Demo Data from EDBT 2026 / reviewers in the wild / expert
Pooja Hanavadi Balaraju
dblp:241/1732
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
0000-0001-5446-5848ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1 · 1 since 2021
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 |
Wireless networking · 56% Network performance modeling · 44% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Wireless networking
cross-layer optimization |
0.6 | 1 | 2022 | Queuing Over Ever-Changing Communication Scenarios in Tactical Networks · IEEE Trans. Mob. Comput. 2022 |
Network performance modeling
queueing analysis |
0.6 | 1 | 2022 | Queuing Over Ever-Changing Communication Scenarios in Tactical Networks · IEEE Trans. Mob. Comput. 2022 |
Methods — techniques the papers use, named apart from their topics
stochastic modeling · 0.6queueing theory · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Queuing Over Ever-Changing Communication Scenarios in Tactical NetworksabstractThis paper introduces a hierarchy of queues complementing each other to handle ever-changing communication scenarios in tactical networks. The first queue stores the QoS-constrained messages from command and control systems. These messages are fragmented into IP packets, which are stored in a queue of packets (second) to be sent to the radio buffer (third), which is a queue with limited space therefore, open to overflow. We start with the hypothesis that these three queues can handle ever-changing user(s) data flows (problem$A$) through ever-changing network conditions (problem$B$) using cross-layer information exchange, such as buffer occupancy, data rate, queue size and latency (problem$A|B$). We introduce two stochastic models to create sequences of QoS-constrained messages ($A$) and to create ever-changing network conditions ($B$). In sequence, we sketch a control loop to shape$A$to$B\;$to test our hypothesis using model$A|B$, which defines enforcement points at the incoming/outgoing chains of the system together with a control plane. Then, we discuss experimental results in a network with VHF radios using data flows that overflows the radio buffer over ever-changing data rate patterns. We discuss quantitative results showing the performance and limitations of our solutions for problems$A$,$B$, and$A|B$. Roberto Rigolin Ferreira Lopes, Pooja Hanavadi Balaraju, Paulo H. L. Rettore, Peter Sevenich |
IEEE Trans. Mob. Comput. | 2 |