Demo Data from SIGIR 2026 / reviewers in the wild / expert
Mikhail Galeev
dblp:222/8131
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Embedded and real-time systems · 100% | |
| Computer networks
1 paper |
Wireless networking · 67% Cellular and mobile networks · 33% |
Topics — the 5 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Embedded and real-time systems › cyber-physical system platforms
industrial automation |
0.4 | 1 | 2019 | Extending Accurate Time Distribution and Timeliness Capabilities Over the Air to Enable Future Wireless Industrial Automation Systems · Proc. IEEE 2019 |
Embedded and real-time systems › real-time communication › real-time networks
time-sensitive networking |
0.4 | 1 | 2019 | Extending Accurate Time Distribution and Timeliness Capabilities Over the Air to Enable Future Wireless Industrial Automation Systems · Proc. IEEE 2019 |
Cellular and mobile networks
5g |
0.1 | 1 | 2019 | Extending Accurate Time Distribution and Timeliness Capabilities Over the Air to Enable Future Wireless Industrial Automation Systems · Proc. IEEE 2019 |
Wireless networking › reliable wireless communication › mission-critical wireless communication
industrial wireless |
0.1 | 1 | 2019 | Extending Accurate Time Distribution and Timeliness Capabilities Over the Air to Enable Future Wireless Industrial Automation Systems · Proc. IEEE 2019 |
Wireless networking › wireless network protocols
wireless synchronization |
0.1 | 1 | 2019 | Extending Accurate Time Distribution and Timeliness Capabilities Over the Air to Enable Future Wireless Industrial Automation Systems · Proc. IEEE 2019 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Extending Accurate Time Distribution and Timeliness Capabilities Over the Air to Enable Future Wireless Industrial Automation SystemsabstractMany industrial automation systems rely on time-synchronized (and timely) communication among sensing, computing, and actuating devices. Advances in Ethernet enabled by time-sensitive networking (TSN) standards, being developed by the IEEE 802.1 TSN Task Group, are significantly improving time synchronization as well as worst case latencies. Next-generation industrial systems are expected to leverage advances in distributed time coordinated computing and wireless communications to enable greater levels of automation, efficiency, and flexibility. Significant progress has been made in extending accurate time synchronization over the air (e.g., 802.1AS profile for IEEE 802.11/Wi-Fi). Given the inherently unreliable, varying capacity and latency prone characteristics associated with wireless communications, proving the feasibility of worst case latency performance over the wireless medium is a major research challenge. More specifically, understanding what levels of capacity, reliability, and latency could be guaranteed over wireless links with high reliability are important research questions to guide the development of new radios, protocols, and time coordinated applications. This paper provides an overview of the potential applications, requirements, and unique research challenges to extend TSN capabilities over wireless. The paper also describes advances in wireless technologies (e.g., next-generation 802.11 and 5G standards) toward achieving reliable and accurate time distribution and timeliness capabilities. It also provides a classification of wireless applications and a reference architecture for enabling the integration of wired and wireless TSN capabilities in future industrial automation systems. Dave Cavalcanti 0001, Javier Perez-Ramirez, Mohammad Mamunur Rashid, Juan Fang 0003, Mikhail Galeev, Kevin B. Stanton |
Proc. IEEE | 5 |