IAGON intends to bring decentralization into mainstream businesses and consumer markets. In order to achieve this, IAGON was designed and built to integrate seamlessly into existing IT infrastructure without the need for expensive resources to deploy.
Figure 5 is a graphical representation of IAGON serving as a middleware between server- database and frontend-backend in existing IT infrastructure. IAGON can work with both SQL and NoSQL database structures that are commonly used today without the need for expensive migration processes or specialized resources to implement and deploy. IAGON provides a security layer because it identifies specific digital fingerprints associated with the request going through the server to identify if a request is an honest node.
Figure 6 provides an overview of IAGON in a private and public Blockchain network. It serves as a layer to allow data to be securely stored within both private and public blockchains. Using machine learning al- gorithms and encryption/decryption protocols, IAGON is able to provide a secure method in storing data across platforms.
IAGON can be configured to serve not only as a secure platform to integrate with existing blockchains but also utilize its data mining feature to process data. IAGON scales by distributing processing load across a decentralized network and securely stores data the across different decentralized platforms. This is done through IAGON machine learning algorithm that works to distribute the data based on the task it is required to undertake. IAGON uses both supervised and unsupervised machine learning method known as semi-supervised learning to both process and distribute data across decentralized networks.
The introduction of Regulation EU 2016 /679 to replace Directive 95/46/EC, introduced more stringent regulations in regards to data processing and mining of data of personal records. The regulation introduces certain restriction on the collection and processing of personal data including limitations on the free movement and sharing of such data (EU, 2016).
In order to remain compliant with local regulatory restrictions on data mining and processing , IAGON will limit and restrict the type of processing being done on its platform. It will perform this by using geolocation algorithms to identify the source of the user and the destination the data is being sent. In general IAGON encrypts all data within its platform hence the process of piecing together personal data or identifying individuals based on the data it processes is technically impossible. In most use cases IAGON is a pass-through entity as such is holds no data within its facility and only serves as a security layer between the data flowing through its systems.
The architecture of IAGON’s Open Source platform can be broken down into three unique sections . The sections are the machine learning algorithm ,the Blockchain and miners , and the encryption /decryption protocol . When a request is sent to IAGON,the machine learning algorithm sends blocks of data over to the miners to process and find for matching signatures .These blocks of data are then sent back to be validated over the block - chain along with an output which the machine learning algorithm will use to identify a node. It will be impos- sible to identify a node without processing the data in multiple blocks and to identify a correlation thus this provides a level of anonymity and privacy to the users utilizing IAGON’s platform.Individual miners will not be able to identify a certain request or node unless they have access to enough blocks . Blocks are distributed evenly to miners by utilizing proof of variance and does not store any ofthe data within theirlocal systems .This allows data to be process anonymously without being able to identify any single node individually ex- cept through the machine learning algorithm . In addition ,Miners are incentivized to process the data quickly to earn rewards , as such it would not be ideal for miners to actually spend time, energy and money to try to store or process thedata.
The Blockchain allows data to be broken down into blocks and sent across nodes. The hashing algorithm utilizes SHA256 and hashes each block with its previous hash to create a chain . When data isreceived back from an individual node, the data output will be matched against the hash of its corresponding block and validated against its header to determine if the output data is valid. This way of processing provides a unique method towards distributed processing as it provides a layer of integrity to the data being processed and to determine if the output has been tempered in any way. In the event any of the miners have manipulat- ed the data in anyway, the returning block will be rejected and the block will be sent over to a different node to be reprocessed . Miners receive incentives based upon the number of processes they perform – in simple speak, the more data they process the bigger the incentives.
The encryption and decryption protocol allows for secure storage of data within any external or internal platforms. This provides a unique approach towards decentralization as any external platform with an API can simply be integrated to IAGON’s platform to utilize its services.What makes IAGONunique is the factthat IAGON is able to integrate seamlessly with current database architecture including SQL,NoSQL ,Big data databases,privateBlockchain,hyperledger,or any public Blockchain or decentralized network.
IAGON is an AI that learns over time. To achieve this, IAGON learns through a method known as reinforcement learning. Reinforcement learning is the science of decision making to handle a dynamic environment. This means IAGON undergoes an active learning process to optimize its decision making process to determine its course of action. This creates and unparalleled paradigm towards how IAGON handles its input. Using a method known as Markov Decision Process that is based on probability theory, IAGON tries to determine an optimized form of reward system that improvises its actions to maximize its reward system over time.
Reinforcement learning is the intersection of various paradigms in science as describe in Figure 8:
The Markov Decision Process can be describe using the following algorithm:
The end goal is pick actions that maximizes future rewards
Markov state is unique in its approach because it bases decision making of the future independent of the past given the present (David Silver). This is represented by the information state (a.k.a Markov state) if and only if:
The information state proves that if the present state of a system is known, then the historical actions need not be considered as the results of the future will be independent to the historical state.
IAGON takes a very different approach towards data mining. IAGON does this by utilizing a private Blockchain with public network protocols over API networks. A miner does not need to store any of the data in order to mine, the miner’s sole duty is to honestly process the data and send the output back to IAGON’s machine learning algorithm for analysis.
Data mining on IAGON ’s platform does not have the need to perform complex algorithm to solve an equation. Instead, IAGON uses the decentralized computing network to distribute load and increase speed for mundane data processing tasks . Block tasks are distributed to miners using the proof of variance method. Miners will need to match the data signature from the data input and find its corresponding data object in the block and return the data output. The miners do not need to store any of the data it processes, and once the data has been validated to belong to the specific block, the miner is considered to have mined the block. The miner receives rewards based on the number of data points it mines, and if no data is found within the block the miner does not receive any reward. This will incentivize miners to complete mining the entire block and to increase the number of blocks they mine. The incentive mechanism discourages miners from just mining a block until the first data output is achieved because of the speed limitations associated with network connections will prove to be uneconomical , as such miners will be encouraged for their own benefit to completely mine the entire block to find all possible data points that matches the data input.
Blocks are generated at a bounded rate and there are no communication between miner ’s clients . The server connecting the miners to IAGON’s platform uses a multithreaded server to distribute and receive results. Blocks are sent over HTTP-based protocols so that clients inside firewalls can connect to it. There are two methods currently to approach block storage and removal from miner’s unit. The option would be to pro- cess purely in memory provided by the random -access memory unit in a computer or introducing a garbage collector program that effectively removes the block from disk. The mining client architecture should allow it to run as a background process or a GUI application. To support different architectures, the best approach would be to create multiple threads , where one thread does communication and data processing while the other thread handle GUI interactions (Anderson, 2002). Proof of variance allows IAGON to identify the typical speed at which miners take to process a block. In the event a miner is disconnect , goes offline or does not complete computation on its block , the block is resent to other nodes in the network.
IAGON leverages the Blockchain technology to maintain honesty of nodes across IAGON distributed data mining algorithm. The Blockchain uses SHA256 algorithm of previous blocks to maintain a chain link to its historical state (in this case data).This allows IAGON to incentivize miners on its platform to process data honestly and to guard against deliberate manipulation of the data output. Using the Blockchain , IAGON’s machine learning algorithm can quickly identify if a data output mined from a block is actually a valid part of the block. This can be achieve within the framework of a simple Blockchain similar to that used by ‘Bitcoin’ by hashing the inputs with the hash of the previous block. Genesis block are created internally within the private blockchain . The Blockchain presents a unique approach towards sharing data across a decentralized network. The data can be stored, processed and validated by a network of nodes or it can be stored and validated within an internal facility where the processing is outsourced to a decentralized network of nodes . The Blockchain allows consistency to be maintained throughout the entire data structure.
One of the major reason the Blockchain is maintained privately is to compete with big data databases in the market in terms of volume , variety and velocity . A private Blockchain allows for the research , development and facility cost to be borne by IAGON’s team with input from various stakeholders as oppose to getting multiple parties to reach a large enough consensus before making big development changes to improve the system . In order to keep up with massive read and write operations within its private Blockchain , IAGON might in the future scale to introduced multiple private Blockchains to reduce the potential of a single point of failure which can bring the down whole system by using a masterless architecture.
IAGON will expand its operations to support using itsSmartComputing Grid andSecure Lake technologies on the Tangle platform , in addition to operating them on the Ethereum Blockchain . The Tangle technology is based on application of a directed acyclic graph (DAG). Mathematically ,the Tangle generates a stochastic process on the space of Directed Acyclic Graphs (DAGs)that“grows” in time by attaching new vertices to the graph according to a Poissonian clock . Yet, no vertices (edges ) are deleted . When that clock signals the system , a new vertex appears and attaches itself to positions on the graph selected by random walk processesontheprior stateofthegraph(Popovet al.,2017).
The application of the Tangle technology assists in resolving some of the issues associated with the implementation of the Blockchain technology for a large scale of operations, including the difficulties to scale the blockchain, to achieve consensus on the validity of blocks when the new blocks continuously arrive. By applying the Tangle technology , IAGON can offer an alternative solution for organizations with Big Data repositories that can support large scales of processing and storage management tasks.
IAGON does not use the Blockchain like other cryptocurrencies. Even its use case approaches data process - ing in a more conventional method hence using a POW (proof of work) or POS (proof of stake) mechanism to reward a particular miner for discovering a particular block is not a viable solution. Hence IAGON uses its own mechanism for determining miners’ contribution and processing speed using a method know as proof of variance . Proof of variance classifies each miner based on their contribution into a pool. Miners within the same pool then compete which each other. Miners from lower pools get upgraded or downgraded based on several factors but the two main factors are speed and amount of data miners are able to find. Proof of variance uses a combination of algebraic theory and probability functions to compute a miner ’s contribution and which pool the miner can be classified under. This allows for newer miners to profit from mining data and increase their processing assets exponentially while miners investing more into their assets can obtain an immediate return on their investment. The probability theory utilizes both discrete and continuous functions and results of mining change over time.
Block Imaging : Block imaging is the method in which certain subset of the Blockchain is imaged or copied to be randomly distributed across the node. An image of the block sent to nodes will mean the Blockchain does not undergo any sort of permutation and remains immutable . Theoretically , randomly selected blocks are branched and distributed to nodes for processing. The imaging algorithm is a suitable method that is scalable to solve arbitrarily large problems by using distributed nodes. To create the algorithm for block imaging, we assume that and are block separable:
assuming a variable A as a block:
If , where is treated as the block row index and as the block column index the function can be expressed as:
When hence and once all subvectors are size 0, and are fully separable . Fully separable blocks have no restrictions on partitioning with the end goal is to allow for each block to be handled by separate process and does not involve the transfer of block matrices among processes (Parikh and Boyd, 2012).
Binomial Distribution : To ascertain distribution of blocks within a set (blocks are assumed to include 0 as the genesis block), for natural numbers n and k, where n ≥ k ≥ 0, the binomial coefficients are arranged into rows for successive values of n, and in which k ranges from 0 to n. Since blocks are defined in natural numbers and can be defined as the coefficient of the monomial in the expansion of . The coefficient allows for the use of binomial theorem to scale data block distribution using:
Solving for where is a non-negative integer provides the number of k-combinations (Molenaar, 1970; Fog, 2008).
This method allows for scalability as block numbers grow and dependent algorithms no longer require data to be parsed from the entire Blockchain once sufficient volume has been obtained.
Continuous Time : IAGON uses a particular mathematical dynamic knows as continuous time as a framework to perform its calculations given that the time dimension grows linearly. Continuous time would account for the potential limitations that exist with using discrete time models when dealing with continuous simulations.
Proof of Variance : IAGON uses probability density function in determining data distribution and miner classification. It utilizes a function of continuous random variables whose value at any given point in a sample space is defined as the relative likelihood of a miner finding a data output within an n number of blocks. Blocks are distributed in this manner to miners throughout its system where the general likely hood of miners with higher probability levels can process data at higher speeds. Since the function utilizes continuous variables over time, it allows the classification of miners based on performance rather than a lottery system or having a stake within the particular system.
And joint continuously in a domain, D in the n-dimensional space of variables between X1….Xn:
Finally, variance is used to identify a particulars miner grouping within a performance vs time metric:
The proof of variance algorithm is unique to the use case in regards to different domains used in its calculations. Since blocks are generated in continuous time and processing happens asynchronously, the usage of probability functions allows for a fairer system of rewarding miners based on the group the miner is competing in. Proof of variance allows for new miners to improve their computational power over time and existing miners with greater computational power and connection speed to earn rewards proportional to their contributions.
Like all autonomous systems, there is always a need for some form of manual intervention when dealing with anomalies. The resolution protocol has a set of rules when dealing with anomalies to either resolve it automatically or perform further processing by sandboxing the request and allow manual intervention to resolve the conflict.
The encryption/decryption protocol is used for internally stored data. All data stored within IAGON’s platform is encrypted to some degree to protect the data in the event of a breach. IAGON has a variety of options to store data on its platform including SQL,NoSQL, private Blockchains and other 3rd party storage providers whichare compliantwithregulatory requirements.IAGONatits coreuseAES-256 toencrypt anddecryptdata. AES -256 is the encryption standard recommended by the NIST (National Institute of Standards and Technology) anduses a symmetric key algorithm.
The IAGON Pre-sale begins on May 27th, 16:00 CEST and lasts for 30 days. Pre-sale will be done through Iagon website - https://iagon.com/
The Pre-sale offers 20% of the tokens at a price of:
The Pre-Sale Eth Price Is Pegged At Minimum $1,000 USD
Individuals who participated in the Dragonchain pre-sale will have the right to buy according to their DSS score, which will be locked according to when the previous contribution was made and pegged ETH price. Otherwise, they can take advantage of the new prices. Purchases can be made in ETH
The IAGON crowdsale (Token Sale ) begins on July 7th . Token sale lasts for 30 -60 days , depending on sale. In addition to the Pre-sale, the crowdsale offers 50% of the IAGON tokens to the public (offering in total 500, 000,000 tokens).
Purchases can be made via all ETH according to the following rates:
Total amount of IAG tokens for two phases: 700,000,000 tokens
Other 30% of the tokens (max. 300,000,000 tokens) will be dedicated to: 10% for IAGON’s team; 10% for advisors and bounty hunters; 10% for development.
Our Soft Capis 5 million USD and HardCapis 50 millionUSD.
Team tokens are allocated by the following:
Purchases can be made via all ETH, Bank Transfer or debit/card (We also use Changelly as our API and this allows for us to convert other curriences to ETH on site, before purchase).
Please follow the detailed instructions for Token Sale fiat money transfers on our website.
IAGON’s executive team is lead by Dr. Navjit Dhaliwal, a highly experienced professional in the field of cryptocurrency investments and financial operations. IAGON’s team members are:
Dr. Elad Harison in an expert on Data Mining and Machine Learning, Economist and Industrial Engineer, who is in charge of IAGON’s architecture planning and operations. He is the former Head of the Industrial Engineering Department at Shenkar College and an accomplished economic advisor and analyst in the private sector in Israel and in the EU, where he led business feasibility studies, market research and statistical analysis and IT ar- chitecture changes for the European Commissio, several European governments, KLM-Air France and an Israeli Bank, among others.
Dr. Navjit Dhaliwal is IAGON’s CEO and founder, aiming to revolutionize the world’s centralized cloud industry by offering a decentralized cloud services platform. In the past, Navjit was a medical entrepreneur in the field of dentistry, successfully leading Norway’s Mjøsa Tannklinikk’s operations and doubling its revenues in one year.
Dr. Claudio Lima is a seasoned executive, global CTO, VP of innovation and thought leader in advanced energy and telecom/IT working with emerging technologies, new businesses and digital transformation. At Iagon he identifies new areas of technology, landscape, developments and opportunities and creates plans to implement them for Iagon and its clients.
The Token Contract and associated audits will be published at a later date on Etherscan. We invite all potential participants to review them for features and functionality.
By participating in the IAGON AS’ (“IAGON ”) Pre-sale and/or Token Generating Event (the “TGE”) Crowdsale (the Pre-sale and the TGE together referred to as the “Crowdsale ”), as defined in the IAGON whitepaper (the “Whitepaper ”), or making use of any information in the Whitepaper or in IAGON’s business plan or available on the iagon.com website, you agree to the statements provided in this disclaimer (the “Disclaimer”). You further understand and accept that the information provided in the Whitepaper and on the website are of descriptive nature only, and does not provide any legal rights to the user unless explicitly stated.
General Warning – By using the services provided by IAGON, you as either a Crowdsale participant or User of IAGON’s alpha products or services (the “User”), fully understands and agrees with the following:
Tax Warning – The User understands and accepts that IAGON does not act as a tax agent of User. The User bears the sole responsibility to determine its tax responsibility of the contribution into the Smart Contract System to create and obtain IAG token(s), and to determine whether the ownership, usage, the potential value appreciation or depreciation, or any gain or loss by the purchase or sale of the IAG token, have tax implications for such User. More specifically , the User fully understands and agrees to the following:
No Warranties – All information provided within the Whitepaper and within IAGON’s business plan is provided “AS-IS” and with no warranties whatsoever on the IAG token, the Smart Contract System and /or the success of the IAGON platform , including the accuracy , completeness or the use of any information provided therein, to the extent permitted by any applicable law. This includes, but is not limited to, express or implied warranties of title, merchantability or fitness for a particular purpose, are made with respect to the information, or any use of the information, on this site or platform.
Disclaimer Of Liability – The User acknowledges and agrees , to the extent permitted by any applicable law, that the User will not hold IAGON or any associated parties, including but not limited to any group entity , management , developers , contractors or shareholders , liable for any and all damages or injury whatsoever caused by or related to the use of, or the inability to use the IAG token, the Smart Contract System or the IAGON platform, under any cause or action whatsoever of any kind in any jurisdiction. IAGON specifically, without limitations, disclaims liability for any loss or damages, including incidental or consequential damages, and assumes no responsibility or liability for any loss or damage suffered by any person as a result of the use, misuse or reliance of any of the information or content in the Whitepaper or in IAGON’s business plan or on the www.iagon.com website.
Under no circumstances shall IAGON, or any associated parties as stated above , be liable to the User for any special, indirect, incidental , consequential , exemplary or punitive damages (including lost or anticipated revenues or profits and failure to realise expected savings arising from any claim relating to the services provided by IAGON) whether such claim is based on warranty, contract, tort ( including negligence or strict liability) or otherwise or likelihood of the same.
The User further specifically acknowledges that IAGON, or any associated parties as stated above, are not liable , and the User agrees to not hold them liable , for the conduct of any third parties , including other creators of IAG token (s), and that the risk of creating , holding and using IAG token (s) rests entirely with the User
Use At Your Own Risk – By ustilising the Crowdsale Smart Contract System for IAGON, the IAGON platform or the www.iagon.com website, including but not limited to, the transferring of any assets to IAGON AS, the User undertakes and understands all possible risks that directly or indirectly arise from the activity connected with the User’s participation in the Crowdsale and/or use of IAGON’s services and products.
Force-Majeure – User understands that IAGONwill not be liable to User for any breach hereunder, including for failure to deliver or delays in delivery of the Services occasioned by causes beyond the control of IAGON including but not limited to unavailability of materials , strikes, labour slowdowns and stoppages , labour shortages , lockouts , fires, floods , earthquakes , storms , droughts , adverse weather, riots, thefts , accidents , embargoes , war (whether or not declared ) or other outbreak of hostilities, civil strife, acts of governments, acts of God, governmental acts or regulations, orders or injunctions, or other reasons, whether similar or dissimilar to the foregoing (each a “Force Majeure Event”).
Miscellaneous / Final Warning – Pre-sale and/or TGE participations can be considered high-risk trading ; utilising IAG tokens via the Crowdsale or utilising services offered in the Whitepaper , through the Smart Contract System, the IAGON platform and on the www.iagon.com website, may result in significant losses or even in a total loss of all value submitted and obtained.
This Disclaimer is valid as of 2 April 2018, as amended from time to time
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