Elastic Resource Provisioning for Increased Energy Efficiency and Resource Utilization in Cloud-RANs

2020 ◽  
Vol 172 ◽  
pp. 107170
Author(s):  
Abolfazl Hajisami ◽  
Tuyen X. Tran ◽  
Ayman Younis ◽  
Dario Pompili
Keyword(s):  
Energy Efficiency ◽  
Resource Utilization ◽  
Resource Provisioning

A Value Based Dynamic Resource Provisioning Model in Cloud

2013 ◽  
Vol 3 (2) ◽  
pp. 35-46 ◽  
Author(s):  
Sandeep K. Sood
Keyword(s):  
Resource Utilization ◽  
Virtual Machines ◽  
Fault Tolerant ◽  
Resource Provisioning ◽  
Resource Usage ◽  
Resource Manager ◽  
Usage Rate ◽  
Computing Paradigm ◽  
A Value ◽  
Dynamic Resource Provisioning

Cloud computing has become an innovative computing paradigm, which aims at providing reliable, customized, Quality of Service (QoS) and guaranteed computing infrastructures for users. Efficient resource provisioning is required in cloud for effective resource utilization. For resource provisioning, cloud provides virtualized computing resources that are dynamically scalable. This property of cloud differentiates it from the traditional computing paradigm. But the initialization of a new virtual instance causes a several minutes delay in the hardware resource allocation. Furthermore, cloud provides a fault tolerant service to its clients using the virtualization. But, in order to attain higher resource utilization over this technology, a technique or a strategy is needed using which virtual machines can be deployed over physical machines by predicting its need in advance so that the delay can be avoided. To address these issues, a value based prediction model in this paper is proposed for resource provisioning in which a resource manager is used for dynamically allocating or releasing a virtual machine depending upon the resource usage rate. In order to know the recent resource usage rate, the resource manager uses sliding window to analyze the resource usage rate and to predict the system behavior in advance. By predicting the resource requirements in advance, a lot of processing time can be saved. Earlier, a server has to perform all the calculations regarding the resource usage that in turn wastes a lot of processing power thus decreasing its overall capacity to handle the incoming request. The main feature of the proposed model is that a lot of load is being shifted from the individual server to the resource manager as it performs all the calculations and therefore the server is free to handle the incoming requests to its full capacity.

scholarly journals A REVIEW ON ENGERY EFFICIENT STRATEGY FOR TASK ALLOCATION IN CLOUD ENVIRONMENT

2016 ◽  
Vol 15 (9) ◽  
pp. 7035-7040
Author(s):  
Sakshi Grover ◽  
Mr. Navtej Singh Ghumman
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Resource Provisioning ◽  
Research Issues ◽  
Efficient Management ◽  
Dynamic Resource Provisioning ◽  
Computing Platforms ◽  
And Performance ◽  
Cloud Applications ◽  
Allocation Algorithms

Although cloud computing is now becoming more advanced and matured as many companies have released their own computing platforms to provide services to public, but the research on cloud computing is still in its infancy. Apart from many other challenges of cloud computing, efficient management of energy is one of the most challenging research issues. In this paper we review the existing algorithm of dynamic resource provisioning and allocation algorithms and holistically work to boost data center energy efficiency and performance. This particular paper purposes a) heterogeneous workload and its implication on data centers energy efficiency b) solving the problem of VM resource scheduling to cloud applications

scholarly journals Dynamic Resource Provisioning for Energy Efficiency in Wireless Access Networks: A Survey and an Outlook

2014 ◽  
Vol 16 (4) ◽  
pp. 2259-2285 ◽  
Author(s):  
Lukasz Budzisz ◽  
Fatemeh Ganji ◽  
Gianluca Rizzo ◽  
Marco Ajmone Marsan ◽  
Michela Meo ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Resource Provisioning ◽  
Access Networks ◽  
Wireless Access ◽  
Wireless Access Networks ◽  
Dynamic Resource Provisioning ◽  
Dynamic Resource

scholarly journals A New Resources Provisioning Method Based on QoS Differentiation and VM Resizing in IaaS

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Rongdong Hu ◽  
Guangming Liu ◽  
Jingfei Jiang ◽  
Lixin Wang
Keyword(s):  
Energy Efficiency ◽  
Energy Efficient ◽  
Resource Provisioning ◽  
Application Performance ◽  
Qos Differentiation ◽  
Different Types ◽  
Speed Up ◽  
Google Cluster Trace ◽  
Real Time Application ◽  
Host Resource

In order to improve the host energy efficiency in IaaS, we proposed an adaptive host resource provisioning method, CoST, which is based on QoS differentiation and VM resizing. The control model can adaptively adjust control parameters according to real time application performance, in order to cope with changes in load. CoST takes advantage of the fact that different types of applications have different sensitivity degrees to performance and cost. It places two different types of VMs on the same host and dynamically adjusts their sizes based on the load forecasting and QoS feedback. It not only guarantees the performance defined in SLA, but also keeps the host running in energy-efficient state. Real Google cluster trace and host power data are used to evaluate the proposed method. Experimental results show that CoST can provide performance-sensitive application with a steady QoS and simultaneously speed up the overall processing of performance-tolerant application by 20~66%. The host energy efficiency is significantly improved by 7~23%.

scholarly journals Energy efficiency of cooperative D2D communications underlaying LTE-A networks

2018 ◽  
Vol 189 ◽  
pp. 03016 ◽  
Author(s):  
Xiaoying Zhang ◽  
Ahmed Khwaja ◽  
Muhammad Naeem ◽  
Alagan Anpalagan
Keyword(s):  
Energy Efficiency ◽  
Power Allocation ◽  
Resource Utilization ◽  
Energy Efficient ◽  
Average Energy ◽  
D2d Communication ◽  
Cellular Communications ◽  
D2d Communications ◽  
Allocation Algorithm ◽  
Power Resources

Device-to-device (D2D) communications underlaying LTE-A networks is expected to bring significant benefits for resource utilization and energy efficiency (EE) improvement of user equipment (UE). However, the allocation of radio and power resources to D2D communications needs elaborate coordination, because of the interference between D2D communications and cellular communications. In this paper, we propose an energy-efficient cooperative D2D communication (EECD2D) technique using a power allocation algorithm, aiming at maximizing EE introduced by D2D communications in LET-A networks. Specifically, we define four D2D and cellular combinations based on distances, and analyze average EE of EECD2D and that of cooperative D2D communications without optimization. Results show that average EE of our algorithm is much higher than that without optimization, and closer D2D cooperators and distant cellular UEs whose uplink resource is reused, achieve highest average energy efficiency.

scholarly journals Cooperatively Improving Data Center Energy Efficiency Based on Multi-Agent Deep Reinforcement Learning

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2071
Author(s):  
Ce Chi ◽  
Kaixuan Ji ◽  
Penglei Song ◽  
Avinab Marahatta ◽  
Shikui Zhang ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Reinforcement Learning ◽  
Resource Utilization ◽  
Data Center ◽  
Data Centers ◽  
Optimization Method ◽  
Comparison Method ◽  
Cooling Systems ◽  
Model Free ◽  
Multi Agent

The problem of high power consumption in data centers is becoming more and more prominent. In order to improve the energy efficiency of data centers, cooperatively optimizing the energy of IT systems and cooling systems has become an effective way. In this paper, a model-free deep reinforcement learning (DRL)-based joint optimization method MAD3C is developed to overcome the high-dimensional state and action space problems of the data center energy optimization. A hybrid AC-DDPG cooperative multi-agent framework is devised for the improvement of the cooperation between the IT and cooling systems for further energy efficiency improvement. In the framework, a scheduling baseline comparison method is presented to enhance the stability of the framework. Meanwhile, an adaptive score is designed for the architecture in consideration of multi-dimensional resources and resource utilization improvement. Experiments show that our proposed approach can effectively reduce energy for data centers through the cooperative optimization while guaranteeing training stability and improving resource utilization.

scholarly journals AN Efficient Ant Colony Optimization Algorithm for Resource Provisioning in Cloud

2019 ◽  
Vol 8 (4) ◽  
pp. 421-429
Keyword(s):  
Ant Colony Optimization ◽  
Resource Utilization ◽  
Optimization Algorithm ◽  
Spanning Tree ◽  
Resource Provisioning ◽  
Ant Colony ◽  
Search Process ◽  
Ant Colony Optimization Algorithm ◽  
Hybrid Scheme ◽  
Resources Management

Paper Several Ant Colony Optimization (ACO) techniques for Cloud resources management are considered by many researchers. ACO techniques in existence still need some improvements for effective resource management and planning with the heterogeneous and voluminous services offered. Hence, an optimized hybrid scheme that combined deterministic characteristics for exploiting ACO search process is proposed. Spanning Tree (ST) algorithm was chosen in the hybridization that obtained a faster convergence speed, minimized makespan time and throughput that ensured resource utilization in least time and cost. Extensive experiments were conducted in cloudsim simulator provided an efficient result compared to other ACO techniques as it significantly improves performance.

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