IEEE Transactions on Emerging Topics in Computing最新文献_第7页

Unleashing the Potential of Skyrmion Racetrack Memory as Energy-Efficient On-Chip Memory 释放Skyrmion赛道存储器作为高能效片上存储器的潜力

IF 4.8 2区计算机科学

IEEE Transactions on Emerging Topics in Computing Pub Date : 2026-04-01 Epub Date: 2026-04-13 DOI: 10.1109/TETC.2026.3681511

Yong-Cheng Liaw;Ya-Hui Yang;Shuo-Han Chen

{"title":"Unleashing the Potential of Skyrmion Racetrack Memory as Energy-Efficient On-Chip Memory","authors":"Yong-Cheng Liaw;Ya-Hui Yang;Shuo-Han Chen","doi":"10.1109/TETC.2026.3681511","DOIUrl":"https://doi.org/10.1109/TETC.2026.3681511","url":null,"abstract":"Skyrmion racetrack memory (SK-RM) is a promising replacement for static random-access memory (SRAM) as an on-chip memory device owing to its high memory density and near-zero static power consumption. Unlike other nonvolatile random-access memories (NVRAMs), SK-RM requires shift operations to move data bits across access ports, where data reads and writes are performed, along the racetrack. To facilitate data management on SK-RM, word-based mapping and bit-interleaved mapping architectures have been proposed. While word-based mapping can achieve higher energy efficiency by re-permutating existing skyrmions to compose new data patterns, bit-interleaved mapping achieves shorter latency by parallel data reads and writes. However, when SK-RM is used as on-chip memory or as a cache device, current mapping architectures often lead to issues such as unpredictable access performance or excessive energy consumption during cache operations. This paper addresses the aforementioned concerns by proposing a dual-write-mode (SK-DWM) strategy that leverages the advantages of existing mapping architectures and allows seamless switching of the data update policy on SK-RM. In addition, to adaptively fit the write latency requirement of each on-chip memory access, this study further proposes the SK-DWM<inline-formula><tex-math>$^{+}$</tex-math></inline-formula> strategy to adjust the data update policy dynamically for either low-latency or energy-efficient data updates. The effectiveness of the proposed strategy is demonstrated through benchmark-driven experiments.","PeriodicalId":13156,"journal":{"name":"IEEE Transactions on Emerging Topics in Computing","volume":"14 2","pages":"500-514"},"PeriodicalIF":4.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148509436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing the Security of Rollup Sequencers Using Decentrally Attested TEEs 利用分散认证tee增强Rollup测序器的安全性

IF 4.8 2区计算机科学

IEEE Transactions on Emerging Topics in Computing Pub Date : 2026-04-01 Epub Date: 2026-03-17 DOI: 10.1109/TETC.2026.3671408

Giovanni Maria Cristiano;Salvatore D’Antonio;Jonah Giglio;Giovanni Mazzeo;Luigi Romano

{"title":"Enhancing the Security of Rollup Sequencers Using Decentrally Attested TEEs","authors":"Giovanni Maria Cristiano;Salvatore D’Antonio;Jonah Giglio;Giovanni Mazzeo;Luigi Romano","doi":"10.1109/TETC.2026.3671408","DOIUrl":"https://doi.org/10.1109/TETC.2026.3671408","url":null,"abstract":"The growing scalability demand of public Blockchains led to the rise of Layer-2 solutions, such as <italic>Rollups. Rollups improve transaction throughput by processing operations off-chain and posting the results on-chain. A critical component in Rollups is the <italic>Sequencer, responsible for receiving, ordering and batching transactions before they are submitted to the Layer-1 blockchain. While essential, the centralized nature of the Sequencer makes it vulnerable to attacks, such as censorship, transaction manipulation and tampering. To enhance its security, there exist solutions in the literature that shield the Sequencer inside a <italic>Trusted Execution Environment (TEE). However, the attestation of TEEs introduces additional centralization, which is in contrast with the core Blockchain principle. In this paper, we proposed a TEE-secured Sequencer equipped with a decentralized attestation mechanism. Design and implementation details of the proposed solution are given, with a focus on the system architecture, the TEE integration, and the decentralization of the attestation process. Additionally, we conducted an experimental evaluation on a realistic Rollup testnet. Experimental results showed that this approach ensures Sequencer integrity without sacrificing compatibility or deployability in existing Layer-2 architectures.","PeriodicalId":13156,"journal":{"name":"IEEE Transactions on Emerging Topics in Computing","volume":"14 2","pages":"440-455"},"PeriodicalIF":4.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148509983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Error Detection Schemes for Barrett Modular Multiplication of CT-BU on FPGA in PQC and FHE 基于FPGA的CT-BU巴雷特模乘法在PQC和FHE中的错误检测方案

IF 5.4 2区计算机科学

IEEE Transactions on Emerging Topics in Computing Pub Date : 2026-04-01 Epub Date: 2026-06-04 DOI: 10.1109/TETC.2026.3698063

Paresh Baidya;Rourab Paul;Vikas Srivastava;Sumit Kumar Debnath

{"title":"Error Detection Schemes for Barrett Modular Multiplication of CT-BU on FPGA in PQC and FHE","authors":"Paresh Baidya;Rourab Paul;Vikas Srivastava;Sumit Kumar Debnath","doi":"10.1109/TETC.2026.3698063","DOIUrl":"https://doi.org/10.1109/TETC.2026.3698063","url":null,"abstract":"Unintentional or intentionally faults into hardware accelerators of Post-Quantum Cryptography (PQC) or Fully Homomorphic Encryption (FHE) algorithms may lead to the leakage of sensitive information. If appropriate fault protection mechanisms are not employed, recent PQC schemes such as Kyber, Dilithium, Falcon, and NTRU, as well as FHE schemes such as Brakerski-Fan-Vercauteren (BFV) and Brakerski Gentry Vaikuntanathan (BGV), may leak sensitive information at the hardware implementation level. This work proposes three efficient recomputation-based fault detection methods for Barrett Modular Multiplication (<inline-formula><tex-math>$BMM$</tex-math></inline-formula>) in the Cooley–Tukey Butterfly Unit (<inline-formula><tex-math>$CT$</tex-math></inline-formula>-<inline-formula><tex-math>$BU$</tex-math></inline-formula>) of Number Theoretic Transform (<inline-formula><tex-math>$NTT$</tex-math></inline-formula>), implemented on a Field-Programmable Gate Array (FPGA) for PQC and FHE algorithms. The <inline-formula><tex-math>$CT$</tex-math></inline-formula>-<inline-formula><tex-math>$BU$</tex-math></inline-formula> and <inline-formula><tex-math>$BMM$</tex-math></inline-formula> are fundamental components in lattice-based PQC and FHE schemes. This paper introduces a new algorithm, Recomputation with Swapped Operand (RESWO), for fault detection. While Recomputation with Negated Operand (RENO) and Recomputation with Shifted Operand (RESO) are existing methods used in other PQC hardware algorithms. To the best of our knowledge, RENO and RESO have never been used in wordwise <inline-formula><tex-math>$BMM$</tex-math></inline-formula> before. The proposed RESWO method consumes a comparable number of slices to RENO and RESO. However, for most PQC and FHE variants, RESWO achieves lower energy consumption and reduced slice utilization compared to both RENO and RESO. The fault detection efficiency of RESWO, RENO, and RESO is nearly <inline-formula><tex-math>$sim$</tex-math></inline-formula>100%.","PeriodicalId":13156,"journal":{"name":"IEEE Transactions on Emerging Topics in Computing","volume":"14 2","pages":"734-745"},"PeriodicalIF":5.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148236424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ColReg: A Generative Subjective Logic-Driven Crowd-AI Collaborative Regression Framework for Vehicle Damage Estimation 基于生成主观逻辑驱动的人群-人工智能协同回归框架的车辆损伤评估

IF 4.8 2区计算机科学

IEEE Transactions on Emerging Topics in Computing Pub Date : 2026-04-01 Epub Date: 2026-03-04 DOI: 10.1109/TETC.2026.3688166

Yang Zhang;Ruohan Zong;Lanyu Shang;Huimin Zeng;Zhenrui Yue;Dong Wang

{"title":"ColReg: A Generative Subjective Logic-Driven Crowd-AI Collaborative Regression Framework for Vehicle Damage Estimation","authors":"Yang Zhang;Ruohan Zong;Lanyu Shang;Huimin Zeng;Zhenrui Yue;Dong Wang","doi":"10.1109/TETC.2026.3688166","DOIUrl":"https://doi.org/10.1109/TETC.2026.3688166","url":null,"abstract":"The vehicle damage poses a significant concern in urban transportation and public safety due to its potential to disrupt traffic flow, increase infrastructure maintenance costs, and elevate safety risks for motorists and pedestrians in our community. This paper develops a principled human-AI collaborative regression framework that effectively harnesses the collective intelligence of both AI and crowdsourced human workers to quantify the damage incurred by a vehicle following collisions, accidents, or natural events. We refer to such a problem as the collaborative <italic>vehicle damage estimation (VDE) problem. Our work is motivated by the complementary strengths of AI and human intelligence. On one hand, manual vehicle damage inspections, while thorough, are known for being time-consuming and prone to human errors. On the other hand, despite AI’s efficiency and consistency, it can encounter challenges in providing accurate damage assessments due to its limitations in comprehending the complex context of vehicle damage imagery. To address such challenges, our paper focuses on leveraging crowdsourced human intelligence for contextual understanding and nuanced reasoning to assist AI in addressing the VDE problem. In particular, we develop <italic>ColReg, a crowd-AI collaborative regression model that establishes a virtual interaction between the crowd and AI to collectively provide accurate vehicle damage estimation under a principled subjective logic framework. Evaluation results on a real-world VDE application show that ColReg outperforms both AI-regression models and crowd-AI collaboration baselines in accurately estimating vehicle damages across various evaluation scenarios.","PeriodicalId":13156,"journal":{"name":"IEEE Transactions on Emerging Topics in Computing","volume":"14 2","pages":"570-587"},"PeriodicalIF":4.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11505736","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148507596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Breakout Local Search for Load-Balanced Federated Learning in Multi-BS Networks Multi-BS网络中负载均衡联邦学习的突破局部搜索

IF 5.4 2区计算机科学

IEEE Transactions on Emerging Topics in Computing Pub Date : 2026-03-02 DOI: 10.1109/TETC.2026.3667101

Mina Kato;Xun Yuan;Tiago Koketsu Rodrigues;Fengxiao Tang;Ming Zhao;Nei Kato

{"title":"Breakout Local Search for Load-Balanced Federated Learning in Multi-BS Networks","authors":"Mina Kato;Xun Yuan;Tiago Koketsu Rodrigues;Fengxiao Tang;Ming Zhao;Nei Kato","doi":"10.1109/TETC.2026.3667101","DOIUrl":"https://doi.org/10.1109/TETC.2026.3667101","url":null,"abstract":"Federated learning (FL) relies on timely participation of multiple devices, yet the round time is often dominated by the slowest user under heterogeneous wireless conditions. In multi-base-station (multi-BS) environments with nonlinear concurrent uplink and diverse backhaul capacities, selecting an appropriate set of participants becomes a challenging combinatorial optimization problem. We cast the problem as a round-time–centric optimization with reference-latency-scaled fairness penalties to enforce diversity, cohort size, and BS load balance. To solve it efficiently, we propose a Breakout Local Search (BLS) solver that couples k-opt local refinement with approximate screening and adaptive three-mode perturbations under a wall-clock budget, enabling efficient exploration–exploitation. Extensive simulations under hotspot and throttled-backhaul scenarios show that the proposed method reduces round time by 80–90% compared with particle swarm optimization (PSO) and Random, and by 29–75% compared with Greedy and simulated annealing (SA), while lowering the overall objective by 80–84% relative to PSO and Random and 50–67% relative to Greedy and SA, across various diversity weights and target participant sizes. The results highlight the effectiveness of our BLS method in FL participant selection under realistic and difficult network conditions.","PeriodicalId":13156,"journal":{"name":"IEEE Transactions on Emerging Topics in Computing","volume":"14 1","pages":"364-376"},"PeriodicalIF":5.4,"publicationDate":"2026-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147429294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Graph-Based Anomaly APT Attack Detection via Threat Intelligence 基于威胁情报的基于图的异常APT攻击检测

IF 5.4 2区计算机科学

IEEE Transactions on Emerging Topics in Computing Pub Date : 2026-02-24 DOI: 10.1109/TETC.2026.3665235

Chun-I Fan;Cheng-Han Shie;Ying-Chan Chang;Tao Ban;Tomohiro Morikawa;Takeshi Takahashi

{"title":"Graph-Based Anomaly APT Attack Detection via Threat Intelligence","authors":"Chun-I Fan;Cheng-Han Shie;Ying-Chan Chang;Tao Ban;Tomohiro Morikawa;Takeshi Takahashi","doi":"10.1109/TETC.2026.3665235","DOIUrl":"https://doi.org/10.1109/TETC.2026.3665235","url":null,"abstract":"Among Advanced Persistent Threats in recent years, hackers have combined multiple defense evasion techniques to hide themselves from the detection of traditional antivirus software. For example, the combination of fileless malware and Living Off the Land techniques and abusing legitimate cloud services force the enterprises have gradually adopted the Endpoint Detection and Response (EDR) instead. However, EDR has the disadvantage that this tool may produce massive false alarms. This situation force security maintainer and analysts to be burdened with a large amount of additional analyses. We proposed an anomaly detection system based on graphs. First, we input a provenance graph containing threat intelligence constructed by the normal behaviors of the system. After that, the system learns the potential structured information from the provenance graph for detecting the abnormal behavior of a host. The results show that the proposed system can effectively detect abnormal event logs. Moreover, we reduce the number of false alarms by up to 97.67%. The improvement dramatically reduces the heavy burdens on the security maintainers from the analyses of the records. Furthermore, the performance of the designed system shows that the abnormal detection based on the graph neural network is superior to a traditional neural network.","PeriodicalId":13156,"journal":{"name":"IEEE Transactions on Emerging Topics in Computing","volume":"14 1","pages":"348-363"},"PeriodicalIF":5.4,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147429290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Anonymous Task Assignment and Worker Payment in Mobile Crowdsensing 移动众测中的匿名任务分配与工人报酬

IF 5.4 2区计算机科学

IEEE Transactions on Emerging Topics in Computing Pub Date : 2026-02-16 DOI: 10.1109/TETC.2026.3662784

Tyler Nicewarner;Ali Allami;Dan Lin

{"title":"Anonymous Task Assignment and Worker Payment in Mobile Crowdsensing","authors":"Tyler Nicewarner;Ali Allami;Dan Lin","doi":"10.1109/TETC.2026.3662784","DOIUrl":"https://doi.org/10.1109/TETC.2026.3662784","url":null,"abstract":"Ensuring efficient task assignment and secure payment in mobile crowdsensing while preserving worker location privacy remains a challenging problem. Existing solutions either rely on expensive encryption schemes, employ blockchain-based verification that incurs high computational and gas costs, or use differential privacy techniques that degrade spatial accuracy. This paper introduces the Privacy-preserving Task Assignment and Payment (PTAP) framework, a lightweight solution built upon secure multi-party computation (SMPC). PTAP employs additive secret sharing and a challenge–response mechanism across three semi-honest servers to achieve anonymous task allocation and payment without blockchain or zero-knowledge proofs. The framework guarantees full unlinkability between worker identities, task locations, and payment records while maintaining accurate location-based assignment and supporting traceability for dispute resolution. Experimental evaluation using the MP-SPDZ framework demonstrates scalability to over 1.5 million workers and 7 million payment tokens. The average end-to-end completion time is approximately 35.4 seconds, with zero gas cost. Compared to the state-of-the-art AVeCQ system (Koutsos et al. 2025), which requires about 13 minutes and 37 MWei per transaction on the Goerli network for only 1,024 users. The results confirm PTAP’s efficiency, scalability, and strong privacy guarantees for large-scale mobile crowdsensing deployments.","PeriodicalId":13156,"journal":{"name":"IEEE Transactions on Emerging Topics in Computing","volume":"14 1","pages":"332-347"},"PeriodicalIF":5.4,"publicationDate":"2026-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11397269","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147429297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

FairRFL: Fair and Robust Federated Learning in the Presence of Selfish Clients FairRFL：自私客户端存在下的公平稳健的联邦学习

IF 5.4 2区计算机科学

IEEE Transactions on Emerging Topics in Computing Pub Date : 2026-02-11 DOI: 10.1109/TETC.2026.3661199

Andrea Augello;Ashish Gupta;Giuseppe Lo Re;Sajal K. Das

{"title":"FairRFL: Fair and Robust Federated Learning in the Presence of Selfish Clients","authors":"Andrea Augello;Ashish Gupta;Giuseppe Lo Re;Sajal K. Das","doi":"10.1109/TETC.2026.3661199","DOIUrl":"https://doi.org/10.1109/TETC.2026.3661199","url":null,"abstract":"Federated Learning (FL) is a paradigm that enables collaborative machine learning without disclosing the local data of the participants. However, in real-world FL deployment scenarios, some unscrupolous clients may alter the training process to skew the global model towards their local optimum, unfairly prioritizing their data distribution. Their influence can degrade overall model performance for normal clients and reduce fairness in the system. We call this novel category of misbehaving clients “selfish”. This work proposes a <bold>Fair and <bold>Robust strategy for aggregation in the <bold>Federated Learning (FL) server to mitigate the effect of Selfish clients (FairRFL). FairRFL incorporates a novel technique to recover (or estimate) the true updates from selfish clients by using robust statistics, specifically the median of norms. The presented strategy, through the inclusion of the recovered updates in the aggregation process, is robust against selfish behavior. Through extensive empirical evaluations with WISDM-W and CIFAR-10 datasets, we observe that a selfish client can increase the model accuracy on its data by up to 39% and more than quadruple the accuracy variance among clients, which FairRFL can address perfectly and recover performance fairness across normal clients.","PeriodicalId":13156,"journal":{"name":"IEEE Transactions on Emerging Topics in Computing","volume":"14 1","pages":"316-331"},"PeriodicalIF":5.4,"publicationDate":"2026-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11391495","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147429287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Toward Scalable Multi-Chip Wireless Networks With Near-Field Time Reversal 具有近场时间反转的可扩展多芯片无线网络

IF 5.4 2区计算机科学

IEEE Transactions on Emerging Topics in Computing Pub Date : 2026-02-10 DOI: 10.1109/TETC.2026.3661404

Ama Bandara;Fátima Rodríguez-Galán;Pau Talarn;Elana Pereira de Santana;Evgenii Vinogradov;Peter Haring Bolívar;Eduard Alarcón;Sergi Abadal

{"title":"Toward Scalable Multi-Chip Wireless Networks With Near-Field Time Reversal","authors":"Ama Bandara;Fátima Rodríguez-Galán;Pau Talarn;Elana Pereira de Santana;Evgenii Vinogradov;Peter Haring Bolívar;Eduard Alarcón;Sergi Abadal","doi":"10.1109/TETC.2026.3661404","DOIUrl":"https://doi.org/10.1109/TETC.2026.3661404","url":null,"abstract":"The concept of Wireless Network-on-Chip (WNoC) has emerged as a potential solution to address the escalating communication demands of modern computing systems due to its low-latency, versatility, and reconfigurability. However, for WNoC to fulfill its potential, it is essential to establish multiple high-speed wireless links across chips. Unfortunately, the compact and enclosed nature of computing packages introduces significant challenges in the form of Co-Channel Interference (CCI) and Inter-Symbol Interference (ISI), which not only hinder the deployment of multiple spatial channels, but also severely restrict the symbol rate of each individual channel. In this paper, we posit that Time Reversal (TR) could be effective in addressing both impairments in this static scenario, thanks to its spatiotemporal focusing capabilities even in the near-field. Through comprehensive full-wave simulations and bit error rate analysis in multiple chip layouts with multiple frequency bands, we provide evidence that TR can increase the symbol rate by an order of magnitude, enabling the deployment of multiple concurrent links and achieving aggregate speeds exceeding 100 Gb/s. Finally, we evaluate the impact of reducing the sampling rate of the TR filter on the achievable speeds, paving the way to practical TR-based wireless communications at the chip scale.","PeriodicalId":13156,"journal":{"name":"IEEE Transactions on Emerging Topics in Computing","volume":"14 1","pages":"303-315"},"PeriodicalIF":5.4,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11391496","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147429265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Divided-QUBO-Based Quantum Algorithm for Optimal Wireless Link Scheduling 基于划分qubo的最优无线链路调度量子算法

IF 4.8 2区计算机科学

IEEE Transactions on Emerging Topics in Computing Pub Date : 2026-01-01 Epub Date: 2025-11-13 DOI: 10.1109/TETC.2025.3630066

Yue Ruan;Pengyue Chen;Zhongge Yang;Wei Zhao;Fengxiao Tang;Zhi Liu;Nei Kato

{"title":"The Divided-QUBO-Based Quantum Algorithm for Optimal Wireless Link Scheduling","authors":"Yue Ruan;Pengyue Chen;Zhongge Yang;Wei Zhao;Fengxiao Tang;Zhi Liu;Nei Kato","doi":"10.1109/TETC.2025.3630066","DOIUrl":"https://doi.org/10.1109/TETC.2025.3630066","url":null,"abstract":"Link scheduling in wireless communication aims to minimize interference and maximize channel utilization. When accurate channel state information (CSI) is available, optimal scheduling can be achieved by modeling link interference as a conflict graph and solving the weighted maximum independent set problem (WMIS). However, the NP-hard nature of WMIS presents significant computational challenges in obtaining high-quality solutions efficiently. To tackle this challenge, we first propose a divided QUBO model, which formulates the original problem into sub-models within non-overlapping subspaces. Building upon this, we then develop a corresponding algorithm called DQAOA, which further narrows the search space within solution bounds established by classical greedy algorithms and semi-definite programming. Using a specialized mixing operator (the XY-mixer), the algorithm confines the evolution to each reduced subspace and runs in parallel. Additionally, an auxiliary Hamiltonian inspired by counter-diabatic driving is introduced into the core evolution equation to accelerate convergence. The experimental results on the IBM Qiskit platform demonstrate that DQAOA outperforms classical methods and other QAOA variants, providing an efficient and reliable solution for optimal link scheduling in wireless networks.","PeriodicalId":13156,"journal":{"name":"IEEE Transactions on Emerging Topics in Computing","volume":"14 1","pages":"17-29"},"PeriodicalIF":4.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148507587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0