Ph. D. Project
Title:
Self-Adaptive blockchain framework for distributed SDN
Dates:
2022/08/30 - 2025/07/24
Student:
Supervisor(s):
Description:
According to a recent Gartner's report, one million new Internet of Things (IoT) devices will be sold every hour by 2021, which inevitably comes along
with new challenges and demands in terms of high bandwidth, security, ubiquitous accessibility and dynamic management of communication networks.
Software-defined networking (SDN) has emerged as a response to the limitations and complexities of traditional network architectures, aiming at
consolidating the control over network devices into a logically centralized (software) controller. Nonetheless, the increasing number of smart connected
devices in IoT environments implies relying on more than one controller, which is also referred to as distributed SDN (dSDN) in the scientific literature. The
use of multiple SDN controllers poses a number of challenges as, for example, the need to reach consensus among multiple controllers, or to deal with
security issues including trust and accountability.
To overcome these issues, the blockchain technology is receiving a growing attention in the scientific community, as it offers powerful tamper-proof logging
and auditing capabilities where trust and control are not anymore centralized and black-boxed, but rather decentralized and transparent (i.e., no need for a
central trusted authority). Despite the advantages of blockchain, this technology comes along with constraints, particularly regarding communication delays
that may impact on the overall system/application performance and Service Level Agreement (SLA) guarantees. Those delays mainly result from the
consensus protocol underlying blockchain, which is used to maintain synchronized all the blockchain copies across the nodes involved in the consensus
decision-making process. Given this problem, it is all the more important to come up with innovative and smart ways of evaluating and mitigating those
impacts.
This is where this PhD thesis comes into play. First, it introduces a rigorous methodology to identify and formalize the impacts of blockchain on
the end-to-end dSDN architecture performance in terms of trade-off between convergence time, security and scalability. Secondly, it progresses the current
state-of-the-art by investigating, designing and evaluating a novel adaptive blockchain consensus protocol that best meets the trade-off problem. The
novelty and originality of the proposal lies in the fact that the consensus protocol is able to self-adapt, at any time, to evolving application needs while
maintaining the best trade-off point. In this work, we claim that proposing such new adaptive and smart consensus protocols are key to the success of
integrating blockchain with existing systems and network solutions.
with new challenges and demands in terms of high bandwidth, security, ubiquitous accessibility and dynamic management of communication networks.
Software-defined networking (SDN) has emerged as a response to the limitations and complexities of traditional network architectures, aiming at
consolidating the control over network devices into a logically centralized (software) controller. Nonetheless, the increasing number of smart connected
devices in IoT environments implies relying on more than one controller, which is also referred to as distributed SDN (dSDN) in the scientific literature. The
use of multiple SDN controllers poses a number of challenges as, for example, the need to reach consensus among multiple controllers, or to deal with
security issues including trust and accountability.
To overcome these issues, the blockchain technology is receiving a growing attention in the scientific community, as it offers powerful tamper-proof logging
and auditing capabilities where trust and control are not anymore centralized and black-boxed, but rather decentralized and transparent (i.e., no need for a
central trusted authority). Despite the advantages of blockchain, this technology comes along with constraints, particularly regarding communication delays
that may impact on the overall system/application performance and Service Level Agreement (SLA) guarantees. Those delays mainly result from the
consensus protocol underlying blockchain, which is used to maintain synchronized all the blockchain copies across the nodes involved in the consensus
decision-making process. Given this problem, it is all the more important to come up with innovative and smart ways of evaluating and mitigating those
impacts.
This is where this PhD thesis comes into play. First, it introduces a rigorous methodology to identify and formalize the impacts of blockchain on
the end-to-end dSDN architecture performance in terms of trade-off between convergence time, security and scalability. Secondly, it progresses the current
state-of-the-art by investigating, designing and evaluating a novel adaptive blockchain consensus protocol that best meets the trade-off problem. The
novelty and originality of the proposal lies in the fact that the consensus protocol is able to self-adapt, at any time, to evolving application needs while
maintaining the best trade-off point. In this work, we claim that proposing such new adaptive and smart consensus protocols are key to the success of
integrating blockchain with existing systems and network solutions.
Keywords:
Blockchain, Software-Defined Networking, Networking, Security, Artificial Intelligence
Department(s):
| Modeling and Control of Industrial Systems |
