# The Decentralized Storage Market
> **Alternative Specification** where makers request a N number of nodes and takers post their peerIDs that should not forefill more than 33%(example)of N Nodes, the DAO verifies Data Availability, Decentralization and Speed(in the future).

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## Abstract

In the age of decentralized storage solutions, guaranteeing data integrity and availability while ensuring cost-efficiency remains paramount. This project presents an alternative model for a decentralized order book system utilizing IPFS and Ethereum, where node operators take orders directly from the order book, thereby storing their IPFS peer IDs for specific content identifiers (CIDs). In this model, content creators (makers) specify the number of nodes required to store a CID, the hosting duration, and the price, which includes a staked Ethereum token generating interest over time.

Node operators (takers) fulfill these storage orders by distributing the data across their networks, as directed by the makers. The Validator DAO's software periodically verifies the hosting status by extracting order information, utilizing IPFS commands to confirm peer IDs, and validating file sharing. Through IPFS DHT operations, the Validator DAO ensures that node operators meet their obligations. Additionally, future implementations will include speed verification by downloading random data chunks. The Validator DAO logs compliance events, which are displayed on the decentralized application (DApp) frontend, giving a transparent view of nodes’ performances and payment calculations.

Payments to node operators are facilitated daily by unlocking the makers' staked Ethereum upon successful validation. This model provides a dynamic and flexible approach to decentralized storage, allowing for reduced costs and efficient resource management while ensuring data availability and integrity through rigorous validation mechanisms.

## Key Concepts

* **Order Taking**: Node operators take orders from the order book that specify the number of nodes, hosting time, and price.
* **Peer ID Storage**: Node operators store their IPFS peer IDs where the file should be distributed.
* **Validator DAO**:
* Extracts information from the taken orders.
* Verifies the existence of peer IDs.
* Uses IPFS find peer and DHT findprovs to check file sharing.
* Validates by downloading a random chunk of data (future use).
* **Payment Mechanism**:
* The Validator DAO logs compliance and triggers daily payments to the node operators.
* Node operators fetch payments from the order book using locked Ethereum of the makers.

## Generalities

* Node operators take orders directly from the order book, specifying the number of nodes to store the file.
* The Validator DAO periodically verifies the hosting by checking IPFS peer IDs and file sharing using IPFS commands.
* The system calculates payments based on the compliance and logs events into the Validator DAO.
* The Node operators can fetch payments daily from the order book using the locked Ethereum of the makers.

### Use Case Diagram

@startuml
actor Maker as M
actor NodeOperator as N
actor ValidatorDAO as V

usecase "Create Order" as CO
usecase "Post Order to IPFS" as POI
usecase "Take Order" as TO
usecase "Store Peer IDs" as SPI
usecase "Verify Hosting" as VH
usecase "Daily Payment" as DP
usecase "Calculate Price" as CP

M --> CO : Create new order
M --> POI : Post order to IPFS

CO --> POI : Posts CID, price, nodes, TTL

N --> TO : Take order
N --> SPI : Store Peer IDs

V --> VH : Verify hosting by fetching peer data
VH --> CP : Calculate prices
VH --> DP : Log compliance and trigger payments

DP --> N : Fetch daily payments
@enduml

### Sequence Diagram

@startuml
actor Maker as M
actor NodeOperator as N
actor ValidatorDAO as V

M -> Order: createOrder(CID, price, nodes, ttl)
Order -> IPFS: post(CID)
Order -> OrderBook: addOrder(CID, price, nodes, ttl)

N -> OrderBook: takeOrder(CID)
OrderBook -> N: assign(CID, peers)
N -> IPFS: storePeerId(CID, peerId)

V -> OrderBook: fetchOrders()
V -> OrderBook: fetchOrderDetails(CID)
V -> IPFS: findPeer(peerId)
V -> IPFS: dhtFindProvs(CID)
V -> IPFS: downloadChunk(CID) # future use

alt if valid
    V -> PaymentContract: logCompliance(CID, peerId)
    N -> PaymentContract: fetchDailyPayment(CID)
end
@enduml

### Activity Diagram

@startuml
start
:Maker creates order;
:Post order to IPFS;
:Node operator takes order;
:Store peer IDs;
:Periodic validation;
if (Valid hosting?) then (yes)
    :Log compliance;
    :Calculate price to pay;
    :Trigger daily payments;
else (no)
    :Handle non-compliance;
endif
:Node operator fetches payment;
stop
@enduml

### Component Diagram

@startuml
package "Decentralized Order Book System" {
    [Order Management] <<component>> {
        Order
        + createOrder(string CID, uint256 price, uint256 nodes, uint256 ttl)
        + postToIPFS()
    }
    
    [Order Book] <<component>> {
        + addOrder(CID, price, nodes, ttl)
        + takeOrder(CID)
        + fetchOrders()
        + fetchOrderDetails(CID)
    }
    
    [Storage Management] <<component>> {
        IPFS
        + post(CID)
        + findPeer(peerId)
        + dhtFindProvs(CID)
        + storePeerId(CID, peerId)
        + downloadChunk(CID) // future use
    }
    
    [Validation and Payment] <<component>> {
        ValidatorDAO
        + verifyHosting(CID, peerId)
        + calculatePrice(CID)
        + logCompliance(CID, peerId)
        + triggerDailyPayments(CID)
    }
    
    [Payment Management] <<component>> {
        PaymentContract
        + fetchDailyPayment(CID)
    }
}

[Order Management] --> [Order Book]
[Order Management] --> [Storage Management]
[Order Book] --> [Storage Management]
[External Interface] : keeps relationships
[Validation and Payment] --> [Order Book]
[Validation and Payment] --> [Storage Management]
[Validation and Payment] --> [Payment Management]
[Payment Management] --> [Order Book]
@enduml

## Tokenomics (General Maths)

1. **Data Availability**:

**Probability of File Availability**:

Referencing redundancy and uptime:

$$ P_{\text{availability}} = 1 - (1 - U)^R $$

where:

* $U$ is the uptime of a single node (e.g., 0.99 for 99% uptime).
* $R$ is the redundancy, i.e., the number of nodes hosting the file.
This is corroborated by the principles outlined in "Cryptographic File System" by M. Blaze, et al., and "An Analysis of Decentralized Network Performance" by D. Anderson, et al.

2. **Decentralization**:

**Entropy of Node Distribution**:

$$ H = -\sum_{i=1}^{n} p_i \log_2(p_i) $$

This takes into account node distribution to measure decentralization, similar to the entropy measures discussed in "Decentralized Information Flow Control" by A. Sabelfeld and A.C. Myers.

**Proof-of-Access Validation**:

$$ P_{\text{valid}} = \frac{\text{Number of Successful Validations}}{\text{Total Number of Attempts}} $$

Referencing schemes like those in "Proofs of Data Reliability in Cloud Storage" by J. Sun et al.

3. **Speed**:
Average Download Speed:

$$ S_{\text{avg}} = \frac{B_{\text{total}}}{N_{\text{concurrent}}} $$

Based on "Performance of Distributed Storage Systems" by R. Rodrigues and B. Liskov.

Tokenomics and Pricing Model:
With a user-driven order book to set prices, the mechanism incorporates human oracles to ensure competitiveness.

Average User-Set Price Calculation:

$$ P_{\text{avg}} = \frac{\sum_{i=1}^{n} P_i}{n} $$

Where:

* $P_i$ is the price per byte set by each user.
* $n$ is the number of price-setting users (or orders).
This user-driven mechanism leverages decentralized finance (DeFi) mechanisms similar to liquidity pools and Automated Market Makers (AMM).

**Storage Price per Byte**:

Revised to include the average user-set price:

$$ P_{\text{byte}} = \frac{P_{\text{avg}}}{U} $$

Where:

Uptime $U$ is the average uptime of nodes.

**Reward per Valid Proof**:

$$ R_{\text{proof}} = k \times Uptime \times Bandwidth \times \frac{1}{Redundancy} $$

Penalty for Failed Proof:

$$ S_{\text{penalty}} = \frac{\text{Staked Amount}}{\text{Number of Failed Proofs}} $$

Practical Example:
Define Parameters:

Uptime $U = 0.99$
Redundancy $R = 3$
User-set prices $P_1, P_2, \ldots, P_n$
Proportionality constant $k = 0.0001$

**Calculate Average User-Set Price**:

Assume prices set by users are $P_1 = 0.00004 \text{ ETH/byte}, P_2 = 0.00005 \text{ ETH/byte}, ..., P_n = 0.00003 \text{ ETH/byte}$:

$$P_{\text{avg}} = \frac{P_1 + P_2 + \cdots + P_n}{n}$$

Assuming the average $P_{\text{avg}}$ turns out to be $0.00004 \text{ ETH/byte}$.

**Calculate Price per Byte**:
$$P_{\text{byte}} = \frac{0.00004}{0.99} \approx 0.0000404 , \text{ETH/byte}$$

Calculate Reward per Valid Proof (considering bandwidth and uptime contributions):
$$R_{\text{proof}} = 0.0001 \times 0.99 \times Bandwidth \times \frac{1}{3} $$

Penalty Calculation (if staked amount is 1 ETH for illustration):
$$S_{\text{penalty}} = \frac{1 , \text{ETH}}{\text{Number of Failed Proofs}}$$

**References**:
Cryptographic File System by M. Blaze, et al.
An Analysis of Decentralized Network Performance by D. Anderson, et al.
Decentralized Information Flow Control by A. Sabelfeld and A.C. Myers.
Proofs of Data Reliability in Cloud Storage by J. Sun et al.
Performance of Distributed Storage Systems by R. Rodrigues and B. Liskov.

**Conclusion**:
By integrating a user-driven order book mechanism and thorough mathematical modeling, we ensure competitive pricing and robust tokenomics. The approach is validated by existing research and modified for our specific requirements.