Guo Zhao^1,2, Chi Zhang^1,2,*, Qiyuan Ren^1,2

Energy Engineering, Vol.121, No.11, pp. 3355-3379, 2024, DOI:10.32604/ee.2024.053130 - 21 October 2024

Abstract In the context of China’s “double carbon” goals and rural revitalization strategy, the energy transition promotes the large-scale integration of distributed renewable energy into rural power grids. Considering the operational characteristics of rural microgrids and their impact on users, this paper establishes a two-layer scheduling model incorporating flexible loads. The upper-layer aims to minimize the comprehensive operating cost of the rural microgrid, while the lower-layer aims to minimize the total electricity cost for rural users. An Improved Adaptive Genetic Algorithm (IAGA) is proposed to solve the model. Results show that the two-layer scheduling model with More >

Junqing Bai¹, Qiuchao Dai^1,*, Yingying Li²

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5083-5103, 2024, DOI:10.32604/cmc.2024.050921 - 20 June 2024

Abstract To support the explosive growth of Information and Communications Technology (ICT), Mobile Edge Computing (MEC) provides users with low latency and high bandwidth service by offloading computational tasks to the network’s edge. However, resource-constrained mobile devices still suffer from a capacity mismatch when faced with latency-sensitive and compute-intensive emerging applications. To address the difficulty of running computationally intensive applications on resource-constrained clients, a model of the computation offloading problem in a network consisting of multiple mobile users and edge cloud servers is studied in this paper. Then a user benefit function EoU (Experience of Users) is… More >

Mohit Agarwal^1,*, Shikha Gupta²

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6103-6119, 2022, DOI:10.32604/cmc.2022.030778 - 28 July 2022

Abstract Task scheduling in highly elastic and dynamic processing environments such as cloud computing have become the most discussed problem among researchers. Task scheduling algorithms are responsible for the allocation of the tasks among the computing resources for their execution, and an inefficient task scheduling algorithm results in under-or over-utilization of the resources, which in turn leads to degradation of the services. Therefore, in the proposed work, load balancing is considered as an important criterion for task scheduling in a cloud computing environment as it can help in reducing the overhead in the critical decision-oriented process.… More >

Nana Zhang¹, Kun Zhu¹, Shi Ying^{1, *}, Xu Wang²

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 471-499, 2020, DOI:10.32604/cmc.2020.010117 - 20 May 2020

Abstract Software defect prediction is a research hotspot in the field of software engineering. However, due to the limitations of current machine learning algorithms, we can’t achieve good effect for defect prediction by only using machine learning algorithms. In previous studies, some researchers used extreme learning machine (ELM) to conduct defect prediction. However, the initial weights and biases of the ELM are determined randomly, which reduces the prediction performance of ELM. Motivated by the idea of search based software engineering, we propose a novel software defect prediction model named KAEA based on kernel principal component analysis… More >

Yuankun Yan^1,*, Yan Kong¹, Zhangjie Fu^1,2

Journal of Information Hiding and Privacy Protection, Vol.1, No.3, pp. 143-155, 2019, DOI:10.32604/jihpp.2019.07772

Abstract Nowadays, emergency accidents could happen at any time. The accidents occur unpredictably and the accidents requirements are diversely. The accidents happen in a dynamic environment and the resource should be cooperative to solve the accidents. Most methods are focusing on minimizing the casualties and property losses in a static environment. However, they are lack in considering the dynamic and unpredictable event handling. In this paper, we propose a representative environmental model in representation of emergency and dynamic resource allocation model, and an adaptive mathematical model based on Genetic Algorithm (GA) to generate an optimal set More >

R. Sujatha¹, M. Ramakrishnan², N. Duraipandian³, B. Ramakrishnan⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.105, No.1, pp. 47-68, 2015, DOI:10.3970/cmes.2015.105.047

Abstract The functions of digital signature and public key encryption are simultaneously fulfilled by signcryption, which is a cryptographic primitive. To securely communicate very large messages, the cryptographic primitive called signcryption efficiently implements the same and while most of the public key based systems are suitable for small messages, hybrid encryption (KEM-DEM) provides a competent and practical way. In this paper, we develop a hybrid signcryption technique. The hybrid signcryption is based on the KEM and DEM technique. The KEM algorithm utilizes the KDF technique to encapsulate the symmetric key. The DEM algorithm utilizes the Adaptive More >