Energy-Efficient Data Transfers in Large-Scale Distributed Systems

2013 ◽  
pp. 363-380
Keyword(s):  
Distributed Systems ◽  
Energy Efficient ◽  
Large Scale ◽  
Efficient Data ◽  
Data Transfers

Energy Efficient Data Collection in Large-Scale Internet of Things via Computation Offloading

2019 ◽  
Vol 6 (3) ◽  
pp. 4176-4187 ◽  
Author(s):  
Guorui Li ◽  
Jingsha He ◽  
Sancheng Peng ◽  
Weijia Jia ◽  
Cong Wang ◽  
...  
Keyword(s):  
Data Collection ◽  
Internet Of Things ◽  
Energy Efficient ◽  
Large Scale ◽  
Computation Offloading ◽  
Efficient Data ◽  
Efficient Data Collection

scholarly journals Energy-efficient data transfers in radio astronomy with software UDP RDMA

2018 ◽  
Vol 79 ◽  
pp. 215-224 ◽  
Author(s):  
Przemyslaw Lenkiewicz ◽  
P. Chris Broekema ◽  
Bernard Metzler
Keyword(s):  
Radio Astronomy ◽  
Energy Efficient ◽  
Efficient Data ◽  
Data Transfers

ERIDIS: ENERGY-EFFICIENT RESERVATION INFRASTRUCTURE FOR LARGE-SCALE DISTRIBUTED SYSTEMS

2011 ◽  
Vol 21 (02) ◽  
pp. 133-154 ◽  
Author(s):  
ANNE-CECILE ORGERIE ◽  
LAURENT LEFEVRE
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Distributed Systems ◽  
Energy Efficient ◽  
Large Scale ◽  
Generic Framework ◽  
Peer To Peer Systems ◽  
Dedicated Networks ◽  
Electrical Consumption ◽  
Hardware Designs

At the age of petascale machines, cloud computing and peer-to-peer systems, large-scale distributed systems need an ever-increasing amount of energy. These systems urgently require effective and scalable solutions to manage and limit their electrical consumption. As of now, most efforts are focused on energy-efficient hardware designs. Thus, the challenge is to coordinate all these low-level improvements at the middleware level to improve the energy efficiency of the overall systems. Resource-management solutions can indeed benefit from a broader view to pool the resources and to share them according to the needs of each user. In this paper, we propose ERIDIS, an Energy-efficient Reservation Infrastructure for large-scale DIstributed Systems. It provides a unified and generic framework to manage resources from Grids, Clouds and dedicated networks in an energy-efficient way.

An Energy-Efficient Data Dissemination Scheme in Large-Scale Wireless Sensor Networks

2013 ◽  
Vol 5 (3) ◽  
pp. 34-54
Author(s):  
Shiow-Fen Hwang ◽  
Han-Huei Lin ◽  
Chyi-Ren Dow
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Storage ◽  
Energy Efficient ◽  
Large Scale ◽  
Data Dissemination ◽  
Wireless Sensor ◽  
Event Data ◽  
Efficient Data

In wireless sensor networks, due to limited energy, how to disseminate the event data in an energy-efficient way to allow sinks quickly querying and receiving the needed event data is a practical and important issue. Many studies about data dissemination have been proposed. However, most of them are not energy-efficient, especially in large-scale networks. Hence, in this paper the authors proposed an energy-efficient data dissemination scheme in large-scale wireless sensor networks. First, the authors design a data storage method which disseminates only a few amount event data by dividing the network into regions and levels, and thus reducing the energy consumption. Then, the authors develop an efficient sink query forwarding strategy by probability analysis so that a sink can query events easily according to its location to reduce the delay time of querying event data, as well as energy consumption. In addition, a simple and efficient maintenance mechanism is also provided. The simulation results show that the proposed scheme outperforms TTDD and LBDD in terms of the energy consumption and control overhead.

Efficient Update Control of Bloom Filter Replicas in Large Scale Distributed Systems

2010 ◽  
pp. 785-807 ◽  
Author(s):  
Yifeng Zhu ◽  
Hong Jiang
Keyword(s):  
Distributed Systems ◽  
Large Scale ◽  
Control Mechanism ◽  
False Negative ◽  
Bloom Filter ◽  
Analytical Models ◽  
Bloom Filters ◽  
Distributed Environment ◽  
Membership Query ◽  
Efficient Data

This chapter discusses the false rates of Bloom filters in a distributed environment. A Bloom filter (BF) is a space-efficient data structure to support probabilistic membership query. In distributed systems, a Bloom filter is often used to summarize local services or objects and this Bloom filter is replicated to remote hosts. This allows remote hosts to perform fast membership query without contacting the original host. However, when the services or objects are changed, the remote Bloom replica may become stale. This chapter analyzes the impact of staleness on the false positive and false negative for membership queries on a Bloom filter replica. An efficient update control mechanism is then proposed based on the analytical results to minimize the updating overhead. This chapter validates the analytical models and the update control mechanism through simulation experiments.

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