Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Manuel D. Serrat Olmos

dblp:89/11358 · also Manuel David Serrat Olmos · DBLP profile ↗
← Back
2ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 2

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 · 50% Internet of things and sensor networks · 50%
Network and information security
1 paper
Network security · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks
delay tolerant networks
0.212015
CoCoWa: A Collaborative Contact-Based Watchdog for Detecting Selfish Nodes · IEEE Trans. Mob. Comput. 2015
Wireless networking
mobile ad hoc networks
0.212015
CoCoWa: A Collaborative Contact-Based Watchdog for Detecting Selfish Nodes · IEEE Trans. Mob. Comput. 2015
Network security › intrusion detection and prevention
intrusion detection
0.212015
CoCoWa: A Collaborative Contact-Based Watchdog for Detecting Selfish Nodes · IEEE Trans. Mob. Comput. 2015
Network security › wireless network security
selfish node detection
0.212015
CoCoWa: A Collaborative Contact-Based Watchdog for Detecting Selfish Nodes · IEEE Trans. Mob. Comput. 2015
Distributed systems › peer-to-peer systems
cooperation enforcement
0.112015
CoCoWa: A Collaborative Contact-Based Watchdog for Detecting Selfish Nodes · IEEE Trans. Mob. Comput. 2015

Methods — techniques the papers use, named apart from their topics

collaborative contact-based diffusion · 0.7
YearPublicationVenuePosition
2015 CoCoWa: A Collaborative Contact-Based Watchdog for Detecting Selfish Nodes
abstract
Mobile ad-hoc networks (MANETs) assume that mobile nodes voluntary cooperate in order to work properly. This cooperation is a cost-intensive activity and some nodes can refuse to cooperate, leading to a selfish node behaviour. Thus, the overall network performance could be seriously affected. The use of watchdogs is a well-known mechanism to detect selfish nodes. However, the detection process performed by watchdogs can fail, generating false positives and false negatives that can induce to wrong operations. Moreover, relying on local watchdogs alone can lead to poor performance when detecting selfish nodes, in term of precision and speed. This is specially important on networks with sporadic contacts, such as delay tolerant networks (DTNs), where sometimes watchdogs lack of enough time or information to detect the selfish nodes. Thus, we propose collaborative contact-based watchdog (CoCoWa) as a collaborative approach based on the diffusion of local selfish nodes awareness when a contact occurs, so that information about selfish nodes is quickly propagated. As shown in the paper, this collaborative approach reduces the time and increases the precision when detecting selfish nodes.
Enrique Hernández-Orallo, Manuel D. Serrat Olmos, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni
IEEE Trans. Mob. Comput.2
2012 Evaluation of collaborative selfish node detection in MANETS and DTNs
abstract
Mobile ad-hoc Networks (MANETs) and Delay Tolerant Networks (DTN) rely on network cooperation schemes to work properly. Nevertheless, if nodes have a selfish behaviour and are unwilling to cooperate, the overall network performance could be seriously affected. The use of watchdogs is a well-known mechanism to detect selfish nodes. Nevertheless, the detection process performed by watchdogs can fail, generating false positives and false negatives that can induce a wrong behaviour.
Enrique Hernández-Orallo, Manuel D. Serrat Olmos, Juan-Carlos Cano, Carlos T. Calafate, Pietro Manzoni
MSWiM2