Multiplexing and congestion control

1. A method for managing traffic congestion in a network, the method comprising:

obtaining parameters of the network at a network management server;

modeling traffic for a group of flows in the network based on the parameters to generate a model of the traffic including model flows, the modeling being performed by the network management server;

controlling an operational condition of the network to manage the traffic congestion in accordance with the model by generating traffic instructions at the network management server for combining selected flows of the group of flows based on the model flows, a probability of traffic, available bandwidth and a predicted bandwidth, and based on a congestion factor, wherein the congestion factor is a policy parameter for how close to full capacity a channel is to be loaded; and

adding priority information into the selected flows to indicate a priority of transmitting to be followed by network devices, wherein the priority information causes a network device to delay transmission of a first packet from a combined traffic flow and causes the network device to queue the first packet behind a second packet of the combined traffic flow.

2. The method of claim 1 , comprising reducing packet processing overhead by reducing a number of packets having control information to be analyzed, wherein reducing of the packet processing overhead includes aggregating independent packets of the group of flows during the combining of the selected flows, wherein the modeling of the traffic is based on utilizing Fourier transforms.

3. The method of claim 2 , wherein the control information includes address information and quality of service information.

4. The method of claim 1 , comprising transmitting the traffic instructions from the network management servers to one or more network elements for adjusting routing to combine the selected flows, wherein the selected flows are limited to a same layer of the network.

5. The method of claim 1 , further comprising estimating the model flows utilizing an estimation process selected from the group consisting of ad hoc determination, sampling, feedback controls, or combinations thereof.

6. The method of claim 1 , wherein the modeling of the traffic is based on probability waves, wherein a height of each of the probability waves at time t is equal to the probability of traffic, P(t) at the time t, and wherein the selected flows are chosen based on the corresponding probability waves of the selected flows when combined approximating a square wave.

7. The method of claim 6 , wherein the combining of the selected flows is based on using a formula B′=ΣBP i (t)≦B(1−ε), where ε is the congestion factor, wherein a probability wave of flow i is P i (t), wherein B is the available bandwidth, and wherein B′ is a predicted bandwidth.

8. The method of claim 1 , further comprising:

selecting the flows to be combined such that the resulting combination waveforms are characterized by a relation Pa(t)+Pb(t)=X, where Pa is the probability wave for flow a, Pb is the probability wave for flow b, and X is the probability of traffic, wherein the probability of traffic can be greater than 1, corresponding to a defined overbooking level.

9. The method of claim 1 , wherein the combining of the selected flows comprises selecting flows of the group of flows to avoid beat frequencies.

10. A server for managing traffic congestion in a network, the server comprising:

a memory storing computer instructions; and

a processor in communication with the memory, wherein the processor, responsive to executing the computer instructions performs operations comprising:

modeling traffic for a group of flows in the network based on parameters of the network to generate a model of the traffic including model flows;

generating traffic instructions to manage the traffic congestion in accordance with the model,

wherein the traffic instructions include combining selected flows of the group of flows based on the model flows, a probability of traffic, available bandwidth and a predicted bandwidth, and based on a congestion factor, wherein the congestion factor is a policy parameter for how close to full capacity a channel is to be loaded, and

wherein the traffic instructions include aggregating independent packets of the group of flows during the combining of the selected flows thereby reducing packet processing overhead by reducing a number of packets having control information to be analyzed; and

adding priority information into the selected flows to indicate a priority of transmitting to be followed by network devices, wherein the priority information causes a network device to delay transmission of a first packet from a combined traffic flow and causes the network device to queue the first packet behind a second packet of the combined traffic flow.

11. The server of claim 10 , wherein the modeling of the traffic is based on utilizing Fourier transforms.

12. The server of claim 10 , wherein the processor, responsive to executing the computer instructions performs operations comprising: transmitting the traffic instructions to one or more network elements for the combining of the selected flows and for the aggregating of the independent packets.

13. The server of claim 10 , wherein the combining of the selected flows comprises selecting flows of the group of flows having a same wavelength or harmonics of the same wavelength.

14. The server of claim 10 , wherein the modeling of the traffic is based on probability waves, wherein a height of each of the probability waves at time t is equal to the probability of traffic, P(t) at the time t, and wherein the selected flows are chosen based on the corresponding probability waves of the selected flows when combined approximating a square wave.

15. The server of claim 14 , wherein the combining of the selected flows is based on using a formula B′=ΣBP i (t)≦B(1−ε), where ε is the congestion factor, wherein a probability wave of flow i is P i (t), wherein B is the available bandwidth, and wherein B′ is a predicted bandwidth.

16. A non-transitory computer-readable storage medium comprising computer instructions, which, responsive to being executed by a processor of a network management server, cause the processor to perform operations comprising:

obtaining parameters of the network;

modeling traffic for a group of flows in the network based on the parameters to generate a model of the traffic including model flows;

controlling an operational condition of the network to manage the traffic congestion in accordance with the model by generating traffic instructions at the network management server for combining selected flows of the group of flows based on the model flows, a probability of traffic, available bandwidth and a predicted bandwidth, and based on a congestion factor, wherein the congestion factor is a policy parameter for how close to full capacity a channel is to be loaded; and

adding priority information into the selected flows to indicate a priority of transmitting to be followed by network devices, wherein the priority information causes a network device to delay transmission of a first packet from a combined traffic flow and causes the network device to queue the first packet behind a second packet of the combined traffic flow.

17. The non-transitory computer-readable storage medium of claim 16 , wherein the generating of the model traffic flows is based on utilizing Fourier transforms.

18. The non-transitory computer-readable storage medium of claim 16 , wherein the combining of the selected flows comprises at least one of: selecting flows of the group of flows having a same wavelength or harmonics of the same wavelength, or selecting flows of the group of flows to avoid beat frequencies.