Demo Data from EDBT 2026 / reviewers in the wild / expert
Jillian Cannons
dblp:77/1297
· DBLP profile ↗
5ranked-venue papers
5as first author
0since 2021 · last 2009
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 2 · 2 first-authorComputer networks · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 1 · 1 first-author
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.
| Theoretical computer science
3 papers |
Coding theory · 63% Information theory · 25% Graph algorithms and graph theory · 12% | |
| Computer networks
2 papers |
Routing and switching · 57% Wireless networking · 43% | |
| Network and information security
1 paper |
Digital forensics and information hiding · 100% |
Topics — the 11 heaviest of 12, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Coding theory
network coding |
0.1 | 2 | 2008 | Network Coding Capacity With a Constrained Number of Coding Nodes · IEEE Trans. Inf. Theory 2008 Network routing capacity · IEEE Trans. Inf. Theory 2006 |
Routing and switching
routing |
0.1 | 1 | 2008 | Network Coding Capacity With a Constrained Number of Coding Nodes · IEEE Trans. Inf. Theory 2008 |
Coding theory › network coding
network coding capacity |
0.1 | 1 | 2008 | Network Coding Capacity With a Constrained Number of Coding Nodes · IEEE Trans. Inf. Theory 2008 |
Wireless networking
network capacity |
0.1 | 1 | 2006 | Network routing capacity · IEEE Trans. Inf. Theory 2006 |
Information theory
coding capacity |
0.1 | 1 | 2006 | Network routing capacity · IEEE Trans. Inf. Theory 2006 |
Digital forensics and information hiding › watermarking
image watermarking |
0.0 | 1 | 2004 | Design and statistical analysis of a hash-aided image watermarking system · IEEE Trans. Image Process. 2004 |
Digital forensics and information hiding
watermarking |
0.0 | 1 | 2004 | Design and statistical analysis of a hash-aided image watermarking system · IEEE Trans. Image Process. 2004 |
Graph algorithms and graph theory › graph algorithms
network flow |
0.0 | 1 | 2006 | Network routing capacity · IEEE Trans. Inf. Theory 2006 |
Digital forensics and information hiding › watermarking
watermark detection |
0.0 | 1 | 2004 | Design and statistical analysis of a hash-aided image watermarking system · IEEE Trans. Image Process. 2004 |
Information theory
hypothesis testing |
0.0 | 1 | 2004 | Design and statistical analysis of a hash-aided image watermarking system · IEEE Trans. Image Process. 2004 |
Information theory › statistical inference › detection and estimation
receiver operating characteristic |
0.0 | 1 | 2004 | Design and statistical analysis of a hash-aided image watermarking system · IEEE Trans. Image Process. 2004 |
Methods — techniques the papers use, named apart from their topics
capacity function characterization · 0.2fractional routing · 0.1capacity computation · 0.1statistical image model · 0.1monte carlo simulation · 0.1chernoff bound · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2009 | An algorithm for wireless relay placementabstractAn algorithm is given for placing relays at spatial positions to improve the reliability of communicated data in a sensor network. The network consists of many power-limited sensors, a small set of relays, and a receiver. For each sensor, the receiver receives a direct signal as well as an indirect signal from one of the available relays. The relays rebroadcast the transmissions in order to achieve diversity at the receiver. Both amplify-and-forward and decode-and-forward relay networks are considered. Channels are modeled with Rayleigh fading, path loss, and additive white Gaussian noise. Performance analysis and numerical results are given. Jillian Cannons, Laurence B. Milstein, Kenneth Zeger |
IEEE Trans. Wirel. Commun. | 1 |
| 2008 | Network Coding Capacity With a Constrained Number of Coding NodesabstractWe study network coding capacity under a constraint on the total number of network nodes that can perform coding. That is, only a certain number of network nodes can produce coded outputs, whereas the remaining nodes are limited to performing routing. We prove that every nonnegative, monotonically nondecreasing, eventually constant, rational-valued function on the nonnegative integers is equal to the capacity as a function of the number of allowable coding nodes of some directed acyclic network. Jillian Cannons, Kenneth Zeger |
IEEE Trans. Inf. Theory | 1 |
| 2006 | Network routing capacityabstractWe define the routing capacity of a network to be the supremum of all possible fractional message throughputs achievable by routing. We prove that the routing capacity of every network is achievable and rational, we present an algorithm for its computation, and we prove that every rational number in (0, 1] is the routing capacity of some solvable network. We also determine the routing capacity for various example networks. Finally, we discuss the extension of routing capacity to fractional coding solutions and show that the coding capacity of a network is independent of the alphabet used Jillian Cannons, Randall Dougherty, Christopher F. Freiling, Kenneth Zeger |
IEEE Trans. Inf. Theory | 1 |
| 2005 | Network routing capacityabstractWe define the routing capacity of a network to be the supremum of all possible fractional message throughputs achievable by routing. We prove that the routing capacity of every network is achievable and rational, we present an algorithm for its computation, and we prove that every non-negative rational number is the routing capacity of some network. We also determine the routing capacity for various example networks. Finally, we discuss the extension of routing capacity to fractional coding solutions and show that the coding capacity of a network is independent of the alphabet used Jillian Cannons, Randall Dougherty, Christopher F. Freiling, Kenneth Zeger |
ISIT | 1 |
| 2004 | Design and statistical analysis of a hash-aided image watermarking systemabstractThis paper develops a joint hashing/watermarking scheme in which a short hash of the host signal is available to a detector. Potential applications include content tracking on public networks and forensic identification. The host data into which the watermark is embedded are selected from a secret subset of the full-frame discrete cosine transform of an image, and the watermark is inserted through multiplicative embedding. The hash is a binary version of selected original image coefficients. We propose a maximum likelihood watermark detector based on a statistical image model. The availability of a hash as side information to the detector modifies the posterior distribution of the marked coefficients. We derive Chernoff bounds on the receiver operating characteristic performance of the detector. We show that host-signal interference can be rejected if the hash function is suitably designed. The relative difficulty of an eavesdropper's detection problem is also determined; the eavesdropper does not know the secret key used. Monte Carlo simulations are performed using photographic test images. Finally, various attacks on the watermarked image are introduced to study the robustness of the derived detectors. The joint hashing/watermarking scheme outperforms the traditional "hashless" watermarking technique. Jillian Cannons, Pierre Moulin |
IEEE Trans. Image Process. | 1 |