Press Release
WarRin Protocol: A point-to-point anonymous privacy communication system
Dr.WarRin
Summary
This white paper provides an explanation of the WarRin protocol and related blockchain, point-to-point, network value, transport protocol, and encryption algorithms. The limited space will highlight the WRC allocation scheme and purpose of the WarRin Protocol Token, which is important for achieving the WRC’s stated objectives. This white paper is for informational purposes only and is not a promise of final implementation details. Some details may change during the development and testing phases.
1. Introduction
Traditional centralized communication systems such as WeChat,WhatsApp, FacebookMessage,Google Allo,Skype face a range of problems, including government surveillance, privacy breaches, and inadequate security, and the WarRin protocol proposes apoint-to-pointencrypted communications system that leveragesblockchain technology, combined with Double Ratc het algorithms, pre-keys, and extended X3DH handshakes. The WarRin Protocol uses The Generalized Directional Acyclic Graph and Curve25519,AES-256, and HMAC-SHA256 as the pronamor, allowing each account to have its own unique account chain, providing unlimited instant communication between points and unlimited scalability, anonymity, integrity, consistency, and asynchronousness.
2. WarRin Protocol communication system
2.1 Two types of communication
The Waring Protocol communication system divides chat channels into two types.
Two modes of communication
- General Chat mode: Using point-to-point encrypted communication, the service side has access to the key and can log in via multiple devices.
- Secret Chat mode: Encrypted communication using point-to-point can only be accessed through two specific devices.
The design combines some of the advantages of raiBlocks multi-chain construction with IOTA/Byteball DAG, which we call the Waring protocol. With improvements, we have given the WarRin protocol greater throughput and faster processing power while ensuring the security of the ledger, and network nodes can store the ledger in less space and search their communications accounts quickly in the ledger. When two users communicate, third parties contain content that neither manager can access. When a user is chatting in secret, the message contains multimedia that can be designated as a self-destruct message, and when the message is read by the user, the message is automatically destroyed within the specified time. Once the message expires, it disappears on the user’s device.
2.2 How chat history is encrypted
2.2.1 MTProto Transport Protocol
MTProto transport protocol
The WarRin communication system draws on RaiBlocks’ multi-chain structure for point-to-point communication. Each account has its own chain that records the sending and receiving behavior of the account. For example, in Figure 1, there are 7 accounts, each with 7 chain records of the account sending and receiving communications. On the graph, horizontal coordinates represent the timeline, and portrait coordinates represent the index of the account.
Transferring information from one account to another requires two transactions: one to send a communication from the sender’s transfer content, and one to receive information to add that content to the content of the receiving account. Whether in a send-side account or a receiving account, a PoW proof of work with the previous communication content Hash is required to add new communications to the account. In the account chain, poWwork proves to be an anti-spam communication tool that can be done in seconds. In a single account chain, the Hash field of the previous block is known to pre-generate the PoW required for subsequent blocks. Therefore, as long as the time between the two communications is greater than the time required to generate the PoW, the user’s transaction will be completed instantaneously.
In such a design, only the receiving end of the communication is required for settlement. The receiving end places the received communication signature on the account chain, which is called accepted communication. Once accepted, the receiving end then broadcasts the communication to the ledger of the other nodes. However, there may be situations where the receiving end is not online or is subject to a DoS attack, which prevents the receiving end from putting the receiving side communication on the account chain, which we call uncommoted transactions. The X symbol in Figure 1 represents an open transaction sent from Account 2 to Account 5.
Obviously, because only the sending and receiving sides of the communication are required to settle, such communication is very lightweight, all traffic can be transmitted in a UDP package and processed very quickly. At the same time, all communications in an account are kept in one chain, with great integrity, and the ledger can be trimmed to a minimum. Some nodes are not interested in spending resources to store the full communication history of the account; They are only interested in the current communications for each account. When an account communicates, its accumulated information is encoded, and these nodes only need to keep track of the latest blocks so that historical data can be discarded while maintaining correctness. Such communication is only possible if the sending and receiving sides trust each other and are not the final settlement of the entire network consensus. There is a security risk in the absence of trust on the sending and receiving ends, or in situations where the receiving end is attacked by DoS without the sender’s knowledge.
We have observed that although each account has a separate chain, the entire ledger can be expressed in the form of a WarRin object. As shown in Figure 2, this is represented by the WarRin astros trading on all accounts in Figure 1.
The first unit in the WarRin object is the Genesis unit, the next six cells represent the allocation of the initial token, and the other units correspond to the communication transactions between the account chains. We use the symbol a/b to represent a communication transaction, where the sender is a andthe recipient is b. The last 4/1 unit in Figure 2 is the last communication corresponding to Figure 1 – sending communication from account 4 to account 1. A transaction in Figure 1 is a confirmation of the latest block or the latest communication on the account chains of both parties to the communication, reflected in Figure 2 as a reference to the latest units of the account chains of both parties to the communication. Take unit 4/1, for example, where the latest block on account 4 was the receiving block for 2/4 trades and the newest block on account 1 was the send block for 1/5 trade. So on the DAG, the 4/1 cell refers to the 2/4 cell and the 1/5 cell.
The WarRin protocol uses triangular shrapned storage technology to crack impossible triangles in the blockchain through the shrapghine technology, with extensive node engagement and decontalination while maintaining high throughput and security:
- Complete shraping of blockchain status;
- Secure and low-cost cross-synth trading;
- Completely random witness selection;
- Flexible and efficient configuration
Complete decentralization ensures absolute security and scalability of the standard chain.
(Figures above show seven Ling-shaped objects:2/1 one;3/2 one… )
2.2.2 Curve25519 Elliptic Curve Encryption Algorithm
Curve25519, proposed by Daniel Bernstein, is anelliptic curve algorithm for the exchange of The Montgomery Curve’s Difi Herman keys.
Montgomery Curve Curve Mathematical Expression:
Curve25519 Curve Mathematical Expression:
Curve25519 encryption algorithms are used for standard private and public keys, and the private keys used for Curve25519
encryption algorithms are typically defined as secret
indices, corresponding to
public keys, coordinate points, which are usually sufficient to perform ECDH (elliptical) and symmetrical elliptic curve encryption algorithms. If one party wants to send information to the other party and the other party has the
public
and private keys, perform the following
calculation:
Generate a one-time random secret
index, calculated using Montgomery, because the message is a symmetrical password encrypted using 256-bit sharing, such as AES using a 256-bit integer
one-time public key, as akey, and 256-bit integer is a
prefix to encrypted information. Once a party to
the public
key receives this message, it can start by calculating , that is ,
the receiver recovers the shared secret and
is able to decrypt the rest of the information.
3. Incentives
On the basis of the WarRin agreement, by adding the incentive layer, we can effectively avoid the whole network being attacked and eliminate spam. As long as honest nodes control most of the calculations, for an attacker, the network is robust because of its simplicity of structure, and nodes need little coordination to work at the same time. They do not need to be authenticated because information is not sent to a location.
3.1 WRC Certificate
WRC issued a total of 2,500,000 pieces and continued to increment according to the WoRin gain function.
3.1.1 WoRin Gain Function
3.1.2 WoRin gain function control table
| The WoRin gain function is compared to the table | ||
| Number of layers /F | Growth factor /I | WRC circulation |
| [1,50] | 0.002 | 334918.8057 |
| [51,100] | 0.002 | 780024.2108 |
| [101,150] | 0.004 | 1177129.617 |
| [151,200] | 0.006 | 1487860.923 |
| [201,250] | 0.01 | 1722637 |
| [251,300] | 0.016 | 1894309.216 |
| [301,400] | 0.03 | 2101623.789 |
| [401,500] | 0.06 | 2217555.464 |
| [501,1000] | 0.1 | 2450712.257 |
| [1001,2000] | 0.12 | 2557457.3 |
According to the Gain function, the
larger the number of layers,
the greater the growth rate, the faster each layer is filled, and the
greater the circulation.
3.2 Allocation
WarRin protocol node distribution
3.2.1 Node allocation
Set the initial price
to 0.02,the layer where the first node is located is , according to the equation of the iso-difference column, there is , so that the
node token is assigned to the piece, for the price of
the layer where the node
is located, there is a
set.
For example, the number of tiers in which the 98th node is located is Tier 13, and the price of Tier 13 is 0.214,the tokens assigned by Tier 98 are
3.2.2 Total number of address assignments
Each node occupies one address, and the total number of addresses is
4. The use
WRC is the native pass-through of the WarRin protocol, andWRC will assign to Genesis nodes according to the above allocation scheme, which together form the entire network, andWRC can be used in the following scenarios, including but not limited to:
Pay the network’s gas charges, i.e. for transferring money and invoking smart contracts;
System Staking tokens, used for node elections and token issues;
The capital is lent to the validator in exchange for the amount of the reward;
Voting rights for system proposals;
The means of payment for apps developed on WoRin Services;
WoRin Storage is a means of payment on the decentralization storage;
WoRin DNS domain name and WoRin WWW website means of payment;
WoRin Proxy agents hide the means of payment for body and IP addresses;
WoRin Proxy penetrates payment methods reviewed by local ISPs
……
5. Conclusions
Metcalfe’s Law states that thevalue of a network is equal to the square of the number of nodes within the network, and that the value of the network is directly related to the square of the number of connected users. That is ( the
value factor, the number of
users.) That is, the greater the number of users on a network, the greater the value of the entire network and each computer within that network. The WarRin protocol also follows this law, and when the number of nodes reaches a certain level, the entire network becomes more robust.
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application platform, https://github.com/ethereum/wiki/wiki/White-Paper, 2013.
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optimal resilience, in Proceedings of the thirteenth annual ACM symposium on
Principles of distributed computing, p. 183–192. ACM, 1994.
[4] M. Castro, B. Liskov, et al., Practical byzantine fault tolerance, Proceedings of the
Third Symposium on Operating Systems Design and Implementation (1999), p. 173–
186, available at http://pmg.csail.mit.edu/papers/osdi99.pdf.
[5] EOS. IO, EOS. IO technical white paper,
https://github.com/EOSIO/Documentation/blob/master/TechnicalWhitePaper.md,
2017.
[6] D. Goldschlag, M. Reed, P. Syverson, Onion Routing for Anony- mous and
Private Internet Connections, Communications of the ACM, 42, num. 2 (1999),
http://www.onion-router.net/Publications/CACM-1999.pdf.
[7] L. Lamport, R. Shostak, M. Pease, The byzantine generals problem, ACM
Transactions on Programming Languages and Systems, 4/3 (1982), p. 382–401.
[8] S. Larimer, The history of BitShares,
https://docs.bitshares.org/bitshares/history.html, 2013.
[9] M. Luby, A. Shokrollahi, et al., RaptorQ forward error correction scheme for
object delivery, IETF RFC 6330, https://tools.ietf.org/html/rfc6330, 2011.
[10] P. Maymounkov, D. Mazières, Kademlia: A peer-to-peer infor- mation system
based on the XOR metric, in IPTPS ’01 revised pa- pers from the First International
Workshop on Peer-to-Peer Systems, p. 53–65, available at
http://pdos.csail.mit.edu/~petar/papers/ maymounkov-kademlia-lncs.pdf, 2002.
About Author
Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.
Press Release
Grassroots Opposition to AI Data Centers Surges 4x in 4 Months; Over 360K Mobilizing in 37 States
New joint study reveals a rapidly growing, bipartisan backlash against Big Tech’s physical infrastructure, with a new local opposition group forming every day
United States, 28th Apr 2026 — Today, the Coalition for Responsible Data Center Development, Evitable, and Together Against AI released the Data Center Opposition Report, which documents an unprecedented surge in grassroots opposition to hyperscale AI data centers across the United States. The report identifies 268 local data center opposition groups organizing through Facebook.
According to the report, more than 360,000 Americans have mobilized to resist the construction of hyperscale data center facilities across 37 states. Total opposition membership has quadrupled since December 2025, with more than one new group forming per day. The opposition is spread between blue and red states, as well as over 100,000 people in swing states.
The largest planned AI data centers will have an electrical capacity of over 1 gigawatt (1,000 megawatts), which is as much as the entire city of Seattle. This enormous scale and energy consumption is one of the main reasons for the surge in opposition. “Many people are concerned about the effects of million-square-foot data centers that would use as much electricity as entire cities,” said Matthew Shaw, one of the authors. “The construction of power-hungry hyperscale data centers is raising alarms among locals about everything from power bills and water use to noise and pollution,” he added.
On top of this, non-disclosure agreements (NDAs) are a common practice in the process of land acquisition and rezoning for data centers. “Many people are understandably frustrated,” Matthew Shaw says, “because deals are being made behind NDAs to put giant data centers next to residential neighborhoods, and subsidize them with 90% tax cuts.”
“The massive data centers AI companies want to build are proving incredibly unpopular with local communities. They have to fight to get their concerns addressed; plans for datacenters are getting rushed through without citizens’ consent,” said David Krueger, CEO of Evitable. “We’re keen to show people the scope of this resistance and how they can help support people involved in these fights.”
“Initially, we just wanted to make a list of opposition groups so people could find one near them,” said Matthew Shaw, one of the report’s authors. “But when we updated the membership counts in February, we were shocked at how quickly the movement had grown, so we decided to track the numbers on a monthly basis.”
Opposition groups across America are collectively fundraising approximately $1.4 million, with a median ask of just $8,000 per campaign. The publicly available donation links are listed in the report’s appendix.
To read the report, visit datacenteropposition.com. The data will be updated monthly.
Media Contact
Organization: Coalition for Responsible Data Center Development
Contact Person: Matthew Shaw
Website: https://datacenteropposition.com
Email: Send Email
Country:United States
Release id:44420
The post Grassroots Opposition to AI Data Centers Surges 4x in 4 Months; Over 360K Mobilizing in 37 States appeared first on King Newswire. This content is provided by a third-party source.. King Newswire makes no warranties or representations in connection with it. King Newswire is a press release distribution agency and does not endorse or verify the claims made in this release. If you have any complaints or copyright concerns related to this article, please contact the company listed in the ‘Media Contact’ section
About Author
Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.
Press Release
Backyard Adventures: Life Lessons From Chickens
Cheri Magnuson debuts her chicken-keeping memoir, The Adventures of Dumdum, for Explora Books this year. The book features a collection of heartwarming stories portraying the challenges and joys of animal husbandry, centered on a directionally impaired Polish hen named Dumdum.
Vancouver, British Columbia, Canada, 28th Apr 2026 – After retiring from engineering in 2013, Cheri Magnuson established the Coldstream Icelandic Sheep Farm in Maine. She raises sheep specifically for their fleeces, which she sells to artisans and spinners. Her farming philosophy dictates that no animal is raised for food; instead, the sheep are treated as companion animals in farming from birth.

Magnuson’s experience as a shepherd is shaped by the loss of her son, who dies by suicide the same year her first lambs are born. She manages this ongoing grief alongside the seasonal demands of lambing season on a sheep farm, which she describes as a source of hope and personal promise.
In addition to shepherding, Magnuson writes poetry and true stories about her animals to express her internal feelings and memories. She openly discusses her dyslexia and memoir writing, as well as her history of feeling different from traditional social norms, viewing her unique spirit and her work on the Maine sheep farm as her intended purpose.
The Life Lessons
Cheri Magnuson chronicles her deep bond with Dumdum, a directionally impaired hen whose frequent accidents require constant care and protection. This relationship serves as a vital emotional anchor, showing how small-scale farming and animal care offer profound insights into a life shaped by personal loss. This experience yields several key lessons from her life with chickens.
-
Embracing One’s Unique Nature
Magnuson reflects on her identity as someone who has long felt different. She draws a parallel to Dumdum’s poor sense of direction, suggesting that difference is not a defect but an inherent trait. Rather than measuring oneself against conventional standards of normality, she emphasizes self-acceptance, identity, and finding comfort within one’s own path.
-
Resilience in the Face of Grief
The book revolves around the coexistence of joy and grief. Magnuson portrays her Maine sheep farm life as a place of recovery following the loss of her son. The endurance of her hens—such as Lady Guinevere surviving a harsh winter and frostbite to hatch a chick—depicts persistence amid hardship, offering a grounded example of resilience in grief and rural life.
-
The Weight of Personal Responsibility
A key lesson in the book involves responsibility and care. After a neighbor’s miscount leaves Dumdum exposed to freezing conditions, Magnuson realizes that the well-being of those in her care cannot be entrusted to others. She assumes full responsibility, reinforcing themes of farm stewardship and animal care responsibility.
-
Finding Hope and Renewal
Even against the backdrop of grief, the cyclical nature of farm life points to renewal. The anticipation of new lambs and the growth of the flock signal continuity and change. These patterns imply the perennial nature of life—the unceasing possibility of meaning, healing, and renewal through farming life.
-
Authenticity and Vulnerability
Magnuson maintains transparency about her dyslexia and grammatical inconsistencies in her writing. This choice conveys a commitment to authentic memoir writing rooted in lived experience. In doing so, she frames authenticity as a willingness to remain visible in one’s own voice, rather than conforming to external expectations.
Through the rhythms of farm life and the fragile, persistent presence of Dumdum, Magnuson traces a way of living that holds grief and care in the same hand. Her farm stories suggest that meaning is not found in overcoming loss, but in learning to live responsibly, honestly, and attentively within it.
Follow The Adventures of Dumdum on Amazon and other major retailers.
About Explora Books
Explora Books is a book marketing firm located in the heart of Vancouver, British Columbia, Canada. The company specializes in self-publishing and marketing, taking pride in its exhaustive research and creative strategies that provide wider avenues for aspiring authors to gain recognition for their works. Explora Books aims to guide authors through the complexities of self-publishing, offering convenient solutions to navigate this process. The firm fosters and redefines creativity and innovation, setting new industry standards. Explora Books is dedicated to empowering authors globally.
Media Contact
Organization: Explora Books Ltd
Contact Person: Simon Pratt
Website: https://explorabooks.com/home
Email: Send Email
Contact Number: +16043306795
Address:Jameson Offices, 838 W Hastings St w, Vancouver, BC V6C 0A6, Canada
City: Vancouver
State: British Columbia
Country:Canada
Release id:44446
The post Backyard Adventures: Life Lessons From Chickens appeared first on King Newswire. This content is provided by a third-party source.. King Newswire makes no warranties or representations in connection with it. King Newswire is a press release distribution agency and does not endorse or verify the claims made in this release. If you have any complaints or copyright concerns related to this article, please contact the company listed in the ‘Media Contact’ section
About Author
Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.
Press Release
Neel Somani Explains How Complementarity Shapes Power and Commodity Markets
San Francisco, CA , 28th April 2026, ZEXPRWIRE — Neel Somani is breaking down one of the more advanced concepts in market design and quantitative modeling: complementarity, a framework that helps explain how interconnected prices and incentives behave in power and commodity markets.
Known for translating complex financial and infrastructure systems into understandable concepts, Somani recently outlined how complementarity appears throughout energy trading, power pricing, and commodities. Drawing from his experience as a former quantitative researcher at Citadel in the commodities group, he explained why many markets cannot be solved through a single optimization problem alone.
Beyond Traditional Optimization
Most people are familiar with optimization in simple terms: finding the best possible outcome under a set of constraints. Businesses optimize costs, investors optimize returns, and grid operators optimize power dispatch.
Complementarity goes one step further.
Rather than solving one isolated problem, complementarity involves multiple optimization problems that depend on each other simultaneously. Each variable affects the others, creating a feedback loop that must eventually converge to equilibrium.
According to Neel Somani, this framework appears constantly in commodities markets for those who know where to look.
Natural Gas and Power: A Classic Example
One of the clearest examples is the relationship between natural gas and electricity prices.
In many regions, electricity is generated by burning natural gas. That means gas prices directly influence the cost of producing power. If gas prices rise, the marginal cost of generation often rises as well, pushing electricity prices higher.
But the relationship also runs in reverse.
If electricity demand surges and power prices increase, demand for gas-fired generation can rise, which in turn influences gas prices.
This creates a two-way dependency:
-
Power prices are influenced by gas prices
-
Gas prices are influenced by power demand and power prices
Instead of a one-directional equation, traders and modelers often solve these variables iteratively, moving back and forth until the system converges.
“That’s a complementarity problem,” Somani explains. “It’s not just one optimization problem. It’s two optimization problems that depend on each other.”
How Bidding Behavior Impacts Power Prices
Neel Somani also highlighted another real-world example: electricity market bidding behavior.
In many wholesale power markets, generators submit bids stating the price at which they are willing to produce electricity. The market operator then stacks these bids from lowest to highest cost until enough supply is selected to meet demand.
The final accepted bid sets the uniform clearing price, meaning all selected generators receive that same market price.
For most producers, the rational strategy is simple: bid close to marginal cost.
If it costs a generator $20 to produce power, bidding $20 improves the chance of being selected. Because many generators are infra-marginal, meaning they are selected before the last unit sets price, their own bid may not determine the final payment they receive.
When the Marginal Unit Knows It Matters
The problem becomes more complex when a generator expects to be the last accepted unit, the marginal supplier that sets price for everyone else.
In that case, incentives change.
Instead of bidding strictly at cost, that generator may choose to bid a premium to increase profits. But once one participant changes behavior, the clearing price can shift, potentially changing which generator becomes marginal.
This creates another feedback loop:
-
Power price depends on submitted bids
-
Submitted bids depend on expected power price
As a result, sophisticated market participants may model this through repeated iterations:
-
Assume everyone bids marginal cost
-
Solve for the clearing price
-
Adjust bids for the marginal supplier
-
Recalculate price
-
Repeat until equilibrium is reached
Again, this is a complementarity problem, where market outcomes and participant behavior shape each other simultaneously.
Why This Matters in Real Markets
Understanding complementarity is valuable because many real markets are not linear.
Prices do not simply respond to supply and demand in a static way. Instead:
-
Incentives react to prices
-
Prices react to incentives
-
Inputs affect outputs
-
Outputs affect future inputs
This is especially true in energy, where physical constraints, fuel markets, weather, regulation, and strategic bidding all interact.
For traders, investors, and policymakers, recognizing these relationships can provide a deeper understanding of volatility, pricing anomalies, and equilibrium behavior.
A Builder of Complex Systems
Neel Somani’s ability to explain these concepts reflects a career built around high-complexity systems.
He graduated from University of California, Berkeley with a triple major in mathematics, computer science, and business administration. He later worked at Airbnb and Citadel before founding Eclipse in 2022, which went on to raise $65 million.
Today, his focus includes machine learning research, education, and philanthropy, while continuing to share practical insights on markets and optimization.
Seeing What Others Miss
Neel Somani’s broader point is that complementarity problems exist across commodities markets far beyond just gas and power.
For those who understand how systems interact, these relationships become opportunities for better modeling, smarter decision-making, and clearer market intuition.
As markets grow more interconnected, the ability to recognize second-order dynamics may become just as valuable as understanding first-order supply and demand itself.
To learn more visit: https://www.neelsomani.com/
About Author
Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.
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