managing lte ip transport networks with route · pdf filemanaging lte ip transport networks...

WHITE PAPER
Managing LTE IP Transport Networks with Route Analytics

Copyright 2014, Packet DesignPage 2 of 13
Table of Contents
Executive Summary 3
LTE Core and Backhaul Transport Architectures 4
Why IP Networks Are Inherently Unpredictable 4
Traditional Network ManagementMany Points of View, No Big Picture 5
Route AnalyticsSeeing the Network from the Routers Point of View 6
Improving LTE Network Management with Route Analytics 7
Conclusion 10

Executive Summary
Mobile operators today confront a major evolution in their network architecture, service traffic, and economics. The explosion of smartphones, tablets and High Speed Packet Access (HSPA) mobile broadband traffic has driven the roll-out of Long Term Evolution (LTE) based on 3GPP standards. While mobile operators have relied for years on IP/MPLS networks for their mobile core backbone communications, LTE is driving a significant transformation of many mobile backhaul networks from statically engineered ATM over SONET architectures to Layer 3 IP/MPLS networks, particularly in the aggregation or High Radio Access Network (HRAN) layer. While the precise nature of this transformation varies dramatically depending on the legacy network assets and services, theres no question that the evolution to IP/MPLS requires a new approach to network Operations and Management (OAM).
An inherent OAM challenge of IP is its dynamic nature. Unlike circuit-based TDM network architectures of the past, IP networks can continuously and automatically reroute traffic paths around link failures and other changes in the network infrastructure. The result is an intelligent but unpredictable network topology that can not only cause delays to sensitive voice and broadband traffic, but also make management visibility and operational processes much more challenging. Traditional network management tools dont provide visibility into IP network dynamics, without which it is difficult to reduce OPEX Key Performance Indicators (KPIs) such as Mean Time to Detection (MTTD) and Mean Time to Repair (MTTR). In addition, lack of insight into dynamic network behavior impedes accurate maintenance and capacity planning, leading to costly operations errors and CAPEX waste.
Route analytics technology, which taps into the networks live routing protocol control plane to provide real-time, network-wide insight of the operational routing topology and the traffic flowing across all network paths and links, is a key OAM technology for LTE mobile core and backhaul IP networks. Deployed by hundreds of telecom and mobile operators today, route analytics transforms IP/MPLS network management processes, helping engineering and operations teams deliver optimal service performance, speed problem resolution, strengthen change management processes, proactively uncover network vulnerabilities, increase capacity planning efficiency and ensure network and service resilience.
Effective integration of route analytics within the LTE mobile core and backhaul IP/MPLS network OAM portfolio can help mobile operators ensure higher service quality, leading to lower subscriber churn and reacquisition costs while reducing IP network OPEX and CAPEX.

LTE Core and Backhaul Transport Architectures
Long Term Evolution (LTE) and System Architecture Evolution (SAE) as defined by the Third-Generation Partnership Project (3GPP) introduced significant architectural changes to mobile operator networks. Of greatest interest to those responsible for deploying and managing the underlying transport is the fact that unlike previous standards, LTE and SAE together introduce a completely IP-based communications paradigm: Evolved Packet System (EPS). EPS employs an IP-based Bearer concept, essentially IP packet flows with defined Quality of Service (QoS), as the communications channel between handsets and tablets (the User Equipment or UE in 3GPP parlance) and the Internet via core network (CN) gateways (see Figure 1).
Figure 1: System Architecture Evolution/Evolved Packet Core (source: 4G Americas)
3G Mobile operators have for years operated IP/MPLS VPN backbone networks to interconnect their core nodes. With the onset of LTE, the much larger metro area backhaul networks that transport traffic from eNodeB cell sites must transform to handle IP traffic flows. Some mobile operators are choosing to utilize IP-friendly Layer 2 networks based on carrier Ethernet for backhaul transport, but for most operators IP/MPLS networks will be the transport network architecture of choice for LTE backhaul.
There are a number of different approaches to designing these IP/MPLS backhaul networks. For example, due to the need to accommodate legacy ATM transport of 2.5G and 3G traffic, some operators are using point-to-point MPLS Layer 2 VPN tunnels to transport backhaul traffic between eNodeB sites and core gateways. Others are choosing to utilize Layer 3 VPNs in the backhaul networks. While there are many architectural variants of IP/MPLS backhaul networks, they all must offer a high degree of resilience via

router, link and path redundancy, as well as automated traffic re-routing around failures via standards-based OSPF or IS-IS protocols. In some cases, mobile operators will additionally implement MPLS Traffic Engineering (TE) via RSVP-TE tunnels to ensure bandwidth availability and fast re-route (FRR) for failure recovery. Given the size and the complexity of these networks, it is critical that mobile operators possess strong OAM capabilities based on next-generation technologies and tools that can address the dynamic nature of IP/MPLS networks and also provide visibility into their Layer 2 VPN tunnels.
Why IP Networks Are Inherently Unpredictable
LTE is just the latest example of the convergence of all types of communication over IP. A major reason that IP became the de facto worldwide standard for data communications networks is its automated resiliency based on intelligent IP routing protocols that control the traffic routing topology. But while IPs distributed routing intelligence makes it efficient and resilient, it also makes IP network behavior unpredictable and harder to manage. IP routing protocols automatically calculate traffic routes or paths from any point to any other point in the network based on the latest known state of network elements. Any change to those elements causes the routing topology to be recalculated dynamically. While this means highly resilient traffic delivery with low administrative overhead, it also creates endless variability in the active routing topology. Large networks with many redundant links can be in any one of millions of possible active routing topology states, which makes it much harder to understand and manage how traffic will be delivered (see Figure 2).
The lack of network management visibility into dynamic network behavior can be seen in the time-consuming process of correlating service problems to non device-specific network causes. For example, when a user reports a service performance problem that doesnt stem from an obvious hardware failure, pinpointing the root cause can be quite difficult because in a large, complex IP network, IT engineers have no way to know the route the traffic took through the network, the relevant links servicing the traffic, whether those links were congested at the time of the problem or even which devices were servicing the traffic. Without understanding these factors, troubleshooting processes become slow, inefficient guesswork games played by highly paid escalation engineers, increasing MTTR and raising OPEX. Change management processes suffer from the same problem, since engineers making planned configuration changes in the network have little or no idea of how the network-wide routing and traffic delivery behavior will change once the configuration change is made. This can lead to higher OPEX because changes must be rolled back or corrected, impacting service reliability and customer satisfaction.

Figure 2: The dynamic nature of IP routing presents a mathematically daunting challenge to network management. In the illustrated network above, there are only 4 core routers and 5 edge routers. If one assumes that traffic only enters the network from the edges, the routed topology (combination of routed paths) can be in any one of 55 (3,125) possible states, or 53 (125) probable states. As a network expands and the number of interconnected routers grows, the complexity of understanding the networks behavior increases exponentially.
For relatively non-critical applications like email and web browsing, the impact of routing and traffic changes may be slight, but for mobile voice, SMS, data services, interactive gaming, and streaming media, which have sensitive latency requirements, the impact can be dire.
Next-generation OAM approaches are needed to manage IP network unpredictability, prevent and mitigate the service impacts of routing and traffic changes, and lower costs.
Traditional Network ManagementMany Points of View, No Big Picture
Network managements purpose is to overcome the complexity inherent in a large network and provide better visibility to network operations and engineering. The overarching architectural principle of todays network management is to gather information on a vast number of different points in th

managing lte ip transport networks with route · pdf filemanaging lte ip transport networks...

Documents