Network stochastic cross-layer optimization for meeting traffic flow availability target at minimum cost

A system comprising a computer readable medium storing processor executable instructions and a least one processor, wherein execution of the processor executable instructions cause the at least one processor to:

• generate a minimum monetary cost network model capable of satisfying a traffic demand and responsive to a set of variables each defining one of a network cost, a physical layer feature, or a logical layer feature, a set of constraints defining a relationship between at least two variables from the set of variables, and an objective to reduce the monetary cost of a network defined by the minimum monetary cost network model;
• generate an optimization set of network failures Fo;
• iteratively, until the current minimum monetary cost network satisfies the traffic demands given a random set of failures FR:
• update the minimum monetary cost network model capable of satisfying the traffic demand given Fo and generated responsive to the set of variables, the set of constraints, and the objective to reduce the monetary cost of the network;
• generate a random set of failures FR;
• determine whether the minimum cost monetary network model satisfies the traffic demand given FR;
• in response to determining that the minimum cost network does not satisfy the traffic demands given FR, select a subset of failures from FR and add the subset of failures from FR to FO;
• and
• in response to determining that the minimum cost network satisfies the traffic demands given FR, output the current minimum cost network model.

A computer readable medium storing processor executable instructions thereon, wherein execution of the processor executable instructions cause a processor to:

• generate a minimum monetary cost network model capable of satisfying a traffic demand and responsive to a set of variables each defining one of a network cost, a physical layer feature, or a logical layer feature, a set of constraints defining a relationship between at least two variables from the set of variables, and an objective to reduce the monetary cost of a network defined by the minimum monetary cost network model;
• generate an optimization set of network failures Fo;
• iteratively, until the current minimum monetary cost network satisfies the traffic demands given a random set of failures FR:
• update the minimum monetary cost network model capable of satisfying the traffic demand given Fo and generated responsive to the set of variables, the set of constraints, and the objective to reduce the monetary cost of the network;
• generate a random set of failures FR;
• determine whether the minimum cost monetary network model satisfies the traffic demand given FR;
• in response to determining that the minimum cost network does not satisfy the traffic demands given FR, select a subset of failures from FR and add the subset of failures from FR to FO;
• and
• in response to determining that the minimum cost network satisfies the traffic demands given FR, output the current minimum cost network model.

A method for designing a network, the method comprising:

• receiving a set of optimization network failures Fo, an occurrence probability for each of the failures in Fo, and a target availability for each of a plurality of flows;
• generating a minimum monetary cost network model capable of satisfying a traffic demand responsive to a long-term capacity requirement of the minimum cost network model;
• iteratively, until a probability of each of the plurality of flows being satisfied across each of the failures in Fo is greater than the respective target availability for each of the plurality of flows:
• updating the minimum monetary cost network model responsive to a short-term capacity requirement of the minimum cost network model given each of the failures in Fo;
• and
• calculating the probability of each of the plurality of flows being satisfied across each of the failures in Fo.