Presented at All Things Open 2023 Presented by Karl Mozurkewich - Storj Title: What Does Real World Mass Adoption of Decentralized Tech Look Like? Abstract: We delve into the transformative potential of decentralized technology. Beginning with a brief overview of the rise of centralization with the advent of the internet and the counter-shift marked by blockchain we explore the intrinsic characteristics of decentralized and distributed systems, such as trustless operations, peer-to-peer networks, and enterprise application scalability. Various sectors, including finance, supply chains, media and entertainment, data science and cloud infrastructure are on the brink of disruption. The societal implications are vast, with the potential for greater individual empowerment, a greener planet and more viable resource utilization, but concerns about data security persist. Find more info about All Things Open: On the web: https://www.allthingsopen.org/ Twitter: https://twitter.com/AllThingsOpen LinkedIn: https://www.linkedin.com/company/all-things-open/ Instagram: https://www.instagram.com/allthingsopen/ Facebook: https://www.facebook.com/AllThingsOpen Mastodon: https://mastodon.social/@allthingsopen Threads: https://www.threads.net/@allthingsopen 2023 conference: https://2023.allthingsopen.org/

1. What Does Real World
Mass Adoption of
Decentralized Tech Look
Like?
All Things Open 2023
Karl Mozurkewich, Sr. Enterprise Architect

2. Introduction
What does it mean to be centralized?
The US National Institute of Standards and Technology (NIST) defines cloud computing as
“a model for enabling ubiquitous, convenient, on-demand network access to a shared pool
of configurable computing resources (e.g., networks, servers, storage, applications,
services) that can be rapidly provisioned and released with minimal management effort or
service provider interaction.”1
According to NIST, cloud computing is composed of the
following (figure 1):
● Five essential characteristics—On-demand self- service, broad network access,
resource pooling, rapid elasticity and measured service
● Three service models—Software as a Service (SaaS), Platform as a Service
(PaaS) and Infrastructure as a Service (IaaS)
● Four deployment models—Private cloud, community cloud, public cloud and
hybrid cloud
Daniel D. Wu, Ph.D., CISA, CISM - 29 September 2021 - Decentralized Cloud Computing

3. Introduction
What does it mean to be Decentralized?
Tenets
● No central points of control
● Curb inequality
● Smooth Network Effects
Daniel D. Wu, Ph.D., CISA, CISM - 29 September 2021 - Decentralized Cloud Computing
Design Traits
● Secure-by-Default (Zero Trust)
● Efficient resource usage
● Resilient Operation

4. Historical Context
● Internet
● Usenet / IRC
● Napster / Gnutella / Bittorrent
● Bitcoin and the emergence of
blockchain technology.

5. Characteristics of Decentralized Systems
“create a technical drawing that represents a
centralized data network”
“create a technical drawing that represents a
distributed data storage network.”

6. Characteristics of Decentralized Systems
Decentralized Systems == Distributed Systems
● CAP
● Trustless operations. (Zero-Trust)
● Peer-to-peer networks
● Scalability
● Fault Tolerance
● Transparency and immutability. (maybe)
● Open Source

7. Geographically diverse data centers
Virtually unlimited bandwidth
Complex routing between PoPs
Global container distribution
Minimal localized high speed storage
Latency sensitive applications
The state of distributed
compute today.

8. Centralized Applications
Central Authority
Single Point of Failure
Opaque
Security by People
Trust me
Decentralized Applications
Consensus
Distributed Nodes
Transparent
Security by Math
Zero trust
VS
Decentralized services are fundamentally different
from centralized services

9. Centralized Applications
Amazon
Google
Microsoft
Secretary of State
Decentralized Applications
Storj
Filecoin
Ethereum
Bitcoin
VS
Decentralized services are fundamentally different
from centralized services

10. Sectors Vulnerable to Disruption
● Financial systems and banking (e.g., decentralized finance and
embedded finance)
● Supply chains (e.g., transparent and traceable goods).
● Social media (e.g., decentralized platforms).
● Web hosting and storage (e.g., web services).
● Governance and voting systems.
“Only a crisis - actual or perceived - produces real change. When that crisis occurs, the actions that
are taken depend on the ideas that are lying around.”
― Milton Friedman

11. Adoption - What does It look like?
B2B vs. B2C - Approaches differ for the end-users
B2B requires:
● Certainty
● Known Quantities, TCO
● Guarantees
● Regular Updates
● Provenance
B2C requires:
● Speed
● Network Effects
● Personalization
● Silent & Graceful
Errors

12. Adoption - Real World Examples
● Infrastructure
a. Compute / time sharing (Livepeer, Akash, Valdi)
b. Storage (Storj, Filecoin)
● Decentralized Identity
● Mobile Telecommunication infrastructure
(MVNOs, DePIN)
● Distributed Data Exchanges

13. Let’s look at
cloud object
storage
Outcome first: migrate from Hyperscalers
(AWS, Azure, GCP)
Reduce cost, increase privacy and
security, democratize cloud economy,
minimize centralized dependencies
But you can’t skimp on the actual cloud
storage - it has to be good (Performance,
durability, compatibility)
Exceed feature parity, example, regionless
global implementation

14. Adoption Architecture - Storj has 3 key elements
System Overview
Nodes
Tens of thousands of shared hard drives
store data on the network, without access to
any complete file or usable data
Supply
Applications
Client applications store encrypted and
encoded files split into pieces and stored
across a distributed network
Demand
Satellites
The network enables applications to store
data, ensures data reliability, manages
access controls and data audit/repair
Protocol
15

15. Storj uses encryption and erasure encoding to
distribute data keeping it durable and available
Encode & Split
Encrypt
AES-256-GCM
Identify Nodes Distribute
Decrypt Data Assemble File Download Segments Identify Nodes

16. Storj Bridges Web2 & Web3
Decentralized
infrastructure

17. Storj solves uses cases in Web2 and Web3
Built for Web3 and Web2 use cases
Storj
Blockchain Fast
Sync
AI/ML/HPC
Workloads
Video Storage &
Streaming
Software
Distribution
Web3 Web2
Applications
Media Storage Backup & DR
IPFS Pinning

18. Challenges for of Adoption
● Scalability concerns
○ Adoption Curve inflection: Zero-Sum to
Positive-Sum
● Integration and Compatibility
● Cohort Bootstrapping
*UX
*Security Issues
Ian Gonsher

19. Overview of Adoption - Commercial Implications
Technology Adoption Bell-Curve (Rogers 2003)
● Empowerment of individuals and reduced
intermediary friction
● Potential for more efficient distribution of
resources (AirBnB for X)

20. Commercial Implications - ESG

21. How Storj DCS is Green
Pre-existing
Hardware
No Dedicated Data
Centers
Energy Efficient
Storage

22. Commercial Implications - ESG

23. Distributed architecture
provides radical
cost advantages…
*Per website (https://aws.amazon.com/s3/pricing/?nc=sn&loc=4) as of April 3, 2023
**Wasabi typically stores in one data center. Pricing is for storage in 3 locations: Oregon, Virginia and Plano,
TX per website: https://wasabi.com/cloud-storage-pricing/#three-info
Cost to store 100 TB for one year
(storage only)
Data transfer, API,
and egress fees
not included
90 day minimum
storage length,
egress throttling
Predictable fees
and no minimum
storage length
28

24. Displacing Incumbents - Gaining Adoption
● New technology must provide current
market functionality to Users
○ At-least as good as current technology features
● Increase value from novel architectures and
implementation choices
● Solve the same problem a better way
● Market leaders will react slowly

25. Displacing Incumbents - Gaining Adoption
Results of 2022 vs 2023 Performance Tuning
Comparing 2022 and 2023 Storj Performance Tests
Transferring a large dataset to Digital Ocean droplets from Storj and a single region in AWS with
downloads at progressively increasing distance from origin

26. Displacing Incumbents - Open Source Ethos
Tenets of Open Source contribution, specifically
applicable to decentralized and distributed systems:
● Redistribution
● Source Availability
● Integrity of Provenance
● No Discrimination (Fields or Groups)
● Technology-Neutral

27. Future Predictions
● Growing integration of AI with decentralized tech
● Evolution of open / decentralized marketplaces
● Interoperability between different decentralized platforms
will increase
● The emergence of new collaboration structures built upon
distributed tech.
● AWS will lose market dominance within six years
crn - https://www.crn.com/news/cloud/cloud-market-share-q2-2023-aws-microsoft-google-battle
AWS - 32% (-2%)
Azure - 23% (even)
GCP - 11% (+1%)

28. Q & A