research/incentivization.md

Waku is a family of decentralized communication protocols. The Waku network consists of independent nodes running the corresponding protocols. Waku needs incentivization (i13n) to ensure proper node behavior in the absence of any centralized coordinator.

In this document, we overview the problem of i13n in decentralized systems. We classify the possible methods of i13n and give example used in prior successful P2P networks. We then briefly introduce Waku and outline the unique i13n challenges it presents.

We then go into more detail into one of the Waku's protocols, Store, responsible for archival storage. We propose an i13n scheme for Store and implement an MVP solution. We discuss the choices we have made for the MVP version, and what design options may be considered in the future.

Classification of i13n tools

We can think of incentivization tools as a two-by-two matrix:

• rewards vs punishment;
• monetary vs reputation.

In other words, there are four quadrants:

• monetary reward: the client pays the server;
• monetary punishment: the server makes a deposit in advance and gets slashed in case of misbehavior;
• reputation reward: the server's reputation increases if it behaves well;
• reputation punishment: the server's reputation decreases if it behaves badly.

Reputation can only work if there are tangible benefits of having a high reputation and drawbacks of having a low reputation. For example:

• clients are more likely to connect to servers with high reputation;
• clients disconnect from servers with low reputation.

In the presence of monetary rewards, low-reputation servers miss out on potential revenue or lose their deposit. Without the monetary aspects, low-reputation nodes can't get as much benefit from the network. Reputation either assumes a repeated interaction (i.e., local reputation), or some amount of trust (centrally managed rankings).

Ideally, monetary motivation should be atomically linked with performance. A node should be rewarded if and only if it performed the desired action. Analogously, it should be punished if and only it it misbehaved. In other words, if the client pays first, the server cannot deny service, and if the client pays after the fact, it's impossible to default on the obligation.

In blockchain networks, the desired behavior of miners or validators can be automatically verified and rewarded with native tokens (or punished by slashing). Enforcing atomicity in decentralized data-focused networks can be challenging: it is non-trivial to prove that a certain piece of data was sent or received. Therefore, such cases may warrant a combination of monetary and reputation-based approaches.

Related work

There have been many example of incentivized decentralized systems.

Early P2P file-sharing

Early P2P file-sharing networks employed reputation-based approaches and stickly defaults. For instance, in BitTorrent, a peer by default shares pieces of a file before having received it in whole. At the same time, the bandwidth that a peer can use depends on how much is has shared previously. This policy rewards nodes who share by allowing them to download file faster. While this reward is not monetary, it has proven to be sufficient in practice.

Blockchains

The key innovation of Bitcoin, inherited and built upon by later blockchain networks, is the introduction of native monetary i13 mechanism. In the case of Bitcoin, miners create new blocks and are automatically rewarded with newly mined coins, as prescribed by the protocol. An invalid block will be rejected by other nodes and not rewarded, which incentivizes good behavior. There are no intrinsic monetary punishments in Bitcoin, only rewards. However, mining nodes are required to expend physical resources for block generation.

Proof-of-stake consensus algorithms introduced intrinsic monetary punishments in the blockchain context. A validator locks up (stakes) native tokens and gets rewarded for validating new blocks. In case of misbehavior, the deposit is automatically taken away (i.e., the bad actor is slashed).

Decentralized storage

Multiple decentralized storage networks have appeared in recent years, including Codex, Storj, Sia, Filecoin, IPFS. They combine the techniques from early P2P file-sharing and blockchain-inspired reward mechanisms.

Waku

Waku is a family of protocols (see architecture) for a modular decentralized censorship-resistant P2P communications network. The backbone of Waku is the Relay protocol (RLN-Relay is an spam-protected version of the protocol). Additionally, there are three light (client-server, request-response) protocols: Filter, Store, and Lightpush.

There is no strict definition of a full node vs a light node in Waku (see https://github.com/waku-org/research/issues/28). In this document, we may refer to a node that is running Relay and Store (server-side) as a full node, and to a node that is running a client-side of any of the light protocols as a light node.

In light protocols, a client sends a request to a server. A server (a Relay node) performs some actions and returns a response, in particular:

• Filter: the server will relay (only) messages that pass a filter to the client;
• Store: the server responds with messages broadcast within the specified time frame;
• Lightpush: the server publishes the client's message to the Relay network.

Waku i13n challenges

As a communication protocol, Waku lacks consensus or a native token. These properties bring Waku closer to purely reputation-incentivized file-sharing systems. Our goal nevertheless is to combine monetary and reputation-based incentives in Waku. The rationale for that is that monetary incentives have demonstrated their robustness in blockchain networks, and are well-suited for a network designed to scale well beyond the initial phase when it's mainly maintained by enthusiasts for altruistic reasons.

In our i13n framework, currently Waku only operates under reputation-based rewards and punishments. While RLN-Relay adds monetary punishments for spammers, slashing is yet to be activated.

Waku Store

In this section, we design a monetary-based i13n scheme for Waku Store. Similar techniques may be later applied to other protocols.

Store is a client-server protocol. A client asks the node to respond with relevant messages previously relayed through the Relay protocol. A relevant message is a message that has been broadcast via Relay within the specified time frame. The response may be split into multiple parts, as specified by pagination parameters.

Let's say, a client issues a request to the server. We want the following to happen:

• the server responds quickly;
• all the messages in the response are relevant;
• the response contains only relevant messages.

From a security standpoint, each Store node should enforce limits on requests as to not be DoS-ed.

As Waku doesn't intent to establish consensus over past messages, we can only rely on heuristics to determine whether a message had been relayed earlier. To decrease the chance of missing some messages, a client may query multiple servers and combine their replies (union of all messages; messages reported by some majority of servers, etc).

Store i13n MVP

We propose Store-i13n-MVP - the simplest version of i13n in Store.

In broad strokes:

• client: I want this piece of history
• server (after internal calculations): here is the price
• client: pays (if price is ok; otherwise conversation ends)
• server: responds with data
• client: checks the data: if data is irrelevant - decreases server's reputation
• client (optionally): queries another server; compares responses; maybe decreases reputation of both (?) if responses diverge. Or queries 3 servers and assumes that messages returned by 2/3 or 3/3 are "real" ("Never Take Two Chronometers to Sea").

Evaluation

We measure the performance of our i13-ed Store protocol by the following metrics...

TODO: how do we check if we've solved the problem?

Future work

Store-i13n-MVP is the simplest protocol we can start with. Let us now outline the design choices to be made if we were to go beyond MVP.

Price discovery

An incentive scheme should balance the costs and benefits for a node. Rewards should compensate the cost of good behavior. Punishments should offset the benefits that bad behavior may bring.

In the MVP i13n protocol, clients and servers establish a free market by negotiating prices. A server should understand its true costs to negotiate effectively. The costs of a Store server are storage, bandwidth, and computation.

Let us assume a constant flow of messages per epoch and a constant flow of requests for older messages. There are two processes: storing incoming messages, and serving old messages to clients.

The cost of storing incoming messages for one epoch is composed of:

• storage:
  • storage costs of all older messages: proportional to cumulative (message size x time stored);
  • storage costs of newly arrived messages: proportional to message size;
  • a constant cost for I/O operations (storing new messages);
• bandwidth (download) for receiving new messages: proportional to the total size of incoming messages per epoch;
• computational costs of receiving and storing new messages.

(Strictly speaking, the I/O cost may not always be constant due to caching, disk fragmentation, etc.)

The cost of storing messages to clients, per epoch, is composed of:

• storage: none (it's accounted for as storing cost);
• bandwidth
  • upload: proportional to (number of clients) x (length of time frame requested) x (message size);
  • download: proportional to the number of requests;
• computational cost of handling requests.

Storage is likely the dominating cost. Storage costs is proportional to the amount of information stored and the time it is stored for. A cumulative cost of storing a single message grows linearly with time. Assuming a constant stream of new messages, the total storage cost is quadratic in time.

The number of messages in a response may be approximated by the length of the time frame requested. This assumes that messages are broadcast in the Relay network at a constant rate.

Computation: the server spends computing cycles while handling requests. This costs likely depends not only on the computation itself, but also at the database structure. For example, retrieving old or rarely requested messages from the local database may be more expensive than fresh or popular ones due to caching.

RLN as a proxy for message relevance

RLN (rate limiting nullifiers) is a method of spam prevention in Relay (RLN-Relay). The message sender generates a proof of enrollment in some membership set. Multiple proofs generated within one epoch lead to punishment. This technique limits the message rate from each node to at most one message per epoch.

In the i13n context, we can't prove whether a message has indeed been broadcast in the past. Instead, we use RLN proofs as a proxy metric. A valid RLN proof signifies that the message has been generated by a node with an active membership during a particular epoch. Note that a malicious node with a valid membership can generate messages but not broadcast them. Such messages would not be "relevant" (i.e., other nodes would be unaware of them), but they would satisfy the RLN-based heuristic.

Ideally, we would like to punish a server that omits relevant messages. But as this can't be proven, we resort to reputation in this case. In other words: if a client is dissatisfied with the response, it simply won't query this server anymore. A way for the client to know (with some certainty) whether relevant messages have been omitted is to query another server.

Privacy considerations

Light protocols, in general, have weaker privacy properties than P2P protocols. In a client-server exchange, a client wants to selectively interact with the network. By doing so, it often reveals what it is interested in (e.g., subscribes to particular topics).

A malicious Store server can spy on a client in the following ways:

• track what time frames a client is interested in;
• analyze the timing of requests;
• link requests done by the same client.

Payment methods

The MVP protocol is agnostic to payment methods. However, some payment methods may be more suitable than others.

What we want from a payment method:

• wide distribution (many people already have it);
• high liquidity (i.e., easy to buy or sell at a reasonable exchange rate);
• low latency;
• high security.

Let's list all (decentralized) payment options that we have:

• proof-of-work: outsource-able, unavailable for consumer hardware - or is it? (Equihash etc)
• proof-of-X (storage, etc)
• cryptocurrency:
  • ETH
  • a token on Ethereum (ERC20)
  • a token on another EVM blockchain
  • a token on an EVM-based rollup
  • a token on a non-EVM blockchain (BTC / Lightning?)

Note also that there may be different market models. One model is that each client pays for its requests. Another model assumes that (centralized) applications built on top of Waku buy "credits" in bulk for their users, for whom using the application (which may involve querying Store servers under the hood) is free of charge.

Incentive compatibility

In file storage, I store a file and I pay for the ability to query it later. In Store, Alice relays a message, a server stores is, and later Bob queries it (and pays for it under an i13n scheme). Is there a mismatch between who incurs costs and who pays for it? Shall we think of ways to make Alice incur some costs too? See: https://github.com/waku-org/research/issues/32

Generalization for other Waku protocols

We plan to generalize i13n for Store to other Waku protocols, in particular, to light protocols (Lightpush and Filter).

Appendix: Deviations from the desired behavior

There are multiple ways for a node to deviate from the desired behavior. We look at potential misbehavior from the server side and from the client side separately.

Server: Slow response

The server takes too long to respond. Possible reasons:

• the server is offline accidentally;
• the request describes too many relevant messages (the server is overwhelmed);
• the server is malicious and deliberately delays the response;
• the server doesn't have some of the relevant messages and tries to request them from other nodes.

Server: Incomplete response

A relevant message is missing from the response. Possible explanations:

• the server didn't receive the message when it was broadcast;
• the server deliberately withholds the message.

Contrary to blockchains, Relay doesn't have consensus over relayed messages. Therefore, it's impossible to distinguish between the two scenarios above.

Server: Irrelevant response

The response contains a message that is not relevant. There are two scenarios here depending on whether RLN proofs are enforced. If RLN is not enforced, a server may insert any number or irrelevant messages into the response. If RLN is enforced, a server can only do so as long as it has a valid membership to generate the respective proofs. This doesn't eliminate the attack but limits its consequences.

Client: Too many requests

The client sends many request to the server within a short period of time. This may be seen as a DoS attack.

Client: Request is too large

The client sends a response that incurs excessive expenses on the server. For example, the request covers a very long period in history, or, more generically, a period that contains many messages. This may also be seen as a DoS attack.