Transactional stream processing engines (TSPEs) are central to modern stream applications handling shared mutable states. However, their full potential, particularly in adaptive scheduling, remains largely unexplored....
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In Intelligent Transportation Systems(ITS),controlling the trafficflow of a region in a city is the major ***,allocation of the traffic-free route to the taxi drivers during peak hours is one of the challenges to control...
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In Intelligent Transportation Systems(ITS),controlling the trafficflow of a region in a city is the major ***,allocation of the traffic-free route to the taxi drivers during peak hours is one of the challenges to control the trafficfl***,in this paper,the route between the taxi driver and pickup location or hotspot with the spatial-temporal dependencies is ***,the hotspots in a region are clustered using the density-based spatial clustering of applications with noise(DBSCAN)algorithm tofind the hot spots at the peak hours in an urban ***,the optimal route is allocated to the taxi driver to pick up the customer in the *** allocating the optimal route,each route between the taxi driver and the hot spot is mapped to the number of taxi *** the map function,the optimal map is selected using the rain opti-mization algorithm(ROA).If more than one map function is obtained as the opti-mal solution,the map between the route and the taxi driver who has done the least number of trips in the day is chosen as thefinal solution This optimal route selec-tion leads to control of the trafficflow at peak *** of the approach depicts that the proposed trafficflow control scheme reduces traveling time,wait-ing time,fuel consumption,and emission.
Satellite imagery is found to be beneficial in many disciplines such as land use analysis, urban planning, and environmental monitoring. However, accurate segmentation of land features from satellite images requires m...
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Learning a good similarity measure for large-scale high-dimensional data is a crucial task in machine learning applications, yet it poses a significant challenge. Distributed minibatch Stochastic Gradient Descent (SGD...
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Fog computing is considered a derivative of cloud computing that aims to reduce the huge transmission latency and CPU time, as well as the overall cost of resource usage in the cloud. The deployment of Internet-o...
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Fog computing is considered a derivative of cloud computing that aims to reduce the huge transmission latency and CPU time, as well as the overall cost of resource usage in the cloud. The deployment of Internet-of-Things (IoT) enabled smart systems, which frequently demand real-time processing, is rapidly expanding. Following that, the volume of generated data and computation workload dramatically increased. Fog resources are limited and typically resource constrained. Therefore, it is impossible to execute all tasks at the edge network. To support the increasing amounts of data and computation, cloud computing, associated with significant delays in transmission and processing of workload, is used. The distribution of tasks between the cloud and fog layer and the allocation of layer resources to satisfy the users' demands prevents layer oversaturation, service degradation, and resource failure due to excessive workload is challenging. This paper proposes a layer fit algorithm that evenly distributes tasks between the fog and cloud, based on priority levels. Also, a Modified Harris-Hawks Optimization (MHHO) based meta-heuristic approach is proposed to assign the best available resource to a task within a layer. The key intention of this paper is to reduce the makespan time, task execution cost, and power consumption and enhance resource usage in both the fog and cloud layer. The simulations are performed using the iFogSim simulation toolkit. The proposed layer fit algorithm and the Modified Harris-Hawks Optimization (MHHO) are compared with the traditional Harris-Hawks Optimization (HHO), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and the Firefly Algorithm (FA). Based on the experimental results, the MHHO has improved the performance of the system in terms of makespan time, execution cost, and energy consumption. The ability of the MHHO to balance the load across resources yields a significant improvement when the number of tasks increases as c
Compared with traditional environments,the cloud environment exposes online services to additional vulnerabilities and threats of cyber attacks,and the cyber security of cloud platforms is becoming increasingly promin...
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Compared with traditional environments,the cloud environment exposes online services to additional vulnerabilities and threats of cyber attacks,and the cyber security of cloud platforms is becoming increasingly prominent.A piece of code,known as a Webshell,is usually uploaded to the target servers to achieve multiple *** Webshell attacks has become a hot spot in current ***,the traditional Webshell detectors are not built for the cloud,making it highly difficult to play a defensive role in the cloud ***,a Webshell detection system based on deep learning that is successfully applied in various scenarios,is proposed in this *** system contains two important components:gray-box and neural network *** gray-box analyzer defines a series of rules and algorithms for extracting static and dynamic behaviors from the code to make the decision *** neural network analyzer transforms suspicious code into Operation Code(OPCODE)sequences,turning the detection task into a classification *** experiment results show that SmartEagleEye achieves an encouraging high detection rate and an acceptable false-positive rate,which indicate its capability to provide good protection for the cloud environment.
We present a decoupled,linearly implicit numerical scheme with energy stability and mass conservation for solving the coupled Cahn-Hilliard *** time-discretization is done by leap-frog method with the scalar auxiliary...
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We present a decoupled,linearly implicit numerical scheme with energy stability and mass conservation for solving the coupled Cahn-Hilliard *** time-discretization is done by leap-frog method with the scalar auxiliary variable(SAV)*** only needs to solve three linear equations at each time step,where each unknown variable can be solved *** is shown that the semi-discrete scheme has second-order accuracy in the temporal *** convergence results are proved by a rigorous analysis of the boundedness of the numerical solution and the error estimates at different *** examples are presented to further confirm the validity of the methods.
This paper is concerned with the existence of nodal solutions for the following quasilinear Schr?dinger equation with a cubic term ■ where N ≥ 3, λ > 0, the function V（|x|） is a radially symmetric and positive...
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This paper is concerned with the existence of nodal solutions for the following quasilinear Schr?dinger equation with a cubic term ■ where N ≥ 3, λ > 0, the function V（|x|） is a radially symmetric and positive potential. By using the variational method and energy comparison method, for any given integer k ≥ 1, the above equation admits a radial nodal solution Uk,4λhaving exactly k nodes via a limit ***, the energy of Uk,4λis monotonically increasing in k and for any sequence {λ_n}, up to a subsequence,■ converges strongly to some ■ as λ_n→+∞, which is a radial nodal solution with exactly k nodes of the classical Schr¨dinger equation ■ Our results extend the existing ones in the literature from the super-cubic case to the cubic case.
The paper introduces a hybrid product recommendation system that combines popularity-based and content-based filtering methods. The aim is to enhance the accuracy and relevance of product suggestions by utilizing both...
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This paper investigates equivalence of square multivariate polynomial matrices with the determinant being some power of a univariate irreducible *** authors give a necessary and sufficient condition for this *** the a...
This paper investigates equivalence of square multivariate polynomial matrices with the determinant being some power of a univariate irreducible *** authors give a necessary and sufficient condition for this *** the authors present an algorithm to reduce a class of multivariate polynomial matrices to their Smith forms.
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