Demo Data from VLDB 2026 / reviewers in the wild / expert
Shane Leonard
dblp:183/4675
· DBLP profile ↗
4ranked-venue papers
0as first author
0since 2021 · last 2017
0000-0002-5411-4789ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 3Applied, 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.
| Network and information security
1 paper |
Cryptographic primitives and cryptanalysis · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
3 papers |
Embedded and real-time systems · 100% | |
| Software engineering, system software, and programming languages
1 paper |
Operating systems · 100% | |
| Computer networks
1 paper |
Internet of things and sensor networks · 100% |
Topics — the 6 heaviest of 8, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Operating systems › special-purpose operating system
embedded operating system |
0.3 | 1 | 2017 | The Tock Embedded Operating System · SenSys 2017 |
Cryptographic primitives and cryptanalysis
random number generation |
0.2 | 1 | 2016 | Robust, low-cost, auditable random number generation for embedded system security · SenSys 2016 |
Cryptographic primitives and cryptanalysis › random number generation
true random number generator |
0.2 | 1 | 2016 | Robust, low-cost, auditable random number generation for embedded system security · SenSys 2016 |
Embedded and real-time systems
embedded system security |
0.2 | 1 | 2016 | Robust, low-cost, auditable random number generation for embedded system security · SenSys 2016 |
Internet of things and sensor networks
wireless sensor network |
0.1 | 1 | 2016 | Rebooting the Embedded System: Demo Abstract · SenSys 2016 |
Cryptographic primitives and cryptanalysis › random number generation
entropy source |
0.1 | 1 | 2016 | Robust, low-cost, auditable random number generation for embedded system security · SenSys 2016 |
Methods — techniques the papers use, named apart from their topics
type safety · 0.6memory isolation · 0.6avalanche noise · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | The Tock Embedded Operating SystemabstractLow-power microcontrollers lack some of the hardware features and most of the memory resources that usually enable multiprogrammable systems. Accordingly, operating system software for these platforms has not provided important features like memory isolation, dynamic memory allocation, and flexible concurrency. However, an emerging class of embedded applications are software platforms, rather than single purpose devices. Tock, a new operating system for low-power platforms, takes advantage of the limited hardware-protection mechanisms available on recent microcontrollers and the type-safety features of the Rust programming language to provide a multiprogramming environment that offers isolation of software faults, memory protection, and efficient memory management for dynamic application workloads written in any language while retaining the dependability requirements of long-running devices. Amit Levy 0001, Bradford Campbell, Branden Ghena, Daniel B. Giffin, Shane Leonard, Pat Pannuto, Prabal Dutta, Philip Alexander Levis |
SenSys | 5 |
| 2016 | Robust, low-cost, auditable random number generation for embedded system securityabstractThis paper presents an architecture for a discrete, high-entropy hardware random number generator. Because it is constructed out of simple hardware components, its operation is transparent and auditable. Using avalanche noise, a non-deterministic physical phenomenon, the circuit is inherently probabilistic and resists adversarial control. Furthermore, because it compares the outputs from two matched noise sources, it rejects environmental disturbances like RF energy and power supply ripple. The resulting hardware produces more than 0.98 bits of entropy per sample, is inexpensive, has a small footprint, and can be disabled to conserve power when not in use. Ben Lampert, Riad S. Wahby, Shane Leonard, Philip Alexander Levis |
SenSys | 3 |
| 2016 | Rebooting the Embedded System: Demo AbstractabstractFor the last fifteen years, research explored the hardware, software, sensing, communication abstractions, languages, and protocols that could make networks of small, embedded devices---motes---sample and report data for long periods of time while unattended. Today, the application and technological landscapes have shifted, introducing new requirements and new capabilities. Hardware has evolved past 8 and 16 bit microcontrollers: there are now 32 bit processors with lower energy budgets and greater computing capability. New wireless link layers have emerged, creating protocols that support direct interaction with users, but introduce novel limitations that systems must consider. Programming language advances have led to the ability to write system kernels that guarantee safety and reliability while maintaining low overhead. The time has come to look beyond optimizing networks of motes. We look towards new technologies such as Bluetooth Low Energy, Cortex M processors, and capable multi-process operating systems, with new application spaces such as personal area networks, and new capabilities and requirements in security and privacy to inform contemporary hardware and software platforms. It is time for a new, open experimental platform in this post-mote era. Amit Levy 0001, Bradford Campbell, Branden Ghena, Shane Leonard, Pat Pannuto, Philip Alexander Levis, Prabal Dutta |
SenSys | 4 |
| 2015 | YouEDU: Addressing Confusion in MOOC Discussion Forums by Recommending Instructional Video Clips
Jagadish Venkatraman, Shane Leonard, Andreas Paepcke |
EDM | 3 |