Wanbo Zhang¹, Yuqi Fan¹, Jun Zhang¹, Xu Ding^2,*, Jung Yoon Kim^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 863-885, 2024, DOI:10.32604/cmes.2024.047295

Abstract Users and edge servers are not fully mutually trusted in mobile edge computing (MEC), and hence blockchain can be introduced to provide trustable MEC. In blockchain-based MEC, each edge server functions as a node in both MEC and blockchain, processing users’ tasks and then uploading the task related information to the blockchain. That is, each edge server runs both users’ offloaded tasks and blockchain tasks simultaneously. Note that there is a trade-off between the resource allocation for MEC and blockchain tasks. Therefore, the allocation of the resources of edge servers to the blockchain and the MEC is crucial for the… More >

Laila Almutairi¹, Shabnam Mohamed Aslam^2,*

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2791-2811, 2023, DOI:10.32604/cmc.2023.040268

Abstract The rapid growth of service-oriented and cloud computing has created large-scale data centres worldwide. Modern data centres’ operating costs mostly come from back-end cloud infrastructure and energy consumption. In cloud computing, extensive communication resources are required. Moreover, cloud applications require more bandwidth to transfer large amounts of data to satisfy end-user requirements. It is also essential that no communication source can cause congestion or bag loss owing to unnecessary switching buffers. This paper proposes a novel Energy and Communication (EC) aware scheduling (EC-scheduler) algorithm for green cloud computing, which optimizes data centre energy consumption and traffic load. The primary goal… More >

Yuxuan Zhong¹, Siya Xu¹, Boxian Liao¹, Jizhao Lu², Huiping Meng², Zhili Wang¹, Xingyu Chen^1,*, Qinghan Li³

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2629-2644, 2023, DOI:10.32604/cmc.2023.035526

Abstract With the continuous progress of information technique, assisted driving technology has become an effective technique to avoid traffic accidents. Due to the complex road conditions and the threat of vehicle information being attacked and tampered with, it is difficult to ensure information security. This paper uses blockchain to ensure the safety of driving information and introduces mobile edge computing technology to monitor vehicle information and road condition information in real time, calculate the appropriate speed, and plan a reasonable driving route for the driver. To solve these problems, this paper proposes a trusted edge resource allocation framework for assisted driving… More >

V. Dhilip Kumar¹, J. Praveenchandar², Muhammad Arif^3,*, Adrian Brezulianu⁴, Oana Geman⁵, Atif Ikram^3,6

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2179-2188, 2023, DOI:10.32604/cmc.2023.034764

Abstract Cloud Technology is a new platform that offers on-demand computing Peripheral such as storage, processing power, and other computer system resources. It is also referred to as a system that will let the consumers utilize computational resources like databases, servers, storage, and intelligence over the Internet. In a cloud network, load balancing is the process of dividing network traffic among a cluster of available servers to increase efficiency. It is also known as a server pool or server farm. When a single node is overwhelmed, balancing the workload is needed to manage unpredictable workflows. The load balancer sends the load… More >

Chumei Wen¹, Delu Zeng^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1617-1636, 2024, DOI:10.32604/cmes.2023.029864

Abstract With the rapid development of Network Function Virtualization (NFV), the problem of low resource utilization in traditional data centers is gradually being addressed. However, existing research does not optimize both local and global allocation of resources in data centers. Hence, we propose an adaptive hybrid optimization strategy that combines dynamic programming and neural networks to improve resource utilization and service quality in data centers. Our approach encompasses a service function chain simulation generator, a parallel architecture service system, a dynamic programming strategy for maximizing the utilization of local server resources, a neural network for predicting the global utilization rate of… More >

Yonghui Lin¹, Zhengyu Zhu^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 663-677, 2024, DOI:10.32604/cmes.2023.028584

Abstract In this paper, we investigate IRS-aided user cooperation (UC) scheme in millimeter wave (mmWave) wireless-powered sensor networks (WPSN), where two single-antenna users are wireless powered in the wireless energy transfer (WET) phase first and then cooperatively transmit information to a hybrid access point (AP) in the wireless information transmission (WIT) phase, following which the IRS is deployed to enhance the system performance of the WET and WIT. We maximized the weighted sum-rate problem by jointly optimizing the transmit time slots, power allocations, and the phase shifts of the IRS. Due to the non-convexity of the original problem, a semidefinite programming… More >

Sai Liu¹, Zhenjiang Zhang^1,*, Guangjie Han², Bo Shen¹

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2651-2668, 2023, DOI:10.32604/iasc.2023.038477

Abstract Integrated satellite-terrestrial network (ISTN) has been considered a novel network architecture to achieve global three-dimensional coverage and ultra-wide area broadband access anytime and anywhere. Being a promising paradigm, cloud computing and mobile edge computing (MEC) have been identified as key technology enablers for ISTN to further improve quality of service and business continuity. However, most of the existing ISTN studies based on cloud computing and MEC regard satellite networks as relay networks, ignoring the feasibility of directly deploying cloud computing nodes and edge computing nodes on satellites. In addition, most computing tasks are transferred to cloud servers or offloaded to… More >

Ilyоs Abdullaev¹, Natalia Prodanova², K. Aruna Bhaskar³, E. Laxmi Lydia⁴, Seifedine Kadry^5,6,7, Jungeun Kim^8,*

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1463-1477, 2023, DOI:10.32604/cmc.2023.038417

Abstract Recently, computation offloading has become an effective method for overcoming the constraint of a mobile device (MD) using computation-intensive mobile and offloading delay-sensitive application tasks to the remote cloud-based data center. Smart city benefitted from offloading to edge point. Consider a mobile edge computing (MEC) network in multiple regions. They comprise N MDs and many access points, in which every MD has M independent real-time tasks. This study designs a new Task Offloading and Resource Allocation in IoT-based MEC using Deep Learning with Seagull Optimization (TORA-DLSGO) algorithm. The proposed TORA-DLSGO technique addresses the resource management issue in the MEC server,… More >

S. Kanmani^1,*, M. Murali²

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2583-2598, 2023, DOI:10.32604/csse.2023.037265

Abstract The introduction of new technologies has increased communication network coverage and the number of associating nodes in dynamic communication networks (DCN). As the network has the characteristics like decentralized and dynamic, few nodes in the network may not associate with other nodes. These uncooperative nodes also known as selfish nodes corrupt the performance of the cooperative nodes. Namely, the nodes cause congestion, high delay, security concerns, and resource depletion. This study presents an effective selfish node detection method to address these problems. The Price of Anarchy (PoA) and the Price of Stability (PoS) in Game Theory with the Presence of… More >

A. Richard William^1,*, J. Senthilkumar², Y. Suresh², V. Mohanraj²

Computer Systems Science and Engineering, Vol.47, No.1, pp. 777-790, 2023, DOI:10.32604/csse.2023.031753

Abstract In cloud computing Resource allocation is a very complex task. Handling the customer demand makes the challenges of on-demand resource allocation. Many challenges are faced by conventional methods for resource allocation in order to meet the Quality of Service (QoS) requirements of users. For solving the about said problems a new method was implemented with the utility of machine learning framework of resource allocation by utilizing the cloud computing technique was taken in to an account in this research work. The accuracy in the machine learning algorithm can be improved by introducing Bat Algorithm with feature selection (BFS) in the… More >