Cloud computing is a systematic delivery of computing resources as services to the consumers via the Internet. Infrastructure
as a Service (IaaS) is the capability provided to the consumer by enabling smarter access to the processing, storage,
networks, and other fundamental computing resources, where the consumer can deploy and run arbitrary software including
operating systems and applications. The resources are sometimes available in the form of Virtual Machines (VMs). Cloud
services are provided to the consumers based on the demand, and are billed accordingly. Usually, the VMs run on various
datacenters, which comprise of several computing resources consuming lots of energy resulting in hazardous level of carbon
emissions into the atmosphere. Several researchers have proposed various energy-efficient methods for reducing the energy
consumption in datacenters. One such solutions are the Nature-Inspired algorithms. Towards this end, this paper presents a
comprehensive review of the state-of-the-art Nature-Inspired algorithms suggested for solving the energy issues in the Cloud
datacenters. A taxonomy is followed focusing on three key dimension in the literature including virtualization, consolidation,
and energy-awareness. A qualitative review of each techniques is carried out considering key goal, method, advantages, and
limitations. The Nature-Inspired algorithms are compared based on their features to indicate their utilization of resources
and their level of energy-efficiency. Finally, potential research directions are identified in energy optimization in data centers.
This review enable the researchers and professionals in Cloud computing datacenters in understanding literature evolution
towards to exploring better energy-efficient methods for Cloud computing datacenters
