FACULTY OF INFORMATION AND COMMUNICATION
TECHNOLOGY
DCOMP 217 DISTRIBUTED SYSTEMS
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: Distributed Systems
: week 4
: week 11
: Mr Kamara
: Nour S. Haidara
: 905003395
: BIT3101
: Semester Seven
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1
Contents
Introduction: Background on the Selected Scenario: Netflix Content Delivery................. 2
Problem Statement ....................................................................................................................2
Objectives of a Distributed Solution (Netflix Open Connect) ..............................................3
Literature Review................................................................................................................ 4
Literature Review: Challenges in System Design and the Emergence of Distributed Solutions
for Content Delivery .....................................................................................................................4
System Design .................................................................................................................... 8
Challenges of Existing Centralized Systems..................................................................................9
The Need for a Distributed Solution.......................................................................................... 10
Simulation Development .................................................................................................. 12
Technologies used and development methodology ................................................................. 12
Expected benefits ...................................................................................................................... 13
Final Report ...................................................................................................................... 13
Bibliography ..................................................................................................................... 15
2
Introduction: Background on the Selected Scenario: Netflix Content
Delivery
The scenario revolves around Netflix's global content delivery challenge, which
became increasingly prominent with the massive growth in Netflix streaming
since 2011. As Netflix became a significant portion of overall internet traffic, the
traditional methods of content delivery faced considerable strain. The core
problem was efficiently and reliably delivering high-quality video content to
millions of members worldwide, across tens of thousands of device and network
configurations.
Initially, content delivery relied on a more centralized approach or independent
Content Delivery Networks (CDNs), which involved content traveling long
distances and through multiple networks. This "long haul" delivery model
presented significant issues, including high costs for Internet Service Providers
(ISPs) due to international infrastructure, increased latency, and a higher
probability of network congestion and "packet loss," leading to a degraded user
experience (e.g., buffering or lower video quality). The very essence of the
internet, as a "network of networks," highlighted the need for cooperation
between content providers and ISPs to ensure a seamless experience for the
end-user.
Problem Statement
The central problem addressed by Netflix's Open Connect initiative is the
inefficient and potentially unreliable delivery of high-volume video content to a
globally distributed user base through a traditional internet infrastructure that
was not designed to handle such scale and demand.
More specifically, the key issues a non-distributed (or less distributed) system
would face include:
3

Network Congestion and Packet Loss: When content is served from a
distant, single source, it must traverse numerous routers and networks.
This increases the chances of encountering congested links, leading to
discarded data packets and a poor streaming experience.

High Transit and Backhaul Costs for ISPs: ISPs incur significant expenses
for long-haul and international network capacity to fetch content from
remote origin servers.

Suboptimal User Experience: Increased latency and buffering due to
geographical distance and network inefficiencies directly impact the
quality of experience for Netflix members.

Lack of Scalability: A centralized delivery model struggles to scale
economically and efficiently with the exponential growth of content
consumption and user demand.

Limited Control and Flexibility: ISPs have less control over how and when
the large volume of Netflix traffic enters their networks, potentially leading
to peak-hour bandwidth strain.
Objectives of a Distributed Solution (Netflix Open Connect)
To overcome these challenges, Netflix developed and implemented Open
Connect, a highly distributed content delivery network, with the following primary
objectives:
1. Localize Netflix Traffic: Bring Netflix TV shows and movies as close as
possible to members, minimizing the network and geographical distances
video bits must travel. This is achieved by deploying Open Connect
Appliances (OCAs) directly within ISP networks or at Internet Exchange
Points (IXPs).
2. Improve User Experience: Ensure members have a consistently highquality video experience from wherever they are in the world by reducing
latency, buffering, and video quality degradation.
3. Enhance Network Efficiency for ISPs: Reduce transit charges and the need
for expensive international backhaul capacity for ISP partners. By
offloading Netflix traffic locally, Open Connect minimizes the burden on
upstream network capacity.
4
4. Optimize Bandwidth Usage: Implement sophisticated video compression
and encoding techniques to deliver high-quality content using the least
amount of data, further reducing traffic across networks.
5. Increase Network Resilience and Reliability: By distributing content across
thousands of OCAs, the system becomes more resilient to individual
component failures, as traffic can be redirected to other available servers.
6. Foster Collaboration with ISPs: Work directly and collaboratively with ISPs
to manage and optimize content delivery, benefiting both Netflix and its
mutual customers.
7. Enable Proactive Content and Software Updates: Utilize off-peak fill
windows to proactively download content and software updates to OCAs,
preventing additional strain on network capacity during peak hours.
Literature Review
Literature Review: Challenges in System Design and the Emergence of
Distributed Solutions for Content Delivery
This literature review synthesizes key concepts and challenges in traditional
system design, highlighting the imperative shift towards distributed solutions,
particularly in the context of large-scale content delivery. Drawing insights from
discussions on distributed systems characteristics and a specific case study of
Netflix's Open Connect, this review identifies critical problems faced by
centralized architectures and articulates how distributed paradigms provide
effective resolutions.
1. Challenges of Traditional Centralized Systems
Traditional, often monolithic or centralized, system architectures, while simpler to
design and manage in smaller scales, face significant limitations when confronted
with modern demands for global reach, high availability, and massive data
throughput. Several inherent challenges make these systems increasingly
untenable for large-scale applications:

Heterogeneity: Modern computing environments are inherently diverse,
comprising a myriad of hardware platforms, operating systems,
5
programming languages, and communication protocols. A centralized
system struggles to seamlessly interoperate across this vast and evolving
ecosystem, leading to compatibility issues and integration complexities.

Concurrency Management: As user bases expand and simultaneous
requests become the norm, managing concurrent access to shared
resources within a single system becomes a substantial hurdle.
Inadequate concurrency control can lead to data inconsistencies,
deadlocks, and severe performance bottlenecks.

Lack of Fault Tolerance: Centralized systems represent a single point of
failure. The breakdown of a critical component, such as a server or a
database, can render the entire system inoperable, leading to significant
downtime and loss of service. This vulnerability underscores the need for
architectures that can withstand partial failures without complete system
collapse.

Scalability Limitations: Scaling a centralized system to accommodate
growing user numbers and increasing data volumes is often a non-linear
and expensive process. Vertical scaling (upgrading existing hardware) has
physical and economic limits, while horizontal scaling (adding more
machines) is difficult to implement efficiently in a monolithic design.
Consequently, performance degrades disproportionately with increased
load.

Performance and Latency Issues: For geographically dispersed users,
content served from a distant central server incurs high network latency.
Data must traverse numerous network hops, increasing transmission times
and vulnerability to congestion. This leads to a degraded user experience,
particularly for latency-sensitive applications like real-time communication
or high-definition video streaming, where buffering and quality reduction
become prevalent.

Operational Costs: Maintaining an extensive, long-haul network
infrastructure to connect distant users to a centralized data source is
financially intensive for service providers. This includes costs associated
with international transit and backhaul capacity.
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
Market Control and "Termination Monopoly": In scenarios involving
content delivery, Internet Service Providers (ISPs) can exercise a
"termination monopoly" over the last mile of content delivery to
consumers. This allows for potential anti-competitive practices, such as
"double-charging" content providers for traffic already paid for by endusers, or intentionally inducing congestion to coerce content providers into
costly direct peering agreements. Such practices not only harm content
providers but also limit consumer choice and degrade overall internet
quality.
2. The Imperative for Distributed Solutions
The inherent limitations of centralized systems have driven the widespread
adoption of distributed computing paradigms. A distributed system, defined as a
collection of independent computers that communicate and coordinate their
actions solely by message passing, presents itself as a robust solution to the
challenges. Key motivations for constructing distributed systems include:

Enhanced Reliability and Availability: By distributing components and
replicating data across multiple nodes, distributed systems can tolerate
individual component failures without interrupting the entire service. This
redundancy ensures high availability and resilience, crucial for missioncritical applications.

Superior Scalability: Distributed architectures are designed for horizontal
scaling, allowing for the seamless addition of more computing resources
to handle increasing loads. This enables systems to expand efficiently and
economically, ensuring sustained performance as demand grows.

Improved Performance and Reduced Latency: By enabling parallel
execution of tasks and the geographical distribution of resources and data,
distributed systems can significantly reduce latency and improve overall
system performance. This is particularly vital for delivering content and
services to a global audience.

Resource Sharing and Collaboration: Distributed systems inherently
facilitate the sharing of physical and logical resources across a network.
They also enable collaborative work and the natural distribution of
7
information, fostering efficiency and innovation across diverse user
groups.

Transparency: A well-designed distributed system aims to provide various
forms of transparency (e.g., access, location, failure, concurrency,
replication, migration, performance, scaling) to users and developers,
making the underlying distribution largely invisible and simplifying
interaction.
3. Content Delivery Networks (CDNs) as a Distributed Solution: The Netflix Open
Connect Model
Content Delivery Networks (CDNs) represent a prominent application of
distributed systems principles, specifically addressing the challenges of largescale content distribution. Netflix's Open Connect exemplifies a highly evolved,
purpose-built CDN that directly tackles the problems identified with traditional
content delivery:

Localized Traffic Delivery: Open Connect strategically deploys "Open
Connect Appliances" (OCAs)—purpose-built servers—at Internet Exchange
Points (IXPs) and directly within ISP networks worldwide. This brings
Netflix's extensive content catalog geographically closer to its members,
drastically reducing the "network and geographical distances that video
bits must travel."

Optimized User Experience: By localizing content, Open Connect minimizes
latency and the risk of network congestion and packet loss. This translates
directly to a consistently high-quality video streaming experience for
Netflix members, characterized by less buffering and higher resolutions.

Significant Cost Savings for ISPs: The cooperative model, with Netflix
providing OCAs free of charge to ISPs, eliminates or significantly reduces
the transit charges ISPs would otherwise incur for fetching content over
long distances. This localized traffic offloads a substantial burden from ISP
backbone networks, contributing to overall internet efficiency.

Bandwidth Efficiency: Beyond physical proximity, Netflix employs
advanced video compression and encoding techniques. These innovations
8
ensure that high-quality video streams consume the least possible amount
of data, further optimizing bandwidth usage across the entire network.

Increased Resilience and Availability: The distributed nature of thousands
of OCAs across 142 countries ensures high availability. If one OCA or
network path experiences an issue, client devices can be seamlessly
steered to an optimal alternative, guaranteeing uninterrupted service.

Proactive Content Updates: Netflix leverages predictive algorithms to preposition content and software updates to OCAs during off-peak hours.
This proactive caching minimizes bandwidth strain during peak usage
times and ensures that popular content is readily available.

Collaborative Partnership: Open Connect embodies a cooperative
approach between content providers and ISPs. By directly engaging with
ISPs and offering solutions that mutually benefit both parties (improved
quality for consumers, cost savings for ISPs), it promotes a sustainable
ecosystem for online content delivery.
Conclusion
The evolution of digital services, characterized by exponential growth in user
numbers and data volumes, has exposed critical vulnerabilities and inefficiencies
in traditional centralized system architectures. The shift towards distributed
systems is not merely a technological trend but a fundamental necessity for
achieving the reliability, scalability, performance, and cost-effectiveness required
by modern applications. Content Delivery Networks, as exemplified by Netflix's
Open Connect, stand as a testament to the power of distributed computing in
addressing complex, real-world challenges, transforming the landscape of global
content delivery, and fostering a more efficient and resilient internet ecosystem.
System Design
Existing systems face several challenges that highlight the critical need for
distributed solutions. These challenges can be broadly categorized and are
addressed by the principles and practical implementations of distributed
computing.
9
Fig1:System Architecture for the Netflix CDN
Challenges of Existing Centralized Systems
Based on the provided documents, the challenges of traditional, often
centralized, systems include:

Heterogeneity: Systems must cope with diverse hardware, operating
systems, communication architectures, programming languages, software
interfaces, security measures, and information representations. Ensuring
interoperability across these varied components is a significant challenge
for non-distributed systems.

Concurrency: In systems where multiple users or processes access shared
resources, managing simultaneous requests without conflicts is complex
and critical for proper functioning.

Fault Tolerance: A single point of failure in a centralized system can lead
to the entire system crashing. Traditional systems struggle to ensure that
the failure of one component does not bring down the whole system.

Scalability: As the number of users or the volume of data grows,
traditional systems often struggle to maintain efficiency and performance.
Scaling up a centralized system can be costly and complex.
10

Performance and Latency: When content or services are located far from
the end-user, data must travel through many networks and routers,
leading to increased delays (latency) and potential congestion. This can
result in a poor user experience, especially for demanding applications like
video streaming.

Cost of Infrastructure: Building and maintaining international networks for
content delivery, especially over long distances, is expensive.

"Termination Monopoly": Internet Service Providers (ISPs) can exert
control over traffic delivery to consumers within their networks. This can
lead to potential issues like "double-charging" content providers for traffic
their customers have already paid for or creating perverse incentives
where ISPs might allow congestion to force content providers to pay for
direct connections.
fig2:Termination Monopoly (reduces cost)
The Need for a Distributed Solution
Distributed systems offer solutions to these challenges by leveraging multiple
interconnected computers to work cooperatively. The benefits and reasons for
adopting distributed solutions include:

Enhanced Reliability and Availability: By replicating data and services
across different locations, distributed systems can ensure long-term
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preservation and data backup. If one component fails, others can continue
to operate, preventing system-wide outages.

Improved Scalability: Distributed systems are inherently designed to
handle increasing loads and users by distributing computational tasks and
allowing for the addition of more resources. This makes them more
efficient and responsive to growing demand.

Increased Performance through Content Proximity: Solutions like Content
Delivery Networks (CDNs), which are distributed networks of local servers,
move content closer to consumers. This significantly reduces geographic
distance, minimizes the number of routers data must traverse, and
alleviates congestion, leading to better delivery times and a higher quality
of experience for users.
Fig3: Transit (improves scalability, performance, and reliability)

Cost Efficiency: By moving content closer to consumers, CDNs can reduce
the transit costs for ISPs, enabling more efficient delivery traffic and
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potentially freeing up long-haul network infrastructure for other critical
services.

Transparency: Distributed systems aim to hide the complexities of
distribution from users and application programmers, making the system
appear as a single, coherent entity. This includes transparency in access,
location, failures, replication, migration, concurrency, and performance.

Resource Sharing and Collaboration: Distributed systems facilitate sharing
resources like printers and databases among many users, reducing
ownership costs. They also enable collaborative work and the inherent
distribution of information across different individuals and locations.

Handling Increased Demand: As demonstrated during the COVID-19
pandemic, distributed solutions like CDNs were crucial in helping internet
networks adapt to massively increased loads and meet the demand for
high-speed broadband and online services.
In summary, the limitations of centralized systems in handling heterogeneity,
ensuring reliability, scaling efficiently, and providing optimal performance,
especially in content delivery, necessitate the adoption of distributed solutions.
These solutions, exemplified by CDNs like Netflix's Open Connect, provide a
robust, scalable, and efficient framework for modern internet services.
Simulation Development
Technologies used and development methodology
For the simulation of a content delivery network, I used Cisco Packet Tracer to
draw the topologies, to configure the ports and the interfaces allowing
connecting connectivity, cost reduction, security and scalability within the
network, hence enhancing the performance of the overall network. To complete
the configurations, I drew inspiration from Cisco’s online resources and YouTube
tutorial videos. For the security of the system, I configured an ASA server which
acts as a firewall within the Netflix network to protect it from outside threats. I
implemented technologies such as DMZ, AAA, SSH, VLAN segmentation, NAT,
ACL, inspection policy and address translation. The DMZ serves to protect (by
creating a buffer zone) Netflix’s internal network from public facing services like
the services of the Point of Presence server. The AAA allows the identification
13
and the filtering of network’s inner workings base on privacy levels. The SSH in
this case will encrypt any data that is transmitted within network. The content is
encrypted using symmetric encryption algorithms such as AES where the public
and private keys are the same. Hence it will allow faster transmission of the
cryptogram and enhance performance. The NAT will create a common IP address
for connecting multiple devices to a network hence, so ensuring the privacy of
the individual IP addresses on the individual devices. The inspection policy will in
turn act as a standardizing blueprint for the network. Identifying areas of
improvements and managing risks efficiently. For where the Netflix server
communicates with a ISP’s Server for respond to a user’s content request we
implemented a reverse proxy server technology. A reverse proxy is a server that
sits in front of one or more web servers, intercepting requests from clients and
forwarding them to the appropriate web servers. This setup is different from a
forward proxy, which sits in front of clients and forwards their requests to web
servers.
Expected benefits

Load balancing

Caching

Layered security

Optimized performance

Scalability
Final Report
Netflix faced significant challenges in delivering high-quality video content to a
global audience due to the limitations of traditional, centralized content delivery
systems. These systems struggled with issues such as network congestion, high
latency, scalability limitations, fault tolerance, and high operational costs. The
growing demand for seamless streaming required a more efficient, scalable, and
resilient solution.
To address these challenges, Netflix developed Open Connect, a highly
distributed Content Delivery Network (CDN). This system deploys Open
Connect Appliances (OCAs) in strategic global locations, such as Internet
14
Exchange Points (IXPs) and within ISP networks, to bring content closer to end
users.
Key benefits of the distributed solution include:

Enhanced User Experience: Reduced latency and buffering, improving
video quality.

Cost Efficiency for ISPs: Minimizing transit and backhaul costs.

Scalability: Seamless horizontal scaling to meet increasing demand.

Reliability and Fault Tolerance: High availability due to distributed
architecture.

Security: Implementation of advanced network security techniques (ASA
firewall, DMZ, AAA, SSH, NAT, ACL).

Collaboration with ISPs: A mutually beneficial model supporting ISP
networks.
The project also involved simulation using Cisco Packet Tracer, demonstrating
configurations that enhance security, performance, and scalability through
technologies like firewalls, VLAN segmentation, NAT, and reverse proxy servers.
Overall, Netflix Open Connect exemplifies how distributed systems can
efficiently address the limitations of centralized models, ensuring superior
content delivery and user satisfaction.
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Bibliography
Bilha, T., 2025. Distributed Systems Chapter 1 , Gaborone, Botswana: LUCT.
Buyya, K. P. a. R., 2007. [Online]
Available at: http://www.hit.bme.hu/~jakab/edu/litr/CDN/CDN-Taxonomy.pdf
[Accessed 2025].
Netflix, 2025. Open Connect. [Online]
Available at: https://openconnect.netflix.com/en/
[Accessed 1 June 2025].what
Pallis, A. V. a. G., 2003. "Content delivery networks: status and trends,". In: Internet
Computing. s.l.:IEEE.