Integrated Data Reorganization and Disk Mapping for Reducing Disk Energy Consumption

2007 ◽  
Author(s):  
Seung Woo Son ◽  
Mahmut Kandemir
Keyword(s):  
Energy Consumption ◽  
Data Reorganization ◽  
Disk Energy

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

scholarly journals SEA: SSD Staged Energy Efficient Object Storage System Architecture

2020 ◽  
Vol 9 (7) ◽  
pp. 884-893
Keyword(s):  
Energy Consumption ◽  
System Architecture ◽  
Energy Efficient ◽  
Heat Dissipation ◽  
Storage Systems ◽  
Storage System ◽  
Hard Disk Drives ◽  
Solid State Drives ◽  
Object Storage ◽  
Disk Energy

The advent of social media, smart mobile devices and the Internet of Things (IoT) has led to the generation of unstructured data at an astronomical rate, thereby creating an ever-increasing demand for object storage. These object storage systems consume a lot of energy, resulting in increased heat dissipation, greater cooling requirements (which in turn consumes more energy), higher operational costs, and excessive carbon footprint. Although there has been some progress in building energy-efficient disk systems, works on energy-efficient object storage systems are still in the nascent stage. In this paper, we propose SEA: An SSD Staged Energy Efficient Object Storage System Architecture, wherein we introduce a staging layer comprising Solid State Drives (SSDs) on top of the existing object storage system consisting primarily of Hard Disk Drives (HDDs). SSDs not only consume lesser power as compared to HDDs but are also much faster. Leveraging SSDs for staging reduces the number and frequency of requests hitting the object storage system underneath, allowing us to selectively spin down a substantial number of disks without violating any Service Level Agreements driven by Quality of Service requirements while reducing the total disk energy consumption. Given the high-performance characteristics of SSDs, this SSD staging layer significantly enhances the performance of the object storage system as a whole. As a case study, we have modeled this architecture for OpenStack Swift. Our simulation results using a Dropbox-like workload show that, even after factoring in the additional energy consumed by the SSD staging layer, our model was able to reduce the total disk energy consumption by up to 15.235 % and improve performance by up to 29.06 %.

Lay Perceptions of Energy Consumption

2009 ◽  
Author(s):  
Shahzeen Z. Attari ◽  
Michael L. DeKay ◽  
Cliff I. Davidson ◽  
Wandi Bruine de Bruin
Keyword(s):  
Energy Consumption ◽  
Lay Perceptions

Study on Energy Consumption by Land Cargo Transportation

ICCTP 2009 ◽  
2009 ◽  
Author(s):  
Shunquan Huang ◽  
Siqin Yu ◽  
Zhongmin Liu
Keyword(s):  
Energy Consumption ◽  
Cargo Transportation

Interference mitigation in point to point wireless sensor networks using LSP protocol and time division multiplexing approach

2020 ◽  
Vol 39 (4) ◽  
pp. 5449-5458
Author(s):  
A. Arokiaraj Jovith ◽  
S.V. Kasmir Raja ◽  
A. Razia Sulthana
Keyword(s):  
Energy Consumption ◽  
Large Scale ◽  
Control Parameter ◽  
Interference Mitigation ◽  
Wireless Sensor ◽  
Point To Point ◽  
A Minor ◽  
Two Stages ◽  
Time Division ◽  
And Control

Interference in Wireless Sensor Network (WSN) predominantly affects the performance of the WSN. Energy consumption in WSN is one of the greatest concerns in the current generation. This work presents an approach for interference measurement and interference mitigation in point to point network. The nodes are distributed in the network and interference is measured by grouping the nodes in the region of a specific diameter. Hence this approach is scalable and isextended to large scale WSN. Interference is measured in two stages. In the first stage, interference is overcome by allocating time slots to the node stations in Time Division Multiple Access (TDMA) fashion. The node area is split into larger regions and smaller regions. The time slots are allocated to smaller regions in TDMA fashion. A TDMA based time slot allocation algorithm is proposed in this paper to enable reuse of timeslots with minimal interference between smaller regions. In the second stage, the network density and control parameter is introduced to reduce interference in a minor level within smaller node regions. The algorithm issimulated and the system is tested with varying control parameter. The node-level interference and the energy dissipation at nodes are captured by varying the node density of the network. The results indicate that the proposed approach measures the interference and mitigates with minimal energy consumption at nodes and with less overhead transmission.

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