Auto-IP traffic optimization in mobile telecommunications systems

• US 20050041584A1
• Filed: 08/13/2004
• Published: 02/24/2005
• Est. Priority Date: 08/14/2003
• Status: Active Grant

• Current Assignee: Telcordia Technologies Incorporated (Telefonaktiebolaget LM Ericsson)
• Original Assignee: Telcordia Technologies Incorporated (Telefonaktiebolaget LM Ericsson)
• Inventors: Siegell, Bruce, Lau, Richard
• Granted Patent: US 7,466,652 B2
• Time in Patent Office: Days
• US Class Current: 370/235
• CPC Class Codes: H04L 41/0866 Checking the configuration
• CPC Class Codes: H04L 41/0893 Assignment of logical groups to network elements
• CPC Class Codes: H04L 41/0894 Policy-based network configuration management
• CPC Class Codes: H04L 41/5003 Managing SLA; Interaction between SLA and QoS
• CPC Class Codes: H04L 47/10 Flow control; Congestion control
• CPC Class Codes: H04L 47/193 at the transport layer, e.g. TCP related
• CPC Class Codes: H04L 47/20 Traffic policing
• CPC Class Codes: H04L 47/22 Traffic shaping
• CPC Class Codes: H04L 47/2416 Real-time traffic
• CPC Class Codes: H04L 47/27 Evaluation or update of window size, e.g. using information derived from acknowledged [ACK] packets
• CPC Class Codes: H04W 24/02 Arrangements for optimising operational condition
• CPC Class Codes: H04W 28/02 Traffic management, e.g. flow control or congestion control
• CPC Class Codes: H04W 8/18 Processing of user or subscriber data, e.g. subscribed services, user preferences or user profiles; Transfer of user or subscriber data

Abstract

A system and method for the implementation of fine-grained quality of service in a mobile telecommunications environment uses an Auto-IP Policy Decision Point (PDP) to determine what traffic optimizations actions should be taken in reaction to various network conditions. The Auto-IP PDP uses as inputs information from a G_b interface probe to determine the user identification of an IP data flow, information from the radio access network (RAN) network management system (NMS) regarding network congestion. The cell traffic information is passed onto a traffic analysis and processing engine, the Auto-IP PDP which maps the real-time traffic information into an n-dimensional traffic model. An automated policy decision guiding algorithm is executed on the n-dimensional traffic model and selects policy based on the traffic and cell congestion conditions, without human intervention. Additionally, a consistency check is performed to ensure that new policies are consistent with existing policies. The policy decision outcome is forwarded to the Auto-IP Traffic Optimizer that acts on the network at a point in the network (G_i) that is different from where traffic problem occurs in the RAN. The Auto-IP Traffic Optimizer implements the decisions of the Auto IP-PDP by performing traffic shaping, TCP window clamping or other traffic optimization procedures on a cell-by-cell basis.

Claims

1. In a mobile telecommunications network in which a plurality of mobile stations communicate through a radio access network (RAN) through a network having at least one Serving GPRS Support Node (SGSN) and at least one Gateway GPRS Support Node (GGSN) through the Internet to a plurality of servers, a system for the automatic optimization of traffic comprising:

one or more G_b probes for extracting information from the interface between the RAN and the SGSN including the identity of each user associated with a specific data flow;

a network management system (NMS) for providing congestion and traffic information from the RAN;

a customer database for providing information regarding the type and quality of service for each user of a mobile station;

a policy decision point wherein information from the G_b probes, the NMS and the customer database is used to determine actions to be taken to optimize traffic for each data flow on a cell-by-cell basis; and

,

a traffic optimizer for implementing the actions determined by the policy decision point.

2. The system of claim 1 further comprising an IP probe for providing information regarding delay in the Internet which information if provided to the policy decision point.

3. The system of claim 1 wherein the policy decision point comprises a means for automatically generating a policy decision based on a finite state machine that automatically determines an action to be taken depending on the information received regarding the state of the network.

4. The system of claim 1 wherein the policy decision point further comprises a means for checking the consistency of new policies with existing policies.

5. The system of claim 4 wherein an alarm is raised to the user of the policy decision point in cases where a new policy is identified as inconsistent with an existing policy.

6. The system of claim 1 wherein the traffic optimizer separates traffic arriving from the Internet into components identified by the identity of the cell in the RAN through which the traffic will pass.

7. The system of claim 4 wherein the separated traffic is optimized on a cell-by-cell basis using an optimization technique selected from the group consisting of:

TCP window clamping, admission control mechanisms, compression, TCP ACK spacing, local TCP acknowledgements, IP Traffic shaping and local TCP retransmissions.

8. The system of claim 1 wherein the traffic optimizer is located at the G_o interface.

9. The system of claim 1 wherein the Home Location Register (HLR) provides additional information regarding the user of mobile stations in the network.

10. The system of claim 1 wherein the policy decision point is implemented in an Intelligent Service Control Point (ISCP).

12. The method of claim 10 further comprising the step of collecting data from one or more IP probes regarding delay in the Internet and inputting said collected data into the policy decision point.

11. A method for automatic optimization of traffic flow between users of mobile stations and servers connected through a radio access network (RAN), a packet-based core network and the Internet comprising the steps of:

extracting information from the interface between the RAN and the packet-based network including the identity of each user associated with a specific traffic flow;

collecting information from a network management system (NMS) regarding congestion and traffic information from the RAN;

retrieving data from a customer database regarding the type and quality of service for each user of a mobile station;

inputting the extracted RAN information, collected NMS information, and retrieved customer data into a policy decision point;

determining at the policy decision point what actions are to be taken to optimize traffic for each data flow; and

,

sending the actions to a traffic optimizer to implement the actions on a cell-by-cell basis.

13. The method of claim 11 wherein the step of determining the actions to be taken further comprises the use of a finite state machine to automatically determine which actions are necessary to move from an unacceptable state to an acceptable state or from a sub-optimal state to an acceptable state.

14. The method of claim 11 wherein the step of determining the actions to be taken further comprises checking the consistency of new policies with existing policies.

15. The method of claim 14 wherein the step of checking the consistency further comprises the step of raising an alarm to the user of the policy decision point in cases where a new policy is identified as inconsistent with an existing policy.

16. The method of claim 11 further comprising the step of separating traffic arriving from the Internet at the traffic optimizer into components identified by the identity of the cell in the RAN through which the traffic will pass.

17. The method of claim 16 wherein the separated traffic is optimized on a cell-by-cell basis using an optimization technique selected from the group consisting of:

TCP window clamping, admission control mechanisms, compression, TCP ACK spacing, local TCP acknowledgements, IP Traffic shaping and local TCP retransmissions.