COST OPTIMIZATION OF ALLOCATING VIRTUAL NETWORK FUNCTIONS WITH PRECEDENCE IN MULTICAST NETWORKS

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2019-01-01
Authors
Chalamalasetty, Ramcharan
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Ahmed E. Kamal
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Electrical and Computer Engineering

The Department of Electrical and Computer Engineering (ECpE) contains two focuses. The focus on Electrical Engineering teaches students in the fields of control systems, electromagnetics and non-destructive evaluation, microelectronics, electric power & energy systems, and the like. The Computer Engineering focus teaches in the fields of software systems, embedded systems, networking, information security, computer architecture, etc.

History
The Department of Electrical Engineering was formed in 1909 from the division of the Department of Physics and Electrical Engineering. In 1985 its name changed to Department of Electrical Engineering and Computer Engineering. In 1995 it became the Department of Electrical and Computer Engineering.

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1909-present

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  • Department of Electrical Engineering (1909-1985)
  • Department of Electrical Engineering and Computer Engineering (1985-1995)

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Electrical and Computer Engineering
Abstract

In the past few years, Network Function Virtualization (NFV) has been widely used to reduce the operational and capital costs of implementing network functions with better performance and easier network management. NFV is a network architecture completely built relying on Virtual Network Functions (VNFs). Quite a few developments have been done for the optimization of resource allocation to implement VNFs in various networks. In this report, an algorithm for reducing the cost of placing the VNFs within a Multicast network along with a choice of selecting the precedence of the VNFs is presented. The proposed approach is formulated as a Mixed Integer Linear Programming (MILP) model based on a main objective of minimizing the cost of resource allocation with Precedence in Multicast Networks. Finally, we evaluate the algorithm through simulations in CPLEX and demonstrate the results.

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Tue Jan 01 00:00:00 UTC 2019