Internet DRAFT - draft-deng-ippm-wireless
draft-deng-ippm-wireless
IPPM L. Deng
Internet-Draft Z. Cao
Intended status: Informational China Mobile
Expires: August 16, 2014 February 12, 2014
Problem Statement for IP measurement in mobile networks
draft-deng-ippm-wireless-01.txt
Abstract
This document analyzes the potential problems of applying existing
IP-based performance measurement methods to wireless accessing
environments. It suggests that a more flexible passive measuring
framework and performance metrics, such as congestion ratio are
needed.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Motivation . . . . . . . . . . . . . . . . . . . . . . . . . 3
2.1. Dynamic Load Balancing . . . . . . . . . . . . . . . . . 3
2.2. Radio Congestion Detection . . . . . . . . . . . . . . . 4
2.3. Accurate Troubleshooting . . . . . . . . . . . . . . . . 5
2.4. Summary . . . . . . . . . . . . . . . . . . . . . . . . . 6
3. Further Considerations . . . . . . . . . . . . . . . . . . . 7
3.1. Congestion ratio metric . . . . . . . . . . . . . . . . . 7
3.2. Multi-hop Measurement Framework . . . . . . . . . . . . . 7
4. Security Considerations . . . . . . . . . . . . . . . . . . . 7
5. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 7
6. References . . . . . . . . . . . . . . . . . . . . . . . . . 8
6.1. Normative References . . . . . . . . . . . . . . . . . . 8
6.2. Informative References . . . . . . . . . . . . . . . . . 8
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 8
1. Introduction
It is well-accepted that mobile Internet usage is going to increase
fast in the coming years and replace the traditional voice service to
be the dominant revenue source for mobile operators. In the
meantime, fast evolving network and terminal technologies and
changing service trend (e.g. social networking, video on demand,
online reading, etc.) results in higher user service requirement.
Therefore, as the basic infrastructure service provider, operators are
deemed responsible for mobile Internet end-to-end performance, for
subscribers want to get what they want, which gives rise to a basic
yet important question: how does network service provider manage end-
to-end service quality? In particular, there are two goals for
operator's quality management initiative:
o to make sure and validate the QoS metrics of specific IP flows
against the values pre-defined by the service SLA(Service Level
Agreement) from the user/service provider's point of view; and
o to make sure and validate the sanity of network devices/links.
In this draft, we present three usecases and the potential problems
of applying existing IP-based performance measurement methods to
wireless accessing environments, where resource pooling and dynamic
load balancing techniques are employed to accommodate explosively
increasing data traffic, and suggest requirements for more robust
passive measuring methods and performance metrics for such
environment.
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2. Motivation
2.1. Dynamic Load Balancing
Pooling technology has been introduced to the user plane in the
packet switched domain of operator's core network for cellular
subscribers since 3GPP Release 5 (3GPP TS23.236). With pooling, the
traffic path from user equipments to the Internet via core network
is not static, but rather dynamically assigned to a proper instance
of an device pool, according to load balancing policies. The
assignment is dynamically made at the time of user equipment's
attachment establishment with the cellular core network, and would
remain unchanged unless the mobile terminal detaches from the network
or moves outside the base-stations' coverage subordinating to the
specific core network's device pool.
As shown by Figure 1, potential device pools along the path all the
way from the user terminal via the packet switching domain of the
mobile network core to a third party service provider over the
Internet. Examples of network devices that can be poolized
include SGSN(Serving GPRS Support Node) and GGSN(Gateway GPRS
Supporting Node). Moreover, the service provider could also
implement load balancing on the server's side either via server-
pooling within a data center or via (third party) CDN nodes.
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Radio |Packet |Internet
Access |Switching |
Network |Core Network |
| +--------+ +----+---+ +--------+
| |+------+| |+------+| |+------+|
| +-->|SGSN_1|+------->|GGSN_1|+--+ ||SERV_1||
| | |+------+| |+------+| | |+------+|
+--+ +--+--+ +-----+ | | | | | | | |
| |---->| +--->| +--+ |+------+| |+------+| | |+------+|
|UE| |NodeB| | RNC | ||SGSN_2|| ||GGSN_2|| +---->|SERV_2||
| |....>| |...>| |... |+------+| |+------+| |+------+|
+--+ +--+--+ +-----+ . | | | | | |
| . | ... | | ... | | ... |
| . |+------+| |+------+| |+------+|
+--------------------+ ...>|SGSN_N|........>|GGSN_M|........>|SERV_K||
| Injected Traffic | |+------+| |+------+| |+------+|
| ---------------> | +--------+ +----+---+ +--------+
| Actual Traffic | |
| ...............> | |
+--------------------+
Figure 1: Active Measuring Traffic versus Actual Traffic in case of
Device Pooling
Hence, under such environments, if active performance measurement
methods[RFC4656][RFC5357] are employed, the injected bogus data
traffic may traverse along a different path to the one used by the
targeted traffic or even interfere with them due to the subtle nature
of wireless-involved links (as explained in the next subsection).
2.2. Radio Congestion Detection
Mobile Internet usage is going to increase fast in the coming years
due to the following facts: on one hand, as a result of pervasively
deployed and fast maturing 3G/4G cellular technologies combined with
smartphone's dominance in mobile handset's market, Internet data
traffic via mobile operator's packet switched core network manifests
to be an increasingly important contributor to the operator's
revenue. On the other hand, wireless technologies (such as Wi-Fi
through APs or cellular networks through small cells) are more and
more accepted by the end users, either at home, in the office or in a
public place, to be carrying the "last mile" to various portable
personal computing devices.
There are two common features of the above two scenarios:
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o the combination of both wireless and wired links along the end-to-
end traffic path, and
o almost all the time, the wireless "last mile" would be the
bottleneck of end-to-end service quality.
To make more efficient use of relatively more scarce radio resources,
it is important for the core network to understand the congestion
status of both wireless and wired links along the traffic path, and
make proper management of data traffic through cell reselection or
load balancing via pooling.
However, the wireless link's thoughput is consistently subject to
other interfering factors (e.g. distance to the nearest base
station, terminal's radio signal strength, random interference,
shadowing of buildings, multipath fading, etc.), which should be
properly filtered out before handing over to the network management,
as they are rooted in terminal mobility and outside the realm of
mobile accessing network.
In other words, there is considerable gap between IP measurement
results to the performance evaluation and fault detection
requirements in mobile-involved environment, if we directly employ
existing passive performance measurement
methods[I-D.draft-chen-ippm-coloring-based-ipfpm-framework].
2.3. Accurate Troubleshooting
As shown in Figure 2, it is quite common that there are path
partitions (belonging to different operation and management
departments) along the local data path from the UE to the Internet
within an mobile operator's local network. For large operators,
employing layered network operation and management architecture based
on geographic partitions, there may be a further more subpath
partitioning between local IP backhaul (managed by state
sub-ordinaries) and national IP backhaul (managed by header quarters).
Moreover, for roaming cases under home-routed mode (meaning all the
traffic from a roaming UE would first traverse from the visited ISP
and potentially another Internet operator before getting back to
homing ISP network.
Take the example of a mobile subscriber getting access from a 3GPP
network for example, besides a local mobile network operator,
intermediary ISPs may exist between its traffic before it reaches the
Internet. Moreover, within the local operator's network, radio
access network (RAN), RAN backhaul and local core network could
actually be constructed and managed by stuff from different
departments, for they mainly come from different technical
background.
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In such complex situations, it can become frustrating to respond
quickly to a simple UoE complaint, due to the exponentially exploded
complexity to accurately locate the potential faults/congestion in a
transient wireless-involved end2end data path.
On the other hand, tunnels, including GRE [RFC2784], GTP [TS29.060],
IP-in-IP [RFC2003] or IPSec [RFC4301] etc, are widely deployed in
3GPP networks. And in 3GPP network tunnels are used to carry end
user flows within the backhaul network. Tunnels brings another
complexity in realizing effective troubleshooting using end2end
passive methods.
\\|/
|
|
+-|---+ +------+ +------+ +------+
+--+ | | Tunnel1 | | Tunnel2 | | Ext | |
|UE|-(RAN)-| eNB |===========| S-GW |=========| P-GW |--------| SP |
+--+ | | RAN | | Core | |Network | |
+-+---+ Backhaul +---+--+ Network +---+--+ +---+--+
Figure 2: Example of path partition in 3GPP network
In other words, a flexible passive measurement framework, capable of
dynamic troubleshooting for partitioned data link, even in case of
tunnels or autonomous entities is highly valuable. However, neither
current active measurement framework as used by OWAMP[RFC4656]/
TWAMP[RFC5357], nor the passive framework proposed in
[I-D.draft-chen-ippm-coloring-based-ipfpm-framework] could fit in
such case.
2.4. Summary
In summary, for mobile-ended data paths, we believe there is need for
o viable passive measurement framework for active measurements
inject extra traffic, which may traverse along a different path to
the one used by the targeted traffic or even interfere with them.
o robust metric against transient wireless conditions, as there is
considerable gap between existing IP measurement metrics (e.g.
delay, jitter, throughput etc.), which are subject to change
caused by external environmental factors and of little use to
operator's traffic management from the network side.
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o flexible and trustworthy measurement mechanisms for accurate
performance monitory and troubleshooting from multi-hop data link
across operation boundaries.
3. Further Considerations
3.1. Congestion ratio metric
ECN signal for congestion measurement are signalled at IP header by
intermediary devices before actual congestion occurs, which is
expected to be an effective indicator to potential QoE degradation,
irrespective to traffic pattern/wireless conditions.
[I-D.draft-hedin-ippm-type-p-monitor] proposes to echo ECN-flags into
TWAMP-test feedback for active measurement. While, packet-level
echoing is not viable in passive framework, it is also suspected that
more meaningful aggregated information (such as congestion extent,
defined as the ratio of marked packets versus all packets from a
given IP flow) would be preferred.
3.2. Multi-hop Measurement Framework
In current active measurement framework, there is only two entities
on the data path, the sender and the reflector. Hence it is not
straightforward how to apply this framework to an integral multi-hop
passive measurement case.
On the other hand, the centralized multi-hop passive framework
proposed in [I-D.draft-chen-ippm-coloring-based-ipfpm-framework]
could encounter problems when there is no prior knowledge about or
control over different partitions along the overall data path. In
other words, path discovery mechanism is needed to identify potential
measurement nodes along the way during/before the actual passive
measurement.
4. Security Considerations
If measurements nodes from different operational domains are used,
proper device authentication and report authenticity protection
mechanisms should also be considered in a complete interworking-
capable solution.
5. IANA Considerations
None.
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6. References
6.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119, March 1997.
[RFC2234] Crocker, D., Ed. and P. Overell, "Augmented BNF for Syntax
Specifications: ABNF", RFC 2234, November 1997.
6.2. Informative References
[I-D.draft-chen-ippm-coloring-based-ipfpm-framework]
Chen, M., Liu, H., Yin, Y., Papneja, R., Abhyankar, S.,
and G. Deng, "Coloring based IP Flow Performance
Measurement Framework", draft-chen-ippm-coloring-based-
ipfpm-framework-01 (work in progress), October 2013.
[I-D.draft-hedin-ippm-type-p-monitor]
Hedin, J., Mirsky, G., and S. Baillargeon, "Differentiated
Service Code Point and Explicit Congestion Notification
Monitoring in Two-Way Active Measurement Protocol
(TWAMP)", draft-hedin-ippm-type-p-monitor-02 (work in
progress), October 2013.
[RFC4656] Shalunov, S., Teitelbaum, B., Karp, A., Boote, J., and M.
Zekauskas, "A One-way Active Measurement Protocol
(OWAMP)", RFC 4656, September 2006.
[RFC5357] Hedayat, K., Krzanowski, R., Morton, A., Yum, K., and J.
Babiarz, "A Two-Way Active Measurement Protocol (TWAMP)",
RFC 5357, October 2008.
Authors' Addresses
Lingli Deng
China Mobile
Email: denglingli@chinamobile.com
Zhen Cao
China Mobile
Email: caozhen@chinamobile.com
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