Task offloading technology plays a crucial role in the Internet of Vehicles (IoV) by minimizing processing delays through the joint optimization of heterogeneous computing resources supported by vehicles, roadside uni...
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Network virtualization can effectively establish dedicated virtual networks to implement various network ***,the existing research works have some shortcomings,for example,although computing resource properties of ind...
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Network virtualization can effectively establish dedicated virtual networks to implement various network ***,the existing research works have some shortcomings,for example,although computing resource properties of individual nodes are considered,node storage properties and the network topology properties are usually ignored in Virtual Network(VN)modelling,which leads to the inaccurate measurement of node availability and *** addition,most static virtual network mapping methods allocate fixed resources to users during the entire life cycle,and the users’actual resource requirements vary with the workload,which results in resource allocation *** on the above analysis,in this paper,we propose a dynamic resource sharing virtual network mapping algorithm named NMA-PRS-VNE,first,we construct a new,more realistic network framework in which the properties of nodes include computing resources,storage resources and topology *** the node mapping process,three properties of the node are used to measure its mapping ***,we consider the resources of adjacent nodes and links instead of the traditional method of measuring the availability and priority of nodes by considering only the resource properties,so as to more accurately select the physical mapping nodes that meet the constraints and conditions and improve the success rate of subsequent link ***,we divide the resource requirements of Virtual Network Requests(VNRs)into basic subrequirements and variable sub-variable requirements to complete dynamic resource *** former represents monopolizing resource requirements by the VNRs,while the latter represents shared resources by many VNRs with the probability of occupying resources,where we keep a balance between resource sharing and collision among users by calculating the collision *** results show that the proposed NMAPRS-VNE can increase the average acceptance rate and network revenu
Simultaneous anammox and denitrification(SAD) is an efficient approach to treat wastewater having a low C/N ratio;however, few studies have investigated a combination of SAD and partial nitritation(PN). In this study,...
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Simultaneous anammox and denitrification(SAD) is an efficient approach to treat wastewater having a low C/N ratio;however, few studies have investigated a combination of SAD and partial nitritation(PN). In this study, a lab-scale up-flow blanket filter(UBF) and zeolite sequence batch reactor(ZSBR) were continuously operated to implement SAD and PN advantages, respectively. The UBF achieved a high total nitrogen(TN) removal efficiency of over 70% during the start-up stage(days 1–50), and reached a TN removal efficiency of 96%in the following 90 days(days 51–140) at COD/NH_(4)^(+)-N ratio of 2.5. The absolute abundance of anammox bateria increased to the highest value of 1.58 × 107copies/μL DNA;Comamonadaceae was predominant in the UBF at the optimal ratio. Meanwhile, ZSBR was initiated on day 115 as fast nitritation process to satisfy the influent requirement for the UBF. The combined process was started on day 140 and then lasted for 30 days, during the combined process, between the two reactors, the UBF was the main contributor for TN(66.5% ± 4.5%)and COD(71.8% ± 4.9%) removal. These results demonstrated that strong SAD occurred in the UBF when following a ZSBR with in-situ NOB elimination. This research presents insights into a novel biological nitrogen removal process for low C/N ratio wastewater treatment.
This letter considers a hybrid reconfigurable intelligent surface (RIS) assisted integrated sensing and communication (ISAC) system, where each RIS element can flexibly switch between the active and passive modes. Sub...
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With the emergence of more and more Web services, finding suitable services becomes a difficult problem. Service link prediction is employed to disclose relationships among services, which facilitates the further deve...
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This paper concerns ultimately bounded output-feedback control problems for networked systems with unknown nonlinear dynamics. Sensor-to-observer signal transmission is facilitated over networks that has communication...
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This paper concerns ultimately bounded output-feedback control problems for networked systems with unknown nonlinear dynamics. Sensor-to-observer signal transmission is facilitated over networks that has communication *** transmissions are carried out over an unreliable communication channel. In order to enhance the utilization rate of measurement data, a buffer-aided strategy is novelly employed to store historical measurements when communication networks are inaccessible. Using the neural network technique, a novel observer-based controller is introduced to address effects of signal transmission behaviors and unknown nonlinear *** the application of stochastic analysis and Lyapunov stability, a joint framework is constructed for analyzing resultant system performance under the introduced controller. Subsequently, existence conditions for the desired output-feedback controller are delineated. The required parameters for the observerbased controller are then determined by resolving some specific matrix inequalities. Finally, a simulation example is showcased to confirm method efficacy.
The development of smart mobile devices brings convenience to people's lives, but also provides a breeding ground for Android malware. The sharp increasing malware poses a disastrous threat to personal privacy in ...
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The development of smart mobile devices brings convenience to people's lives, but also provides a breeding ground for Android malware. The sharp increasing malware poses a disastrous threat to personal privacy in the information age. Based on the fact that malware heavily resorts to system application programming interfaces(APIs) to perform its malicious actions,there has been a variety of API-based detection *** of them do not consider the relationship between APIs. We contribute a new approach based on the enhanced API order for Android malware detection, named EAODroid, which learns the similarity of system APIs from a large number of API sequences and groups similar APIs into clusters. The extracted API clusters are further used to enhance the original API calls executed by an app to characterize behaviors and perform classification. We perform multi-dimensional experiments to evaluate EAODroid on three datasets with ground truth. We compare with many state-of-the-art works, showing that EAODroid achieves effective performance in Android malware detection.
Early fire Due to the small target and the occurrence of early scene complexity, the existing fire detection methods make it very easy to miss the detection of false detection phenomena. To address the above problems,...
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The broad learning system(BLS) based on the minimum mean square error(MMSE) criterion can achieve outstanding performance without spending too much time in various machine learning ***, when data are polluted by non-G...
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The broad learning system(BLS) based on the minimum mean square error(MMSE) criterion can achieve outstanding performance without spending too much time in various machine learning ***, when data are polluted by non-Gaussian noise, the stability of BLS may be destroyed because the MMSE criterion is sensitive to outliers. Different from the MMSE criterion, the minimum error entropy(MEE) criterion utilizes the kernel function to capture high-dimensional information and decrease the negative influence of outliers, which will make BLS more discriminative and robust. Nevertheless, the computational complexity of MEE is high due to a double summation of the data size. To solve these issues, this paper proposes a new robust BLS variant based on the quantized minimum error entropy(QMEE) criterion, in which a quantization operation is used to reduce the computational complexity of MEE. The proposed model BLS-QMEE is optimized by the fixed-point iterative method, and a sufficient condition for its convergence is provided. Compared with the standard BLS and other existing robust variants of BLS, BLS-QMEE performs more satisfactorily without consuming too much time. The desirable performance of BLS-QMEE is verified by various experiments on function approximation, several public datasets, and a practical application.
As wafer circuit widths shrink less than 10 nm,stringent quality control is imposed on the wafer fabrication processes. Therefore, wafer residency time constraints and chamber cleaning operations are widely required i...
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As wafer circuit widths shrink less than 10 nm,stringent quality control is imposed on the wafer fabrication processes. Therefore, wafer residency time constraints and chamber cleaning operations are widely required in chemical vapor deposition, coating processes, etc. They increase scheduling complexity in cluster tools. In this paper, we focus on scheduling single-arm multi-cluster tools with chamber cleaning operations subject to wafer residency time constraints. When a chamber is being cleaned, it can be viewed as processing a virtual wafer. In this way, chamber cleaning operations can be performed while wafer residency time constraints for real wafers are not violated. Based on such a method, we present the necessary and sufficient conditions to analytically check whether a single-arm multi-cluster tool can be scheduled with a chamber cleaning operation and wafer residency time constraints. An algorithm is proposed to adjust the cycle time for a cleaning operation that lasts a long cleaning ***, algorithms for a feasible schedule are also *** an algorithm is presented for operating a multi-cluster tool back to a steady state after the cleaning. Illustrative examples are given to show the application and effectiveness of the proposed method.
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