A MULTISINK ENERGY-EFFICIENT ROUTING PROTOCOL FOR WIRELESS BODY AREA NETWORK
Bibliographic record
Abstract
Rapid advancements in wireless sensor network have significantly supported the wireless body area networks (WBAN). In WBAN, especially in medical application, the energy efficiency of the sensor nodes is critical in the Intra-body communication level. In this case, the communication occurs between the sensor nodes (placed inside the human tissue) and sink node (placed on the human skin). Thus, replacing the battery of these sensor nodes is challenging. Several studies in Intra-body communication have focused on reducing the energy consumption by decreasing the distance required to transmit the sensed data. However, the stability of the system (overall lifetime of the system) is not achieved due to the variation in the lifetime of the sensor nodes. Herein, some sensor nodes act as relay nodes. These relay nodes are responsible for sensing, receiving, and aggregating the sensed data from the neighboring sensor nodes, and further sending it to the sink node. The present study describes a unique approach to achieving an energy- efficient routing protocol that guarantees a prolonged lifetime of the sensor, thereby stabilizing the system. Moreover, the peer-to-peer communication between the sensor and sink nodes is also investigated with respect to the mobility model. In conclusion, this study aims to remove the burden from sensor nodes by using multiple sink nodes in order to achieve the shortest distance of communication between the sensor and sink nodes, which could prolong the lifetime of sensor nodes and the overall stability of the system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".