DeepAI
Log In Sign Up

Energy-Efficient Distributed Machine Learning in Cloud Fog Networks

05/20/2021
by   Mohammed M. Alenazi, et al.
0

Massive amounts of data are expected to be generated by the billions of objects that form the Internet of Things (IoT). A variety of automated services such as monitoring will largely depend on the use of different Machine Learning (ML) algorithms. Traditionally, ML models are processed by centralized cloud data centers, where IoT readings are offloaded to the cloud via multiple networking hops in the access, metro, and core layers. This approach will inevitably lead to excessive networking power consumptions as well as Quality-of-Service (QoS) degradation such as increased latency. Instead, in this paper, we propose a distributed ML approach where the processing can take place in intermediary devices such as IoT nodes and fog servers in addition to the cloud. We abstract the ML models into Virtual Service Requests (VSRs) to represent multiple interconnected layers of a Deep Neural Network (DNN). Using Mixed Integer Linear Programming (MILP), we design an optimization model that allocates the layers of a DNN in a Cloud/Fog Network (CFN) in an energy efficient way. We evaluate the impact of DNN input distribution on the performance of the CFN and compare the energy efficiency of this approach to the baseline where all layers of DNNs are processed in the centralized Cloud Data Center (CDC).

READ FULL TEXT
05/07/2021

Energy-Efficient AI over a Virtualized Cloud Fog Network

Deep Neural Networks (DNNs) have served as a catalyst in introducing a p...
03/27/2022

Energy Efficient VM Placement in a Heterogeneous Fog Computing Architecture

Recent years have witnessed a remarkable development in communication an...
12/19/2018

Energy Efficient IoT Virtualization Framework with Peer to Peer Networking and Processing

In this paper, an energy efficient IoT virtualization framework with P2P...
05/04/2021

The Synergy of Complex Event Processing and Tiny Machine Learning in Industrial IoT

Focusing on comprehensive networking, big data, and artificial intellige...
08/10/2019

Cloud-based Management of Energy-Efficient Dense IEEE 802.11ax Networks

During the last decade, the number of devices connected to the Internet ...
08/11/2020

Trust-Based Cloud Machine Learning Model Selection For Industrial IoT and Smart City Services

With Machine Learning (ML) services now used in a number of mission-crit...
05/02/2020

Energy Efficient Neural Network Embedding in IoT over Passive Optical Networks

In the near future, IoT based application services are anticipated to co...