The Great Chains of Computing: Informatics at Multiple Scales by Kevin Kirby, James Walden, Rudy Garns, Maureen Doyle

Get full text

A Study of Big Data in Cloud Computing by Imran Khan

“… Over the last two decades, the size and amount of data has increased enormously, which has changed traditional methods of data management and introduced two new technological terms: big data and cloud computing. Addressing big data, characterized by massive volume, high velocity and variety, is quite challenging as it requires large computational infrastructure to store, process and analyze it. …”
Get full text

Face Mask Detection at the Fog Computing Gateway by Srinivasa Raju Rudraraju, Nagender Kumar Suryadevara, Atul Negi

Get full text

The Fog Computing Paradigm: Scenarios and Security Issues by Ivan Stojmenovic, Sheng Wen

Get full text

An Edge Computing Collaboration Solution for Internet of Vehicles by Vu Khanh Quy, Dang Van Anh, Vi Hoai Nam, Nguyen Minh Quy, Anh-Ngoc Le

Get full text

Editorial: Artificial Intelligence and Cybersecurity in Pervasive Computing by Ji-Jian Chin

“…This issue features seven articles on these intersections, including four AI articles exploring natural language processing and computer vision, and three cybersecurity articles covering cryptography, medical devices, and maritime security.…”
Get full text

REVIEW ON FOG COMPUTING – APPLICATIONS, SECURITY, AND SOLUTIONS by Varun Varma Sangaraju, SV Achuta Rao, Amjan Shaik, Prasuna VG, Nagaraju P B S.R.K.R.

“…A distributed computing model known as fog computing lies near the user for efficient data processing and analysis. …”
Get full text

Memory technology enabling future computing systems by Paolo Fantini

“…This work draws the directions that address the building of more efficient future computing systems, namely, (a) the memory and storage technology roadmap; (b) innovative interconnect systems between memory and logic devices; and (c) overcoming of the von Neumann computing paradigm.…”
Get full text

Survey on edge computing technology for autonomous driving by Pin LYU, Jia XU, Taoshen LI, Wenbiao XU

“…Edge computing plays an extremely important role in the environment perception and data processing of autonomous driving.Autonomous driving vehicles can expand their perception scope by obtaining environmental information from edge nodes, and can also deal with the problem of insufficient computing resources by offloading tasks to edge nodes.Compared with cloud computing, edge computing avoids high latency caused by long-distance data transmission, and provides autonomous driving vehicles with faster responses, and relieves the traffic load of the backbone network.Firstly, the edge computing-based cooperative perception and task offloading technologies for autonomous vehicles were introduced firstly, and related challenging issues were also proposed.Then the state-of-the-art of cooperative perception and task offloading technologies were analyzed and summarized.Finally, the problems need to be further studied in this field were discussed.…”
Get full text

A blockchain sharding scheme in edge computing by Jun WANG, Jianwei MA, Jinxi LUO

“…The low security and poor privacy of the data in edge computing restrict the development of edge computing.Block chains can provide security for data in edge computing using their own tamper resistance, while protecting privacy by use of traceability.But the bottleneck of blockchain's scalability has become a barrier to their application in the field of edge computing.To solve the problem that blockchain can not meet the needs of a large number of nodes to process data at the same time when applied to edge computing, a two-layer sharding scheme was presented, which meets the needs of edge computing scenarios.Geographic location-based partitioning of nodes was implemented using the improved K-means algorithm, and a local blockchain network consensus (LBNC) algorithm was designed based on the idea of delegated proof of stake (DPoS) and practical Byzantine fault tolerance (PBFT).Simulation results show that the proposed scheme has less delay and higher throughput than those of PBFT, and the total throughput increases with the number of shards.…”
Get full text

Practical few-atom quantum reservoir computing by Chuanzhou Zhu, Peter J. Ehlers, Hendra I. Nurdin, Daniel Soh

“…We demonstrate that the quantum reservoir outperforms traditional classical reservoir computing in both memory retention and nonlinear data processing through two tasks, namely, the prediction of time-series data using the Mackey-Glass task and the classification of sine-square waveforms. …”
Get full text

The Opportunities and Challenges in Integrating AI with Quantum Computing by Tomasz Słapczyński, Marlena Stradomska

“… The convergence of Artificial Intelligence (AI) and Quantum Computing (QC) marks a potentially transformative technological frontier. …”
Get full text

Service migration of heterogeneous cloud computing platform by Feng WEI, Fei DING, Pengju JIAO, Yang LI, Yanshan CHEN, Dengyin ZHANG

“…With the rapid development of 5G communication technology,Internet+ and the Internet of things (IoT),cloud computing as an Internet-based virtual resource management and a distributed computing technology,provides services to users in a dynamic,on-demand and measurable manner.The solution of migrating the service platform to the cloud computing platform can realize rapid service deployment and effectively save service innovation and operating cost.With the research of the cloud computing platform-based service migration technology,the China Mobile’s OpenStack-based cloud computing architecture was taken as an example.The technical principles and core points of the mainstream service migration schemes were analyzed,such as offline migration,online migration based on platform functions,online service migration based on the agent block level and online service migration based on agent file level.The general service migration process and method were also given.Finally,three types of online migration schemes were experimentally verified through the actual platform.The technical advantages and adaptation scenarios were analyzed separately to guide the production practice of future business migration.…”
Get full text

Fast Optical Switching for Computing-Power Interconnects by YIN Lin, WANG Fu, WANG Xiaolong, GUO Wenkui, ZONG Yichen

“…On the one hand, high density, low-latency processing and computing resource scheduling are required within the AIDC to meet large-scale real-time training and reasoning. …”
Get full text

QPSO-Based Adaptive DNA Computing Algorithm by Mehmet Karakose, Ugur Cigdem

“…Some contributions provided by the proposed QPSO based on adaptive DNA computing algorithm are as follows: (1) parameters of population size, crossover rate, maximum number of operations, enzyme and virus mutation rate, and fitness function of DNA computing algorithm are simultaneously tuned for adaptive process, (2) adaptive algorithm is performed using QPSO algorithm for goal-driven progress, faster operation, and flexibility in data, and (3) numerical realization of DNA computing algorithm with proposed approach is implemented in system identification. …”
Get full text

Seismic Wave Propagation Simulation With Quantum Computing by Xixiang Wen, Yanfei Wang

“…Abstract Nowadays, the utilization of quantum computing is on the rise, with its applications extending across numerous fields. …”
Get full text

Massive Crowd Simulation With Parallel Computing on GPU by Vincenzo Lombardo, Davide Gadia, Dario Maggiorini

“…Traditional approaches to crowd simulation rely on heavy Central Processing Unit (CPU) computation. This approach has limitations in terms of scalability and performance, which are solvable with the use of Graphics Programming Units (GPUs) and parallel computing techniques. …”
Get full text

On the Lanczos Method for Computing Some Matrix Functions by Ying Gu, Hari Mohan Srivastava, Xiaolan Liu

Get full text

Compressing Neural Networks on Limited Computing Resources by Seunghyun Lee, Dongjun Lee, Minju Hyun, Heeje Kim, Byung Cheol Song

“…This enables rapid and stable sub-network discovery, significantly improving the pruning process. Second, to minimize the computational cost of knowledge distillation, we introduce a synthetic teacher assistant that leverages precomputed fixed knowledge—referring to the stored feature maps/logits of the teacher network. …”
Get full text

Biomimetic Computing for Efficient Spoken Language Identification by Gaurav Kumar, Saurabh Bhardwaj

“…The suggested technique demonstrates promising potential for practical applications in the field of multi-lingual voice processing.…”
Get full text