Intelligent Optimization of Wireless Sensor Networks through Bio-Inspired Computing: Survey and Future Directions by Sohail Jabbar, Rabia Iram, Abid Ali Minhas, Imran Shafi, Shehzad Khalid, Muqeet Ahmad

“…This survey article is a comprehensive discussion on Intelligent Optimization of Wireless Sensor Networks through Bio-Inspired Computing. The marvelous perfection of biological systems and its different aspects for optimized solutions for non-biological problems is presented here in detail. …”
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Design of MobileNetV3 network accelerator based on dynamic adaptive computing engine by Xiang Haobin, Yang Ruimin, Wu Wentao, Li Chunlei, Dong Yan

“…To address this problem, this paper proposes a MobileNetV3 network accelerator based on a dynamic adaptive computing engine. Firstly, a pipeline inference architecture of local perception area convolution is designed to achieve highly parallel processing and buffer scheduling of features and weights. …”
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Edge computing for detection of ship and ship port from remote sensing images using YOLO by Vasavi Sanikommu, Sai Pravallika Marripudi, Harini Reddy Yekkanti, Revanth Divi, R. Chandrakanth, P. Mahindra

“…This deployment will ensure scalability, efficient processing, and reduced reliance on central computing resources, making it especially suitable for maritime settings in which real-time monitoring is vital. …”
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Dynamic QoS-aware intelligent edge computing resource management algorithm for body area networks by MU Siqi, WEN Shuo, LU Yang, AI Bo

“…Firstly, considering the Markov nature of multi-source task priorities and channel state changes in BAN, the original stochastic optimization problem was transformed into an infinite horizon Markov decision process problem. Then, a multi-source task priority sequence for each BAN was constructed and an online decision-making method that integrated proximal policy optimization (PPO) was proposed for task offloading and computing resource allocation. …”
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Scalable Resource Provisioning Framework for Fog Computing Using LLM-Guided Q-Learning Approach by Bhargavi Krishnamurthy, Sajjan G. Shiva

“…The experimental results ensure that the proposed framework is good with respect to processing delay, energy consumption, load balancing, and service level agreement violation under a finite and infinite fog computing environment. …”
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Real-Time Compressive Sensing MRI Reconstruction Using GPU Computing and Split Bregman Methods by David S. Smith, John C. Gore, Thomas E. Yankeelov, E. Brian Welch

“…We have accelerated our CS MRI reconstruction by factors of up to 27 by using a split Bregman solver combined with a graphics processing unit (GPU) computing platform. The increases in speed we find are similar to those we measure for matrix multiplication on this platform, suggesting that the split Bregman methods parallelize efficiently. …”
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Future perspectives on internet of vehicles resource management: digital twin-enabled edge computing frameworks by Jihong Xie, Gui Wu, Xiang Zhou, Shanshan Deng

“…DTs replicate real entities in the virtual domain with real-time control, diagnostics, maintenance, and better management. With edge computing, processing data near the source, these technologies significantly lower response time and optimize system performance. …”
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Flexible hybrid edge computing IoT architecture for low-cost bird songs detection system by Francisco A. Delgado-Rajó, Carlos M. Travieso-Gonzalez

“…This study proposes a flexible hybrid edge computing IoT architecture for a low-cost bird song detection system. …”
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Computing medial axis of a simple polygon in linear time based on R-L sequence by Hongyu Chen, Xiaodiao Chen, Yizhao Xue

“…Medial axis computation has wide applications in pattern recognition, image processing, finite element mesh generation, and CNC tool path extraction. …”
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ScalEdge: A framework for scalable edge computing in Internet of things–based smart systems by Mohammad Babar, Muhammad Sohail Khan

“…The Internet of things (IoT) devices are resource-constrained, unable to process compute-intensive tasks. The convergence of edge computing and IoT with computation offloading offers a feasible solution in terms of performance. …”
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An efficient and secure data auditing scheme based on fog-to-cloud computing for Internet of things scenarios by Jun-Feng Tian, Hao-Ning Wang

“…Since the fog computing center only has a part of the private key generated using the identity information, the security of the system will not be damaged due to the leakage of part of the private key held by the fog center, and the fog center significantly participates in the signature generation process, which significantly reduces the computation and communication overhead of the Internet of things device. …”
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A data and knowledge-driven practice for ensuring stability in ultra-large intelligent computing clusters by NIU Hongweihua, HUANG Yongbao, DING Guoqiang, HUANG Bao, ZHAO Zhiwen, XU Yang, WANG Tao, ZHANG Ruiling, WANG Xuan, ZHANG Yixiang

“…A data and knowledge-driven stability assurance scheme for such clusters was proposed to address the issues of frequent hardware failures, persistently high task training failure rates, and difficulties in cross-domain problem localization within ultra-large intelligent computing clusters with over ten thousand computing cards. …”
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Secure intelligent reflecting surface assisted mobile edge computing system with wireless power transfer by Dawei Wang, Xuanrui Li, Menghan Wu, Yixin He, Yi Lou, Yu Pang, Yi Lu

“…Then, powered by the harvested energy, all WDs securely offload their computation tasks through the two links in the time division multiple access mode. …”
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Preface to Special Issue on Scientific Computing and Learning Analytics for Smart Healthcare Systems (Part II) by Chinmay Chakraborty, Sayonara Barbosa, Lalit Garg

“… This special issue introduces emerging intelligent healthcare technologies that incorporate big medical data, artificial intelligence, scientific computing, federated learning, bio-inspired computation, the Internet of Medical Things, security and privacy, semantic databases, etc. …”
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An energy-saving virtual machine scheduling algorithm for resource management based on cloud computing technology by Liangyu Zhang

“…In this paper, the current research status of cloud computing and virtual machine scheduling in cloud computing environments is analyzed, and the concept and characteristics, classification, application scenarios, and key technologies of cloud computing are elaborated. …”
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Service Virtualization Using a Non-von Neumann Parallel, Distributed, and Scalable Computing Model by Rao Mikkilineni, Giovanni Morana, Daniele Zito, Marco Di Sano

“…This paper describes a prototype implementing a high degree of transaction resilience in distributed software systems using a non-von Neumann computing model exploiting parallelism in computing nodes. …”
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Enhancing Property-Based Token Attestation With Homomorphic Encryption (PTA-HE) for Secure Mobile Computing by Thinh Le Vinh, Huan Thien Tran, Samia Bouzefrane

“…This paper proposes PTA-HE, an enhanced Property-based Token Attestation scheme integrated with Homomorphic Encryption (HE), specifically designed to address critical security challenges in mobile cloud computing environments. Traditional Property-based Token Attestation (PTA) protocols, although foundational, inherently lack robust mechanisms to secure sensitive data during active processing stages, exposing data to potential confidentiality and integrity breaches. …”
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Paint shop vehicle sequencing based on quantum computing considering color changeover and painting quality by Jing Huang, Qing Chang, Hua-Tzu Fan

“…With typically hundreds of vehicles in one shift, the paint shop sequencing problem is intractable in classical computing. In this paper, we propose to solve a general paint shop sequencing problem using state-of-the-art quantum computing algorithms. …”
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Task Offloading with LLM-Enhanced Multi-Agent Reinforcement Learning in UAV-Assisted Edge Computing by Feifan Zhu, Fei Huang, Yantao Yu, Guojin Liu, Tiancong Huang

“…Unmanned aerial vehicles (UAVs) furnished with computational servers enable user equipment (UE) to offload complex computational tasks, thereby addressing the limitations of edge computing in remote or resource-constrained environments. …”
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Fault-Tolerant Scheduling Mechanism for Dynamic Edge Computing Scenarios Based on Graph Reinforcement Learning by Yuze Zhang, Geming Xia, Chaodong Yu, Hongcheng Li, Hongfeng Li

“…With the proliferation of Internet of Things (IoT) devices and edge nodes, edge computing has taken on much of the real-time data processing and low-latency response tasks which were previously managed by cloud computing. …”
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