准备写论文,论文大纲和数据搞定

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下面直接给**论文产出阶段Post-Phase-3.5)操作流程**。
目标不是继续开发系统,而是把**已有平台 → 可发表实验结果**。
你现在的系统已经满足论文最低条件:
* ✅ 可复现实验seed
* ✅ baselinegradient / flooding / random
* ✅ 多指标PDR + airtime + TX cost
* ✅ 自动实验 runner
接下来只做 **科研标准三件事**
---
# 一、跑大量 seeds统计显著性
## 为什么必须做
现在结果:
```
PDR ≈ 18%
```
LoRa + 随机信道 → **方差极大**
单次结果 = 不可发表。
论文要求:
> expectation over randomness
即:
[
Result = E_{seed}[metric]
]
---
## 目标规模(直接照做)
| 项目 | 建议值 |
| --------- | ---------- |
| seeds 数量 | **3050** |
| 每 seed 时长 | 100s保持一致 |
| topology | 固定 |
| traffic | 固定 |
| 唯一变量 | RNG seed |
---
## 修改 runner核心思想
你已经有:
```
run_experiments.py
```
现在只加一层:
```python
for seed in range(50):
config.RANDOM_SEED = seed
run_single_experiment(...)
```
输出结构:
```
results/
gradient/
seed_0.json
seed_1.json
...
flooding/
random/
```
---
## 每个 json 至少包含
```json
{
"pdr": 0.187,
"airtime": 0.368,
"tx_total": 217,
"tx_per_success": 36.1
}
```
---
## 然后做统计汇总
计算:
```
mean
std
95% CI
```
公式:
[
CI = 1.96 \cdot \frac{\sigma}{\sqrt{N}}
]
---
# 二、生成 Tradeoff 图(论文核心)
这是**最关键步骤**。
论文 reviewers 不看日志,只看图。
---
## 图 1必须PDR vs Airtime
### 含义
证明:
> flooding 高 PDR 是用 airtime 换来的
---
### 横纵轴
```
x: airtime_usage (%)
y: PDR (%)
```
每个算法一个点(带 error bar
---
### Python 示例
```python
plt.errorbar(
airtime_mean,
pdr_mean,
xerr=airtime_ci,
yerr=pdr_ci,
fmt='o',
label='gradient'
)
```
---
### 论文意义(非常重要)
这是:
> efficiency frontier
审稿人一眼能理解贡献。
---
## 图 2必须TX Cost vs PDR
```
x: tx_per_success
y: PDR
```
解释:
```
能量效率 ↔ 可靠性 tradeoff
```
---
## 图 3强烈建议Airtime Budget Curve
固定 airtime 上限:
```
10%
20%
30%
...
```
看谁 PDR 更高。
这属于:
> fair resource comparison
非常论文化。
---
## 输出格式
保存:
```
figures/
pdr_vs_airtime.pdf
pdr_vs_cost.pdf
```
⚠️ 必须 PDF矢量图
---
# 三、写 Method + Evaluation论文主体
你现在不要写 Introduction。
只写两章:
```
III. Method
IV. Evaluation
```
---
## (1) Method 章节结构(直接按这个写)
### A. Network Model
描述:
* N nodes
* single gateway
* LoRa PHY abstraction
* collision model
不用写代码细节。
---
### B. Routing Algorithms
三个 subsection
#### 1. Gradient Routing
写:
* hello dissemination
* distance metric
* next-hop selection
给一个公式:
[
Cost_i = w_1 RSSI + w_2 HopCount
]
(即使当前权重简单也可以)
---
#### 2. Flooding (Baseline)
说明:
```
each node rebroadcasts once
```
强调:
> upper-bound reliability baseline
---
#### 3. Random Forwarding
说明:
```
random neighbor selection
```
作为 lower baseline。
---
### C. Evaluation Metrics你 Phase-3.5 的贡献)
定义:
#### Packet Delivery Ratio
[
PDR = \frac{received}{generated}
]
#### Airtime Usage
[
A = \frac{\sum TX_time}{simulation_time}
]
#### Transmission Cost
[
C = \frac{total_tx}{successful_packets}
]
这一节其实已经是论文贡献点。
---
## (2) Evaluation 章节结构
### A. Experimental Setup
写:
| 参数 | 值 |
| -------- | ----- |
| Nodes | 12 |
| Area | 800 m |
| Duration | 100 s |
| Seeds | 50 |
---
### B. Reliability Comparison
放表格:
| Algo | PDR | CI |
| ---- | --- | -- |
---
### C. Efficiency Tradeoff核心
插入:
* PDR vs Airtime 图
写一句关键论文句式:
> Gradient achieves comparable reliability while consuming significantly less channel airtime.
---
### D. Discussion
直接写你已经发现的:
```
Flooding improves reliability by saturating the channel rather than improving routing efficiency.
```
这句话就是论文卖点。
---
# 四、你接下来真实的 TODO最终版
直接复制给执行 AI
```markdown
# Paper Production TODO
## Phase-Paper-1: Statistical Experiments
- [ ] run 50 seeds per algorithm
- [ ] save per-seed JSON results
- [ ] compute mean/std/95%CI
## Phase-Paper-2: Figure Generation
- [ ] plot PDR vs Airtime (error bars)
- [ ] plot PDR vs TX_cost
- [ ] export PDF figures
## Phase-Paper-3: Method Section
- [ ] network model description
- [ ] routing algorithm definitions
- [ ] metric formalization
## Phase-Paper-4: Evaluation Section
- [ ] experiment setup table
- [ ] comparison tables
- [ ] tradeoff analysis text
```
---
# 五、一个关键判断(你现在的位置)
你已经从:
```
工程实现阶段
```
进入:
```
科研结果生产阶段
```
后续成功与否 **不再取决于算法**,而取决于:
```
统计严谨性 + 图表达能力
```