Evidence map›Paper›PMID 36433314›Full record

ArticleSensors (Basel, Switzerland)2022

Computation Offloading Game for Multi-Channel Wireless Sensor Networks.

Heng-Cheng Hu, Pi-Chung Wang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

2 authors.

Heng-Cheng HuDepartment of Computer Science and Engineering, National Chung Hsing University, Taichung 402, Taiwan.
Pi-Chung WangDepartment of Computer Science and Engineering, National Chung Hsing University, Taichung 402, Taiwan.ORCID 0000-0002-4220-2853

Funding

National Science and Technology Council 111-2221-E-005 -045
6 · The paper itself

Abstract

Computation offloading for wireless sensor devices is critical to improve energy efficiency and maintain service delay requirements. However, simultaneous offloadings may cause high interferences to decrease the upload rate and cause additional transmission delay. It is thus intuitive to distribute wireless sensor devices in different channels, but the problem of multi-channel computation offloading is NP-hard. In order to solve this problem efficiently, we formulate the computation offloading decision problem as a decision-making game. Then, we apply the game theory to address the problem of allowing wireless sensor devices to make offloading decisions based on their own interests. In the game theory, not only are the data size of wireless sensor devices and their computation capability considered but the channel gain of each wireless sensor device is also included to improve the transmission rate. The consideration could evenly distribute wireless sensor devices to different channels. We prove that the proposed offloading game is a potential game, where the Nash equilibrium exists in each game after all device states converge. Finally, we extensively evaluate the performance of the proposed algorithm based on simulations. The simulation results demonstrate that our algorithm can reduce the number of iterations to achieve Nash equilibrium by 16%. Moreover, it improves the utilization of each channel to effectively increase the number of successful offloadings and lower the energy consumption of wireless sensor devices.

Indexed as

channel gaincomputation offloadinggame theoryNash equilibriumwireless sensor devices

Identifiers

PMID36433314
PMCPMC9698174

What OpenQuestion holds

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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.