This is my presentation at IFIP Networking 2018 in Zurich.
In this paper, we propose a cloud-assisted network as an alternative connectivity provider.
More details: https://kkpradeeban.blogspot.com/2018/05/moving-bits-with-fleet-of-shared.html
The presentation slides of my Ph.D. thesis proposal ("CAT" as known in my university). I received a score of 18/20.
Supervisors:
Prof. Luís Veiga (IST, ULisboa)
Prof. Peter Van Roy (UCLouvain)
Jury:
Prof. Javid Taheri (Karlstad University)
Prof. Fernando Mira da Silva (IST, ULisboa)
Services that access or process a large volume of data are known as data services. Big data frameworks consist of diverse storage media and heterogeneous data formats. Through their service-based approach, data services offer a standardized execution model to big data frameworks. Software-Defined Networking (SDN) increases the programmability of the network, by unifying the control plane centrally, away from the distributed data plane devices. In this paper, we present Software-Defined Data Services (SDDS), extending the data services with the SDN paradigm. SDDS consists of two aspects. First, it models the big data executions as data services or big services composed of several data services. Then, it orchestrates the services centrally in an interoperable manner, by logically separating the executions from the storage. We present the design of an SDDS orchestration framework for network-aware big data executions in data centers. We then evaluate the performance of SDDS through microbenchmarks on a prototype implementation. By extending SDN beyond data centers, we can deploy SDDS in broader execution environments.
https://kkpradeeban.blogspot.com/2018/04/software-defined-data-services.html
This is the presentation I did to the audience of EMJD-DC Spring Event 2017 Brussels to discuss my research. http://kkpradeeban.blogspot.be/2017/05/emjd-dc-spring-event-2017.html
International Refereed Journal of Engineering and Science (IRJES) is a peer reviewed online journal for professionals and researchers in the field of computer science. The main aim is to resolve emerging and outstanding problems revealed by recent social and technological change. IJRES provides the platform for the researchers to present and evaluate their work from both theoretical and technical aspects and to share their views.
The presentation slides of my Ph.D. thesis proposal ("CAT" as known in my university). I received a score of 18/20.
Supervisors:
Prof. Luís Veiga (IST, ULisboa)
Prof. Peter Van Roy (UCLouvain)
Jury:
Prof. Javid Taheri (Karlstad University)
Prof. Fernando Mira da Silva (IST, ULisboa)
Services that access or process a large volume of data are known as data services. Big data frameworks consist of diverse storage media and heterogeneous data formats. Through their service-based approach, data services offer a standardized execution model to big data frameworks. Software-Defined Networking (SDN) increases the programmability of the network, by unifying the control plane centrally, away from the distributed data plane devices. In this paper, we present Software-Defined Data Services (SDDS), extending the data services with the SDN paradigm. SDDS consists of two aspects. First, it models the big data executions as data services or big services composed of several data services. Then, it orchestrates the services centrally in an interoperable manner, by logically separating the executions from the storage. We present the design of an SDDS orchestration framework for network-aware big data executions in data centers. We then evaluate the performance of SDDS through microbenchmarks on a prototype implementation. By extending SDN beyond data centers, we can deploy SDDS in broader execution environments.
https://kkpradeeban.blogspot.com/2018/04/software-defined-data-services.html
This is the presentation I did to the audience of EMJD-DC Spring Event 2017 Brussels to discuss my research. http://kkpradeeban.blogspot.be/2017/05/emjd-dc-spring-event-2017.html
International Refereed Journal of Engineering and Science (IRJES) is a peer reviewed online journal for professionals and researchers in the field of computer science. The main aim is to resolve emerging and outstanding problems revealed by recent social and technological change. IJRES provides the platform for the researchers to present and evaluate their work from both theoretical and technical aspects and to share their views.
A Grid Computing Platform where Communication Function is in Balance with Computation and Storage.
Lambda Data Grid Service architecture interacts with Cyber-infrastructure, and overcomes data limitations efficiently & effectively by:
treating the “network” as a primary resource just like “storage” and “computation”
treating the “network” as a “scheduled resource”
relying upon a massive, dynamic transport infrastructure: Dynamic Optical Network
he Named Data Networking (NDN) project proposed an evolution of the IP architecture that generalizes the role of this thin waist, such that packets can name objects other than communication endpoints. More specifically, NDN changes the semantics of network service from delivering the packet to a given destination address to fetching data identified by a given name. The name in an NDN packet can name anything – an endpoint, a data chunk in a movie or a book, a command to turn on some lights, etc. The hope is that this conceptually simple change allows NDN networks to apply almost all of the Internet’s well-tested engineering properties to broader range of problems beyond end-to-end communications.
ORCHESTRATING BULK DATA TRANSFERS ACROSS GEO-DISTRIBUTED DATACENTERSNexgen Technology
bulk ieee projects in pondicherry,ieee projects in pondicherry,final year ieee projects in pondicherry
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
Talk at WRNP/SBRC on 5-May-2018 (https://wrnp.rnp.br/programacao) presenting the state of affairs on Network Service Orchestration (NSO) and its role in the evolving landscape of network softwarization. Based on the NSO survey; https://arxiv.org/abs/1803.06596
This is the 2nd defense of my Ph.D. double degree.
More details - https://kkpradeeban.blogspot.com/2019/08/my-phd-defense-software-defined-systems.html
The presentation slides of my Ph.D. thesis. For more information - https://kkpradeeban.blogspot.com/2019/07/my-phd-defense-software-defined-systems.html
APNIC Training Delivery Manager Terry Sweetser presents an overview of Internet Exchange Points at PacNOG 31, held in Port Vila, Vanuatu from 26 to 30 June 2023.
A Grid Computing Platform where Communication Function is in Balance with Computation and Storage.
Lambda Data Grid Service architecture interacts with Cyber-infrastructure, and overcomes data limitations efficiently & effectively by:
treating the “network” as a primary resource just like “storage” and “computation”
treating the “network” as a “scheduled resource”
relying upon a massive, dynamic transport infrastructure: Dynamic Optical Network
he Named Data Networking (NDN) project proposed an evolution of the IP architecture that generalizes the role of this thin waist, such that packets can name objects other than communication endpoints. More specifically, NDN changes the semantics of network service from delivering the packet to a given destination address to fetching data identified by a given name. The name in an NDN packet can name anything – an endpoint, a data chunk in a movie or a book, a command to turn on some lights, etc. The hope is that this conceptually simple change allows NDN networks to apply almost all of the Internet’s well-tested engineering properties to broader range of problems beyond end-to-end communications.
ORCHESTRATING BULK DATA TRANSFERS ACROSS GEO-DISTRIBUTED DATACENTERSNexgen Technology
bulk ieee projects in pondicherry,ieee projects in pondicherry,final year ieee projects in pondicherry
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
Talk at WRNP/SBRC on 5-May-2018 (https://wrnp.rnp.br/programacao) presenting the state of affairs on Network Service Orchestration (NSO) and its role in the evolving landscape of network softwarization. Based on the NSO survey; https://arxiv.org/abs/1803.06596
This is the 2nd defense of my Ph.D. double degree.
More details - https://kkpradeeban.blogspot.com/2019/08/my-phd-defense-software-defined-systems.html
The presentation slides of my Ph.D. thesis. For more information - https://kkpradeeban.blogspot.com/2019/07/my-phd-defense-software-defined-systems.html
APNIC Training Delivery Manager Terry Sweetser presents an overview of Internet Exchange Points at PacNOG 31, held in Port Vila, Vanuatu from 26 to 30 June 2023.
PITA 27th AGM & Business Forum Expo 23: Internet Exchange PointsAPNIC
APNIC Training Delivery Manager Terry Sweetser presented on smarter networking and Internet traffic efficiency with Internet Exchange Points at the PITA 27th AGM & Business Forum Expo 23, held from 29 May to 1 June 2023, in Port Moresby, Papua New Guinea.
We’re lifting the lid on our Big Data Transport solution. Technology engineered specifically to enable a new era of connectivity for globally dispersed mega data centers.
APNIC Training Delivery Manager for SEA and SA, Shane Hermoso, presents on the importance of peering and IXPs at the Women in Networking series on 17 November 2021
Experimental Evaluation of Large Scale WiFi Multicast Rate Control, By: Varun...Belal Essam ElDiwany
A closer view on the InfoCom'16 paper entitled with "Experimental Evaluation of Large Scale WiFi Multicast Rate Control", for the authors, "Varun Guptay, Craig Guttermany, Yigal Bejerano, Gil Zussmany"
Enjoy .. :)
Keeping the Internet Fast and Resilient for You and Your CustomersCloudflare
Many of the most common uses of the Internet today weren’t envisioned when it was created. In many ways, the success of the Internet and the TCP/IP protocol once envisioned by DARPA is pushing it to the limits. As a result, ensuring high-performance for end-users is complicated. Join Cloudflare experts for a talk that will describe the depth of these problems -- ranging from how routing breaks, to how shortage of IP space (under IPv4) hurts performance, to route leaks -- and how these issues lead to congestion and poor performance. They'll also discuss an approach to solving these challenges given the constraints.
Bench, a Framework for Benchmarking Kafka Using K8s and OpenMessaging Benchma...HostedbyConfluent
In this lightning talk session, we will discuss a messaging benchmark tool developed at Reddit called Bench. Bench quantifies the cost-performance trade-offs of various configurations of messaging systems. Infrastructure engineers can use Bench to determine the number and types of instances needed, estimate the expected throughput and response latency, and test the durability and recoverability of these systems under stress. For most use cases, Bench utilizes load tests included in the OpenMessaging Benchmark Framework. Users can configure these to emulate anticipated scale and message sizes. Additionally, engineers can implement custom tests if an appropriate one does not exist, for example, when an accurate simulation is required for a specific producer/consumer pattern. Finally, Bench uses instance and network pricing of the target cloud environment so that users can determine the cost and performance of the trade-offs of each system configuration.
Presented as part of Container Conference 2018: www.containerconf.in
Deep dive into Kubernetes networking
"Container networking is pretty complex and Kubernetes has taken a unique approach to solve container networking challenges. Both simplicity and scalability have been key design principles of Kubernetes networking. This session will illustrate kubernetes networking concepts with examples and demos. Best practises and considerations for deploying container networks in production using Kubernetes will be covered.
This session will also go into latest developments in Kubernetes networking like Network policy and Service policy using Istio."
Similar to Moving bits with a fleet of shared virtual routers (20)
Google Summer of Code (GSoC) is a remote open-source internship program funded by Google, for contributors to remotely work with an open source organization (and get paid) over a summer.
https://kkpradeeban.blogspot.com/2022/11/google-summer-of-code-gsoc-2023.html
GSoC 2022 comes with more changes and flexibility. This presentation aims to give an introduction to the contributors and what to expect this summer.
https://kkpradeeban.blogspot.com/2022/01/google-summer-of-code-gsoc-2022.html
GSoC 2022 comes with more changes and flexibility. This presentation aims to give an introduction to the contributors and what to expect this summer.
https://kkpradeeban.blogspot.com/2022/01/google-summer-of-code-gsoc-2022.html
Niffler is an efficient DICOM Framework for machine learning pipelines and processing workflows on metadata. It facilitates efficient transfer of DICOM images on-demand and real-time from PACS to the research environments, to run processing workflows and machine learning pipelines.
https://github.com/Emory-HITI/Niffler/
This is an introductory presentation to GSoC 2021. This year there were a few specific changes to GSoC compared to the past years. Specifically, workload and the student stipend have been made half in 2021 compared to the previous years.
We propose Niffler (https://github.com/Emory-HITI/Niffler), an open-source ML framework that runs in research
clusters by receiving images in real-time using DICOM protocol from hospitals' PACS.
This presentation aims to introduce GSoC to new mentors and mentoring organizations. More details - https://kkpradeeban.blogspot.com/2019/12/google-summer-of-code-gsoc-2020-for.html
An introductory presentation to Google Summer of Code (GSoC), focusing on the year 2020. More information can be found at https://kkpradeeban.blogspot.com/search/label/GSoC
The diversity of data management systems affords developers the luxury of building heterogeneous architectures to address the unique needs of big data. It allows one to mix-n-match systems that can store, query, update, and process data based on specific use cases. However, this heterogeneity brings
with it the burden of developing custom interfaces for each data management system. Existing big data frameworks fall short in mitigating these challenges imposed. In this paper, we present Bindaas, a secure and extensible big data middleware that offers uniform access to diverse data sources. By providing a RESTful web service interface to the data sources, Bindaas exposes query, update, store, and delete functionality of the data sources as data service APIs, while providing turn-key support for standard operations involving access control and audit-trails. The research community has deployed Bindaas in
various production environments in healthcare. Our evaluations highlight the efficiency of Bindaas in serving concurrent requests to data source instances with minimal overheads.
This is the presentation of DMAH workshop in conjunction with VLDB'17. This describes my work during my stay at Emory BMI.
More information: https://kkpradeeban.blogspot.com/2017/08/on-demand-service-based-big-data.html
This is a poster I presented at ACRO Summer School at Karlstad University. This presents my PhD work.
More details: http://kkpradeeban.blogspot.com/2017/07/my-first-polygonal-journey.html
The paper presented at SDS'2017 Valencia. More information can be found at http://kkpradeeban.blogspot.com/2017/05/sd-cps-taming-challenges-of-cyber.html
Data centers offer computational resources with various levels of guaranteed performance to the tenants, through differentiated Service Level Agreements (SLA). Typically, data center and cloud providers do not extend these guarantees to the networking layer. Since communication is carried over a network shared by all the tenants, the performance that a tenant application can achieve is unpredictable and depends on factors often beyond the tenant’s control.
We propose ViTeNA, a Software-Defined Networking-based virtual network embedding algorithm and approach that aims to solve these problems by using the abstraction of virtual networks. Virtual Tenant Networks (VTN) are isolated from each other, offering virtual networks to each of the tenants, with bandwidth guarantees. Deployed along with a scalable OpenFlow controller, ViTeNA allocates virtual tenant networks in a work-conservative system. Preliminary evaluations on data centers with tree and fat-tree topologies indicate that ViTeNA achieves both high consolidation on the allocation of virtual networks and high data center resource utilization.
Cloud network systems and applications are tested in simulation and emulation environments prior to physical deployments, at different stages of development. Software-Defined Networking (SDN) enables separating logic and execution from the data plane consisting of switches and hosts, to a logically centralized control plane. The global view and control available to the controller enable incremental updates, management, and allocation of resources to the networks. However, unlike the physical networks or the networks emulated by the emulators, current network simulators still lack integration with the SDN controllers.
Hence, currently it is impossible to efficiently orchestrate a simulated network through a centralized controller, or realistically model the controller algorithms and SDN architectures without having the resources for a one-to-one emulation. To address this, this paper presents SDNSim, an SDN simulation middleware, which leverages the principles of SDN for continuous development of cloud and data center networks. SDNSim is an “SDN-aware” network simulator that integrates with the controller through plugins for southbound protocols such as OpenFlow, to execute the algorithms incrementally thus deployed in the control plane.
Data centers consist of various users with multiple roles and differentiated levels of access. Tenant execution flows can be of different priorities based on the role of the tenant and the nature of the process. Traditionally enterprise network optimizations are made at each specific layer, from the physical layer to the application layer. However, a cross-layer optimization of cloud networks would utilize the data available to each of the layers in a more efficient manner.
This paper proposes an approach and architecture for differentiated quality of service (QoS). By employing a selective redundancy in a controlled manner, end-to-end delivery is guaranteed for priority tenant application flows despite congestion. The architecture, in a higher level, focuses on exploiting the global knowledge of the underlying network readily available to the Software-Defined Networking (SDN) controller to cater the requirements of the tenant applications. QoS is guaranteed to the critical tenant flows in multi-tenant clouds by cross-layer enhancements across the network and application layers.
eScience consists of computation-intensive workflows executing on highly distributed networks. Service compositions aggregate web services to automate scientific and enterprise business processes. Along with the increased demand for data quality and Quality of Service (QoS) for an accurate outcome in a shorter completion time, execution of the eScience workflows and service compositions are also required to be distributed efficiently across various geo-distributed nodes. This paper presents Mayan, a Software-Defined Networking (SDN) based approach for service composition.
Mayan i) facilitates an adaptive execution of scientific workflows, ii) offers a more efficient service composition by leveraging distributed execution frameworks, in addition to the traditional web service engines, and iii) enables a very large-scale reliable service composition by finding and consuming the current best-fit among the multiple implementations or deployments of the same service.
My presentation at The 2nd Portugal|UT Austin summer school in systems and networking and
EMJD-DC spring event 2016
June 3, 2016. Costa da Caparica, Portugal describing my thesis work
How to Split Bills in the Odoo 17 POS ModuleCeline George
Bills have a main role in point of sale procedure. It will help to track sales, handling payments and giving receipts to customers. Bill splitting also has an important role in POS. For example, If some friends come together for dinner and if they want to divide the bill then it is possible by POS bill splitting. This slide will show how to split bills in odoo 17 POS.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdf
Moving bits with a fleet of shared virtual routers
1. Pradeeban Kathiravelu∗†
Marco Chiesa‡
Pedro Marcos§
Marco Canini¶
Luís Veiga∗
∗
INESC-ID Lisboa / Instituto Superior Técnico, Universidade de Lisboa
†
Université catholique de Louvain ‡
KTH §
UFRGS/FURG ¶
KAUST
IFIP Networking 2018.
Zurich, Switzerland. 15th
May, 2018.
1
Moving Bits with a Fleet of
Shared Virtual Routers
2. Introduction
2/20
● Increasing demand for bandwidth.
● Decreasing bandwidth prices.
● Pricing Disparity. E.g. IP Transit Price, 2014 (per Mbps)
○ USA: 0.94 $
○ Kazakhstan: 15 $
○ Uzbekistan: 347 $
● What about latency?
○ Online gaming.
○ High-frequency trading.
○ Remote surgery.
3. Motivation
● Cloud providers have a dedicated connectivity.
○ Well-provisioned and maintained network.
○ Increasing number of regions and points of presence.
● Can a network overlay over cloud instances be used as an
alternative connectivity provider?
○ Cost-effectiveness.
○ High-performance.
○ Optional network services.
3/20
5. Our Proposal: NetUber
● A third-party virtual connectivity provider with no fixed
infrastructure.
○ An overlay network, leveraging multi-cloud infrastructures.
5/20
6. NetUber Application Scenarios
1. Cheaper transfers between two endpoints.
2. Higher throughput or reduced latency.
3. Better alternative to SaaS replication.
4. Network services (compression, encryption, ..).
6/20
7. ● Feasibility Study: Platform Cost of NetUber
7/20
A. Cost of Cloud Instances.
○ Charged per second.
○ Very high.
B. Cost of Bandwidth.
○ Charged per data transferred.
○ Also very high.
C. Cost to connect to
the cloud provider.
Scenario (1 of 4): Cheaper Transfers
8. A) Cost of Cloud Instances: Observations
● 10 Gbps R4 instance (r4.8xlarge) pairs offered only
maximum of 1.2 Gbps of data transfer inter-region.
○ 10 Gbps only inside a placement group.
● We need more pairs
of instances!
8/20
Scenario (1 of 4): Cheaper Transfers
9. Spot Instances!
● Cheaper (up to 90% savings), but volatile, instances.
● Price Fluctuations - Future price unpredictable (for EC2).
● Differing prices among availability zones of a region.
○ Buy from the cheapest availability zones at the moment.
○ Maintain instances in the cheap availability zones.
9/22
Scenario (1 of 4): Cheaper Transfers
10. B) Cost of Bandwidth: Price disparity is real!
10/20
● Regions 1 - 9 (US, Canada, and EU) remain much cheaper
than the others.
Scenario (1 of 4): Cheaper Transfers
11. C) Cost to connect to the cloud provider
11/20
● Connect the end-user to the cloud servers.
● Often provided by the cloud provider.
○ Example: Amazon Direct Connect.
○ Charged per port-hour (e.g. how many hours a 10 GbE port is used).
Scenario (1 of 4): Cheaper Transfers
12. Cloud-Assisted Point-to-Point Connectivity
12/20
● Also cheaper than MPLS networks or transit providers.
○ Thanks to spot instances.
Scenario (2 of 4): Higher throughput or reduced latency
● Better control over the path, compared to the Internet paths.
13. 13/20
Scenario (3 of 4): Better Alternative to SaaS Replication
● Deploy Software-as-a-Service (SaaS) applications in just one region.
○ Use NetUber to access them from another region.
■ Instead of replicating them across multiple cloud regions.
● Access to more regions by leveraging multiple cloud providers.
14. 14/20
Scenario (4 of 4): Network Services
● NetUber uses memory-optimized R4 spot instances.
○ Each instance with 244 GB memory, 32 vCPU, and 10 GbE interface.
● Possibility to deploy network services at the instances.
● Network services.
○ Value-added services for the customer.
■ Encryption, WAN-Optimizer, load balancer, ..
○ Services for cost-efficiency.
■ Compression.
15. Evaluation
● Cheaper point-to-point connectivity.
○ AWS as the overlay cloud provider.
○ Compared against a transit provider and another connectivity provider
with a large global backbone network.
● Improve latency with cloud routes.
○ Compared to ISPs.
○ Traffic sent from: RIPE Atlas Probes and distributed servers.
○ Destination: AWS distributed servers from the AWS regions.
○ ISPs vs. ISP to the nearest AWS region and then NetUber overlay.
15/20
16. 1) Cheaper point-to-point connectivity
16/20
● Expense for 10 Gbps flat connectivity
○ Measured for transfers from EU and USA.
○ Cheaper for data transfers <50 TB.
17. 2) Improve latency with cloud routes
17/20
● Instead of sending traffic A -> Z, can we send A -> B -> Z?
○ B is closer to A. B and Z are servers in cloud regions.
○ B and Z are connected by NetUber overlay.
18. Ping times: ISP vs. NetUber (via region, % improvement)
18/20
● NetUber cuts Internet latencies up to a factor of 30%.
● The use of Direct Connect would make this even better.
19. Related Work
● Industrial efforts on infrastructure to offer connectivity.
○ Teridion - Internet fast lanes for SaaS providers.
○ Voxility - Large scale globally distributed infrastructure as an alternative
to transit providers.
● Previous research focus on technical side.
○ Not economical aspects - More expensive.
○ NetUber as a cheaper alternative, with spot instances.
19/20
20. Conclusion
● A connectivity provider that does not own the infrastructure.
● “Internet Fast-routes” through cloud-assisted networks.
○ Better than ISPs (~50 - 75 Mbps, often with a cap) for end-users.
● Cheaper point-to-point connectivity.
○ Cheaper than transit providers and similar offerings (for < 50 TB/month).
● Future work:
○ Evaluate NetUber for more parameters (loss rate, jitter, ..)
○ Evaluate the cost with more cloud providers and pairs of regions.
20/20
21. Conclusion
21/21
Thank you!
● A connectivity provider that does not own the infrastructure.
● “Internet Fast-routes” through cloud-assisted networks.
○ Better than ISPs (~50 - 75 Mbps, often with a cap) for end-users.
● Cheaper point-to-point connectivity.
○ Cheaper than transit providers and similar offerings (for < 50 TB/month).
● Future work:
○ Evaluate NetUber for more parameters (loss rate, jitter, ..)
○ Evaluate the cost with more cloud providers and pairs of regions.