Software-Directed Data Access Scheduling for Reducing Disk Energy Consumption

2012 ◽  
Author(s):  
Yuanrui Zhang ◽  
Jun Liu ◽  
Mahmut Kandemir
Keyword(s):  
Energy Consumption ◽  
Data Access ◽  
Disk Energy

scholarly journals Cloud Computing Storage Data Access Control Method Based on Dynamic Re-Encryption

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xiaodan Chen ◽  
Desheng Zeng ◽  
Shuanglong Pang ◽  
Fu Jun
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Access Control ◽  
Data Security ◽  
Control Method ◽  
Data Access ◽  
Key Generation ◽  
Time Consumption ◽  
Data Access Control ◽  
Control Accuracy

In order to improve data security, ensure user privacy, and solve the problems of low data access control accuracy, long time consumption, and high energy consumption in traditional methods, a cloud computing storage data access control method based on dynamic re-encryption is proposed. The principal component analysis method is used to reduce the dimension of the cloud computing storage data, and the random forest algorithm is further used to classify and process the cloud computing storage data according to the processing results. On the basis of data preprocessing, an access control tree is established to obtain the correlation of data nodes. Finally, the dynamic re-encryption method is used for data security state transformation, and the data access control of cloud computing storage is realized through key generation, encryption, re-encryption key generation, and decryption. The experimental results show that the data access control accuracy of the method in this paper is high, time consumption is small, and energy consumption is small, and it is more suitable for cloud computing systems with huge data and information.

scholarly journals PROVIDING HOUSEHOLD CUSTOMERS WITH SMART METERING DATA ON MOBILE DEVICES

2011 ◽  
pp. 344-351
Author(s):  
Syuzanna Hakobyan ◽  
Jan-Philipp Kohlbrecher ◽  
Johannes Pickert ◽  
Uwe Grossmann
Keyword(s):  
Energy Consumption ◽  
Mobile Devices ◽  
Carbon Dioxide Emissions ◽  
Data Access ◽  
Relevant Information ◽  
Energy Data ◽  
Consumption Behavior ◽  
Optimal Load ◽  
Optimum Price ◽  
Current Energy

One option for reducing carbon dioxide emissions is the future use of renewable instead of fossil resources. A consistent prerequisite is the optimization of household customers’ energy consumption behavior. The suitable visualization of energy data, corresponding costs and tariff information on mobile devices is essential to achieve this goal. Energy data are acquired by a smart meter and transferred over wireless networks to a mobile device to provide the customer with relevant information about his current energy usage. The household customer is hence enabled to manage his energy consumption, to hold the optimal load and meet the optimum price. Suitable typs of visualization, specific for different tariffs, are identified and presented together with necessary technologies and methods for communication and data access and delivery.

scholarly journals Leveraging on Deep Memory Hierarchies to Minimize Energy Consumption and Data Access Latency on Single-Chip Cloud Computers

2017 ◽  
Vol 2 (2) ◽  
pp. 154-166 ◽  
Author(s):  
Tahir Maqsood ◽  
Nikos Tziritas ◽  
Thanasis Loukopoulos ◽  
Sajjad A. Madani ◽  
Samee U. Khan ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Data Access ◽  
Single Chip ◽  
Memory Hierarchies ◽  
Access Latency ◽  
Data Access Latency

scholarly journals Cloud hosting services and resources utilizing efficient proxy server based speculative algorithm

2018 ◽  
Vol 7 (4) ◽  
pp. 2687
Author(s):  
Ravi Mahadevan ◽  
Neelamegam Anbazhagan
Keyword(s):  
Energy Consumption ◽  
Service Providers ◽  
Cloud Service ◽  
Data Access ◽  
Data Consistency ◽  
Current Status ◽  
Maintenance Cost ◽  
Proxy Server ◽  
Service Policies ◽  
Qos Performance

Cloud computing is an envisioned technique for service providing paradigm. Currently, many enterprises and organizations are hosting data into cloud service provider to minimize the maintenance cost, energy consumption and improve the data consistency. However, the several cloud servers facing the various hosting service policies, clients may be confused with which cloud server providers are appropriate for storing data and which hosting methodology is inexpensive. The current status quo is clients frequently put data into the single cloud and simply trust to luck. In the paper, proposes a new data hosting redundancy methodology called as Efficient Proxy Server Based Speculative (EPSBS) algorithm that provides accessibility guarantee, reducing hosting service, energy consumption and enhances Quality of Services (QoS) performance concurrently and it requires integrating two key functions. The first function is choosing numerous appropriate cloud service providers and a suitable EPSBS redundancy methodology to store data with guaranteed accessibility. The second key function is triggering a transmission process to reallocate data along with the deviations of data access prototype of clouds.  Based on Experimental evaluations, proposed methodology reduces 0.11 ET (Execution Time), and 0.02 EC (Energy Consumption) and improves 29% HS (Hosting Service size), 2.8 T (Throughput) compared than existing methodologies.

PAP: power aware prediction based framework to reduce disk energy consumption

2020 ◽  
Vol 23 (4) ◽  
pp. 3157-3174 ◽  
Author(s):  
Sumedha Arora ◽  
Anju Bala
Keyword(s):  
Energy Consumption ◽  
Disk Energy
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