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SDN – Shape of Things to Come

Explore the journey of Software Defined Networks, from paradigm shifts to synergy with emerging technologies, enabling agile control and advanced infrastructure management.

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SDN – Shape of Things to Come

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  1. SDN – Shape of Things to Come Satish Kumar Tripathi President, University at Buffalo, State University of New York New York, USA Keynote Speaker, ICSDN 2019, Chennai, India

  2. Software Defined Network(ing) Flexibility Leading to Better Management of Resources Separates Control (Action) and Data (Transport / Forwarding) Resulted in Creative Use Coupled with Granular Operation Worldwide interest as seen by activity in Open Source/Industry/Standards… Synergistic Possibilities Across Competing and Cooperating Technologies SDN – What is it?

  3. How did it start?

  4. Over several decades, the power of technology enabled building of large and complex Information Infrastructure that are extremely capable and flexible. As a consequence, number of users and usage complexity increased many fold.

  5. SDN EvolutionAndThe Path Traversed

  6. Supported byMajor AdvancesAndParadigm Shifts

  7. Circuit Switched Telecom (PSTN) Networks to Packet Switched Data Networks. Paradigm shift: From sending Data over Telecom Network to completing voice circuits over Packet Switched Data Networks PSTN: Public Switched Telephone Network Major Advancesand Paradigm Shifts I

  8. Mobility! Paradigm Shift: From accessing the Network from a “single” designated point, the freedom to access the digital space from anywhere in the network. Major Advancesand Paradigm Shifts II

  9. Emergence of Wireless Communication Systems Paradigm shift: From fully wired systems to a seamless combination of wired and wireless systems. Division of labor – wired deployed for infrastructure and wireless deployed for user access. Major Advancesand Paradigm Shifts III

  10. Emergence of Virtualization Paradigm shift: From dedicated systems for each “Purpose”, to a seamless coexistence of “Purposes” on uniform hardware. Major Advancesand Paradigm Shifts IV

  11. Emergence of Software Defined Controls Paradigm shift: From dedicated systems for each “Purpose”, to a Logically Centrally controlled (uniform) hardware. Major Advancesand Paradigm Shifts V

  12. Uniform Scalable Hardware Data Center in Different Sizes Virtual Machines in the Data Center Software Defined Controls for Repurposing the Data Center hardware to realize the required “Purpose” Software Defined Networks (SDN) SDN Controllers SDN Devices Network Slicing Network Function Virtualization Agility, Accuracy, Quality of Service, Security, Access Control, Network Management, Business Management – All in one Go! What have we Got Here!

  13. Awesome Ability to Define and Control a Software Environment with Agility, Using uniform hardware environment that is easy to scale. Programmable: Communication, Computing Environment, and Storage Facility In Short

  14. VM-1 VM-2 VM-3 VM-4 VM-5 VM-6 VM-N Hypervisor S o f t w a r e Virtualized CPU Virtualized Memory Virtualized Storage Virtualized I/O Communication Operating System Hardware CPU + Memory + Storage Hardware

  15. Technology: Speed and Flexibility Control: Time available to Respond

  16. SDN was the answer But the control element remained predominantly human-driven. Result was increasing concern about Quality, Correctness, Efficiency for Owners, Managers, and Operators of the contemporary Infrastructure.

  17. But...

  18. Why SDN? The question everyone raised was: Is it possible to Respond to the Changing Usage Scenario with Agility?

  19. Confidence stems from the fact that...

  20. Software Defined Network is the separation of Control (Action) Plane and Data (Forwarding) Plane in a contemporary network.

  21. The problem transformed in to one of…

  22. Decide on Action and Implementation A G I L I T Y Understand Observe Control Model Granularity What How why

  23. Why was it so? A G I L I T Y Understand Observe Control Decide on Action and Implementation Granularity Model SOFTWARE DEFINED CONTROLS Since The Discourse Was Always In A Networking Context, It Came To Be Known As SOFTWARE DEFINED NETWORKS

  24. In Fact, it is: Software Defined Network When it Co-exists with contemporary technology environment It is called Software Driven Network

  25. Over a period of time,SDN was progressively perceived as The Network Brain

  26. What was Happening though?The transition was rather swift…

  27. From being aTraditional Network... D E F A B C

  28. Control Plane Data Plane Separated

  29. Control Plane Data Plane Controlled

  30. Control Plane Data Plane Multiple Controllers

  31. Control Plane Data Plane Cooperating Controllers

  32. Granularity Observe-ability Model Control Plane Centralized View Controllability Commands Commands Data Forwarding by each Router or Switch Data Plane Software Defined Controls

  33. Software Defined Networking (SDN) emerged as a • Networking Paradigm • that gives hope to change the limitations of Contemporary Network Infrastructure

  34. Implication? • Focus Shifted to • Policy Enforcement • and • Rapid Network (re)Configuration

  35. Context? Opportunities?? • Emergence of 5G • Deployment of IoT • Use of AI, ML, and Big Data

  36. 5G and SDN Network Function Virtualization. Network Slicing. Managing Attributes for Each Slice. Virtual Network Functions. Creation of New Services on NFV/VNF. Manage Traffic. Orchestrate how devices Communicate. Reason: Increase in Flexibility and Network Programmability.

  37. IoT and SDN IoT Market 21 Billion Devices by 2020! SDN Market to support 139.2 Billion USD. Issue: Elasticity and Agile Data Transfer Allied Market Research, Global Marketing Firm.

  38. AI and SDN vs Humans and Networks AI has the ability to rapidly analyse massive volumes of information to detect patterns, trigger warnings and find anomalies that can help network operators predict a range of network issues before they impact customers.  Human experts are typically excellent at understanding context. Also humans are very good at understanding logic and are very good at making reasonable and informative decisions. Those are weak areas of AI systems.

  39. AI and SDN Taking the key differentiator of human experts and key differentiators of AI systems and bringing them together to provide any network the security, reliability and best experience is fast becoming the norm.

  40. Big Data and SDN Both big data and software-defined networking (SDN) have attracted great interests from both academia and industry. SDN can greatly facilitate big data acquisition, transmission, storage, and processing. On the other hand, big data will have profound impacts on the design and operation of SDN.

  41. Big Data and SDN SDN is useful in solving several issues prevailing with big data applications, including big data processing in cloud data centers, data delivery, joint optimization, scientific big data architectures and scheduling issues. SDN can manage the network efficiently for improving the performance of big data applications. Big data can benefit SDN as well, including traffic engineering, cross-layer design, defeating security attacks, and SDN-based intra and inter data center networks.

  42. What are the Gains?

  43. What Next?

  44. Where Are We?

  45. Workload vs Resources

  46. Ability To Map Resources and Workloads with Agility

  47. User: Speed ⬆️ Latency ⬇️

  48. Technology: Speed ⬆️ Flexibility ⬆️

  49. Network: Bandwidth ⬆️ Latency ⬇️

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