Apply suggestions about network degree and refined wording

Co-authored-by: coot <[email protected]>

Author: ch1bo

docs/leios-design/README.md

@@ -41,7 +41,7 @@ The Linear Leios protocol operates by allowing a second, bigger type of block to
 
 ## Cardano node as a real-time system
 
-The implementation of Leios must be understood in the context of the Cardano node as a concurrent, reactive system operating under real-time constraints in an adversarial environment. While "real-time" in this context does not refer to the millisecond-level hard deadlines found in industrial control systems, timely action nontheless remains crucial to protocol success and network security. 
+The implementation of Leios must be understood in the context of the Cardano node as a concurrent, reactive system operating under real-time constraints in an adversarial environment. While "real-time" in this context does not refer to the millisecond-level hard deadlines found in industrial control systems, timely action at the scale of seconds nontheless remains crucial to protocol success and network security. 
 
 The currently deployed Praos implementation establishes clear [data diffusion targets](https://ouroboros-network.cardano.intersectmbo.org/pdfs/network-design/network-design.pdf#subsection.5.1): blocks must reach 95% of nodes within the 5-second $\Delta$ parameter, with target performance at 98% and stretch goals at 99%. While these are comfortably achieved most of the time, blocks are regularly adopted within 1 second across the network, there are some situations even in the current system where the target is not reached. For example, due to reward calculations happening at the epoch boundary.
 
@@ -55,7 +55,7 @@ The current primary responsibilities of a Cardano node are roughly:
 - Transaction submission: receiving, validating, and transmitting transactions to be included in blocks.
 - Block production: creating new blocks and extending current chain when selected as slot leader. 
 
-Despite this apparent simplicity, this already results in a highly concurrent system once cardinalities of upstream and downstream network peers are considered. A node typically maintains in the order of 10 upstream and 100 downstream connections, each of which may be simultaneously requesting or serving data. All of these operations share critical resources including memory, CPU, and network bandwidth, requiring careful resource management to ensure that timing requirements are met even under load.
+Despite this apparent simplicity, this already results in a highly concurrent system once cardinalities of upstream and downstream network peers are considered. A `cardano-node` with the default configuration maintains 20 upstream hot peers, 10 upstream warm peers and can have up to a few hundred downstream connections, each of which may be simultaneously requesting or serving data. All of these operations share critical resources, including memory, CPU, and network bandwidth, requiring careful resource management to ensure timing requirements are met even under load.
 
 Leios significantly expands this concurrency model by introducing new responsibilities:
 
@@ -775,7 +775,7 @@ Both approaches necessarily abstract real system details and thus provide eviden
 
 Prototypes on real infrastructure validate performance characteristics that simulation typically cannot guarantee. The line between simulation and prototyping is blurry, but both concepts share the trait of allowing rapid exploration of the most uncertain aspects of the design before committing to a full implementation. Referring back to the key threats and assumptions to validate early, the primary focus of prototyping is on network diffusion performance under high throughput conditions and adversarial scenarios.
 
-**Network diffusion prototype:** An early implementation of the actual Leios network protocols and potential freshest-first delivery mechanisms, that allows running experiments with various network topologies. Ledger validation of Leios concepts is stubbed out and transmitted data is generated synthetically to focus purely on network performance. Deployed to controlled environments like local devnets and private testnets like the the Performance and Testing cluster, this prototype systematically explores how performance scales with network size and block size, tests different topologies, and crucially answers whether the real network stack achieves the diffusion deadlines required by protocol security arguments. Key measurements include endorser block arrival time distributions, freshest-first multiplexing effectiveness, topology impact on diffusion, and behavior under adversarial scenarios including eclipse attempts and targeted withholding. These measurements will answer questions like, "how much" freshest-first delivery we need, whether the proposed network protocols are practical to implement and what protocol parameter are feasible.
+**Network diffusion prototype:** An early implementation of the actual Leios network protocols and freshest-first delivery mechanisms, that allows running experiments with various network topologies. Ledger validation of Leios concepts is stubbed out and transmitted data is generated synthetically to focus purely on network performance. Deployed to controlled environments like local devnets and private testnets like the the Performance and Testing cluster, this prototype systematically explores how performance scales with network size and block size, tests different topologies, and crucially answers whether the real network stack achieves the diffusion deadlines required by protocol security arguments. Key measurements include endorser block arrival time distributions, freshest-first multiplexing effectiveness, topology impact on diffusion, and behavior under adversarial scenarios including eclipse attempts and targeted withholding. These measurements will answer questions like, "how much" freshest-first delivery we need, whether the proposed network protocols are practical to implement and what protocol parameter are feasible.
 
 Adversarial testing represents a crucial aspect of prototype validation. In a controlled environment, some nodes can still be configured to exhibit adversarial behaviors such as sending invalid blocks, withholding information, or attempting to exhaust resources of honest nodes. Observing how honest nodes respond provides evidence that the mitigations described in the design are effective. Despite using real network communication, such systems can still be determinstically simulation-tested using tools like [Antithesis](https://antithesis.com/), which is currently picked up also by node-level tests in the Cardano community via [moog](https://github.com/cardano-foundation/moog). If we can put this technique to use for adversarial testing of Leios prototypes and release candidates, this can greatly enhance our ability to validate the protocol under challenging conditions by exploring a much wider range of adversarial scenarios than would be feasible through manually created rigit test scenarios.