# A Novel Cloud Energy Consumption Heuristic Based on a Network Slicing-Ring Fencing Ratio  
[PERSON]  
1 School of Computing, National College of Ireland, Mayor Square, D01 K6W2 Dublin, Ireland; 1  
[PERSON]  
2 Department of Computer Science, Munster Technological University, Rossa Ave, Bishopstown, T12 P928 Cork, Ireland; [EMAIL_ADDRESS]  
[PERSON]  
1 School of Computing, National College of Ireland, Mayor Square, D01 K6W2 Dublin, Ireland; 1  
Footnote 1: email: [EMAIL_ADDRESS].  
techniques becomes critical to ensure flexibility, isolation, and the dynamic prioritisation of traffic [2; 3]. The concept of a network slice can be traced back to the radio access network (RAN or Fog RAN as shown in Figure 1), which consists of independent network topologies drawn by ring fencing techniques composed of logical ring fences to balance optimal resource allocation while reducing energy consumption [4].  
However, the energy consumption in heterogeneous network slicing architectures has been reported to be significantly high due to poorly optimised resource allocation across virtual networks [5]. Numerous mission-critical applications demand low latency and high reliability and throughput, utilising access technologies such as nonorthogonal multiple access (NOMA) and orthogonal frequency division multiple access (OFDMA). Additional techniques such as the network slicing Aware User Grouping for NOMA and resourcE allocatioN in edge compuTing (AUGMENT) and the dynamic voltage scaling technique (DVS) have been promising for energy-aware computational offloading. The efficient integration of all these methods for effective optimisation of resource allocation in order to achieve lower energy consumption is still an open and complex challenge [6].  
Although NOMA clustering has been proposed for increased channel gain in network slices [5] and numerous strategies enabling efficient computational offloading [6], the need for lower computation execution time and suboptimal resource allocation still persists for cloud-centric architectures. Although cloud topologies could potentially map resources more efficiently in high-quality network slices with improved ring fences, the efficiency is dependent on computational resources, logical ring fences, and the overall slice-to-ring-fence ratio. In this paper, we demonstrate how optimising the ratio between network slices and ring fencing can significantly reduce energy consumption in cloud data centres by minimising the network \"churn\" as much as possible.  
The main contributions of this paper are listed as follows:  
1. We propose an iterative heuristic energy-aware non-convex (IHEA-NC) algorithm proposed based on the network slicing-ring fencing ratio for minimizing energy consumption in cloud architectures.  
Figure 1: Centralised orchestration-based f-RAN network access slicing (from [7]).  
We validate the proposed heuristic (IHEA-NC) through simulations in CloudSim and Amazon Web Services (AWS), achieving 91.46% energy savings compared to existing methods (HA-NC by [PERSON] and [PERSON] [5], PSO by [PERSON] et al. [6]).
3. We demonstrate that the proposed heuristic is scalable and efficient, proving suitability for heterogeneous real-world cloud architectures.  
These contributions lead to the design of a solution-specific uneven network slicing-ring fencing architecture starting from the \"network slice\", which enables network operators to maintain a high level of interaction with clients seeking end-user services, balancing energy consumption and task execution time.  
The remainder of this paper is structured as follows. Section 2 reviews the state-of-the-art in relation to this research. Section 3 describes the proposed equation and the respective environmental setups. Section 4 presents the algorithmic benchmark results and their implications in real-world cloud architectures. Section 5 concludes this paper and discusses future work that is useful for energy consumption in general, especially for data centres.