Mohammad Areeb Qazi, Anees Ur Rehman Hashmi, Santosh Sanjeev, Ibrahim Almakky, Numan Saeed, Camila González, Mohammad Yaqub
Deep Learning has shown great success in reshaping medical imaging, yet it faces several challenges hindering widespread application. Distribution shifts in the continuously evolving data stream and catastrophic forgetting are two barriers that considerably increase the performance gap between research and applications. Continual Learning offers promise in addressing these hurdles by enabling the sequential acquisition of new knowledge without forgetting previous information. In this survey, we comprehensively review the recent literature on continual learning in the medical domain, highlight recent trends, and point out several practical issues. Specifically, we survey the continual learning studies on classification, segmentation, detection, and other related tasks in the medical domain and develop a taxonomy for the reviewed studies. We also critically discuss the current state of continual learning in medical imaging, including identifying open problems and outlining promising future directions. We hope that this survey provides researchers with a useful overview of the developments in the field and further increases engagement with this topic within the community. To keep up with the fast-paced advancements in the field, we will routinely update the repository with the latest relevant papers at https://github.com/BioMedIA-MBZUAI/awesome-cl-in-medical.
{"title":"Continual Learning in Medical Imaging: A Survey and Practical Analysis","authors":"Mohammad Areeb Qazi, Anees Ur Rehman Hashmi, Santosh Sanjeev, Ibrahim Almakky, Numan Saeed, Camila González, Mohammad Yaqub","doi":"10.1145/3785663","DOIUrl":"https://doi.org/10.1145/3785663","url":null,"abstract":"Deep Learning has shown great success in reshaping medical imaging, yet it faces several challenges hindering widespread application. Distribution shifts in the continuously evolving data stream and catastrophic forgetting are two barriers that considerably increase the performance gap between research and applications. Continual Learning offers promise in addressing these hurdles by enabling the sequential acquisition of new knowledge without forgetting previous information. In this survey, we comprehensively review the recent literature on continual learning in the medical domain, highlight recent trends, and point out several practical issues. Specifically, we survey the continual learning studies on classification, segmentation, detection, and other related tasks in the medical domain and develop a taxonomy for the reviewed studies. We also critically discuss the current state of continual learning in medical imaging, including identifying open problems and outlining promising future directions. We hope that this survey provides researchers with a useful overview of the developments in the field and further increases engagement with this topic within the community. To keep up with the fast-paced advancements in the field, we will routinely update the repository with the latest relevant papers at https://github.com/BioMedIA-MBZUAI/awesome-cl-in-medical.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"7 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145770766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dalal Thair, Hala Abdulwahab, Fahad AL-Dhief, Nurhizam Safie
This systematic review provides a detailed analysis of zero-watermarking techniques specifically designed for the safeguarding of 3D video content, which is presented in this study, emphasizing the distinct difficulties and intricacies involved in ensuring the security of digital assets in this specialized field. The research systematically examines various zero-watermarking methodologies through a comprehensive review and comparative analysis, assessing their performance metrics, practical applications, and effectiveness in real-world scenarios. Through a thorough examination and comparative analysis, the study methodically evaluates different zero-watermarking approaches, analyzing their performance indicators, practical uses, and efficacy in real-world situations. The research also examines the incorporation of state-of-the-art technologies, such as Generative Adversarial Networks (GANs) and blockchain, which signify notable progress in the domain of digital watermarking. The aforementioned technologies highlight the necessity for more resilient, undetectable, and secure methods to maintain the authenticity and ownership of 3D video material. This research presented a series of answers to the most significant challenges encountered by previous studies, such as picture quality decline and resistance to geometric assaults. It also addressed the issue of 3D model damage. Ultimately contributing to the development of more sophisticated and reliable digital rights management strategies, the findings of this research emphasize the crucial role of zero watermarking enhanced by artificial intelligence in addressing the specific challenges associated with 3D video content protection.
{"title":"A Systematic Review: Zero-Watermarking Techniques Analysis for 3D Video Protection","authors":"Dalal Thair, Hala Abdulwahab, Fahad AL-Dhief, Nurhizam Safie","doi":"10.1145/3778748","DOIUrl":"https://doi.org/10.1145/3778748","url":null,"abstract":"This systematic review provides a detailed analysis of zero-watermarking techniques specifically designed for the safeguarding of 3D video content, which is presented in this study, emphasizing the distinct difficulties and intricacies involved in ensuring the security of digital assets in this specialized field. The research systematically examines various zero-watermarking methodologies through a comprehensive review and comparative analysis, assessing their performance metrics, practical applications, and effectiveness in real-world scenarios. Through a thorough examination and comparative analysis, the study methodically evaluates different zero-watermarking approaches, analyzing their performance indicators, practical uses, and efficacy in real-world situations. The research also examines the incorporation of state-of-the-art technologies, such as Generative Adversarial Networks (GANs) and blockchain, which signify notable progress in the domain of digital watermarking. The aforementioned technologies highlight the necessity for more resilient, undetectable, and secure methods to maintain the authenticity and ownership of 3D video material. This research presented a series of answers to the most significant challenges encountered by previous studies, such as picture quality decline and resistance to geometric assaults. It also addressed the issue of 3D model damage. Ultimately contributing to the development of more sophisticated and reliable digital rights management strategies, the findings of this research emphasize the crucial role of zero watermarking enhanced by artificial intelligence in addressing the specific challenges associated with 3D video content protection.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"21 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145770763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nowadays, virtual worlds are evolving into immersive metaverses , i.e., collective, shared virtual spaces that arise from the convergence of virtual reality (VR), augmented reality (AR), the internet, and additional digital technologies. These environments allow users to interact through avatars. While research has explored the technologies and social dynamics of the metaverse, two key limitations remain. First, there is no systematic overview of the expertise required to build metaverses and the key publication venues. Second, the socio-technical issues have not been fully synthesized or made instrumental for developing holistic design approaches that address both social and technical constraints. A deeper investigation is needed to guide future research, highlight challenges, and foster collaboration across disciplines. In this paper, we propose a systematic mapping study that addresses the limitations identified. From an initial pool of 2,323 sources, we identify 63 primary resources to (1) characterize the research community around metaverse and (2) elicit, synthesize, and categorize 19 social and 18 technical issues affecting the development of an effective metaverse. Based on our results, we contextualize the catalog of issues with respect to the current body of knowledge, providing insights and a research roadmap that transforms issues into actionable challenges in the scope of a novel, unified research asset coined “metaverse engineering” , i.e., the multidisciplinary discipline to identify processes and instruments to design socio-technical metaverses.
{"title":"Another Brick in the Wall: A Systematic Mapping Study Toward Defining Metaverse Engineering Through Socio-Technical Issues","authors":"Dario Di Dario, Fabio Palomba, Carmine Gravino","doi":"10.1145/3785659","DOIUrl":"https://doi.org/10.1145/3785659","url":null,"abstract":"Nowadays, virtual worlds are evolving into immersive metaverses , i.e., collective, shared virtual spaces that arise from the convergence of virtual reality (VR), augmented reality (AR), the internet, and additional digital technologies. These environments allow users to interact through avatars. While research has explored the technologies and social dynamics of the metaverse, two key limitations remain. First, there is no systematic overview of the expertise required to build metaverses and the key publication venues. Second, the socio-technical issues have not been fully synthesized or made instrumental for developing holistic design approaches that address both social and technical constraints. A deeper investigation is needed to guide future research, highlight challenges, and foster collaboration across disciplines. In this paper, we propose a systematic mapping study that addresses the limitations identified. From an initial pool of 2,323 sources, we identify 63 primary resources to (1) characterize the research community around metaverse and (2) elicit, synthesize, and categorize 19 social and 18 technical issues affecting the development of an effective metaverse. Based on our results, we contextualize the catalog of issues with respect to the current body of knowledge, providing insights and a research roadmap that transforms issues into actionable challenges in the scope of a novel, unified research asset coined “metaverse engineering” , i.e., the multidisciplinary discipline to identify processes and instruments to design socio-technical metaverses.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"111 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145770764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the rapid growth of the Internet of Things, service explosion has become a serious challenge, hindering efficient collaboration in the Cyber-Physical-Social-Thinking (CPST) space. In response, the Internet of X (IoX) under the CPST framework is examined through an in-depth analysis from three dimensions: Internet of Things (IoT), Internet of People (IoP), and Internet of Thinking (IoTk). The rapid growth of IoT devices and data, the significant increase in the frequency of personalized interactions in IoP, and the explosive growth in the demand for IoTk cognitive services have caused existing communication, computing, and storage systems to face problems such as response delays and resource bottlenecks. To address the above challenges, a new AGI-based paradigm is proposed to address the problem of service explosion. The main mitigation approaches include interoperability, data/network efficiency, and security in IoT; scalable user management, personalization, and privacy in IoP; and brain-computer interaction, neural data processing, and brain information privacy in IoTk. Subsequently, the case of smart homes is employed to elaborate on how AGI alleviates the service explosion phenomenon in IoT, IoP, and IoTk scenarios. Finally, the development of artificial super intelligence is anticipated, and potential directions for future research are outlined.
{"title":"AGI-Enabled Solutions for Service Explosion in IoX: A Cyber-Physical-Social-Thinking Perspective","authors":"Qikai Wei, Huansheng Ning, Feifei Shi, Tao Zhu, Jianguo Ding, Abdelouahid Derhab, Mahmoud Daneshmand","doi":"10.1145/3785669","DOIUrl":"https://doi.org/10.1145/3785669","url":null,"abstract":"With the rapid growth of the Internet of Things, service explosion has become a serious challenge, hindering efficient collaboration in the Cyber-Physical-Social-Thinking (CPST) space. In response, the Internet of X (IoX) under the CPST framework is examined through an in-depth analysis from three dimensions: Internet of Things (IoT), Internet of People (IoP), and Internet of Thinking (IoTk). The rapid growth of IoT devices and data, the significant increase in the frequency of personalized interactions in IoP, and the explosive growth in the demand for IoTk cognitive services have caused existing communication, computing, and storage systems to face problems such as response delays and resource bottlenecks. To address the above challenges, a new AGI-based paradigm is proposed to address the problem of service explosion. The main mitigation approaches include interoperability, data/network efficiency, and security in IoT; scalable user management, personalization, and privacy in IoP; and brain-computer interaction, neural data processing, and brain information privacy in IoTk. Subsequently, the case of smart homes is employed to elaborate on how AGI alleviates the service explosion phenomenon in IoT, IoP, and IoTk scenarios. Finally, the development of artificial super intelligence is anticipated, and potential directions for future research are outlined.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"13 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145770765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mengmeng Yang, Youyang Qu, Thilina Ranbaduge, Chandra Thapa, Nazatul Haque Sultan, Ming Ding, Hajime Suzuki, Wei Ni, Sharif Abuadbba, David Smith, Paul Tyler, Josef Pieprzyk, Thierry Rakotoarivelo, Xinlong Guan, Sirine Mrabet
The vision for 6G aims to enhance network capabilities, supporting an intelligent digital ecosystem where artificial intelligence (AI) is a key. However, the expansion of 6G raises critical security and privacy concerns due to the increased integration of IoT devices, edge computing, and AI. This survey provides a comprehensive overview of 6G protocols with a focus on security and privacy, identifying risks that have not been experienced in preceding 5G systems, and presenting mitigation strategies. While many vulnerabilities from earlier generations persist, the introduction of AI/ML introduces novel risks like model inversion and malicious manipulation of AI. Vulnerabilities in emerging personal IoT networks and autonomous vehicles are also underscored, where falsified command signaling or privacy leakage can pose safety and ethical concerns. The survey also discusses the transition toward lattice-based, post-quantum encryption standards, and identifies limitations in current security frameworks and calls for new, dynamic approaches tailored to 6G’s complexity. Close collaboration among stakeholders, including governments, industry, and researchers, is indispensable to developing robust standards, secure architectures, and risk assessment frameworks that address AI, quantum threats, and privacy at scale.
{"title":"From 5G to 6G: A Survey on Security, Privacy, and Standardization Pathways","authors":"Mengmeng Yang, Youyang Qu, Thilina Ranbaduge, Chandra Thapa, Nazatul Haque Sultan, Ming Ding, Hajime Suzuki, Wei Ni, Sharif Abuadbba, David Smith, Paul Tyler, Josef Pieprzyk, Thierry Rakotoarivelo, Xinlong Guan, Sirine Mrabet","doi":"10.1145/3785467","DOIUrl":"https://doi.org/10.1145/3785467","url":null,"abstract":"The vision for 6G aims to enhance network capabilities, supporting an intelligent digital ecosystem where artificial intelligence (AI) is a key. However, the expansion of 6G raises critical security and privacy concerns due to the increased integration of IoT devices, edge computing, and AI. This survey provides a comprehensive overview of 6G protocols with a focus on security and privacy, identifying risks that have not been experienced in preceding 5G systems, and presenting mitigation strategies. While many vulnerabilities from earlier generations persist, the introduction of AI/ML introduces novel risks like model inversion and malicious manipulation of AI. Vulnerabilities in emerging personal IoT networks and autonomous vehicles are also underscored, where falsified command signaling or privacy leakage can pose safety and ethical concerns. The survey also discusses the transition toward lattice-based, post-quantum encryption standards, and identifies limitations in current security frameworks and calls for new, dynamic approaches tailored to 6G’s complexity. Close collaboration among stakeholders, including governments, industry, and researchers, is indispensable to developing robust standards, secure architectures, and risk assessment frameworks that address AI, quantum threats, and privacy at scale.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"34 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145771129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The digital landscape increasingly relies on data exchange, underscoring the importance of Digital Identity Management (DIM) systems. However, current models face vulnerabilities, leading to the demand for more secure, decentralized, and user-centric solutions. Self-sovereign Identity (SSI) has emerged as a promising paradigm supported by blockchain technology, granting users control over their digital identities. This paper reviews existing research and commercial SSI solutions, assessing their feasibility and effectiveness. We thoroughly explore SSI’s concept, structure, and components while addressing challenges like scalability, usability, Quantum computing-based attacks and corresponding resistance mechanisms, data storage, and governance. Additionally, we highlight recent advancements and identify research gaps, suggesting future directions for enhanced DIM solutions.
{"title":"Self-Sovereign Identity as a Secure and Trustworthy Approach to Digital Identity Management: A Comprehensive Survey","authors":"Efat Fathalla, Mohamed Azab, ChunSheng Xin, Hongyi Wu","doi":"10.1145/3785466","DOIUrl":"https://doi.org/10.1145/3785466","url":null,"abstract":"The digital landscape increasingly relies on data exchange, underscoring the importance of Digital Identity Management (DIM) systems. However, current models face vulnerabilities, leading to the demand for more secure, decentralized, and user-centric solutions. Self-sovereign Identity (SSI) has emerged as a promising paradigm supported by blockchain technology, granting users control over their digital identities. This paper reviews existing research and commercial SSI solutions, assessing their feasibility and effectiveness. We thoroughly explore SSI’s concept, structure, and components while addressing challenges like scalability, usability, Quantum computing-based attacks and corresponding resistance mechanisms, data storage, and governance. Additionally, we highlight recent advancements and identify research gaps, suggesting future directions for enhanced DIM solutions.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"23 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145765469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chaoming Shi, Haomeng Xie, Zheng Yan, Laurence T. Yang
Blockchain is a decentralized ledger with a secure and immutable chain structure. The advanced attributes of blockchain, including decentralization, anonymity, transparency, and zero trust support, have positioned it as a transformative technology across different areas of expertise, like medicine, finance, and the Internet of Things (IoT). Nonetheless, blockchain’s progress has been constrained in various aspects, revealing inefficiency, privacy, high transaction fees, and challenges with on-chain storage. To address these limitations, off-chain technology has emerged as a solution by moving computation and storage overhead away from the blockchain. However, a comprehensive survey on off-chain schemes is lacking in the current literature. In this paper, we conduct a thorough survey on off-chain technologies. We first introduce the fundamental concepts and characteristics of both blockchain and off-chain technologies. Furthermore, we establish a thorough taxonomy of off-chain technologies based on distinct application scenarios. We put forth a series of evaluation criteria, based on which we seriously review and analyze the existing off-chain schemes to assess their strengths and limitations. Conclusively, we outline a list of open issues and propose promising future research directions based on our thorough review and analysis on off-chain technologies.
{"title":"A Survey on Off-chain Technologies","authors":"Chaoming Shi, Haomeng Xie, Zheng Yan, Laurence T. Yang","doi":"10.1145/3765897","DOIUrl":"https://doi.org/10.1145/3765897","url":null,"abstract":"Blockchain is a decentralized ledger with a secure and immutable chain structure. The advanced attributes of blockchain, including decentralization, anonymity, transparency, and zero trust support, have positioned it as a transformative technology across different areas of expertise, like medicine, finance, and the Internet of Things (IoT). Nonetheless, blockchain’s progress has been constrained in various aspects, revealing inefficiency, privacy, high transaction fees, and challenges with on-chain storage. To address these limitations, off-chain technology has emerged as a solution by moving computation and storage overhead away from the blockchain. However, a comprehensive survey on off-chain schemes is lacking in the current literature. In this paper, we conduct a thorough survey on off-chain technologies. We first introduce the fundamental concepts and characteristics of both blockchain and off-chain technologies. Furthermore, we establish a thorough taxonomy of off-chain technologies based on distinct application scenarios. We put forth a series of evaluation criteria, based on which we seriously review and analyze the existing off-chain schemes to assess their strengths and limitations. Conclusively, we outline a list of open issues and propose promising future research directions based on our thorough review and analysis on off-chain technologies.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"152 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145765468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Predicting stock prices presents a challenging research problem due to the inherent volatility and non-linear nature of the stock market. In recent years, knowledge-enhanced stock price prediction methods have shown groundbreaking results by utilizing external knowledge to understand the stock market. Despite the importance of these methods, there is a scarcity of scholarly works that systematically synthesize previous studies from the perspective of external knowledge types. Specifically, the external knowledge can be modeled in different data structures, which we group into non-graph-based formats and graph-based formats: 1) non-graph-based knowledge captures contextual information and multimedia descriptions specifically associated with an individual stock; 2) graph-based knowledge captures interconnected and interdependent information in the stock market. This survey paper aims to provide a systematic and comprehensive description of methods for acquiring external knowledge from various unstructured data sources and then incorporating it into stock price prediction models. We also explore fusion methods for combining external knowledge with historical price features. Moreover, this paper includes a compilation of relevant datasets and delves into potential future research directions in this domain.
{"title":"Methods for Acquiring and Incorporating Knowledge into Stock Price Prediction: A Survey","authors":"Liping Wang, Jiawei Li, Lifan Zhao, Zhizhuo Kou, Xiaohan Wang, Xinyi Zhu, Hao Wang, Yanyan Shen, Chen Lei","doi":"10.1145/3773079","DOIUrl":"https://doi.org/10.1145/3773079","url":null,"abstract":"Predicting stock prices presents a challenging research problem due to the inherent volatility and non-linear nature of the stock market. In recent years, knowledge-enhanced stock price prediction methods have shown groundbreaking results by utilizing external knowledge to understand the stock market. Despite the importance of these methods, there is a scarcity of scholarly works that systematically synthesize previous studies from the perspective of external knowledge types. Specifically, the external knowledge can be modeled in different data structures, which we group into non-graph-based formats and graph-based formats: 1) <jats:italic toggle=\"yes\">non-graph-based knowledge</jats:italic> captures contextual information and multimedia descriptions specifically associated with an individual stock; 2) <jats:italic toggle=\"yes\">graph-based knowledge</jats:italic> captures interconnected and interdependent information in the stock market. This survey paper aims to provide a systematic and comprehensive description of methods for acquiring external knowledge from various unstructured data sources and then incorporating it into stock price prediction models. We also explore fusion methods for combining external knowledge with historical price features. Moreover, this paper includes a compilation of relevant datasets and delves into potential future research directions in this domain.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"20 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145759516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The rapid advancement of Intelligent Transportation Systems (ITS) has led to a paradigm shift towards the adoption of Connected Autonomous Vehicles (CAVs). In recent years, CAVs have emerged as a prominent research focus due to their potential to reduce road traffic accidents caused by human error, optimize traffic flow, create new economic opportunities, and enhance travel convenience. However, the increasing demand for compute and delay-sensitive applications, such as real-time navigation and sensor data processing, exceeds the capabilities of current onboard vehicle resources. Consequently, task offloading has gained significant attention, allowing certain computational tasks generated by CAVs operations to be offloaded to external cloud or edge servers. The existing review literature has been limited in its focus on task offloading techniques specifically for CAVs architecture. Therefore, this study aims to present a comprehensive survey on task offloading in CAVs through a systematic review guided by key research questions. We first provide a technical background and then propose a broad coverage taxonomy of existing literature, analyzing promising solutions such as Machine Learning (ML) and heuristic-based techniques. In addition, we present a taxonomy of execution environments, metrics, and datasets. Finally, we highlight key research challenges and future trends, providing valuable insights for advancing task offloading in CAVs architecture.
{"title":"Task Offloading for CAVs Edge Computing Environment: Taxonomy, Critical Review, and Future Road Map","authors":"Bhoopendra Kumar, Aditya Bhardwaj, Dinesh Prasad Sahu","doi":"10.1145/3783984","DOIUrl":"https://doi.org/10.1145/3783984","url":null,"abstract":"The rapid advancement of Intelligent Transportation Systems (ITS) has led to a paradigm shift towards the adoption of Connected Autonomous Vehicles (CAVs). In recent years, CAVs have emerged as a prominent research focus due to their potential to reduce road traffic accidents caused by human error, optimize traffic flow, create new economic opportunities, and enhance travel convenience. However, the increasing demand for compute and delay-sensitive applications, such as real-time navigation and sensor data processing, exceeds the capabilities of current onboard vehicle resources. Consequently, task offloading has gained significant attention, allowing certain computational tasks generated by CAVs operations to be offloaded to external cloud or edge servers. The existing review literature has been limited in its focus on task offloading techniques specifically for CAVs architecture. Therefore, this study aims to present a comprehensive survey on task offloading in CAVs through a systematic review guided by key research questions. We first provide a technical background and then propose a broad coverage taxonomy of existing literature, analyzing promising solutions such as Machine Learning (ML) and heuristic-based techniques. In addition, we present a taxonomy of execution environments, metrics, and datasets. Finally, we highlight key research challenges and future trends, providing valuable insights for advancing task offloading in CAVs architecture.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"9 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145752827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Benjamin Carrion Schafer, Baharealsadat Parchamdar
Approximate Computing in hardware design has emerged as an alternative way to further reduce the power consumption of integrated circuits (ICs) by trading off errors at the output with simpler, and more efficient logic. So far, the main approaches in approximate computing have been to simplify the hardware circuit by applying different approximation primitives of different aggressiveness to the original hardware description until the maximum error threshold is met. Multiple of these primitives can also be combined to obtain better results. These primitives are often applied at different VLSI design stages to maximize their effect. Because of the importance of this topic, there exists a very large body of work and multiple surveys have tried to cover all of it. In this work we take a different approach and concentrate only on approximation computing techniques applied at the High-Level Synthesis (HLS) stage of the VLSI design flow. The reason for this is that approximations applied at the highest possible level of VLSI design abstraction also have the highest impact on the resultant circuit. Moreover, HLS is finally being widely embraced by hardware designers, and this work aims at presenting practical examples of how the different approximation primitives can be easily applied using commercial HLS tools. We finally present some typical pitfalls that designers should avoid when using approximate computing and point to some future direction in this area.
{"title":"Approximate Computing in High-Level Synthesis: From Survey to Practical Implementation","authors":"Benjamin Carrion Schafer, Baharealsadat Parchamdar","doi":"10.1145/3785334","DOIUrl":"https://doi.org/10.1145/3785334","url":null,"abstract":"Approximate Computing in hardware design has emerged as an alternative way to further reduce the power consumption of integrated circuits (ICs) by trading off errors at the output with simpler, and more efficient logic. So far, the main approaches in approximate computing have been to simplify the hardware circuit by applying different approximation primitives of different aggressiveness to the original hardware description until the maximum error threshold is met. Multiple of these primitives can also be combined to obtain better results. These primitives are often applied at different VLSI design stages to maximize their effect. Because of the importance of this topic, there exists a very large body of work and multiple surveys have tried to cover all of it. In this work we take a different approach and concentrate only on approximation computing techniques applied at the High-Level Synthesis (HLS) stage of the VLSI design flow. The reason for this is that approximations applied at the highest possible level of VLSI design abstraction also have the highest impact on the resultant circuit. Moreover, HLS is finally being widely embraced by hardware designers, and this work aims at presenting practical examples of how the different approximation primitives can be easily applied using commercial HLS tools. We finally present some typical pitfalls that designers should avoid when using approximate computing and point to some future direction in this area.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":"6 1","pages":""},"PeriodicalIF":16.6,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145728835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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