Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses
Gemini 2.5 Flash
Gemini 2.5 Flash 87 tok/s
Gemini 2.5 Pro 47 tok/s Pro
GPT-5 Medium 29 tok/s Pro
GPT-5 High 37 tok/s Pro
GPT-4o 85 tok/s Pro
Kimi K2 183 tok/s Pro
GPT OSS 120B 419 tok/s Pro
Claude Sonnet 4 37 tok/s Pro
2000 character limit reached

Energy-efficient Traffic Allocation in SDN-based Backhaul Networks: Theory and Implementation (1609.04844v1)

Published 15 Sep 2016 in cs.NI

Abstract: 5G networks are expected to be highly energy efficient, with a 10 times lower consumption than today's systems. An effective way to achieve such a goal is to act on the backhaul network by controlling the nodes operational state and the allocation of traffic flows. To this end, in this paper we formulate energy-efficient flow routing on the backhaul network as an optimization problem. In light of its complexity, which impairs the solution in large-scale scenarios, we then propose a heuristic approach. Our scheme, named EMMA, aims to both turn off idle nodes and concentrate traffic on the smallest possible set of links, which in its turn increases the number of idle nodes. We implement EMMA on top of ONOS and derive experimental results by emulating the network through Mininet. Our results show that EMMA provides excellent energy saving performance, which closely approaches the optimum. In larger network scenarios, the gain in energy consumption that EMMA provides with respect to the simple benchmark where all nodes are active, is extremely high, reaching almost 1 under medium-low traffic load.

Citations (15)
List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Ai Generate Text Spark Streamline Icon: https://streamlinehq.com

Paper Prompts

Sign up for free to create and run prompts on this paper using GPT-5.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-up Questions

We haven't generated follow-up questions for this paper yet.