In this paper, the problem of low-latency communication and computation resource allocation for digital twin (DT) over wireless networks is investigated. In the considered model, multiple physical devices in the physi...
In this paper, the problem of low-latency communication and computation resource allocation for digital twin (DT) over wireless networks is investigated. In the considered model, multiple physical devices in the physical network (PN) needs to frequently offload the computation task related data to the digital network twin (DNT), which is generated and controlled by the central server. Due to limited energy budget of the physical devices, both computation accuracy and wireless transmission power must be considered during the DT procedure. This joint communication and computation problem is formulated as an optimization problem whose goal is to minimize the overall transmission delay of the system under total PN energy and DNT model accuracy constraints. To solve this problem, an alternating algorithm with iteratively solving device scheduling, power control, and data offloading subproblems. For the device scheduling subproblem, the optimal solution is obtained in closed form through the dual method. Numerical results verify that the proposed algorithm can reduce the transmission delay of the system by up to 51.2% compared to the conventional schemes.
The extraction of EXIF (Exchangeable Image File Format) metadata, which provides information about the aspects of data in digital camera images, is essential in various applications such as geolocation, privacy protec...
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Intrusion detection is a crucial tool for establishing a safe and reliable Network computing environment, considering the widespread and ever-changing nature of cyber threats. Network Computing offers a substantial en...
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ISBN:
(数字)9798350389449
ISBN:
(纸本)9798350389456
Intrusion detection is a crucial tool for establishing a safe and reliable Network computing environment, considering the widespread and ever-changing nature of cyber threats. Network Computing offers a substantial enhancement in cost metrics by dynamically providing IT services inside our present framework of resource, platform, and service consolidations. Given that the majority of cloud computing networks rely on delivering their services via the Internet, they are susceptible to encountering a range of security concerns. Hence, it is imperative to implement an Intrusion Detection System (IDS) in cloud settings to effectively identify novel and unfamiliar threats, alongside established signature-based attacks, with a notable level of precision. In the course of our analysis, we make the assumption that a “anomalous” event in a system or network is equivalent to a “intrusion” event, which occurs when there is a substantial deviation in one or more fundamental activities of the system or network. Several recent proposals have been put out with the objective of creating a hybrid detection mechanism that combines the benefits of signature-based detection techniques with the capability to identify unfamiliar assaults through anomalies. This study presents a novel anomaly detection system at the Network, the virtual machine level, which incorporates a hybrid algorithm. The technique combines the Naive Bayes algorithm and the SVM classification algorithm with k-Means clustering. The objective is to enhance the accuracy of the anomaly detection system. In regard to the general effectiveness in terms of detection rate and low false positive rate, the results of this study indicate that the suggested solution outperforms the traditional models.
We propose a communication and computation efficient second-order method for distributed optimization. For each iteration, our method only requires O(d) communication complexity, where d is the problem dimension. We a...
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In response to legislation, companies are now mandated to honor the right to be forgotten by erasing user data. Consequently, it has become imperative to enable data removal in Vertical Federated Learning (VFL), where...
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作者：
Abdullah, NorizalAyob, MasriSabar, Nasser R.Lam, Meng ChunYong, Liu Chian
Data Mining and Optimisation Lab Faculty of Information Science and Technology Ukm Bangi Selangor 43600 Malaysia La Trobe University
Department of Computer Science and Information Technology Melbourne Australia
Faculty of Information Science Ukm Bangi Selangor 43600 Malaysia Ukm Medical Centre
Department of Anaesthesiology & Intensive Care Jalan Yaacob Latiff Bandar Tun Razak Cheras Kuala Lumpur56000 Malaysia
This work dealt with a real-world Anaesthetist Rostering Problem (ARP) for an on-call shift. An on-call shift for an anaesthetist had already been resolved under the physician's rostering problem. However, in thei...
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The CleverEats application is used for the purpose of evaluation of the packaged food products that all we bought daily. The main theme of this mobile application is to know the maximum intake of the packaged food pro...
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ISBN:
(数字)9798350343878
ISBN:
(纸本)9798350343885
The CleverEats application is used for the purpose of evaluation of the packaged food products that all we bought daily. The main theme of this mobile application is to know the maximum intake of the packaged food products that don’t harmful for our health. The application is used in a way that it scans the product name and then returns the ingredients presents in the food product. Along with the details about the ingredients and the chemicals used while making and packaging product. It also returns the nutrition information of that particular food product. Currently if the user wants to know about the nutrition information and maximum intake of the particular chemicals present in it. Our application minimizes the work for the user. Instead of knowing the information separately it creates a platform where all the related information about the product at one place.
Online social networks have permeated our social lives in the current generation. These sites have allowed us to see our social lives differently than they did in the past. Nowadays we can connect with new friends and...
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In this paper, we propose a generic method for computing the rate-distortion-perception function (RDPF) of a multivariate Gaussian source under tensorizable distortion and perception metrics. Through the assumption of...
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ISBN:
(数字)9798350382846
ISBN:
(纸本)9798350382853
In this paper, we propose a generic method for computing the rate-distortion-perception function (RDPF) of a multivariate Gaussian source under tensorizable distortion and perception metrics. Through the assumption of a jointly Gaussian reconstruction, we establish that the optimal solution of the RDPF belongs to the vector space spanned by the eigenvector of the source covariance matrix. Consequently, the multivariate optimization problem can be expressed as a function of the scalar Gaussian RDPFs of the source marginals, constrained by global distortion and perception levels. Utilizing this result, we devise an alternating minimization scheme based on the block nonlinear Gauss-Seidel method. This scheme solves optimally the optimization problem while identifying the optimal stage-wise distortion and perception levels. Furthermore, the associated algorithmic embodiment is provided, along with the convergence and the rate of convergence characterization. Lastly, in the regime of “perfect realism”, we provide the analytical solution for the multivariate Gaussian RDPF. We corroborate our findings with numerical simulations and draw connections to existing results.
For establishing a high efficient signal communications, a Millimeter-Wave-Massive-MIMO (mmWave-MMIMO) logics are helpful and more speculated. Although current hybrid precoding schemes are computationally complex, how...
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