TDM Network Resource Planning for IoT and 5G Applications - QC-177

Preferred Disciplines: Software Engineering, Information Technology (Masters, PhD or Post-Doc)
Project length: 12-18 months (3 units)
Approx. start date: February 2019
Location: Montreal, QC
No. of Positions: 1
Preferences: Universities in Quebec and Ontario
Company: Ciena

About Company:

Ciena is a network strategy and technology company known for its commitment to customer success. With 25 years of industry leadership, we support more than 1,300 of the world’s largest, most reliable networks. Our technology is complemented with a high-touch consultative business model. We’re committed to developing and applying technologies that facilitate openness, virtualization, automation, collaboration, and a common experience. Technologies that offer the greatest degree of choice deliver the most rewarding customer experiences and business outcomes.

Summary of Project:

Investigating new methods to classify legacy TDM network resources considering the advent of IoT and 5G networks requirements. As Network Providers evolve their legacy TDM to Packet, resolving the optimal migration patterns will be key for their business justification and return on investment. Many of these networks have reached their capacity limit and new applications, such as 5G and Internet of Things, demand new, more performing technology. Finding optimal ways to modernize these networks from the perspectives of both time and cost is thus an important problem.

Enabling Network providers to make informed decisions to justify the significant investment, as well as ensuring the most efficient approach, will be a large factor in the speed at which modern applications can be made available to consumers and business. The results will have significant impact on the telecom industry next large evolution. By looking at the evolution of TDM network planning from a generic perspective, the solution to modernize can span a wide array of specific elements. Fundamentally, optimizing resources to migrate two ends of a traffic path. This path may span; 1) single or multiple nodes across a site, 2) single or multiple sites across a metro area, or, 3) an entire network. Using a black box effect of input and outputs of traffic paths will allow for creating a “network planning tool” which attempts to act as a gateway between legacy circuit, packet and wave (optical) network parameters to help optimize current and future network resources.

Research Objectives/Sub-Objectives:

  • How do we take an existing network and adapt it to the current and future needs of the customer?
  • How can we minimize network downtime and efforts/costs by properly planning the migration/modernization?
  • How can we make the solution generic enough that it takes a set of endpoints as input?
  • What should be done with the enormous amount of data that is generated by the network in the context of its modernization? How can this data be used to design a better future network?


    • To assist the engineer in the process of migrating TDM to packets.
    • To evolve existing RWA algorithm and circuit stitching between different technologies and vendor platforms.
    • Graph database automation.
    • Use of Visual Analytics, and AI/ML if requires.

    Expertise and Skills Needed:

    • Telecommunication skills.
    • Software and automation with optimization.
    • Network planning tools.
    • Knowledge of modelling and solving combinatorial optimization.
    • Mixed integer linear and constraint logic programming and heuristic algorithms.
    • Object oriented software design and implementation.
    • Concurrent and parallel algorithm development expertise.
    • Knowledge of Packet IP and Optical transport network equipment and design.
    • Knowledge of machine learning and associated tools.

    For more info or to apply to this applied research position, please

    1. Check your eligibility and find more information about open projects.
    2. Interested students need to get the approval from their supervisor and send their CV along with a link to their supervisor’s university webpage by applying through the webform or directly to Mel Chaar