Efficient resource provisioning,allocation,and computation offloading are critical to realizing lowlatency,scalable,and energy-efficient applications in cloud,fog,and edge *** its importance,integrating software Defin...
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Efficient resource provisioning,allocation,and computation offloading are critical to realizing lowlatency,scalable,and energy-efficient applications in cloud,fog,and edge *** its importance,integrating software Defined Networks(SDN)for enhancing resource orchestration,task scheduling,and traffic management remains a relatively underexplored area with significant innovation *** paper provides a comprehensive review of existing mechanisms,categorizing resource provisioning approaches into static,dynamic,and user-centric models,while examining applications across domains such as IoT,healthcare,and autonomous *** survey highlights challenges such as scalability,interoperability,and security in managing dynamic and heterogeneous *** exclusive research evaluates how SDN enables adaptive policy-based handling of distributed resources through advanced orchestration ***,proposes future directions,including AI-driven optimization techniques and hybrid *** addressing these emerging opportunities,thiswork serves as a foundational reference for advancing resource management strategies in next-generation cloud,fog,and edge computing *** survey concludes that SDN-enabled computing environments find essential guidance in addressing upcoming management opportunities.
Label correction methods are popular for their simple architecture in learning with noisy labels. However, they suffer severely from false label correction and achieve subpar performance compared with state-of-the-art...
Cloud computing has brought about a significant transformation in the field of Information Technology (IT) by providing the capability to access a shared pool of resources over the internet in a scalable and on-demand...
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A recommender system is an approach performed by e-commerce for increasing smooth users’*** pattern mining is a technique of data mining used to identify the co-occurrence relationships by taking into account the ord...
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A recommender system is an approach performed by e-commerce for increasing smooth users’*** pattern mining is a technique of data mining used to identify the co-occurrence relationships by taking into account the order of *** work will present the implementation of sequence pattern mining for recommender systems within the domain of *** work will execute the Systolic tree algorithm for mining the frequent patterns to yield feasible rules for the recommender *** feature selec-tion's objective is to pick a feature subset having the least feature similarity as well as highest relevancy with the target *** will mitigate the feature vector's dimensionality by eliminating redundant,irrelevant,or noisy *** work pre-sents a new hybrid recommender system based on optimized feature selection and systolic *** features were extracted using Term Frequency-Inverse Docu-ment Frequency(TF-IDF),feature selection with the utilization of River Forma-tion Dynamics(RFD),and the Particle Swarm Optimization(PSO)*** systolic tree is used for pattern mining,and based on this,the recommendations are *** proposed methods were evaluated using the MovieLens dataset,and the experimental outcomes confirmed the efficiency of the *** was observed that the RFD feature selection with systolic tree frequent pattern mining with collaborativefiltering,the precision of 0.89 was achieved.
Intracranial hemorrhage (ICH) is a life-threatening condition that requires rapid and accurate diagnosis to improve treatment outcomes and patient survival rates. Recent advancements in supervised deep learning have g...
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In today’s digital era, the security of sensitive data such as Aadhaar data is of utmost importance. To ensure the privacy and integrity of this data, a conceptual framework is proposed that employs the Diffie-Hellma...
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Sleep paralysis is when you're awake but powerless to move. Although the majority of occurrences are linked to extreme terror and some potentially clinically significant sufferings are connected with the case;litt...
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The perception of offensive language varies based on cultural, social, and individual perspectives. With the spread of social media, there has been an increase in offensive content online, necessitating advanced solut...
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In blockchain networks, transactions can be transmitted through channels. The existing transmission methods depend on their routing information. If a node randomly chooses a channel to transmit a transaction, the tran...
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In blockchain networks, transactions can be transmitted through channels. The existing transmission methods depend on their routing information. If a node randomly chooses a channel to transmit a transaction, the transmission may be aborted due to insufficient funds(also called balance) or a low transmission rate. To increase the success rate and reduce transmission delay across all transactions, this work proposes a transaction transmission model for blockchain channels based on non-cooperative game *** balance, channel states, and transmission probability are fully considered. This work then presents an optimized channel transaction transmission algorithm. First, channel balances are analyzed and suitable channels are selected if their balance is sufficient. Second, a Nash equilibrium point is found by using an iterative sub-gradient method and its related channels are then used to transmit transactions. The proposed method is compared with two state-of-the-art approaches: Silent Whispers and Speedy Murmurs. Experimental results show that the proposed method improves transmission success rate, reduces transmission delay,and effectively decreases transmission overhead in comparison with its two competitive peers.
Currently,edge Artificial Intelligence(AI)systems have significantly facilitated the functionalities of intelligent devices such as smartphones and smart cars,and supported diverse applications and *** fundamental sup...
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Currently,edge Artificial Intelligence(AI)systems have significantly facilitated the functionalities of intelligent devices such as smartphones and smart cars,and supported diverse applications and *** fundamental supports come from continuous data analysis and computation over these *** the resource constraints of terminal devices,multi-layer edge artificial intelligence systems improve the overall computing power of the system by scheduling computing tasks to edge and cloud servers for *** efforts tend to ignore the nature of strong pipelined characteristics of processing tasks in edge AI systems,such as the encryption,decryption and consensus algorithm supporting the implementation of Blockchain ***,this paper proposes a new pipelined task scheduling algorithm(referred to as PTS-RDQN),which utilizes the system representation ability of deep reinforcement learning and integrates multiple dimensional information to achieve global task ***,a co-optimization strategy based on Rainbow Deep Q-Learning(RainbowDQN)is proposed to allocate computation tasks for mobile devices,edge and cloud servers,which is able to comprehensively consider the balance of task turnaround time,link quality,and other factors,thus effectively improving system performance and user *** addition,a task scheduling strategy based on PTS-RDQN is proposed,which is capable of realizing dynamic task allocation according to device *** results based on many simulation experiments show that the proposed method can effectively improve the resource utilization,and provide an effective task scheduling strategy for the edge computing system with cloud-edge-end architecture.
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