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rSEM: System-Entropy-Measure-Guided Routing Algorithm for Industrial Wireless Sensor Networks.
Xiaoxiong Xiong1, Chao Dong1, Kai Niu1
1Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing 100876, China.
A new routing algorithm, rSEM, optimizes industrial wireless sensor networks (iWSNs) by minimizing system entropy. This approach balances power consumption and delay, offering a novel strategy for next-generation iWSNs.
Area of Science:
- Computer Science
- Electrical Engineering
- Network Engineering
Background:
- Industrial wireless sensor networks (iWSNs) face challenges in optimizing routing for power consumption and delay.
- Existing routing algorithms often focus on single performance metrics, neglecting overall network efficiency.
Purpose of the Study:
- To introduce a novel routing algorithm, rSEM, for iWSNs guided by a system entropy measure.
- To optimize iWSN routing by minimizing system entropy, thereby improving overall network performance.
Main Methods:
- A system entropy measure is introduced to guide the routing algorithm (rSEM).
- rSEM utilizes a cluster iWSNs architecture, selecting cluster heads and member nodes based on system entropy.
- Cluster head selection uses traversal, while member selection employs a greedy algorithm to reduce complexity.
Main Results:
- The power consumption of iWSNs using rSEM is comparable to Dijkstra's algorithm in 2D and 3D scenarios.
- rSEM exhibits slightly higher delay compared to the LEACH protocol.
- The algorithm is suitable for networks sensitive to both delay and power consumption.
Conclusions:
- rSEM offers a new paradigm for iWSN routing, considering network topology for improved performance.
- The system entropy measure provides an effective way to balance power consumption and delay in iWSNs.
- rSEM enhances overall network performance beyond solely optimizing power or delay.
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