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Modeling Data-Plane Power Consumption of Future Internet Architectures
With current efforts to design Future Internet Architectures (FIAs), the
evaluation and comparison of different proposals is an interesting research
challenge. Previously, metrics such as bandwidth or latency have commonly been
used to compare FIAs to IP networks. We suggest the use of power consumption as
a metric to compare FIAs. While low power consumption is an important goal in
its own right (as lower energy use translates to smaller environmental impact
as well as lower operating costs), power consumption can also serve as a proxy
for other metrics such as bandwidth and processor load.
Lacking power consumption statistics about either commodity FIA routers or
widely deployed FIA testbeds, we propose models for power consumption of FIA
routers. Based on our models, we simulate scenarios for measuring power
consumption of content delivery in different FIAs. Specifically, we address two
questions: 1) which of the proposed FIA candidates achieves the lowest energy
footprint; and 2) which set of design choices yields a power-efficient network
architecture? Although the lack of real-world data makes numerous assumptions
necessary for our analysis, we explore the uncertainty of our calculations
through sensitivity analysis of input parameters
Modeling the power consumption of a Wifibot and studying the role of communication cost in operation time
Mobile robots are becoming part of our every day living at home, work or
entertainment. Due to their limited power capabilities, the development of new
energy consumption models can lead to energy conservation and energy efficient
designs. In this paper, we carry out a number of experiments and we focus on
the motors power consumption of a specific robot called Wifibot. Based on the
experimentation results, we build models for different speed and acceleration
levels. We compare the motors power consumption to other robot running modes.
We, also, create a simple robot network scenario and we investigate whether
forwarding data through a closer node could lead to longer operation times. We
assess the effect energy capacity, traveling distance and data rate on the
operation time
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