Said Benkirane¹, Azidine Guezzaz¹, Mourade Azrour¹, Akber Abid Gardezi², Shafiq Ahmad³, Abdelaty Edrees Sayed³, Salman Naseer⁴, Muhammad Shafiq^5,*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3781-3794, 2023, DOI:10.32604/cmc.2023.033119

Abstract Today, road safety remains a serious concern for governments around the world. In fact, approximately 1.35 million people die and 2–50 million are injured on public roads worldwide each year. Straight bends in road traffic are the main cause of many road accidents, and excessive and inappropriate speed in this very critical area can cause drivers to lose their vehicle stability. For these reasons, new solutions must be considered to stop this disaster and save lives. Therefore, it is necessary to study this topic very carefully and use new technologies such as Vehicle Ad Hoc Networks (VANET), Internet of Things… More >

Kazuki Abe^1,*, Hideki Fujii², Shinobu Yoshimura²

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1091-1109, 2023, DOI:10.32604/cmes.2022.021376

Abstract Traffic simulators are utilized to solve a variety of traffic-related problems. For such simulators, origin-destination (OD) traffic volumes as mobility demands are required to input, and we need to estimate them. The authors regard an OD estimation as a bi-level programming problem, and apply a microscopic traffic simulation model to it. However, the simulation trials can be computationally expensive if full dynamic rerouting is allowed, when employing multi-agent-based models in the estimation process. This paper proposes an efficient OD estimation method using a multi-agent-based simulator with restricted dynamic rerouting to reduce the computational load. Even though, in the case of… More >

Atif Ishaq Khan^*, Syed Asad Raza Kazmi, Awais Qasim

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1183-1197, 2023, DOI:10.32604/cmc.2023.032691

Abstract A self-adaptive resource provisioning on demand is a critical factor in cloud computing. The selection of accurate amount of resources at run time is not easy due to dynamic nature of requests. Therefore, a self-adaptive strategy of resources is required to deal with dynamic nature of requests based on run time change in workload. In this paper we proposed a Cloud-based Adaptive Resource Scheduling Strategy (CARSS) Framework that formally addresses these issues and is more expressive than traditional approaches. The decision making in CARSS is based on more than one factors. The MAPE-K based framework determines the state of the… More >

Fatih Aydemir¹, Aydin Cetin^2,*

Computer Systems Science and Engineering, Vol.45, No.1, pp. 215-230, 2023, DOI:10.32604/csse.2023.031116

Abstract Dynamic area coverage with small unmanned aerial vehicle (UAV) systems is one of the major research topics due to limited payloads and the difficulty of decentralized decision-making process. Collaborative behavior of a group of UAVs in an unknown environment is another hard problem to be solved. In this paper, we propose a method for decentralized execution of multi-UAVs for dynamic area coverage problems. The proposed decentralized decision-making dynamic area coverage (DDMDAC) method utilizes reinforcement learning (RL) where each UAV is represented by an intelligent agent that learns policies to create collaborative behaviors in partially observable environment. Intelligent agents increase their… More >

S. Sakthivel¹, V. Vivekanandhan^2,*, M. Manikandan²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 853-866, 2023, DOI:10.32604/iasc.2023.026289

Abstract Irrigation plays a significant role in various agricultural cropping methods deployed in semiarid and arid regions where valuable water applications and managing are considered crucial concerns. Multiple factors such as weather, soil, water, and crop data need to be considered for irrigation maintenance in an efficient besides uniform manner from multifaceted and different information-based systems. A Multi-Agent System (MAS) has been proposed recently based on diverse agent subsystems with definite objectives for attaining global MAS objective and is deployed on Cloud Computing paradigm capable of gathering information from Wireless Sensor Networks (WSNs) positioned in rice, cotton, cassava crops for knowledge… More >

Te Xu¹, Zhixian Lin¹, Xinwei Lin¹, Changsheng Lin¹, Feng Gao¹, Zixuan Li², Peiwen Liu^2,*

Energy Engineering, Vol.119, No.4, pp. 1501-1515, 2022, DOI:10.32604/ee.2022.020082

Abstract With the help of smart grid technologies, a lot of electrical loads can provide demand response to support the active power balance of the grid. Compared with centralized control methods, decentralized methods reduce the computational burden of the control center and enhance the reliability of the communication. In this paper, a novel second-order multi-agent consensus control method is proposed for load control problem. By introducing the velocity state into the model, the proposed method achieves better performance than traditional ones. Simulation results verify the effectiveness of the proposed method. More >

Jargalsaikhan Narantuya^1,*, Jun-Sik Shin², Sun Park², JongWon Kim²

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4375-4395, 2022, DOI:10.32604/cmc.2022.023318

Abstract As the complexity of deep learning (DL) networks and training data grows enormously, methods that scale with computation are becoming the future of artificial intelligence (AI) development. In this regard, the interplay between machine learning (ML) and high-performance computing (HPC) is an innovative paradigm to speed up the efficiency of AI research and development. However, building and operating an HPC/AI converged system require broad knowledge to leverage the latest computing, networking, and storage technologies. Moreover, an HPC-based AI computing environment needs an appropriate resource allocation and monitoring strategy to efficiently utilize the system resources. In this regard, we introduce a… More >

J. Arravinth^*, D. Manjula

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 133-147, 2022, DOI:10.32604/iasc.2022.025292

Abstract Cloud computing is the ability to provide new technologies and standard cloud services. One of the essential features of cloud computing is the provision of “unlimited” computer resources to users on demand. However, single cloud resources are generally limited and may not be able to cope with the sudden rise in user needs. Therefore, the inter-cloud concept is introduced to support resource sharing between clouds. In this system, each cloud can tap the resources of other clouds when there are not enough resources to meet the demands of the consumer. In cloud computing, allocating the available resources of service nodes… More >

Farah Tawfiq Abdul Hussien^*, Abdul Monem S. Rahma, Hala Bahjat Abdul Wahab

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 499-514, 2022, DOI:10.32604/iasc.2022.025091

Abstract Providing security for the customers in the e-commerce system is an essential issue. Providing security for each single online customer at the same time is considered a time consuming process. For a huge websites such task may cause several problems including response delay, losing the customer orders and system deadlock or crash, in which reduce system performance. This paper aims to provide a new prototype structure of multi agent system that solve the problem of providing security and avoid the problems that may reduce system performance. This is done by creating a software agent which is settled into the customer… More >

Prohim Tam¹, Sa Math¹, Ahyoung Lee², Seokhoon Kim^1,3,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3319-3335, 2022, DOI:10.32604/cmc.2022.023215

Abstract Federated learning (FL) activates distributed on-device computation techniques to model a better algorithm performance with the interaction of local model updates and global model distributions in aggregation averaging processes. However, in large-scale heterogeneous Internet of Things (IoT) cellular networks, massive multi-dimensional model update iterations and resource-constrained computation are challenging aspects to be tackled significantly. This paper introduces the system model of converging software-defined networking (SDN) and network functions virtualization (NFV) to enable device/resource abstractions and provide NFV-enabled edge FL (eFL) aggregation servers for advancing automation and controllability. Multi-agent deep Q-networks (MADQNs) target to enforce a self-learning softwarization, optimize resource allocation… More >