ZEQoS: A New Energy and QoS-Aware Routing Protocol for Communication of Sensor Devices in Healthcare System
Bibliographic record
Abstract
This paper proposes a novel integrated energy and QoS-aware routing protocol with the considerations of energy, end-to-end latency, and reliability requirements of body area network (BAN) communication. The proposed routing protocol, called ZEQoS, introduces two main modules (MAC layer and network layer) and three algorithms (neighbor table constructor, routing table constructor, and path selector). To handle ordinary packets (OPs), delay-sensitive packets (DSPs), and reliability-sensitive packets (RSPs), the new mechanism first calculates the communication costs, end-to-end path delays, and end-to-end path reliabilities of all possible paths from a source to destination. The protocol then selects the best possible path(s) for OPs, RSPs, and DSPs by considering their QoS requirement. Extensive simulations using OMNeT++ based simulator Castalia 3.2 demonstrate that the performance of the proposed integrated algorithm is satisfactory when tested on a real hospital scenario, and all data types including OPs, DSPs, and RSPs are used as offered traffic. Simulations also show that the ZEQoS also offers better performance in terms of higher throughput, less packets dropped on MAC and network layers, and lower network traffic than comparable protocols including DMQoS and noRouting.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".