会议信息

HPSR 2027: IEEE Conference on High Performance Switching and Routing

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截稿日期:
2026-11-30 还有 49 天
通知日期:
2027-03-01
会议日期:
2027-06-15
会议地点:
Paris, France
届数:
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ICORE: C   浏览: 35916   关注: 9   参加: 3
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HPSR
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会伴指数 (CP-I)

65.0 / 100
全站第 437 名 / 共 5,695 个会议 · 前 8%

系统与体系结构 第 74 / 340

学术认可 (35%)
58
投稿选择性 (20%)
52
会议传承 (20%)
91
社区关注 (10%)
34
资料公开度 (15%)
85

用到的输入: 收录等级：ICORE C · 录用率：51.7%（有记录的 5 届的均值） · 有据可查的届次：28 · 在会伴关注它的研究者：9 人 · 过去 24 个月打开过本页的研究者：4 人

公开资料里还缺: 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 100% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-10-11

征稿

HPSR 2027 (IEEE Conference on High Performance Switching and Routing) is a ICORE C conference held in Paris, France on 2027-06-15. The paper submission deadline is 2026-11-30. Acceptance notifications are sent on 2027-03-01.

The rapid evolution of artificial intelligence, cloud computing, distributed systems, and next-generation communication infrastructures is fundamentally reshaping network requirements. AI training and inference workloads, large-scale distributed applications, and emerging agentic computing systems generate unprecedented traffic volumes, dynamic communication patterns, and stringent performance requirements. Future networks must deliver ultra-low latency, high throughput, predictable performance, resilience, and intelligent resource utilization while operating across data centers, wide-area networks, edge infrastructures, and heterogeneous computing platforms. Furthermore, the evolution of the Digital Continuum—device-to-edge-to-fog-to-Cloud—is converging with AI-native infrastructures, promising low-latency and ubiquitous computation for heterogeneous mobile, IoT, and AI-empowered devices and agents. Emerging 6G system specifications increasingly consider GenAI and Agentic AI functionalities as native components of the 6G core, enabling AI-driven control, orchestration, and service exposure directly within the network fabric. This convergence is expected to foster a rich array of network and computing services aiming at tighter synergy across programmable data planes, control planes, and computing substrates in Next Generation Integrated Communications and Computing Systems. The main focus of HPSR 2027 – the 28th edition of the HPSR conference – will be to assess how these transformative breakthroughs    in AI-native Integrated Communications Systems affect all areas related to switching and routing, traffic engineering, and next generation networks and systems in general. We are soliciting original and thought-provoking works on big data, data analytics, cloud, edge and fog services, and advanced artificial intelligence techniques applied to networking, including the high-performance routing, switching, and traffic engineering, including for AI / GenAI / Agentic AI workloads. Contributions addressing traffic modeling and characterization of AI-centric environments (e.g., LLM training and inference clusters, agentic swarms, federated learning, and digital twins) across data center, wide area, and intra-provider networks are particularly welcome. Works on autonomous networks, AI-native 6G core and RAN, Industry 4.0 and 5.0, social networks, network cybersecurity, network softwarization and virtualization, as well as other advanced topics are also encouraged. Original, previously unpublished research papers describing theoretical advances, experimental efforts, practical experiences, as well as visionary roadmaps in all aspects of switching and routing, traffic modeling, and AI-native next generation networks and systems are solicited. Technical Tracks Track A:  Integrated Communications and Computing Systems Artificial intelligent routing and resource-allocation algorithms Generative AI traffic modeling, routing and switching strategies Collective communications and optimal AI traffic scheduling Digital Continuum – device-to-edge-to-fog-to-Cloud continuum Dynamic bandwidth access and management for smart-factory/Industry 4.0 applications Experimental measurements and testbed implementations Game theory enabling resource allocation and routing High performance, programmable networks. Integrated access and backhaul technologies Integrated caching, computation, and communications Quality of Experience resulting from intelligent routing Quality of Service Optimization and resource allocation Reconfigurable Intelligent surfaces-enabled switching and routing Switching architectures for next generation applications Traffic monitoring and modeling applied to switching and routing Traffic predictions in routing and resource assignment Track B: High-Performance High Functionality Architectures Address lookup algorithms, packet classification, scheduling, and dropping Applications of data science and analysis on high-performance networks, Applications of GPU on network functions. Efficient data structures for networking applications Future technologies for IoT High-speed packet processors ICT enabling technologies for e-health systems Multiprocessor networks Nano-communication networks Non-Terrestrial Communication Systems Integrated Terrestrial and Non-Terrestrial Networks Network management Network traffic characterization and measurements Optical switching and routing Power-aware switching, bridging, and routing protocols Routing and resource allocation for tactile Internet Switching, bridging, and routing protocols for wide-area,data centers Switching support to extended reality (including virtual, augmented, and mixed reality) Traffic characterization and engineering Track C: Autonomous Networks Architectures of high-performance switches and routers, with a focus towards reconfigurable pipelines (P4, OpenFlow, etc.) AI-driven autonomous networking Computation offloading Decentralized applications Decentralized autonomous organizations Economics and pricing Energy harvesting, storage, recycling, wireless power transfer Green network monitoring and routing Medium access control, routing, and path selection Middleware services for wireless, mobile and multimedia networks Mobile social networks and routing Multi-access edge computing (MEC) Network and switch slicing Network performance for Human-Agent-Robot Teamwork (HART) Physical-layer aspects of switching and routing Software-defined networking Space-air-ground integrated networks (SAGIN) Track D: Network Security Adversarial machine learning AI-assisted network security Applied cryptography for cyber, information, and network security Attack prediction, detection, response, and prevention Authentication protocols and key management Cloud, data center, and distributed systems    security Future Internet Architecture (FIA) security and privacy Intrusion detection with artificial intelligent techniques Malware detection and damage recovery Network security and privacy protection Next generation networks and Internet security Security in SDN and networking slicing Security in smart grid communications Security in virtualized network functions built or managed using software-defined networks Security and privacy in the Age of Information Trust management in networks through emerging technologies Virtual Private WANs
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录用率

平均录用率: 49.3% 8 年间 (2000–2011).

年份提交数录用数录用率(%)
2011934649.5%
2010733446.6%
2007945659.6%
20061146153.5%
200521810849.5%
20031165345.7%
20021106357.3%
20001946433%

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CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
AIEEE Transactions on Computers3.8IEEE0018-9340
CFuture Generation Computer Systems5.9Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312
CPattern Recognition Letters3.9Elsevier0167-8655
BPattern Recognition7.6Elsevier0031-3203
IEEE Access3.6IEEE2169-3536

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