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The design of large scale telecommunication networks is more than the technical allocation of capacity and path routing. By examining the design and allocation of resources in a broader sense, telecommunication network planning and management can better deliver value to the various stakeholders. This is significant especially when deploying networks in economically marginal areas such are rural, remote, or economically depressed regions. This paper presents a planning framework to systematically incorporate the influences, resources and decisions to effectively build or expand a network. Using a stake holders, input, process, output, customer approach, six key areas of society that derive value from better communication infrastructure in relatively unique manners were identified. These areas include healthcare, education, business, and others. The framework presented defines the inputs and outputs that accounts for the range of influences and outcomes in a network planning process. Inputs are broken down into four areas of concern (technical, market, financial, and application trends) that can influence how a network could be designed, along with four output areas (auxiliary activities, deployment strategies, technical design, and ownership and access). Through an extensive literature survey across many industries this framework was established to incorporate the many social economic and technical factors that influence telecommunication network planning and design.Keywords Network planning Á Survivable network planning Á Techno-economic planning Á Long range planning Á Network design Á Six sigma sipoc

Designing optimal shared backup path protected networks is a difficult and time-consuming task, and considerable research has been done to develop near optimal heuristics and algorithms that will solve the SBPP model without extensive computing power, but by definition, such methods are suboptimal. This paper introduces a slight modification to the SBPP problem that allows it to be optimally solved using conventional ILP techniques. By allowing working and backup paths to follow multiple routes, the new SBPP model eliminates the numerous 1/0 variables in the conventional model. The fundamental characteristics of SBPP remain intact, with the problem altering only slightly but it allows ILP solvers to find an optimal solution in a time measured in seconds to minutes compared to the days or longer needed for conventional models.

In modeling communication networks for simulation of survivability schemes, one goal is often to design these networks across varying degrees of nodal connectivity to get unbiased performance results. Abstractions of real networks, simple random networks, and families of networks are the most common categories of these sample networks. This paper looks at how using the network family concept provides a solid unbiased foundation to compare different network protection models. The network family provides an advantage over random networks by requiring one solution per average nodal degree, as opposed to have to solve many, which could take a significant amount of time. Also, because the network family looks at a protection scheme across a variety of average nodal connectivities, a clearer picture of the scheme's performance is gained compared to just running the simulation on a single network.

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