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Related Concept Videos

Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
Maximum Power Transfer01:16

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...
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system.
Stability01:28

Stability

The time response of a linear time-invariant (LTI) system can be divided into transient and steady-state responses. The transient response represents the system's initial reaction to a change in input and diminishes to zero over time. In contrast, the steady-state response is the behavior that persists after the transient effects have faded.
The stability of an LTI system is determined by the roots of its characteristic equation, known as poles. A system is stable if it produces a bounded...
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
Power Factor Correction01:20

Power Factor Correction

The power transmission to a factory involves the transfer of apparent power, a combination of active and reactive power. The power factor measures how effectively electrical power is converted into useful work output. The ratio of the real power (KW) that does the work to the apparent power (KVA) supplied to the circuit.

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Related Experiment Videos

Energy-Efficient Dynamic RTO with Enhanced Stability for CoAP-Based IoT Networks.

Suyoung Choi1

  • 1Software Innovation Center, Dong-A University, Busan 49315, Republic of Korea.

Sensors (Basel, Switzerland)
|June 26, 2026
PubMed
Summary

This study introduces a new Dynamic Retransmission Timeout (RTO) algorithm for the Constrained Application Protocol (CoAP) to improve performance in volatile Artificial Intelligence of Things (AIoT) networks. The algorithm enhances reliability and reduces communication time, outperforming existing benchmarks.

Keywords:
CoAPCoCoA+Cooja simulatorFASORGilbert–Elliott modelIoTRTT variabilityadaptive RTOcongestion controldynamic packet lossretransmission timeoutwireless sensor networks

Related Experiment Videos

Area of Science:

  • Computer Science
  • Networking
  • Internet of Things (IoT)

Background:

  • The Constrained Application Protocol (CoAP) is crucial for reliable communication in resource-constrained AIoT and Wireless Sensor Networks (WSNs).
  • CoAP's default retransmission timeout (RTO) mechanism struggles with volatile network conditions, leading to inefficiencies.
  • Existing benchmarks like CoCoA+ and FASOR exhibit limitations such as overly conservative backoffs or retransmission storms.

Purpose of the Study:

  • To propose a novel dual-adaptive Dynamic RTO algorithm for CoAP, addressing performance bottlenecks in heterogeneous IoT environments.
  • To enhance the responsiveness and efficiency of CoAP's RTO mechanism under dynamic and volatile network conditions.
  • To provide a scalable and resource-efficient transport-layer solution for next-generation edge-computing infrastructures.

Main Methods:

  • Developed a dual-adaptive Dynamic RTO algorithm that adjusts its parameter inspection cycle (N) based on Round-Trip Time (RTT) variance.
  • Scaled the tuning coefficient (α) in real-time according to packet loss indicators.
  • Evaluated performance using the Gilbert-Elliott dynamic loss model across multi-hop linear and grid network topologies (1x6, 3x6, 5x6).

Main Results:

  • The proposed Dynamic RTO algorithm optimized the throughput-latency trade-off, achieving a total communication time of 25.92 s in complex grid topologies.
  • Demonstrated superior performance compared to CoCoA+ (14.28% improvement) and FASOR (8.89% improvement).
  • Significantly reduced transmission overhead, limiting cumulative retransmissions to 59 counts under severe localized impairments.

Conclusions:

  • The novel Dynamic RTO algorithm offers a scalable, resource-efficient, and empirically robust transport-layer solution for AIoT and WSNs.
  • The adaptive mechanism effectively handles volatile channel conditions and optimizes communication efficiency.
  • This approach establishes a foundation for improved reliability in next-generation edge-computing infrastructures.