Evidence map›Paper›PMID 32486419›Full record

ArticleSensors (Basel, Switzerland)2020

Analysis for Joint Delay-Power Tradeoff with Buffer/Channel-Aware and its FPGA Implementation in Wireless Sensor Networks.

Joumana Dakkak, Saleh Eisa, Hesham M El-Badawy, Ahmed ElBakly

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Joumana DakkakDepartment of Basic &Applied Sciences, Arab Academy for Science, Technology and Maritime Transport, Cairo 2033, Egypt.
Saleh EisaDepartment of Electronics & Communications Engineering, Arab Academy for Science, Technology and Maritime Transport, Cairo 11799, Egypt.
Hesham M El-BadawyNetwork Planning Department, National Telecommunication Institute (NTI), Cairo 11768, Egypt.
Ahmed ElBaklyDepartment of Basic &Applied Sciences, Arab Academy for Science, Technology and Maritime Transport, Cairo 2033, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, we aim to investigate the delay-power tradeoff problem which is attracting widespread interest due to its importance in wireless technology. This research has two main objectives. First, to assess the effect of different system parameters on the performance metrics. Second, to provide a solution for this optimization problem. A two-state, slow-fading channel is categorized into good and bad channel states. An adaptive transmission and random data arrivals are considered in our model. Each channel category has its own Markov chain, which is used in modeling the system. A joint Buffer-Aware and Channel-Aware (BACA) problem was introduced. In addition, an enhanced iterative algorithm was introduced for obtaining a sub-optimal delay-power tradeoff. The results show that the tradeoff curve is piecewise linear, convex and decreasing. Furthermore, a channel-aware system was investigated to provide analysis of the effect of system parameters on the delay and power. The obtained results show that the dominant factors that control the system performance are based on the arrival rate and the channel goodness factor. Moreover, a simplified field programable gate array (FPGA) hardware implementation for the channel aware system scheduler is presented. The implementation results show that the consumed power for the proposed scheduler is 98.5 mW and the maximum processing clock speed is 190 MHz.

Indexed as

delay-power tradeoffInternet of ThingsMarkov chain

Identifiers

PMID32486419
PMCPMC7309123

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.