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Website daily update for 2024-11-11T04-02-26
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107 changes: 107 additions & 0 deletions content.en/filecoin/dht/2024-45-report.md
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---
title: Week 2024-45
plotly: true
slug: 2024-45
weight: 1045614
---

# Filecoin Report Cal. Week 45 - 2024

## General Information

The following results show measurement data that were collected in calendar week 45 in 2024 from `2024-11-04` to `2024-11-11`.

- Number of crawls `336`
- Number of visits `1,439,595`
> Visiting a peer means dialing or connecting to it. Every time the crawler or monitoring process tries to dial or connect to a peer we consider this as _visiting_ it. Regardless of errors that may occur.
- Number of unique peer IDs visited `1,038`
- Number of unique peer IDs discovered in the DHT `1,038`
- Number of unique IP addresses found `743`

Timestamps are in UTC if not mentioned otherwise.

## Agents

This plot shows the distribution of various user agents over time.

{{< plotly json="/plots/2024/11/04/filecoin-agents-overall-stacked.json" height="600px" >}}

## Churn Analysis

This plot presents the Cumulative Distribution Function (CDF) of peer departure
times from the network over a measurement period of one-week. The plot
basically shows the percentage of nodes online at a point in time (`t=0`) that
will have disconnected after 1 hour, 2 hours, 3 hours, .. up to 24 hours after `t=0`.

- **X-Axis (Time in Hours)**: Represents the elapsed time since the reference
point (`t=0`), measured in hours.
- **Y-Axis (Percentage of Offline Peers)**: Indicates the cumulative
percentage of peers that have disconnected from the network by the
corresponding time interval. Specifically, it shows the proportion of peers
that were online at `t=0` and have since gone offline.

This visualization aids in understanding peer churn dynamics, which is crucial
for optimizing network stability, resource allocation, and improving overall
decentralized network performance.

Note that the sum of the CDF is **NOT** 100%, as it only includes peers that were
online for up to 24h.

{{< plotly json="/plots/2024/11/04/filecoin-network-stability-cdf.json" height="800px" >}}

## Geolocation

Geographical data is sourced from the [MaxMind database](https://www.maxmind.com), which maps IP addresses to corresponding countries.

This bar plot illustrates the distribution of observed nodes across different countries.

{{< plotly json="/plots/2024/11/04/filecoin-geo-agent-All-bars.json" height="600px" >}}

This plot displays the weekly geographical distribution of nodes, categorized by country.

{{< plotly json="/plots/2024/11/04/filecoin-geo-agent-All-lines.json" height="600px" >}}

### Cloud Providers

Cloud providers data is sourced from [Udger](https://udger.com/resources/datacenter-list), which maps IP addresses to known hosting providers.

#### Cloud Hosting Rate

This line chart displays the count of nodes within the Filecoin network that are hosted on known commercial cloud providers, compared to those that are not. It tracks the distribution over a specified period, offering insights into the infrastructure preferences for node hosting.

Regular analysis of this chart can reveal trends in the adoption of cloud services for nodes. Such information is crucial for understanding the network's resilience and the potential reliance on cloud infrastructure.

{{< plotly json="/plots/2024/11/04/filecoin-cloud-rate-agent-All-lines.json" height="600px" >}}

This bar chart presents the weekly distribution of Filecoin nodes among various cloud providers, including nodes not hosted within data centers (grouped under _Non-Datacenter_).

{{< plotly json="/plots/2024/11/04/filecoin-cloud-agent-All-bars.json" height="600px" >}}

The line chart illustrates the trends in the distribution of all Filecoin nodes across cloud providers over the given time period. Note that nodes hosted outside of data centers are not included in this representation.

{{< plotly json="/plots/2024/11/04/filecoin-cloud-agent-All-lines.json" height="600px" >}}

## Crawls

### Protocols

This plot illustrates the evolving count of nodes supporting each of the listed protocols over time. It exclusively presents data gathered from nodes accessible through a libp2p connection via our crawler. The identification of supported protocols relies on the [libp2p identify protocol](https://github.com/libp2p/specs/tree/master/identify), hence necessitating a libp2p connection for discovery.

{{< plotly json="/plots/2024/11/04/filecoin-crawl-protocols.json" height="1200px" >}}

### Errors

{{< plotly json="/plots/2024/11/04/filecoin-connection-errors-single.json" height="600px" >}}

{{< plotly json="/plots/2024/11/04/filecoin-crawl-errors-single.json" height="600px" >}}

## Stale Peer Records

This stacked plot depicts the count of peer records stored within each node's routing table and made accessible through the DHT.
These peer records are used to discover new remote peers within the network, enabling efficient and secure routing towards the target peer or content

Ensuring the reachability of referenced peers shared within the network holds paramount importance. The plot delineates the occurrences of reachable and non-reachable (stale) peer records. Note that nodes running behind a NAT are counted as unreachable even though they may be online.

For instance, if a peer's record is present in the routing tables of 100 other nodes and the peer is reachable, the plot will reflect an increase of 100 in the _online_ category.

{{< plotly json="/plots/2024/11/04/filecoin-stale-records-stacked.json" height="600px" >}}

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