Pipeline Publishing, Volume 5, Issue 4

	This Month's Issue:
	Enabling Innovation

Proactive Device Problem Resolution

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improve the customer experience of smartphone device early adopters. Measuring latency at the edge of the mobile network before packets enter the internet acts as a demarcation point to assist in root cause problem determination.

These KPIs indicate TCP connection creation latency (TCP Access RTT) or TCP packet delivery latency (TCP Data RTT). Both are indicators that are useful in indicating potential smartphone device and transmission path performance problems. The separation of the uplink and downlink KPIs allows identification of the problem areas either in transmission path of the Mobile Data Network or the smartphone device.

By aggregating the per-session TCP latency for a smartphone device to various service delivery components (Devices, Cell Sites, NEs, APNs, Application servers ...), the mobile operator can determine which service delivery components require immediate attention.

Measuring latency on every session is critical to verifying session quality. Proactively isolating quality problems for high value smartphone device early adopter subscribers differentiates high value service providers providing significant added value and revenues.

Service Drop Detection

Service providers that perform up to the user expectations of their valued smartphone device early adopter customers monitor services to ensure they are not impacted by service drops. Existing solution providers trying to re-use legacy solutions built for voice applications utilize old architected solutions to monitor smartphone devices. The problem is these legacy systems only monitor the transport layer for network drops, which was very effective for fixed timeslot voice calls. With new always-on advanced data services, the transport layer could drop but have no effect on user satisfaction of the subscriber if the user wasn't actively transmitting data. Engineers utilizing these old voice dropped call troubleshooting solutions for data service monitoring end up "chasing their tails" and looking to resolve problems that are not customer experience impacting.

A new patent pending indicator allows the detection of the TCP connection drops during the active packet transfer. This type of drop impacts the user's perception of the smartphone device performance. This indicator does not detect TCP connection drops during TCP idle time, i.e. no packet transfer. The TCP Connection Drops KPI allows the detection of the session drops that are user impacting.

Customer experience impacting session drop indicators can be aggregated from per-session to various service delivery components (mobiles, Cells, NEs, APNs, Application servers...), and operators can detect the root cause of problematic smartphone devices.

Mobile service providers that proactively resolve statistically relevant packet loss problems increase user satisfaction.

New service assurance drop detection architecture is required for advanced data services utilizing DPI. Smartphone device monitoring requires not only the transport layer (L2) but also the data services transport layer (L4) and the application layer (L7). Having complete visibility to service affecting session drops is critical to assist in proactive problem resolution to enhance customer satisfaction and increase smartphone device adoption rates.

Service Type Classification

Service type classification with visibility down to the cell site and smartphone device level is critical to intelligently manage the bandwidth burden problem. By over subscribing bursty data traffic (SMS, email, web browsing) and understanding the amount of real-time sustained streaming sessions, service type classification allows mobile service providers to intelligently manage and plan transport build out.

These unique indicators allow the detection of the sustained TCP or UDP traffic based on TCP/UDP port utilization over time. These KPIs indicate which users and which cells have the most sustained traffic, thus the most potential impact on network performance. Furthermore, the end-user customer experience satisfaction levels need to be monitored end-to-end, not just individual device testing, since end-users rate end-to-end the complete user experience when evaluating the performance of a new device.

Customer experience of a smartphone device early adopter is significantly affected by delays in retransmissions, not freeing IP addresses properly, window size buffer problems, and on and on. Monitoring device KPIs coupled with end-to-end performance monitoring provides numerous views to assist the mobile operator proactively resolve problems. And with the total customer experience as the final verdict of customer satisfaction and crossing the chasm, network-wide end-to-end monitoring is required.

The Bottom Line: Profitable Revenues from Achieving Mass Market Approval

More often than not, the root cause of a problem that affects the customer experience of a valued early adopter may not be the device but a server they are accessing, network problems, or application issues, but without the ability to isolate the root cause component, the new smartphone device gets the blame. Therefore, without the proper OSS monitoring system, many new mobile broadband devices and services are destined to fall into the chasm.

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