EDBT 2026 Demo / reviewers in the wild / expert
Mike Yu Cheng
dblp:48/5637
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2007
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 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 |
Distributed systems · 100% | |
| Computer networks
1 paper |
Network management and operations · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Network management and operations › fault management
fault diagnosis |
0.1 | 1 | 2007 | Automated Rule-Based Diagnosis through a Distributed Monitor System · IEEE Trans. Dependable Secur. Comput. 2007 |
Distributed systems › observability
distributed monitoring |
0.1 | 1 | 2007 | Automated Rule-Based Diagnosis through a Distributed Monitor System · IEEE Trans. Dependable Secur. Comput. 2007 |
Distributed systems › fault tolerance
failure diagnosis |
0.1 | 1 | 2007 | Automated Rule-Based Diagnosis through a Distributed Monitor System · IEEE Trans. Dependable Secur. Comput. 2007 |
Distributed systems
fault tolerance |
0.1 | 1 | 2007 | Automated Rule-Based Diagnosis through a Distributed Monitor System · IEEE Trans. Dependable Secur. Comput. 2007 |
Distributed systems › group communication
reliable multicast |
0.0 | 1 | 2007 | Automated Rule-Based Diagnosis through a Distributed Monitor System · IEEE Trans. Dependable Secur. Comput. 2007 |
Methods — techniques the papers use, named apart from their topics
rule-based diagnosis · 0.1fault injection · 0.1causal graph · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2007 | Automated Rule-Based Diagnosis through a Distributed Monitor SystemabstractIn today's world where distributed systems form many of our critical infrastructures, dependability outagesare becoming increasingly common. In many situations, it is necessary to not just detect a failure, but alsoto diagnose the failure, i.e., to identify the source of the failure. Diagnosis is challenging since highthroughput applications with frequent interactions between the different components allow fast errorpropagation. It is desirable to consider applications as black-boxes for the diagnostic process. In thispaper, we propose a Monitor architecture for diagnosing failures in large-scale network protocols. TheMonitor only observes the message exchanges between the protocol entities (PEs) remotely and doesnot access internal protocol state. At runtime, it builds a causal graph between the PEs based on theircommunication and uses this together with a rule base of allowed state transition paths to diagnose thefailure. The tests used for the diagnosis are based on the rule base and are assumed to have imperfectcoverage. The hierarchical Monitor framework allows distributed diagnosis handling failures at individualMonitors. The framework is implemented and applied to a reliable multicast protocol executing on ourcampus-wide network. Fault injection experiments are carried out to evaluate the accuracy and latency ofthe diagnosis. Gunjan Khanna, Mike Yu Cheng, Padma Varadharajan, Saurabh Bagchi, Miguel Correia 0001, Paulo Veríssimo |
IEEE Trans. Dependable Secur. Comput. | 2 |