global internet infrastructure, datacenters, cloud networks, and private networks. By taking advantage of the parallelism, distributed processing, efficient communication, and fine-grained asynchronous execution through an Actor-based programming system, our algorithm is capable of efficiently processing and performing rapid computations on large-scale internet networks. We perform scalability studies on the NERSC Perlmutter supercomputer and the Georgia Tech HPC PACE cluster using three large-scale real-world network datasets and one large-scale synthetic network dataset, achieving up to 91.7% parallel efficiency scaling out to 2K cores and reducing execution time from 5.7 hours to 18.3 seconds, while performing 105.4x better on average compared to related approaches. Our research contributes significantly to facilitating enhanced network management, fault tolerance and resilience, and security, but as well to improving overall network stability, reducing latency, and optimizing energy consumption across the vast internet network devices environment.
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