5,337 research outputs found
Mediator-assisted multi-source routing in information-centric networks
Among the new communication paradigms recently proposed, information-centric networking (ICN) is able to natively support content awareness at the network layer shifting the focus from hosts (as in traditional IP networks) to information objects. In this paper, we exploit the intrinsic content-awareness ICN features to design a novel multi-source routing mechanism. It involves a new network entity, the ICN mediator, responsible for locating and delivering the requested information objects that are chunked and stored at different locations. Our approach imposes very limited signalling overhead, especially for large chunk size (MBytes). Simulations show significant latency reduction compared to traditional routing approaches
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
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