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Record W2751372205

Performance enhancements in wireless multihop ad-hoc networks

2011· dissertation· en· W2751372205 on OpenAlexaff
Fayez Gebali, Lin Cai, Ahmad Ali Abdullah

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsComputer networkWireless ad hoc networkHidden node problemComputer scienceMultiple Access with Collision Avoidance for WirelessWireless networkAd hoc wireless distribution serviceNode (physics)Mobile ad hoc networkThroughputNetwork packetVehicular ad hoc networkWirelessOptimized Link State Routing ProtocolTransmission (telecommunications)Distributed computingRouting protocolWi-Fi arrayEngineeringTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

Improving the performance of the wireless multihop ad hoc networks faces several challenges. In omni-directional antenna based solutions, the use of the RTS/CTS mechanism does not completely eliminate the hidden-terminal and exposed-terminal problems. Deafness is an additional challenge to the directional antenna based solutions. This dissertation, first develops analytical models for quantifying the throughput and delay in wireless multihop ad hoc networks. The models consider the impact of hidden terminals using the realistic signal to interference and noise ratio model and consider random node distribution. The proposed analysis is applicable to many wireless MAC protocols and applications. The analytical results reveal several important issues. The first issue is quantifying the impact of adjusting the transmission range on the throughput and delay in wireless multihop ad hoc networks. The other issue is the hidden terminal region is closely related to the distance between the transmitter and the receiver. Thus, it is possible to adjust the transmission range to optimize the whole network performance. These results provide important guidelines for network planning and protocol optimization in wireless multihop ad hoc networks. Second, it proposes a new Enhanced Busy-tone Multiple Access (EBTMA) medium access control (MAC) protocol for minimizing the negative impact of both the hidden-terminal and the exposed-terminal problems. The new protocol can also enhance the reliability of packet broadcasts and multicasts which are important for many network control functions such as routing. Different from other busy-tone assisted MAC protocols, the protocol uses a non-interfering busy-tone signal in a short period of time, in order to notify all hidden terminals without blocking a large number of nodes for a long time. In addition, the proposed EBTMA protocol can co-exist with the existing 802.11 MAC protocol, so it can be incrementally deployed. Third, it investigates how to support the directional antennas in ad hoc multihop networks for achieving higher spatial multiplexing gain and thus higher network throughput. A new MAC protocol called Dual Sensing Directional MAC (DSDMAC) protocol for wireless ad hoc networks with directional antennas is proposed. The proposed protocol differs from the existing protocols by relying on a dual sensing strategy to identify deafness, resolve the hidden-terminal problem and to avoid unnecessary blocking. Finally, this dissertation provides important results that help for network planning and protocol optimization in wireless multihop ad hoc networks in quantifying the impact of transmission range on the throughput and the delay. The accuracy of these results has been verified with extensive discrete event simulations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.240
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2011
Admission routes1
Has abstractyes

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