Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

No more traffic blues for information transfer: decongesting wireless channels

11.11.2019

A machine-learning algorithm can help select the best channel for communication over a wireless network of resource-constrained devices

The wireless Internet of Things (IoT) is a network of devices in which each device can directly send information to another over wireless channels of communication, without human intervention. With the number of IoT devices increasing every day, the amount of information on the wireless channels is also increasing.


Researchers from the Tokyo University of Science and Keio University propose that a certain machine learning algorithm can help resource-constrained devices on a wireless network select optimal channels for information transmission; this could potentially decongest massive IoT networks.

Credit: Tokyo University of Science

This is causing congestion over the network, leading to loss of information due to interference and the failure of information delivery. Research to solve this problem of congestion is ongoing, and the most widely accepted and applied solution is the "multi-channel" technology. In this technology, information transmission is distributed among various parallel channels based on the traffic in a particular channel at a given time.

But, at present, optimal information transmission channels are selected using algorithms that cannot be supported by most existing IoT devices because these are resource-constrained; i.e., they have low storage capacity and low processing power, and must be power-saving while remaining in operation for long periods of time.

In a recent study published in Applied Sciences, a group of scientists from the Tokyo University of Science and Keio University, Japan, propose the use of a machine-learning algorithm, based on the tug-of-war model (which is a fundamental model, earlier proposed by Professor Song-Ju Kim from Keio University, that is used to solve such problems as that of how to distribute information across channels), to select channels. "We realized that this algorithm could be applied to IoT devices, and we decided to implement it and experiment with it," Professor Mikio Hasegawa, the lead scientist from the Tokyo University of Science, says.

In their study, they built a system in which several IoT devices were connected to form a network and each device could only select one of several available channels through which to transmit information each time. Moreover, each device was resource-constrained.

In the experiment, the devices were tasked with waking up, transmitting one piece of information, going to sleep, and then repeating the cycle a certain number of times. The role of the proposed algorithm was to enable the devices to select the optimal channel each time, such that at the end of it all, the highest possible number of successful transmissions (i.e., when all the information reaches its destination in one piece) has taken place.

The algorithm is called reinforcement-learning and it goes about the task as follows: every time a piece of information is transmitted through a channel, it notes the probability of achieving successful transmissions via that channel, based on whether the information completely and accurately reaches its destination. It updates this data with every subsequent transmission.

The researchers used this setup to also check a) whether the algorithm was successful, b) whether it was unbiased in its selection of channels, and c) whether it could adapt to traffic variations in a channel. For the tests, an additional control system was constructed in which each device was assigned a particular channel and it could not select any other channel when transmitting information.

In the first case, some channels were congested before beginning the experiment, and the scientists found that the number of successful transmissions was larger when the algorithm was used, as opposed to when it was not.

In the second case, some channels became congested when the algorithm was not used, and information could not be transmitted through them after a point of time, causing "unfairness" in channel selection.

However, when the scientists used the algorithm, the channel selection was found to be fair. The findings for the third case clarify those for the previous two cases: when the algorithm was used, devices automatically began to ignore a congested channel and re-used it only when the traffic in it decreased.

"We achieved channel selection with a small amount of computation and a high-performance machine-learning algorithm," Prof Hasegawa tells us. While this means that the algorithm successfully solved the channel selection problem under experimental conditions, its faring in the real world remains to be seen.

"Field experiments to test the robustness of this algorithm will be conducted in further research," the scientists say. They also plan to improve the algorithm in future research by taking into consideration other network characteristics, such as channel transmission quality.

The world is swiftly moving towards massive wireless IoT networks with an increasing number of devices connecting over wireless channels globally. Every possible organization or scholar is taking the opportunity of this moment in the history of time to solve the channel selection problem and get ahead of the game. Prof Hasegawa and his team have managed to take one of the first steps in the race. The future of high-speed, error-free wireless information transmission may be near!

###

About the Tokyo University of Science

Tokyo University of Science (TUS) is a well-known and respected university, and the largest science-specialized private research university in Japan, with four campuses in central Tokyo and its suburbs and in Hokkaido. Established in 1881, the university has continually contributed to Japan's development in science through inculcating the love for science in researchers, technicians, and educators.

With a mission of "Creating science and technology for the harmonious development of nature, human beings, and society", TUS has undertaken a wide range of research from basic to applied science. TUS has embraced a multidisciplinary approach to research and undertaken intensive study in some of today's most vital fields. TUS is a meritocracy where the best in science is recognized and nurtured. It is the only private university in Japan that has produced a Nobel Prize winner and the only private university in Asia to produce Nobel Prize winners within the natural sciences field.

Website: https://www.tus.ac.jp/en/mediarelations/

About Professor Mikio Hasegawa from Tokyo University of Science

Dr Mikio Hasegawa is currently a Professor at the Department of Electrical Engineering, Faculty of Engineering, Tokyo University of Science, Japan. This paper is the latest in a vast body of research presentations, about 130 publications, and in it he serves as the lead author. His research began in 1994 and has spanned fields ranging from Chaos theory to mobile internet and mathematical engineering considering complex systems theories. He has won several awards for his research, including a best paper award in February 2019.

Tsutomu Shimizu | EurekAlert!
Further information:
http://dx.doi.org/10.3390/app9183730

More articles from Information Technology:

nachricht Man versus machine: Can AI do science?
14.01.2020 | Okinawa Institute of Science and Technology (OIST) Graduate University

nachricht Beyond 5G lab: Communication technology of the future
13.01.2020 | Friedrich-Alexander-Universität Erlangen-Nürnberg

All articles from Information Technology >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: Miniature double glazing: Material developed which is heat-insulating and heat-conducting at the same time

Styrofoam or copper - both materials have very different properties with regard to their ability to conduct heat. Scientists at the Max Planck Institute for Polymer Research (MPI-P) in Mainz and the University of Bayreuth have now jointly developed and characterized a novel, extremely thin and transparent material that has different thermal conduction properties depending on the direction. While it can conduct heat extremely well in one direction, it shows good thermal insulation in the other direction.

Thermal insulation and thermal conduction play a crucial role in our everyday lives - from computer processors, where it is important to dissipate heat as...

Im Focus: Fraunhofer IAF establishes an application laboratory for quantum sensors

In order to advance the transfer of research developments from the field of quantum sensor technology into industrial applications, an application laboratory is being established at Fraunhofer IAF. This will enable interested companies and especially regional SMEs and start-ups to evaluate the innovation potential of quantum sensors for their specific requirements. Both the state of Baden-Württemberg and the Fraunhofer-Gesellschaft are supporting the four-year project with one million euros each.

The application laboratory is being set up as part of the Fraunhofer lighthouse project »QMag«, short for quantum magnetometry. In this project, researchers...

Im Focus: How Cells Assemble Their Skeleton

Researchers study the formation of microtubules

Microtubules, filamentous structures within the cell, are required for many important processes, including cell division and intracellular transport. A...

Im Focus: World Premiere in Zurich: Machine keeps human livers alive for one week outside of the body

Researchers from the University Hospital Zurich, ETH Zurich, Wyss Zurich and the University of Zurich have developed a machine that repairs injured human livers and keep them alive outside the body for one week. This breakthrough may increase the number of available organs for transplantation saving many lives of patients with severe liver diseases or cancer.

Until now, livers could be stored safely outside the body for only a few hours. With the novel perfusion technology, livers - and even injured livers - can now...

Im Focus: SuperTIGER on its second prowl -- 130,000 feet above Antarctica

A balloon-borne scientific instrument designed to study the origin of cosmic rays is taking its second turn high above the continent of Antarctica three and a half weeks after its launch.

SuperTIGER (Super Trans-Iron Galactic Element Recorder) is designed to measure the rare, heavy elements in cosmic rays that hold clues about their origins...

All Focus news of the innovation-report >>>

Anzeige

Anzeige

VideoLinks
Industry & Economy
Event News

11th Advanced Battery Power Conference, March 24-25, 2020 in Münster/Germany

16.01.2020 | Event News

Laser Colloquium Hydrogen LKH2: fast and reliable fuel cell manufacturing

15.01.2020 | Event News

„Advanced Battery Power“- Conference, Contributions are welcome!

07.01.2020 | Event News

 
Latest News

A new 'cool' blue

17.01.2020 | Life Sciences

EU-project SONAR: Better batteries for electricity from renewable energy sources

17.01.2020 | Power and Electrical Engineering

Neuromuscular organoid: It’s contracting!

17.01.2020 | Life Sciences

VideoLinks
Science & Research
Overview of more VideoLinks >>>