Jinlin Xu^1,2, Wansu Pan^1,*, Longle Cheng^1,2, Haibo Tan^1,2, Munan Yuan^1,*, Xiaofeng Li^1,2

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1399-1418, 2024, DOI:10.32604/cmc.2024.049622

Abstract The existing multipath routing in Software Defined Network (SDN) is relatively blind and inefficient, and there is a lack of cooperation between the terminal and network sides, making it difficult to achieve dynamic adaptation of service requirements and network resources. To address these issues, we propose a multi-constraint path optimization scheme based on information fusion in SDN. The proposed scheme collects network topology and network state information on the network side and computes disjoint paths between end hosts. It uses the Fuzzy Analytic Hierarchy Process (FAHP) to calculate the weight coefficients of multiple constrained parameters and constructs a composite quality… More >

Zibin Mao¹, Qinghai Zhao^1,2,*, Liang Zhang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 757-792, 2024, DOI:10.32604/cmes.2024.048016

Abstract This paper proposes a multi-material topology optimization method based on the hybrid reliability of the probability-ellipsoid model with stress constraint for the stochastic uncertainty and epistemic uncertainty of mechanical loads in optimization design. The probabilistic model is combined with the ellipsoidal model to describe the uncertainty of mechanical loads. The topology optimization formula is combined with the ordered solid isotropic material with penalization (ordered-SIMP) multi-material interpolation model. The stresses of all elements are integrated into a global stress measurement that approximates the maximum stress using the normalized p-norm function. Furthermore, the sequential optimization and reliability assessment (SORA) is applied to… More >

Thanh-Lam Nguyen¹, Hao Kao¹, Thanh-Tuan Nguyen², Mong-Fong Horng^1,*, Chin-Shiuh Shieh^1,*

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2181-2205, 2024, DOI:10.32604/cmc.2024.047387

Abstract Since its inception, the Internet has been rapidly evolving. With the advancement of science and technology and the explosive growth of the population, the demand for the Internet has been on the rise. Many applications in education, healthcare, entertainment, science, and more are being increasingly deployed based on the internet. Concurrently, malicious threats on the internet are on the rise as well. Distributed Denial of Service (DDoS) attacks are among the most common and dangerous threats on the internet today. The scale and complexity of DDoS attacks are constantly growing. Intrusion Detection Systems (IDS) have been deployed and have demonstrated… More >

Lalit Mohan Patnaik^1,5, Wenfeng Wang^2,3,4,5,6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1203-1215, 2024, DOI:10.32604/cmes.2023.029451

Abstract This article reviews the theory of fairness in AI–from machine learning to federated learning, where the constraints on precision AI fairness and perspective solutions are also discussed. For a reliable and quantitative evaluation of AI fairness, many associated concepts have been proposed, formulated and classified. However, the inexplicability of machine learning systems makes it almost impossible to include all necessary details in the modelling stage to ensure fairness. The privacy worries induce the data unfairness and hence, the biases in the datasets for evaluating AI fairness are unavoidable. The imbalance between algorithms’ utility and humanization has further reinforced such worries.… More >

Ngoc-Khuong Nguyen^1,2, Dac-Nhuong Le¹, Viet-Ha Nguyen², Anh-Cuong Le^3,*

Intelligent Automation & Soft Computing, Vol.38, No.1, pp. 1-18, 2023, DOI:10.32604/iasc.2023.037083

Abstract Text summarization aims to generate a concise version of the original text. The longer the summary text is, the more detailed it will be from the original text, and this depends on the intended use. Therefore, the problem of generating summary texts with desired lengths is a vital task to put the research into practice. To solve this problem, in this paper, we propose a new method to integrate the desired length of the summarized text into the encoder-decoder model for the abstractive text summarization problem. This length parameter is integrated into the encoding phase at each self-attention step and… More >

Xiuhui Diao¹, Pengfei Wang^1,2,*, Weidong Li², Xianwu Chu², Yunming Wang²

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1795-1812, 2024, DOI:10.32604/cmes.2023.030008

Abstract To solve the problem of data fusion for prior information such as track information and train status in train positioning, an adaptive H_∞ filtering algorithm with combination constraint is proposed, which fuses prior information with other sensor information in the form of constraints. Firstly, the train precise track constraint method of the train is proposed, and the plane position constraint and train motion state constraints are analysed. A model for combining prior information with constraints is established. Then an adaptive H_∞ filter with combination constraints is derived based on the adaptive adjustment method of the robustness factor. Finally, the positioning… More >

Zhihong Ouyang^*, Lei Xue, Feng Ding, Yongsheng Duan

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 983-1008, 2023, DOI:10.32604/cmc.2023.042222

Abstract Affinity propagation (AP) is a widely used exemplar-based clustering approach with superior efficiency and clustering quality. Nevertheless, a common issue with AP clustering is the presence of excessive exemplars, which limits its ability to perform effective aggregation. This research aims to enable AP to automatically aggregate to produce fewer and more compact clusters, without changing the similarity matrix or customizing preference parameters, as done in existing enhanced approaches. An automatic aggregation enhanced affinity propagation (AAEAP) clustering algorithm is proposed, which combines a dependable partitioning clustering approach with AP to achieve this purpose. The partitioning clustering approach generates an additional set… More >

Muhammad Fezan Afzal¹, Imran Khan¹, Javed Rashid^1,2,3, Mubbashar Saddique^4,*, Heba G. Mohamed⁵

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3653-3670, 2023, DOI:10.32604/cmc.2023.041627

Abstract Software Product Line (SPL) is a group of software-intensive systems that share common and variable resources for developing a particular system. The feature model is a tree-type structure used to manage SPL’s common and variable features with their different relations and problem of Crosstree Constraints (CTC). CTC problems exist in groups of common and variable features among the sub-tree of feature models more diverse in Internet of Things (IoT) devices because different Internet devices and protocols are communicated. Therefore, managing the CTC problem to achieve valid product configuration in IoT-based SPL is more complex, time-consuming, and hard. However, the CTC… More >

Kun Liu^1,2, Peiran Li³, Yu Zhang^1,*, Jia Ren¹, Xianyu Wang², Uzair Aslam Bhatti¹

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3257-3274, 2023, DOI:10.32604/cmc.2023.039430

Abstract To obtain the optimal Bayesian network (BN) structure, researchers often use the hybrid learning algorithm that combines the constraint-based (CB) method and the score-and-search (SS) method. This hybrid method has the problem that the search efficiency could be improved due to the ample search space. The search process quickly falls into the local optimal solution, unable to obtain the global optimal. Based on this, the Particle Swarm Optimization (PSO) algorithm based on the search space constraint process is proposed. In the first stage, the method uses dynamic adjustment factors to constrain the structure search space and enrich the diversity of… More >

Shengyao Sun^1,2, Ying Du³, Jiajun Chen⁴, Xuan Zhang⁵, Jiwei Zhang^6,*, Yiyi Xu⁷

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2879-2900, 2023, DOI:10.32604/cmc.2023.037483

Abstract In Multi-access Edge Computing (MEC), to deal with multiple user equipment (UE)’s task offloading problem of parallel relationships under the multi-constraints, this paper proposes a cooperation partial task offloading method (named CPMM), aiming to reduce UE's energy and computation consumption, while meeting the task completion delay as much as possible. CPMM first studies the task offloading of single-UE and then considers the task offloading of multi-UE based on single-UE task offloading. CPMM uses the critical path algorithm to divide the modules into key and non-key modules. According to some constraints of UE-self when offloading tasks, it gives priority to non-key… More >