Parallel and Distributed Resource Allocation with Minimum Traffic Disruption for Network Virtualization

Parallel and Distributed Resource Allocation with MinimumTraffic Disruption for Network Virtualization

 

ABSTRACT:

Wireless network virtualization has been advocated as one of the most promising technologies to provide multifarious services and applications for the future Internet by enabling multiple isolated virtual wireless networks to coexist and share the same physical wireless resources. Based on the multiple concurrent virtual wireless networks running on the shared physical substrate, service providers can independently manage and deploy different end-users services. This paper proposes anew formulation for bandwidth allocation and routing problem for multiple virtual wireless networks that operate on top of asingle substrate network to minimize the operation cost of the substrate network.We also propose a preventive traffic disruption model for virtual wireless networks to minimize the amount of traffic that service providers have to reduce when substrate links fail by incorporating `1-norm into the objective function. Dueto the large number of constraints in both normal state and link failure states, the formulated problem becomes a large-scale optimization problem and is very challenging to solve using the centralized computational method. Therefore, we propose the decomposition algorithms using the alternating direction method of multipliers (ADMM) that can be implemented in a parallel and distributed fashion. The simulation results demonstrate the computational efficiency of our proposed algorithms as well as the advantage of the formulated model in ensuring the minimal amount of traffic disruption when substrate links fail.

 OBJECTIVE:

Preventive Traffic Disruption Modeling: We propose apreventive traffic disruption model for virtual networkswhen a substrate link failure event happens. We alsoincorporate `1-norm into the objective function to ensurethe minimal amount of traffic reduction of SPs.

  • Parallel and Distributed Implementation: We propose two algorithms based on the ADMM decomposition technique. The first algorithm provides a parallel computational framework that can be solved concurrently at different computing nodes, and the second algorithm allows SPs and substrate links distributive solve local problems to achieve the global optimal solution.
  • Performance Evaluation: We evaluate the performance ofour proposed algorithms using various system parameters.We also demonstrate the efficacy of our preventive model in reducing the amount of traffic reduction.

INTRODUCTION:

The rapid growth of traffic demand and application prolife ration creates irresistible challenges for traditional wireless networks to ensure the qualify of service (QoS) and quality of experience of subscribers. However, due to the inefficient resource utilization and the tightly coupling between hardware and wireless protocols caused by the inherent design, the current wireless networks and Internet can hardly meet such great expectations without fundamentally changing network architectures. Recently, wireless network virtualization has been proposed as one of the key enablers to overcome the ossification of the current Internet by allowing diverse services and applications coexist on the same infrastructure. In wireless network virtualization,the traditional Internet service providers are decoupled into infrastructure providers (InPs) who own and manage only infrastructure resources, and service providers (SPs) who lease resources from InPs and concentrate on providing services to subscribers. The physical resources that belong to different InPs are virtualized into a single physical substrate network.Consequently, multiple virtual wireless networks are deployed and operated on top of the single substrate network  Asa result, multiple experiments can be performed and tested simultaneously on isolated virtual networks without affecting the operation of the others. Therefore, wireless network virtualization offers great opportunities to shorten the process of evaluating and deploying innovative technologies. Moreover,by sharing the same infrastructure resources, expenses of wireless network expansion and operation can be significantly reduced.

EXISTING SYSTEM:

  1. Liu, F. Yu, H. Ji, and V. Leung, “Virtual resource management ingreen cellular networks with shared full-duplex relaying and wireless virtualization: A game-based approach,” IEEE Transactions on Vehicular Technology, vol. 65, no. 9, pp. 7529–7542, Sep. 2016.

To efficiently allocate physical resources to multiple virtual wireless networks and find the optimal routing solution in each virtual network operated by SPs.

  1. Chen, F. R. Yu, H. Ji, G. Liu, and V. C. M. Leung, “Distributed

virtual resource allocation in small-cell networks with full-duplex selfback haulsand virtualization,” IEEE Transactions on Vehicular Technology,vol. 65, no. 7, pp. 5410–5423, Jul. 2016.

A resourceallocation in virtualized small cell networks with full duplexself-backhauls is formulated.

PROPOSED SYSTEM:

We also propose a preventive traffic disruptionmodel for virtual wireless networks to minimize the amount oftraffic that service providers have to reduce when substrate linksfail by incorporating `1-norm into the objective function. Due

to the large number of constraints in both normal state and link failure states, the formulated problem becomes a large-scale optimization problem and is very challenging to solve using the centralized computational method. Therefore, we propose the decomposition algorithms using the alternating direction method of multipliers (ADMM) that can be implemented in a parallel and distributed fashion. The simulation results demonstrate the computational efficiency of our proposed algorithms as well as the advantage of the formulated model in ensuring the minimal amount of traffic disruption when substrate links fail.

BLOCK DIAGRAM:

Parallel and Distributed Resource Allocation

DESCRIPTION:

The bandwidth allocation can satisfy traffic demands for all virtual networks only when all substrate links are fully available, which we will refer as the normal state. However, unpredictable wireless network events such as link failures may occur anytime. Although when a link failure event happens, the network controller can reformulate the problem in with new system parameters to reallocate bandwidth for all virtual networks, it will take acertain amount of time to wait for network re-convergence.Since different SPs target different types of services and may have stringent reliability and QoS requirements, this performance degradation and severe discontinuation will be intolerable to end-users.

ADVANTAGES:

  • Can be solved concurrently at different computing nodes
  • SP and substrate link distributively solve the local problem to converge to the global optimal solution.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

  • System : Pentium Dual Core.
  • Hard Disk : 120 GB.
  • Monitor : 15’’ LED
  • Input Devices : Keyboard, Mouse
  • Ram : 1GB

SOFTWARE REQUIREMENTS:

  • Operating system : Windows 7.
  • Coding Language : MATLAB
  • Tool : MATLAB R2013A

REFERENCE:

Hung Khanh Nguyen, Student Member, IEEE, Yanru Zhang, Member, IEEE,Zheng Chang, Member, IEEE, and Zhu Han, Fellow, IEEE, “Parallel and Distributed Resource Allocation with MinimumTraffic Disruption for Network Virtualization”, IEEE Transactions on Communications, 2017.

 

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