2 research outputs found
An Energy-driven Network Function Virtualization for Multi-domain Software Defined Networks
Network Functions Virtualization (NFV) in Software Defined Networks (SDN)
emerged as a new technology for creating virtual instances for smooth execution
of multiple applications. Their amalgamation provides flexible and programmable
platforms to utilize the network resources for providing Quality of Service
(QoS) to various applications. In SDN-enabled NFV setups, the underlying
network services can be viewed as a series of virtual network functions (VNFs)
and their optimal deployment on physical/virtual nodes is considered a
challenging task to perform. However, SDNs have evolved from single-domain to
multi-domain setups in the recent era. Thus, the complexity of the underlying
VNF deployment problem in multi-domain setups has increased manifold. Moreover,
the energy utilization aspect is relatively unexplored with respect to an
optimal mapping of VNFs across multiple SDN domains. Hence, in this work, the
VNF deployment problem in multi-domain SDN setup has been addressed with a
primary emphasis on reducing the overall energy consumption for deploying the
maximum number of VNFs with guaranteed QoS. The problem in hand is initially
formulated as a "Multi-objective Optimization Problem" based on Integer Linear
Programming (ILP) to obtain an optimal solution. However, the formulated ILP
becomes complex to solve with an increasing number of decision variables and
constraints with an increase in the size of the network. Thus, we leverage the
benefits of the popular evolutionary optimization algorithms to solve the
problem under consideration. In order to deduce the most appropriate
evolutionary optimization algorithm to solve the considered problem, it is
subjected to different variants of evolutionary algorithms on the widely used
MOEA framework (an open source java framework based on multi-objective
evolutionary algorithms).Comment: Accepted for publication in IEEE INFOCOM 2019 Workshop on Intelligent
Cloud Computing and Networking (ICCN 2019
A Lightweight and Privacy-Preserving Authentication Protocol for Mobile Edge Computing
With the advent of the Internet-of-Things (IoT), vehicular networks and
cyber-physical systems, the need for real-time data processing and analysis has
emerged as an essential pre-requite for customers' satisfaction. In this
direction, Mobile Edge Computing (MEC) provides seamless services with reduced
latency, enhanced mobility, and improved location awareness. Since MEC has
evolved from Cloud Computing, it inherited numerous security and privacy issues
from the latter. Further, decentralized architectures and diversified
deployment environments used in MEC platforms also aggravate the problem;
causing great concerns for the research fraternity. Thus, in this paper, we
propose an efficient and lightweight mutual authentication protocol for MEC
environments; based on Elliptic Curve Cryptography (ECC), one-way hash
functions and concatenation operations. The designed protocol also leverages
the advantages of discrete logarithm problems, computational Diffie-Hellman,
random numbers and time-stamps to resist various attacks namely-impersonation
attacks, replay attacks, man-in-the-middle attacks, etc. The paper also
presents a comparative assessment of the proposed scheme relative to the
current state-of-the-art schemes. The obtained results demonstrate that the
proposed scheme incurs relatively less communication and computational
overheads, and is appropriate to be adopted in resource constraint MEC
environments.Comment: To appear in IEEE GLOBECOM 201