Abstract
The N policy is a buffer and transmission management scheme proposed for nodes in wireless sensor networks to save energy. It exploits the concept that the output radio of a node is initially switched off until a critical queue of packets is built up. Then, the output transmission begins and continues until the buffer is completely flushed. The cycle then repeats. In this study, we analyze a buffer with the N policy, equipped additionally with active queue management, which allows for dropping some packets depending on the current buffer occupancy. This extension enables controlling the performance of the node to a much greater extent than in the original N policy. The main contribution is the formulae for the key performance characteristics of the extended policy: the queue size distribution, throughput, and energy efficiency. These formulae are proven for a model with a general distribution of service time and general parameterizations of active management during the energy-saving and transmission phases. Theoretical results are followed by sample numerical calculations, demonstrating how the system’s performance can be controlled using active management in the transmission phase, the energy-saving phase, or both combined. The influence of the threshold value in an actively managed buffer is then shown and compared with its passive counterpart. Finally, solutions to some optimization problems, with the cost function based on the trade-off between the queue length and throughput, are presented.
| Original language | English |
|---|---|
| Article number | 86 |
| Journal | Applied System Innovation |
| Volume | 7 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - Oct 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- N policy
- active queue management
- energy efficiency
- packet buffer
- queue size distribution
- throughput
- wireless sensor networks
ASJC Scopus subject areas
- Control and Systems Engineering
- Information Systems
- Human-Computer Interaction
- Industrial and Manufacturing Engineering
- Applied Mathematics
- Artificial Intelligence
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