Location: Barcelona (Spain)
Contract: Scholarship
Working day: Part time
Sector: Internet and technology
Vacancies: 1
Discipline: Innovation
Work modality: HybridWho we are:
The i2CAT Foundation is a non-profit research and innovation center that promotes mission-driven R&D activities on advanced Internet architectures, applications, and services. More than 15 years of international research define our expertise in the fields of 5G, IoT, VR, and Immersive Technologies, Cybersecurity, Blockchain, AI, and Digital Social Innovation. The center partners with companies, public administration, academia, and end-users to leverage this knowledge in order to meet real social and business challenges.
The greatest value of i2CAT is the talent of the people who make up our human team. We enjoy a team of people from more than 13 different nationalities and work every day to create and foster a work environment where we all feel comfortable creating, innovating and growing.
Want to know more? Visit our webpage! www.i2cat.net
What would you do:
Software-defined networking (SDN) is an approach that separates the control plane from the data plane, enabling network intelligence to be deployed in a centralized SDN controller for a global view of the network. The initial SDN approach used a single centralized controller, but distributed controllers have emerged to address scalability
issues. One of the challenges of distributed controller architectures is managing controllers effectively, including allocating them to appropriate network locations [1]. The Hierarchical Controller Placement Problem (HCPP) methodology uses a hierarchical architecture with at least two levels of controllers, which improves network
scalability and efficiency. This work is a continuation from our previous work done in [2]. The HCPP methodology solves the problem of controller placement using K-means and K-center algorithms, with a Super Controller (SC) at the top, some Master Controllers (MCs) in the middle, and Domain Controllers (DCs) at the bottom. The problem of optimization is known to be NP-hard, so it is commonly formulated as a Mixed Integer Linear
Programming (MILP) problem. The metric that is optimized in this case is the latency between controller-to-switch communication (CS) communications. To summarize, the main task of this project includes but is not limited to:
1. The plan is to expand the investigation of larger topologies, such as the Full European NREN emulation model, which has 1157 routers. In previous work, controllers were only placed vertically and oversaw a set of switches within their domain. The goal is to extend the hierarchical control plane among controllers to enable communication between them and allow coordination and consensus algorithms to keep them synchronized.
2. The study aims to enhance the reliability of SDN networks when facing network failures, including both single and multiple link failures. It will analyze the impact of these failures on network performance and propose a controller placement method that can handle these failures effectively, ensuring efficient network operation in a practical scenario.
3. Another factors that should be considered when solving this problem is the capacity of both the controller and the link.
4. The main tasks are to design and implement multi-level hierarchical controller placement strategies for SDN networks using a machine learning approach (i.e., genetic algorithms). The purpose is to solve the controller placement problem by considering all relevant constraints, including latency, reliability, and capacity, and comparing it to the exact solution.
References
1. Brandon Heller, Rob Sherwood, and Nick Mckeown. The controller placement problem. Computer Communication Review, 42(4):473-478, 2012. ISSN 01464833. doi:10.1145/2377677.2377767.
2. Kurdman Rasol and J. Domingo-Pascual "Multi-level Hierarchical Controller Placement in Software Defined Networking. In: Ghita B., Shiaeles S. (eds) Selected Papers from the 12th International Networking Conference. INC 2020. Lecture Notes in Networks and Systems, vol 180. Springer, Cham. https://doi.org/10.1007/978-3-030-64758-210
Minimum requirements:
The minimum skills required for the internship include a thorough understanding of SDN architectures, protocols, and technologies, practical experience using network simulation and optimization tools like CPLEX, Gurobi, or Pyomo, and a strong proficiency in the Python programming language.
The main Expectations outcomes as follows:
1. The program involves developing software tools and writing a report related to the Multi-Objective Optimization of Controller Placement.
2. Additionally, the student is expected to produce written works suitable for publication in academic journals or conferences.
3. It is essential that the candidate be enrolled in university studies that allow the processing of an internship agreement.
Desired requirements:
Desired Skills for Internship Candidates (It is expected that the student has the ability to share software
tools and submit the report). The following are some requirements for prospective candidates:
1. Master's degree in computer science, Operations Research, or related field.
2. At least 4 years of experience in software development and network engineering.
3. Deep understanding of SDN architectures, protocols, and technologies.
4. Experience with network simulation and optimization tools such as CPLEX, Gurobi or Pyomo
5. Strong experience with Python programming languages.
6. Strong problem-solving skills and the ability to work independently or in a team environment.
7. Excellent communication and interpersonal skills.
