Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Distributed Loads: Problem Solving

Distributed Loads: Problem Solving

Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...

Distribution Reliability and Automation

Distribution Reliability and Automation

Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...

Control Systems

Control Systems

Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...

Maximum Power Transfer

Maximum Power Transfer

Numerous practical applications within engineering disciplines, such as telecommunications, necessitate optimizing power delivery to a connected load. This pursuit, however, entails inherent internal losses, which can either equal or exceed the power supplied to the load. The Thevenin equivalent circuit is helpful in finding the maximum power a linear circuit can deliver to a load. It is assumed in this context that the load resistance can be adjusted.
By substituting the entire circuit with...

Load-frequency control

Load-frequency control

Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...

Control of Power Flow

Control of Power Flow

There are several methods to control power flow in power systems:

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Occurrence of the amphibians in the Volga, Don River basins and adjacent territories (Russia): research in 1996-2020.

Biodiversity data journal·2021

Same author

Provenance for distributed biomedical workflow execution.

Studies in health technology and informatics·2012

Same author

SHIWA workflow interoperability solutions for neuroimaging data analysis.

Studies in health technology and informatics·2012

See all related articles

Search research articles

Related Experiment Videos

Consensus-based local data aggregation in wireless sensor networks under node failures and transmission-power-based

Iaroslav Biziarkin¹, Nikolai Litvinov², Vladimir Korkhov²

¹St. Petersburg State University, St. Petersburg, Russian Federation. yaroslav.bizyarkin@spbu.ru.

Scientific Reports

|July 1, 2026

Summary

This summary is machine-generated.

Adaptive transmission power control in wireless sensor networks (WSNs) impacts energy use and network lifespan. The Local Voting Protocol (LVP) offers stable data aggregation quality under adaptive power, unlike Metropolis, which performs better with fixed power.

Keywords:

Data aggregation Local voting protocol Metropolis algorithm Metropolis weights Transmission power Wireless sensor network

Related Experiment Videos

Area of Science:

Computer Science
Network Engineering
Distributed Systems

Background:

Wireless Sensor Networks (WSNs) face energy constraints and node failures, impacting network lifetime and data aggregation.
Transmission power directly influences energy expenditure, network longevity, and communication conditions for distributed data aggregation.
Topology control in WSNs affects connectivity and the reliability of local information exchange, especially in energy-limited scenarios.

Purpose of the Study:

To formulate the problem of distributed data aggregation in WSNs with local information constraints and adaptive transmission power control.
To investigate the interplay between adaptive power control (LINT protocol) and decentralized aggregation protocols (Metropolis and LVP).
To compare the performance of Metropolis and LVP under adaptive-range and fixed-range communication.

Main Methods:

Formulated a problem for joint adaptive communication and distributed aggregation in energy-constrained WSNs with local information.
Developed a simulation framework incorporating a standard radio energy model and probabilistic reporting.
Evaluated two local aggregation protocols (Metropolis and LVP) under adaptive and fixed communication ranges.

Main Results:

The relative performance of aggregation protocols is contingent on the communication regime established by power adjustment.
Metropolis is competitive or preferable under fixed-range, symmetric communication.
LVP demonstrates more stable aggregation quality under adaptive transmission power control (LINT), with comparable network lifetime and energy efficiency.

Conclusions:

The choice of aggregation protocol in WSNs should consider the communication regime resulting from adaptive power control.
LVP provides a robust solution for stable data aggregation in WSNs employing adaptive transmission power control.
Joint optimization of communication power and aggregation strategies is crucial for energy-constrained WSNs.