TRACTOR: Traffic‐aware and power‐efficient virtual machine placement in edge‐cloud data centers using artificial bee colony optimization

Abstract

Technology providers heavily exploit the usage of Edge-Cloud Data Centers (ECDC) to meet user demand while the ECDC are large energy consumers. Concerning the decrease of the energy expenditure of ECDCs, task placement is one of the most prominent solutions for effective allocation and consolidation of such tasks onto physical machine (PM). Such allocation must also consider additional optimizations beyond power and must include other objectives, including network-traffic effectiveness. In this study, we present a multi-objective Virtual Machine (VM) placement scheme (considering VMs as fog tasks) for ECDCs called TRACTOR, which utilizes an Artificial Bee Colony optimization algorithm for power and network-aware assignment of VMs onto PMs. The proposed scheme aims to minimize the network traffic of the interacting VMs and the power dissipation of the data center's switches and physical machines. To evaluate the proposed VM placement solution, the VL2 (Virtual Layer 2) and three-tier network topologies are modeled and integrated into the CloudSim toolkit to justify the effectiveness of the proposed solution in mitigating the network traffic and power consumption of the ECDC. Results indicate that our proposed method is able to reduce power energy consumption by 3.5% whilst decreasing network traffic and power by 15% and 30%, respectively, without affecting other Quality of Service parameters.

Green energy‐efficient computing solutions in Internet of Things communications

“…The paper entitled “TRACTOR: Traffic‐Aware and Power‐Efficient Virtual Machine Placement in Edge‐Cloud Data Centers Using Artificial Bee Colony Optimization” by Nabavi et al 10 proposed a new many‐objective virtual machine (VM) placement. They reported that the proposed method is able to reduce energy consumption by 3.5% while decreasing network traffic.…”

Chaotic Salp Swarm Optimization-Based Energy-Aware VMP Technique for Cloud Data Centers

“…The next aim is to reduce the resource consumption and manage resources by an optimum deployment of VM on PM in the CDC. Nabavi et al [ 12 ] presented a multiobjective VMP system (consider VM as a fog task) for the ECDC is known as TRACTOR that uses an ABC optimization method for energy aware assignments of VM on PM. The projected system aims to reduce the network traffic of the related VMs and energy exploitation during the data center changes and PMs.…”

Nature‐inspired virtual machine placement mechanisms: A systematic review

“…In Reference 46, they developed a TRAffic‐aware and power‐efficient VM placemenT algorithm for edge‐clOud data center (TRACTOR), that uses an artificial bee colony (ABC) optimization algorithm for power and network‐aware allocation of VMs onto PMs (viewing VMs as fog jobs). The virtual layer 2 and three‐tier network architectures were modeled and incorporated into the CloudSim toolkit to explain the efficacy of the suggested VMP method in reducing the edge‐cloud data center's energy usage and network traffic.…”