CLOUD -BASED DISASTER MANAGEMENT USING MOBILE EDGE CMPUTING MECHANISM

1017052047 Arunavo Dey

1017052018 Md. Nazmul Huq

FLOODS

• Being a riverine country, floods are very frequent in Bangladesh which takes a great toll on our agriculture

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• BEFORE AFTER

REASON

• The main goal of this paper is to make the people aware ahead of time so that damages can be minimized with the help of fog computing and mobile edge computing.
• As people can be reached effectively through mobile phone contrary to the common practices used.

MOTIVATION ( IMPORTANCE )

• Every year hundreds of people loss their property and even their lives who reside in the costal area
• An early effective warning system can reduce this number to a minimal.

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MOTIVATION ( Limitations of state of the art )

• Existing forecast system is solely dependent on radio and television which is not accessed by many all the time.
• The level of water rises so rapidly that it becomes difficult to alert immediately.
• Existing research works on fog computation contributed only developing a model, or developing a drone system to cover the area or developing a system to mark safety till now.

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MOTIVATION ( Limitations( contd ) )

• In the proposed system, we want to develop a peer to peer connection for disaster warning and needs only one peer to connect to fog layer component which will continue to work in adverse networking situations
• This proposed system needs an unique authorization technique for peers to verify another and trust

Literature review

• Our first paper is “Crowdsourcing-based Disaster Management using Fog Computing in Internet of Things Paradigm”

Ashish Rauniyar , Paal Engelstad , Boning Feng , Do Van Thanh

published in 2016 IEEE 2nd International Conference on Collaboration and Internet Computing

Literature review

• In this paper they proposed a model “Crowdsourcing based disaster management using fog computing” (CDMFC) model in IoT.
• Their proposed model consists of three layers

Sensing layer

Crowd Sourcing layer

CDMFC Model Layer

Cloud Computing Layer

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CDMFC MODEL

CDMFC Layer

Literature review

• Sensing layer
• Collects data and geotags from sensors and forwards them to next layer
• Crowd Sourcing Layer
• The disaster-related and emergency events are sent directly to the CDMFC layer for effective disaster management for public safety by this layer

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Literature review

• CDMFC layer
• Pinpoints the exact location and time
• this layer is equipped with emergency
• contact numbers and is directly accessible to public safety authority
• Cloud Computing Layer
• The non-critical data from crowdsourcing layer and other data from CDMFC model Layer are analyzed and stored in the cloud computing layer

Literature review

• Our second paper is
• “A Cyber Physical Buses-and-Drones Mobile Edge Infrastructure for Large Scale Disaster Emergency Communications”

Mamta Narang, William Liu, Jairo Gutierrez, Luca Chiaraviglio

published in IEEE International workshop on Communication, Computing, and Networking in Cyber Physical Systems (CCNCPS 2017),

AID LIFE MOBILE EDGE INFRASTRUCTURE

Literature review

• In this paper, they developed a buses-and-drones edge infrastructure that is mobile so as to effectively and efficiently support a wide-range of communications and computations services.

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• Specifically, for the disaster region, the coverage and connectivity could be provided by using remote radio head(RRH) mounted on top of the UAVs and buses.

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Literature review

• The goal is to compute the UAV trajectories so as to optimize the coverage for those hard-to-reach zones where the end-users are distributed.

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• the UAVs can continuously fly in the atmosphere in

order to provide basic coverage and emergency services, otherwise, they can fly back to the buses for recharging and/or for waiting for the next mission

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Literature review

• Our third paper is

“The Fog Makes Sense: Enabling Social Sensing Services With Limited Internet Connectivity”

Ruben Mayer, Harshit Gupta, Enrique Saurez

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published in The 2nd International Workshop on Social Sensing (SocialSens 2017),

Literature review

• In this paper they proposed a generic software architecture for social sensing applications that is capable of exploiting the Fog infrastructure.

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• It consists of three components
• Cloud Component
• Fog Component
• Sensor Component

Literature review

• One aspect of this paper is Social Sensing Services in Natural Disasters
• A user interested in knowing whether his family members are okay starts the Sensor Component of the safety check service on his smartphone.

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• Sensor Component (SC) collects the list of phone numbers belonging to the user’s family members.

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Literature review

• Whenever a Fog Component (FC) is able to connect to a SC, it queries that SC with a specific query asking to mark itself OK.
• Upon Enabling Social Sensing Services With Limited Internet Connectivity receiving this query, the SC displays an alert on the smartphone’s screen asking the user to mark himself OK.
• Then, the SC publishes the user’s phone number to its local FC, so that the FC can know about this user’s safe situation.

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Solution Approach

• In our proposed system, we propose a model with three layers
• Cloud Computing Layer
• Fog Layer
• Edge layer

Solution Approach

• Sensor Layer: This layer consists of edge devices i.e. Smart Devices
• Fog layer : In this layer we try to place computation technology on easily reachable devices i.e. mobile towers or routers or gateways
• Cloud Layer : In this layer, critical analysis is performed and any updates get generated

Solution Approach

• We try to develop such a system where peer to peer connection is emphasized when network conditions get worsened.
• Any of them can act then as an independent source to send warning message to others upon receiving authorization permission from fog layer.
• Other peers, in adverse network can receive warning and update from the authorized sender.

Solution Approach

• In normal cell phones, we can send messages from the fog layer
• In this process we can use suitable transmission channels and can perform desirable operations.
• We may need to develop an unique authorization procedure which is at the same time fast and robust.

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