Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: HealthFog: An Ensemble Deep Learning based Smart Healthcare System for
  Automatic Diagnosis of Heart Diseases in Integrated IoT and Fog Computing
  Environments   Cloud computing provides resources over the Internet and allows a plethora of
applications to be deployed to provide services for different industries. The
major bottleneck being faced currently in these cloud frameworks is their
limited scalability and hence inability to cater to the requirements of
centralized Internet of Things (IoT) based compute environments. The main
reason for this is that latency-sensitive applications like health monitoring
and surveillance systems now require computation over large amounts of data
(Big Data) transferred to centralized database and from database to cloud data
centers which leads to drop in performance of such systems. The new paradigms
of fog and edge computing provide innovative solutions by bringing resources
closer to the user and provide low latency and energy-efficient solutions for
data processing compared to cloud domains. Still, the current fog models have
many limitations and focus from a limited perspective on either accuracy of
results or reduced response time but not both. We proposed a novel framework
called HealthFog for integrating ensemble deep learning in Edge computing
devices and deployed it for a real-life application of automatic Heart Disease
analysis. HealthFog delivers healthcare as a fog service using IoT devices and
efficiently manages the data of heart patients, which comes as user requests.
Fog-enabled cloud framework, FogBus is used to deploy and test the performance
of the proposed model in terms of power consumption, network bandwidth,
latency, jitter, accuracy and execution time. HealthFog is configurable to
various operation modes that provide the best Quality of Service or prediction
accuracy, as required, in diverse fog computation scenarios and for different
user requirements.

31
The categories of this paper are: ao-sci
29
The categories of this paper are: funct-an
35
The categories of this paper are: mtrl-th
17
The categories of this paper are: q-fin
13
The categories of this paper are: quant-ph
25
The categories of this paper are: patt-sol
8
The categories of this paper are: hep-ex
11
The categories of this paper are: hep-lat
36
The categories of this paper are: cmp-lg
10
The categories of this paper are: q-bio
32
The categories of this paper are: atom-ph
27
The categories of this paper are: comp-gas
33
The categories of this paper are: plasm-ph
5
The categories of this paper are: gr-qc
20
The categories of this paper are: acc-phys
9
The categories of this paper are: nlin