Performance issues caused by abnormal HTTP/2 SETTINGS frame exchange

**Title: Performance issues caused by abnormal HTTP/2 SETTINGS frame exchange**

We experienced two problems in gRPC communication between our Java client and Python server:

- Java client version: 1.51.0
- Python server version: 1.70

### 1. HTTP/2 SETTINGS frame exchange issue
When creating the channel in the Java gRPC client, the client must wait for the server to return an HTTP/2 SETTINGS frame before updating the channel state to READY (this is specifically implemented in `io.grpc.netty.NettyClientHandler.FrameListener#onSettingsRead`). However, due to a version compatibility problem in our Python gRPC server, the server fails to correctly return the SETTINGS frame, causing the client's channel to remain in the CONNECTING state for a long time.

### 2. Performance bottleneck analysis
In this state, if we send a large number of RPC requests without deadlines, these requests are accumulated as pending streams and stored in the `pendingStreams` property of `DelayedClientTransport`. In our environment, about one million such requests were queued.

When the TCP connection fails to establish, `io.grpc.internal.DelayedClientTransport#reprocess` is triggered. Inside this method, the system calls `pendingStreams.removeAll(toRemove)`. Since `toRemove` is implemented as an ArrayList rather than a Set, it results in an O(n²) complexity. When n is very large (e.g., around one million), this blocks the IO thread for around 30 minutes, causing severe IO thread stalls.

### Suggestions for optimization
Based on these observations, we propose a couple of potential improvements for grpc-java:
1. Introduce a maximum waiting time for the HTTP/2 SETTINGS frame exchange to avoid waiting indefinitely for incompatible server responses.
2. Change the `toRemove` collection in `DelayedClientTransport#reprocess` to a Set implementation, reducing the complexity from O(n²) to O(n).

Inizia da io.grpc.netty.NettyClientHandler.FrameListener#onSettingsRead e io.grpc.internal.DelayedClientTransport#reprocess, concentrandoti sull’attesa di SETTINGS e sulla pulizia di pendingStreams descritte nel report. Esamina come vengono costruiti pendingStreams e toRemove, quindi usa lo scenario segnalato di un milione di richieste per valutare entrambe le ottimizzazioni proposte. Il lavoro è completato quando il comportamento rilevante è limitato o lineare e il thread IO non rimane più bloccato per la durata segnalata.

Scritto dal modello di indicizzazione a partire dal testo della issue.