Demo Data from VLDB 2026 / reviewers in the wild / expert
Matt Trower
dblp:12/10870
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 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 networks
1 paper |
Internet of things and sensor networks · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Internet of things and sensor networks › neighbor discovery
asynchronous neighbor discovery |
0.1 | 1 | 2012 | Searchlight: won't you be my neighbor? · MobiCom 2012 |
Internet of things and sensor networks
neighbor discovery |
0.1 | 1 | 2012 | Searchlight: won't you be my neighbor? · MobiCom 2012 |
Internet of things and sensor networks › wireless sensor network
duty cycling |
0.0 | 1 | 2012 | Searchlight: won't you be my neighbor? · MobiCom 2012 |
Methods — techniques the papers use, named apart from their topics
smartphone experiments · 0.1probabilistic analysis · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | Searchlight: won't you be my neighbor?abstractThe rapid deployment of millions of mobile sensors and smartphones has resulted in a demand for opportunistic encounter-based networking to support mobile social networking applications and proximity-based gaming. However, the success of these emerging networks is limited by the lack of effective and energy efficient neighbor discovery protocols. While probabilistic approaches perform well for the average case, they exhibit long tails resulting in high upper bounds on neighbor discovery time. Recent deterministic protocols, which allow nodes to wake up at specific timeslots according to a particular pattern, improve on the worst case bound, but do so by sacrificing average case performance. In response to these limitations, we have designed Searchlight, a highly effective asynchronous discovery protocol that is built on three basic ideas. First, it leverages the constant offset between periodic awake slots to design a simple probing-based approach to ensure discovery. Second, it allows awake slots to cover larger sections of time, which ultimately reduces total awake time drastically. Finally, Searchlight has the option to employ probabilistic techniques with its deterministic approach that can considerably improve its performance in the average case when all nodes have the same duty cycle. We validate Searchlight through analysis and real-world experiments on smartphones that show considerable improvement (up to 50%) in worst-case discovery latency over existing approaches in almost all cases, irrespective of duty cycle symmetry. Mehedi Bakht, Matt Trower, Robin Kravets |
MobiCom | 2 |