Core Network Optimization: The Control Plane, Data Plane & Beyond

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This presentation takes you through the challenges network operators are facing as they bring in more and more bandwidth-intensive applications to their network. There are ways to optimize the network from the RAN to the Core -- and improve QoS.

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Core Network Optimization: The Control Plane, Data Plane & Beyond

  1. 1. Welcome! October 4 Mobile Data Offloading Optimization November 1 Core Network Optimization: The Control Plane, Data Plane and Beyond December 6 Optimizing Value Added Services (VAS) for Greater Revenue Generation 1
  2. 2. Today’s Topic & Presenters Core Network Optimization: the Control Plane, Data Plane and Beyond Presenters: Karl Wale, Director, Product Marketing Prashant Sharma, Systems Architect (CTO Office) Dikshit Sawhney, Product Manager James Radley, Systems Architect (CTO Office) November 1, 2012 2
  3. 3. Agenda  Overview • Core network optimization strategies • Monitoring, optimization, policy & offloading  Optimizing Network Probe & DPI Systems • Traffic handling, stateful loading, DPI  Signaling Plane Challenges & Solutions • Managing growth in signal plane traffic • Diameter routing & network offloading  Impact of Future Trends • SDN Networks 3
  4. 4. End-to-End LTE Infrastructure Radio Access Network Evolved Packet Core Policy Control IP Multimedia Subsystem User Policy & Mobility Charging Equipment IMS Management Routing Equipment Entity Function Home eNodeB Application Media Server Resource Function User Policy & Equipment Charging Equipment Enforcement Internet Function eNodeB LTE Security Serving Packet Gateway Gateway Gateway 75+ Customer Wins 10G  40G ATCA Traffic Management Audio  Video Conf Macro  Small Cells ~40% ATCA Share Dumb  Smart Pipes ~65% Market Share 4
  5. 5. Mobile Traffic ProfileMore users using more of theirdata allowance Web/InternetMore sessions…moreapplications…more signaling 3x OverallVideo flooding radio & 50% CAGRtransport network Until 2016 Video Stream Web/Internet 7x Video Stream 2x Audio Stream Audio Stream P2P, Voice Etc. P2P, Voice Etc. 2012 2016 5
  6. 6. Optimization vs. Customer Need Voice Era Data Era Slow / no internet Dropped calls Poor video streaming Poor Call Poor quality Poor Data Cant get email Quality QoS Capacity – RAN or core? Coverage ? Bearer or signaling ? Why ? Handovers ? Why ? Internet or access network Policy setting ? Churn Leave voice… Churn Churn due to data … promote …promote based coverage and voice on data capabilities quality Solution needed for 3G today, not only LTE problem 6
  7. 7. Optimization Goals Avoid Churn… QoS Improve Cost Service Revenue Reduction Services Efficiency PlansOpex Reduction Tiered ServicesEfficiency to defer Capex Core Content Based PricingAugment to offload etc. Network Tailored Plans Optimization Plan Deploy Optimize What you invoke and when depends on problem and lifecycle of network 7
  8. 8. Core Network Optimization Tools Network DPI & Policy Probes Intelligent Switch LTE & 3G & Load Balancer Network Core Video Optimization Traffic & Gateways Offload Market For Network Optimization Products Growing by 25% CAGR Strong growth in DPI, Web & Video Optimization Network Optimization Needs Blended Approach …No ‘One Size Fits All’ Solution 8
  9. 9. 3G Networks: Efficiency… Protocol Analysis Signaling Correlation across signaling & bearer Probe Application & QoS KPI awareness Radio Access Network Packet Core PCRF User Control Equipment Plane Femto User Equipment RAN SGSN GGSN PCEF Attributes KPI Layer 7 Awareness Voice  Data Tapped vs Bump in Wire Call  Sessions Temporary vs Permanent Installations Bandwidth  QoS/latency etc. Network Probe 9
  10. 10. 3G Networks: Capacity… Radio Access Network Packet Core PCRF RF & Transport User Control …bandwidth mgmt Equipment Plane Femto User Equipment RAN SGSN GGSN PCEF Transport RF & Transport …direct around core network …transcoding …local content access …local content re-direct …tailored packages Offloading Video Optimization 10
  11. 11. New LTE Networks Radio Access Network Packet Core PCRF How Differ ? User MME RF probe planning Equipment Policy ? HeNB SON …then optimize User Equipment EnodeB SGW PGW PCEF Offloading Video Optimization 11
  12. 12. Poll Question #1  Which do you consider the most important network optimization tool? (Select all that may apply) a. Stand-alone DPI b. Video optimization c. Local content caching & CDN d. DPI capable network probe (L4-7) e. 3G offload f. Small cell / wifi offload g. SON (Self Organizing Network) 12
  13. 13. Role of Stateful Load Balancer Load Balancer Value Adds  Scalability: how to scale up and down? Does it need re- Extended architecting? Scalability Product Life  Extended life: bridge the performance/throughput gap before move to next generation Fault Topology tolerance  Topology Hiding: Hide internal Hiding details (blades/servers) from peers  Fault tolerance: Redirect flow to new active element 13
  14. 14. Load Balancer - 1 DPI Filtering Transport Optimization Load Balancer - 2 DPI Filtering Transport Optimization Flows 1 - 10 Video Optimization Blade – 1 Transcoding Trans-rating User awareness Flows 51-55 Flows 11 - 50 Video Optimization Blade – 2 ATCA Platform Stateful Load Balancer Transcoding Trans-rating … User awareness Video optimization gateway Video Optimization Blade – n Transcoding Trans-rating User awareness blades HTTP/video traffic non–video traffic to be  Transport offloading:  DPI based Filtering: Stop14 passed to video processing of TCP connection that carry Offload handling/optimization
  15. 15. Load Balancer - 1 Control/Data Fault Global QoS mapping Tolerance Load Balancer - 2 Control/Data Fault Global QoS mapping Tolerance Flows 1 - 10 PCEF Blade – 1 Global/User GTPu DPI QoS Flows 51-55 Policy Mapping Flows 11 - 50 PGW + PCEF Gateway PCEF Blade – 2 Global/User GTPu DPI QoS Policy Mapping ATCA Platform Stateful Load Balancer … Control Plane PCEF Blade – n Global/User GTPu DPI QoS Policy Mapping Control Plane Charging GTPc Diameter Control QoS offload plane stacks external links control and data  QoS offloading:  I/O Aggregation: Understand PGW Multiple 10G, 40G Node/network level  Protocol Awareness15
  16. 16. Stateful Load Balancer Extended life cycle using load balancer  Scalability: Upfront load balancer to scale existing network probes/monitoring box  I/O: LB should be able to support large amount of I/O’s  Protocol awareness: LB should understand all of wireless protocols and their transports  Distributed load balancing: LB, itself, should be scalable to support variable number of backend application servers 16
  17. 17. Stateful Load Balancers Carrier Cloud Load Balancers  Scalability: Upfront load balancer to being efficiency of scale in carrier cloud  Fault tolerance: Fault tolerance of LB itself becomes one of the most critical aspect in the carrier cloud. This includes fault tolerance at platform, I/O, blades and application level  Protocol awareness: LB should understand all of wireless protocols and their transports 17
  18. 18. Load Balancer: Key Characteristics ATCA Platform for load balancer  High number of I/O: A heterogeneous platform like ATCA offer variety of I/O solution including centralized and distributed  Specialized processing: State of art packet processing and switching technologies (XLP, OcteonII, NP4, Trident) for common function offload  Fault tolerance: Carrier grade ATCA provides redundancy at I/O, platform elements, backplane and blade level 18
  19. 19. LTE Network Overview Home Subscriber AF IMS Application Server Network Function Mobility Management Policy & Entity Charging Rules Function Internet eNodeB Serving PDN Policy & Charging UE Gateway Gateway Enforcement FunctionWeb Radio S1 S5Email Bearer Bearer Bearer Service Data FlowsVoice Packet Filters 19
  20. 20. Main Drivers of Signaling Traffic  What is driving the signaling traffic in a LTE network? • Data Usage – Multiple connected devices: smartphones, tablets, notebooks, smart cameras, M2M etc. • Small Cells – Future networks will be heterogeneous i.e. a combination of macro and small cells (femto, pico, micro etc.). The evolved CN has to manage a lot more base stations than the legacy networks. • IMS – VoIP based call control network in LTE provides rich communications capabilities not limited to just voice conversation • Policy & Charging Control (PCC) – Policy and service based charging plays a key role in the LTE networks. This is causing a tremendous increase in Diameter signaling traffic with in the EPC that needs to be managed. 20
  21. 21. S1-flex Architecture • S1-flex architecture uses many- to-many network architecture between eNBs and MMEs for load balancing and redundancy purpose. eNB selects a MME on UE registration based on the current resource utilization at each of MMEs in the pool area Pool Area • MME uses a similar logic to MME MME MME select a S-GW from a pool of S- GWs serving the UE area S1 • Possible to re-direct UEs to new MMEs in case of overload at one eNB eNB of the MME in the pool area • S1-flex is a pre-requisite for the Network Sharing architecture discussed in the next chart 21
  22. 22. Network Sharing • This optimization technique involves sharing RAN and CN resources among multiple service providers. It is possible to share just RAN (MOCN) or both RAN and CN nodes (GWCN) • Multiple PLMN-id(s) are broadcasted on the air interface. UE selects a candidate PLMN and RAN assigns the CN node based on resource utilization and current loading of the shared CN elements. • Applicable to both 3G and LTE networks 22
  23. 23. LIPA  Local IP Access (LIPA) • An offload GW is co-located with the small cell (HeNB/HNB) and routes the data destined for home/enterprise network appropriately bypassing the EPC • UE uses standard signaling methods as a regular EPS bearer to setup the LIPA tunnel • LIPA can be enabled on per APN/UE basis 23
  24. 24. SIPTO  Selected IP Traffic Off-load (SIPTO) • Network uses DNS or other mechanisms to select a GW in close proximity to the UE’s point of attachment to the access network and offload the traffic from there • Option to enable off-load on a per UE/APN basis • Applicable to both small cell & macro networks providing E- UTRAN/UTRAN access 24
  25. 25. Multi-mode Small Cells (3G/LTE/WiFi) Non-3GPP Access • Use commonly deployed WiFi access points to offload traffic to the Internet. • Access Network Discovery and Selection Function (ANDSF) helps UE in selecting the appropriate access network based on Operator policies. • Architecture standardized by 3GPP so inter-access mobility is covered. 25
  26. 26. Misc. Network Optimization Techniques • Co-located SGW, PGW and GGSN nodes. This can improve the packet latency by eliminating one of the nodes in the data path. Mainly a deployment decision governed by network topology i.e. ratio of SGWs to PGWs/GGSNs • Similar colocation is possible for control plane nodes i.e. MME & SGSN. Allows for reduction of signaling traffic during inter-RAT (3G<->LTE) mobility • Direct tunnel architecture for UTRAN. This uses a direct connection from RNC to S- GW/GGSN bypassing the SGSN and thus improving packet 26 latency
  27. 27. Policy and Charging ControlArchitecture (PCC) Subscription Profile AF Repository (SPR) Online Sp Rx Charging System (OCS) Policy and Charging Rules Function (PCRF) Gxx Gx BBERF PCEF Gy Gz Offline Charging System Gateway (OFCS) 27
  28. 28. Diameter Routing Agent - DRA  Diameter is extensively used as an AAA protocol in the DB, charging, and policy domains of EPC and contributes to majority of signaling traffic load in the 4G networks.  Scalability demands multiple PCRF(s)/HSS(s) and Charging  DRA helps with routing, load balancing and session management of traffic flowing between these Diameter entities.  DRA ensures:  all Diameter sessions established for a given EPS connection reach the same PCRF when multiple and separately addressable PCRFs have been deployed in a Diameter realm  A DRA can also incorporate SLF functionality to locate HSS for a IMS UE when multiple HSSs are deployed.  A DRA can be implemented as a re-direct or a proxy agent. 28
  29. 29. DRA Deployment Architecture 29
  30. 30. Diameter Signaling Flows - IMS CallSetup (without DRA) 30
  31. 31. Diameter Signaling Flows – Proxy DRA 31
  32. 32. Poll Question #2  How do you see the opportunity for Software Defined Networks (SDN) in your organization? a. Revolutionizes how we architect our networks b. Has real potential but SDN needs to mature as a technology before it will be of use in a live network c. Interesting for some niche functions within the network but will be restricted to a limited set of element types d. Irrelevant as we are already able to manage networks in a way that suites our needs 32
  33. 33. What is a Software Defined Network?  There are two commonly accepted defining attributes of a Software Defined Network (SDN): • Decouples network management elements from the packet forwarding entities. Network intelligence & supporting protocols are maintained independently of the network nodes which actually handle the through traffic. • Provides an API so that application developers can have their own applications directly configure that part of the overall network infrastructure which delivers packets on their behalf.  Although not part of the ‘common definitions’ the abstraction of the various network elements down into a single virtual switch is seen as an important benefit of a SDN. 33
  34. 34. Why All the Excitement?  Possibility for single virtual switch/router image • Facilitates rapid and consistent deployment of new rules across the entire network  Independence to go beyond vendor provided features • Network architects can leverage more of the capabilities of the underlying hardware elements in their network  Promotes innovation • Separation of function allows both network element hardware and switch management suite vendors to break into the market  Allows applications control over their network • Applications get similar control over their ‘virtual slice’ of the network as they have over their virtual server environment 34
  35. 35. Challenges in growing SDN intoCarrier Networks  Topology Management • Most of today’s SDN management s/w deals well with flat full mesh network infrastructures – not dynamic hierarchies.  Policy Policing • How to control how much network resources a management agent can reserve?  Security • How to prevent the creation of illicit portals? • How can a network entity spot a rogue rule?  Traffic Management • While good at creating traffic flow classification rules not so good at defining traffic scheduling characteristics 35
  36. 36. Opportunities De-coupled control & data plane • allows for independent network scaling Standardise network management strategy • while keep flexible hardware choices Allows innovative network appliances to be created • Powerful APIs open up market to much wider developer pool • Applications with integrated control over their network can deliver better services • Provides opportunity to support the less common (or even proprietary) routing/forwarding protocols on Common Off The Shelf (COTS) network devices 36
  37. 37. Basic Model of a Network Appliance New packets arriving enable additional detail to be extracted from flow …approx 10% packets HTTP GMAIL Metadata …Username …Email titleServer Load Open Flow …Content State Machine User Application API Add new entry by default… Application adds …or wait for application Buffered table entry & rule Packets Apply Rule e.g. put into correct priority queue 37
  38. 38. Summary Slide  KW to create  MRF covered in webinar 3 38
  39. 39. Q&A  Contact us! Karl Wale Prashant Sharma karl.wale@radisys.com prashant.sharma@radisys.com James Radley Dikshit Sawhney james.radley@radisys.com dikshit.sawhney@radisys.com ~Please fill out our short survey~ THANK YOU FOR ATTENDING! To register for upcoming webinars: http://go.radisys.com/optimizing.html 39

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