A Load-Balanced Call Admission Controller for IMS Cloud Computing

TL;DR

This paper introduces VLB-CAC, a load-balanced call admission control scheme for IMS cloud servers that optimizes resource allocation and call handling using linear programming and autoscaling, improving overload management.

Contribution

It presents a novel linear programming model for optimal call admission and resource allocation in IMS cloud environments, along with an autoscaler to handle resource limitations.

Findings

Efficient call admission control reduces server overload.

Optimal resource allocation improves system performance.

Autoscaler effectively manages resource constraints.

Abstract

Network functions virtualization provides opportunities to design, deploy, and manage networking services. It utilizes cloud computing virtualization services that run on high-volume servers, switches, and storage hardware to virtualize network functions. Virtualization techniques can be used in IP multimedia subsystem (IMS) cloud computing to develop different networking functions (e.g., load balancing and call admission control). IMS network signaling happens through session initiation protocol (SIP). An open issue is the control of overload that occurs when an SIP server lacks sufficient CPU and memory resources to process all messages. This paper proposes a virtual load balanced call admission controller (VLB-CAC) for the cloud-hosted SIP servers. VLB-CAC determines the optimal call admission rates and signaling paths for admitted calls along with the optimal allocation of CPU and memory resources of the SIP servers. This optimal solution is derived through a new linear programming model. This model requires some critical information of SIP servers as input. Further, VLB-CAC is equipped with an autoscaler to overcome resource limitations. The proposed scheme is implemented in smart applications on virtual infrastructure (SAVI) which serves as a virtual testbed. An assessment of the numerical and experimental results demonstrates the efficiency of the proposed work.