Distributed Storage and Redundancy in Hyphanet

Distributed Storage and Redundancy in Hyphanet

or: How I Learned to Stop Worrying and Love Chunked Data

So you’ve followed the white onion down the Tor rabbit hole, read our previous articles about Hyphanet’s mysterious past, and maybe even compared it to that oniony friend of yours, Tor. You’re intrigued, possibly confused, and definitely wondering:

Okay, cool network. But where the hell does all the data go?

Excellent question, brave explorer of the darknet multiverse. Today, we’re diving headfirst into the magic that makes Hyphanet tick: distributed storage and data redundancy. Think BitTorrent meets RAID, then throw in a dash of paranoid decentralization and a sprinkle of cyberpunk chaos.

Welcome to the world of persistent, anonymous, distributed data.

First, a Reminder: What Is Hyphanet Again?

As discussed in our previous article, Hyphanet (formerly Freenet) is a distributed, censorship-resistant, peer-to-peer data network. It’s designed to allow users to publish and retrieve files anonymously, without worrying about takedowns, subpoenas, or some data center in Ohio catching fire and taking your manifesto with it.

Unlike Tor, which focuses on anonymous routing of live traffic (like web browsing or chat), Hyphanet focuses on storing data that persists over time, even when the original uploader has gone AFK forever.

So how does it actually pull that off?

Let’s lift the curtain.

How Hyphanet Stores Data: Chunks, Keys, and Chaos

In Hyphanet, files aren’t stored as single monolithic blobs. Instead, they’re broken into smaller pieces, called chunks, which are then encrypted and distributed across the network. Think digital dandelion seeds, blowing in the wind, landing wherever they damn well please.

Each chunk is identified and accessed using a key. There are different types of keys (CHKs, SSKs, KSKs), but for our purposes today, let’s keep it simple:

• CHK (Content Hash Key): Used for static, immutable content. Think files, images, videos, or the forbidden PDF you definitely didn’t upload.
• SSK (Signed Subspace Key): Used for content paired with a private key, like a blog, that only the holder of the private key can upload. Your personal namespace. Enables mutable data via versioning.
• KSK (Keyword Signed Key): A more human-readable way to access content. Rarely used anymore because of spam abuse, but hey, it’s a classic. It’s still useful, but only for quick ephemeral use.

Note that KSK and USK are both wrappers around SSK. KSK is just SSK with extra steps in that the hash of the KSK docname is used as the private key of the SSK, from which the public key is derived for fetching. USK is just SSK with a standardized versioning schema added to it. (USK@…/docname/##/foo/bar.baz is converted to SSK@…/docname-##/foo/bar.baz before being fetched, but it will also try fetching ##+++ in the background in case there’s a newer version available)).

UKS can also use DATEHINTs which are special docname suffixes that denote the latest version as of a given year, year+week, year+month, and/or year+month+day. This attempts to solve the problem of trying to use a USK link with a low version number [e.g. 0] when the latest version is thousands of editions ahead.

Files are chunked, hashed, encrypted, and then tossed into the great big bucket of nodes known as the Hyphanet network. But here’s the kicker:

No One Node Stores Everything.

This is not Dropbox. This is not Google Drive. This is the cyberpunk chaos dimension of distributed trustlessness.

Persistence: The Ghost in the (Storage) Machine

So how do these bits stick around?

Welcome to the concept of persistence, a.k.a. “How the hell is my ASCII art of a duck still accessible three years later?”

Hyphanet relies on something called a data store, essentially a big encrypted cache on each participating node. When a user requests a file, the network searches for the chunks needed, pulling them from nearby peers who still have them in their local stores. If a chunk is found, it can be passed along to the requester, and possibly re-cached in the process by intermediate nodes.

This creates a kind of natural replication: the more something is requested, the more copies of its chunks exist throughout the network.

In other words: popularity breeds persistence.

That meme of a cat with a monocle quoting Proust? If everyone’s passing it around, those chunks will live forever.

Your deeply personal manifesto about how pineapples belong on pizza? Not so much, unless you keep seeding it yourself or convince others to love your truth.

Redundancy: Because Shit Breaks

Distributed storage is cool and all, but networks are messy. Nodes go offline. Disks die. Power gets cut. People unplug things to charge their vape pens.

That’s where redundancy kicks in.

Hyphanet builds redundancy into the very structure of chunking and routing.

When you upload a file, Hyphanet doesn’t just store the bare minimum number of chunks. It also stores some extra chunks, kind of like how RAID-5 throws in parity bits to recover from failure.

So even if a few chunks are missing or corrupted, the network can reconstruct the file.

This is done via erasure coding, a fancy math trick that says:

If I break your file into 10 parts, and you lose 3, I can still rebuild it from the other 7. No sweat.

That’s how Hyphanet can shrug off node failures like a hardened sysadmin shrugs off 3 AM pager alerts.

Data Routing: The Dark Magic of Location-Independent Storage

You might be wondering: “Okay, so there’s a chunk of my cat video somewhere on the network. But how do I find it?”

Excellent question, hypothetical hacker.

Hyphanet uses a system called location-independent routing, which is both a mouthful and a mind-bender. In essence, it means:

• Chunks aren’t stored at specific IP addresses.
• Chunks aren’t requested from specific nodes.
• Instead, each node has a unique location key on a virtual keyspace (think a giant 2^256-bit ring), and routes requests toward nodes that are closer (by hash distance) to the chunk you’re looking for.

This sounds abstract, because it is. But the result is a decentralized search mechanism that doesn’t rely on central directories or DNS servers.

It’s like yelling “Hey, who has CHK@blahblah?” into a room full of people, and people pass it on in an encryption-secured and validated game of whisper down the lane until someone somewhere answers back.

The Magic of Caching: Because Nobody Wants to Wait

One of the coolest features of Hyphanet is that it learns as it goes.

When you request a chunk and your node finds it, your node caches it locally. So the next time you, or someone else nearby, requests the same chunk, it’s faster. No more hunting through distant peers like it’s 1999.

This is where the system gets efficient:

• Frequently requested content spreads.
• Rarely accessed stuff fades away.
• The network organically balances performance and privacy.

And just like that, you’ve created a self-healing, crowd-optimized darknet storage party.

What About Deletion?

Ah yes, the eternal question: “How do I delete something from Hyphanet?”

Short answer: you don’t.

Long answer: you don’t, unless nobody cares.

Hyphanet is designed to be censorship-resistant, and that includes resisting deletion. Once a file’s chunks are out in the wild, they’re out there. But don’t panic, this doesn’t mean every bad post lives forever.

Remember that persistence is demand-driven. If something isn’t accessed, it slowly disappears to make room for newer, fresher memes. So in practice, the network forgets over time.

It’s like digital entropy, but with ethics.

What If I Want My Stuff to Stay Forever?

Now you’re asking the real questions.

To keep your data persistent, you have to:

• Regularly request your own content, so it stays fresh in caches.

• Encourage others to access your data. Share links. Bribe friends. Make it spicy.

Hyphanet also offers a plugin called Keepalive, a mechanism for publishers to reinsert content if it starts to vanish. So if you’re running a long-term site or publishing crucial documents, this is your toolkit.

Think of it as gardening. Your data won’t survive unless you water it.

Okay, But What Happens When I Shut Off My Laptop?

Great question, part deux.

When your node goes offline, it forgets everything in its RAM-based caches, but not necessarily its persistent datastore (if you’ve enabled one). So even after a reboot, your node might still be able to serve data chunks you cached earlier.

But if you’re running a transient node (like many casual users do), your cache will empty on every exit. That’s fine, you’re still contributing by routing and requesting content, which keeps the network healthy.

Remember: Hyphanet doesn’t need 100% uptime from every peer. It’s robust because of numbers, not reliability.

TL;DR: So How Does It All Work Again?

Let’s summarize this glorious mess of cyber-distributed storage in plain geek:

• Files are split into encrypted chunks and stored across random peers.
• Each chunk is identified by a cryptographic key.
• The more a chunk is accessed, the more it gets copied and persists.
• Redundancy ensures files can be reconstructed even if some chunks vanish.
• Data is routed by cryptographic key, not location—no central servers, no DNS, no gods.
• Caching makes things faster and more persistent over time.
• You can’t delete stuff directly, but disuse causes decay.
• If you want permanence, keep your node online and keep requesting your own stuff.

In Conclusion: It’s Messy, but It Works

Hyphanet’s storage system isn’t neat. It’s not corporate. It’s not even intuitive at times. But it’s brilliantly chaotic, like all the best things in underground tech.

It survives because it’s decentralized. It persists because people care. And it thrives because of folks like you, paranoid, principled, curious, and a little bit weird.

So next time someone asks, “Where is the data stored in Hyphanet?” you can look them dead in the eye and say:

Everywhere. And nowhere. Also in my garage, apparently.

Happy chunking.