A Taxonomy and Survey of Power Models and Power Modeling for Cloud Servers

2020 ◽  
Vol 53 (5) ◽  
pp. 1-41 ◽  
Author(s):  
Weiwei Lin ◽  
Fang Shi ◽  
Wentai Wu ◽  
Keqin Li ◽  
Guangxin Wu ◽  
...  
Keyword(s):  
Power Modeling ◽  
Power Models ◽  
Cloud Servers

A Decadal Walkthrough on Energy Modelling for Cloud Datacenters

2021 ◽  
pp. 195-204
Author(s):  
Ahan Chatterjee
Keyword(s):  
Load Balancing ◽  
Power Consumption ◽  
Virtual Machines ◽  
Speed Scaling ◽  
Energy Modelling ◽  
Power Models ◽  
Network Usage ◽  
Scale Usage ◽  
Cloud Servers ◽  
Industry Needs

Cloud computing is the growing field in the industry, and every scale industry needs it now. The high scale usage of cloud has resulted in huge power consumption, and this power consumption has led to increase of carbon footprint affecting our mother nature. Thus, we need to optimize the power usage in the cloud servers. Various models are used to tackle this situation, of which one is a model based on link load. It minimized the bit energy consumption of network usage which includes energy efficiency routing and load balancing. Over this, multi-constraint rerouting is also adapted. Other power models which have been adapted are virtualization framework using multi-tenancy-oriented data center. It works by accommodating heterogeneous networks among virtual machines in virtual private cloud. Another strategy that is adopted is cloud partitioning concept using game theory. Other methods that are adopted are load spreading algorithm by shortest path bridging, load balancing by speed scaling, load balancing using graph constraint, and insert ranking method.

Power Modeling Framework for an Asynchronous Processor

2016 ◽  
Vol 25 (06) ◽  
pp. 1650057
Author(s):  
Je-Hoon Lee
Keyword(s):  
Power Consumption ◽  
High Accuracy ◽  
The Other ◽  
Power Model ◽  
Power Modeling ◽  
Modeling Framework ◽  
Low Level ◽  
Architectural Model ◽  
Power Models

This paper presents two power models for an asynchronous processor, A8051. The first one is a pipeline accurate model which models power consumption at each pipeline stage. The other one is a micro-architectural model which models power consumption at micro-operation level. Then, we demonstrate the feasibility of the proposed approach on an A8051 processor case study. The experimental results based on applying the proposed pipeline-accurate and micro-architectural power models on an A8051 processor demonstrate that the proposed power models have high accuracy with simulation times much faster than the conventional low-level power simulator. It also shows similar results compared to the conventional power model for a synchronous processor. Even though the simulation speeds for the proposed power models are approximately 100–900 times faster than the low-level power simulator, the differences are less than 18% and 15%, respectively. Thus, the proposed power models can give a guide for SoC designers who want to integrate the asynchronous processor for low-power SoC design.

scholarly journals An Empirical Algorithm for Power Analysis in Deep Submicron Electronic Designs

VLSI Design ◽  
2002 ◽  
Vol 14 (2) ◽  
pp. 219-227 ◽  
Author(s):  
May Huang ◽  
Raymond Kwok ◽  
Shu-park Chan
Keyword(s):  
Power Analysis ◽  
Deep Submicron ◽  
Register Transfer Level ◽  
Power Modeling ◽  
Empirical Power ◽  
State Dependent ◽  
Simulation Based ◽  
Power Models ◽  
Analysis Strategy ◽  
Logic Level

An empirical algorithm applied to logic level power analysis in deep submicron VLSI designs is introduced in the paper. The method explores a static analysis strategy using unit functions to represent signal transitions. It can be extended to the use of a Register Transfer Level (RTL) power analysis after RTL codes are translated to Boolean equations. A new method for representing state-dependent power models is also introduced in the paper to reduce the complexity of power modeling and to improve the performance of power analysis. The modeling method supports not only the empirical power analysis, but also general simulation-based power analysis methods.

scholarly journals Phase-Based Accurate Power Modeling for Mobile Application Processors

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1197
Author(s):  
Kitak Lee ◽  
Seung-Ryeol Ohk ◽  
Seong-Geun Lim ◽  
Young-Jin Kim
Keyword(s):  
Power Consumption ◽  
Mobile Application ◽  
Total Power ◽  
Average Error ◽  
Power Model ◽  
Power Modeling ◽  
Estimation Errors ◽  
Total Power Consumption ◽  
Battery Capacity ◽  
Power Models

Modern mobile application processors are required to execute heavier workloads while the battery capacity is rarely increased. This trend leads to the need for a power model that can analyze the power consumed by CPU and GPU at run-time, which are the key components of the application processor in terms of power savings. We propose novel CPU and GPU power models based on the phases using performance monitoring counters for smartphones. Our phase-based power models employ combined per-phase power modeling methods to achieve more accurate power consumption estimations, unlike existing power models. The proposed CPU power model shows estimation errors of 2.51% for ARM Cortex A-53 and 1.97% for Samsung M1 on average, and the proposed GPU power model shows an average error of 8.92% for the Mali-T880. In addition, we integrate proposed CPU and GPU models with the latest display power model into a holistic power model. Our holistic power model can estimate the smartphone′s total power consumption with an error of 6.36% on average while running nine 3D game benchmarks, improving the error rate by about 56% compared with the latest prior model.

Control Cloud Data Access Privilge Anonymity with Attributed Based Encryption

2017 ◽  
Vol 7 (8) ◽  
pp. 279
Author(s):  
P. Sudheer ◽  
T. Lakshmi Surekha
Keyword(s):  
Data Privacy ◽  
Low Cost ◽  
Data Access ◽  
Privacy Concerns ◽  
Cloud Data ◽  
Computing Paradigm ◽  
Attribute Based Encryption ◽  
Data Content ◽  
Identity Privacy ◽  
Cloud Servers

Cloud computing is a revolutionary computing paradigm, which enables flexible, on-demand, and low-cost usage of computing resources, but the data is outsourced to some cloud servers, and various privacy concerns emerge from it. Various schemes based on the attribute-based encryption have been to secure the cloud storage. Data content privacy. A semi anonymous privilege control scheme AnonyControl to address not only the data privacy. But also the user identity privacy. AnonyControl decentralizes the central authority to limit the identity leakage and thus achieves semi anonymity. The  Anonymity –F which fully prevent the identity leakage and achieve the full anonymity.

Comparative Study of Cryptography for Cloud Computing for Data Security

2019 ◽  
Vol 13 ◽  
Author(s):  
Priya Mathur ◽  
Amit Kumar Gupta ◽  
Prateek Vashishtha
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Elliptic Curve Cryptography ◽  
Plain Text ◽  
Hybrid Encryption ◽  
Cipher Text ◽  
Business Applications ◽  
Computing Grid ◽  
Cloud Servers ◽  
Client Side

Cloud computing is an emerging technique by which anyone can access the applications as utilities over the internet. Cloud computing is the technology which comprises of all the characteristics of the technologies like distributed computing, grid computing, and ubiquitous computing. Cloud computing allows everyone to create, to configure as well as to customize the business applications online. Cryptography is the technique which is use to convert the plain text into cipher text using various encryption techniques. The art and science used to introduce the secrecy in the information security in order to secure the messages is defined as cryptography. In this paper we are going to review few latest Cryptographic algorithms which are used to enhance the security of the data on the cloud servers. We are comparing Short Range Natural Number Modified RSA (SRNN), Elliptic Curve Cryptography Algorithm, Client Side Encryption Technique and Hybrid Encryption Technique to secure the data in cloud.

Sign in / Sign up

Export Citation Format

Share Document