indian institute of technology kharagpur indian institute of management, kolkata

Indian Institute of Technology Kharagpur

Indian Institute of Management, Kolkata

Bengal Engineering and Science University, Shibpur

National institute of technology, Durgapur

Heritage Institute of Technology, Kolkata

Kalyani Government Engineeting College, Kalyani

Personal Background Indian Scenario Disaster management….

(personal experience)

Scenario User Meet

Advanced Country and Backward Case study to bring out contrast and hopes

Motivation

Summary of criticisms

No comparison or mention of the recent Japan disaster (A.2)

Lack of a detailed sketch of the architecture to be deployed (A.1, A.3)

Absence of a precise problem definition (A.4-A.6), (B.1, B.2)

Our connections with the disaster relief personnel are not clearly stated (C.1, A.9).

Communication infrastructure (A.1 – A.3)

No cellular infrastructure

We propose latency-aware ad-hoc network architecture

SP – Shelter points

MCS – Master control Station

Four tier architecture

Communication infrastructure (A.1 – A.3) Tier - 1: Rescue personnel carrying smart phones that can form a DTN; exchange information among themselves through the DTN

Tier -2: Message packets shall be unloaded into Throwboxes belonging to SPs

Tier – 3: Communication among far apart Throwboxes shall be facilitated through Data Mules

Tier – 4: One of the Throwboxes within a small group shall be elected as the center to communicate through Wi-Fi (Line-of-Sight) devices with other groups as well as with the outside world

MCS

Latency o

f 3hr 2

0 mins

matures…

.Laten

cy = 3

hr. 20 m

ins

Group 1Group 2

Group Center

Group Center

TBTB

Communication infrastructure (A.1 – A.3)

[Saha 12] S. Saha, V. K. Shah, R. Verma, R. Mandal, S. Nandi,” Is It Worth Taking A Planned Approach To Design Ad Hoc Infrastructure For Post Disaster Communication?”, ACM MobiCom Workshop on Challenged Networks (CHANTS) 2012.

Four Tier hybrid Architecture using DTN Nodes, ThrowBoxes(TBs), DataMules(DMs) and WiFi Towers(WTs)

Research problems: 4 tier architecture (A.5, B.1)

Given a (i) initial disaster hit area map which can be realized as a graph G(V,E), where V= {set of ThrowBox (TB) at each shelter point} and E={set of pathways among those TB}. (ii) finite pool of resources and (iii) load (function of no of victims and size of an affected area which is under coverage of one Throwbox) -- what is the minimum achievable latency (L) such that almost 100 % packet delivery is ensured?

Conversely for aforesaid graph with given (i) latency, and (ii) load -- what is the optimal number of network resources that are required to ensure almost 100 % of packet delivery?

As disaster hit area may change with time it is also important to answer with existing network setup and given resource what is the minimum achievable latency with least/ tolerable movement of resources to ensure almost 100% of packet delivery?

Designing the mixed-mode routing protocol lie in dealing with tradeoff between fairness and prioritized access, protocol inter-operability, authentication, universal user/device identity, group multicast, etc.

24 K

M

20 KM

Input Parameters

Area 480 Sq KM

Location Sundarban

Number of TBs 19

Location of TBs Given

Location of MCS Given

No of DTN nodes 10 DTNs/TB

Traffic Rate 4 Packets/hr/DTN11 Packets/hr/DTN

Mobility Model Post office cluster mobility model

Simulator Enhanced ONE Simulator

Affected Area

MCS

Our System Model

List of Components

Quantity

DataMules(DM) 11

WiFi Tower 7

List of Components

Quantity

DataMules(DM) 11

WiFi Tower 8

Required Resources for Satisfying 3hr 20 minutes & 2 hrs 40 Minutes Latency 3

hrs

20

min

sla

tenc

y

2 hr

s 40

m

ins

late

ncy

Comparison between Planned & Random Placement with 3 hrs 20 minutes Latency

Planned Approach Random Approach

Time vs. Delivery Probability for Planned and Unplanned Approach

Degradation of delivery probability due to Deployment Overhead for topological

changes

Time vs. Delivery Probability with Low Load

Topological change towards betterment with Time Keeping Same Latency Constraint

Initial topology Improved Topology

Google Map Based User Interface for Network

Resource Planning

Feeding InputHighlighting Activity Area and Variable Constraints are Fed

ThrowBox & Shelter Point CreationSP and TB are Drawn on Google Map using Google Map

API

Determining Distance Finding out the Geographical and Geodesic Distance between TB’s

for each Combination

Group FormationTB’s form various groups as per the Heuristic

Approach Adopted & Wi-Fi Tower is placed on the Group Center

Finding Data Mule Trajectory

Finding DM trajectory and the number of DM required for each group

Location awareness

Problem Definition

Build an annotated people/resource map Approximate position of the victims and the

resource situation shall be highlighted on a time-varying basis

Location awareness

Solution

Physical co-ordinates provided by smart-phones carried by rescue workers shall serve as anchor points

Clever Crowd Sourcing to identify other users.

Location awareness CaveatsGPS Constraints Many mobile phones (Give a snapshot of your phone)

cannot do GPS localization without wireless connection Atmospheric Condition hinders GPS localization

Mobility and Delay Delay in aggregating the data brings in accuracy as

the user has already moved from the reported position

Mobility induced error correctionMovement is predominantly deterministic

Landmark based localization

Annotate the disaster prone area graph with landmarks Identify them as anchor points

Location awareness

Proposed methodology

In-built sensors of smart phones produce/identify anchor points

Gyroscope, accelerometer – can sense turns/bumps on roads

Relative humidity sensor – can sense the presence of a place like pondBarometric sensor / gravity sensor – can sense the different floors of a building

Location awareness

Initial study: landmarks of the 2nd floor of the CSE Department, IIT Kharagpur Phone : Samsung Galaxy S2

i9100GPlatform : Android 2.3.6 App Used : SensoSaur

CSE IIT Kgp 2nd Floor Plan

04/22/23Swadhin

28

Toilet

Starting/Ending Pt.

Landmarks using GSM signal strength (Manual)29

Strongest (15-22)

Weakest (7-12)

Landmarks using Wi-Fi (Manual) 30

Linksys,HWLAB,Research,Abhishe

k_PC

Linksys,HWLAB,Research,Abhishek_PC,58.x

AP

Linksys,HWLAB,Research

Linksys,Research,HWLAB,58.x AP

Landmarks using light (Day) 31

Highest Light

Highest Light

Lowest Light

Landmarks using light (Night) 32

Bright (Tube Light)

Dark (No Tube Light)

Landmarks using Gyro/Lacc/Magnetometer/Rotation vector

33

Using online social media to gather authentic situational information (A.4) Good indicators of the situation of victims of

man-made calamities – victims themselves can tweet about the extent of damage caused and the specific help required

Recent studies show that 30% of tweets posted immediately after calamities contain situational information …

But only 17% are credible

Using online social media to gather authentic situational information (A.4) Research questions

Judge credibility of the tweets posted immediately after a calamity

Retweets not a good metric since rumors might also get retweeted millions of times

Proposed: identify authoritative experts on calamities Challenge – to discover such experts in Twitter Utilize knowledge of location of the person posting a tweet Analyze local flow patterns Sensor information can be coupled with tweets

Example of rumors after Blasts in Mumbai

http://blogs.wsj.com/indiarealtime/2011/07/15/mumbai-blasts-did-twitter-really-help/

http://www.in.com/news/current-affairs/mumbai-blast-13th-and-on-kasabs-birthday-19724405-in-1.html

Example of rumors after terrorist attack

Examples of rumors after UK Riots

http://www.guardian.co.uk/uk/interactive/2011/dec/07/london-riots-twitter

Examples of rumors after UK Riots

Comparison with relief measure Japanese earthquake India and other developing countries are still not

equipped with an organized post-disaster relief programme

Japan enjoys State and private machineries, Huge economic power, A strong socio-cultural backbone

to combat with post-disaster situation that is non-replicable in the context of India

Japan use UAVs (unnamed aerial vehicles ) and under water robots to analyze post-disaster situation and fix damaged cables

The economic strength of India does not allow of such an infrastructure and an alternative could be to use smart-phones (augmented with various sensors) to design low-cost (possibly not the best) solutions

Online social media: Source of authentic situational information (A.4)

Works as good indicators of the situation of victims of man-made calamities – victims themselves can tweet about the extent of damage caused and the specific help required

Recent studies show that 30% of tweets posted immediately after calamities contain important situational information

Research questions – credibility of the tweets posted Retweets -- not a good metric since rumors might

also get retweeted millions of times

Rumors about disaster on the social media (Mumbai Blast)

http://blogs.wsj.com/indiarealtime/2011/07/15/mumbai-blasts-did-twitter-really-help/

http://www.in.com/news/current-affairs/mumbai-blast-13th-and-on-kasabs-birthday-19724405-in-1.html

Rumors about disaster on the social media (Mumbai Blast)

Rumors about disaster on the social media (UK Riots)

http://www.guardian.co.uk/uk/interactive/2011/dec/07/london-riots-twitter

Rumors about disaster on the social media (UK Riots)

Online social media: Source of authentic situational information (A.4) Identify local authoritative experts – difficult

to track since Twitter-like social media are full of celebrities that completely shadow the presence of these experts

Challenge – to discover such experts Analyze local flow patterns

Sensor information can be coupled with tweets Relevance of a tweet reporting a damage can be

better judged if the location information of the person tweeting is available.

Comparison with relief measure Japanese earthquake India and other developing countries are still not

equipped with an organized post-disaster relief programme

Japan enjoys State and private machineries, Huge economic power, A strong socio-cultural backbone

to combat with post-disaster situation that is non-replicable in the context of India

Japan use UAVs (unnamed aerial vehicles ) and under water robots to analyze post-disaster situation and fix damaged cables

The economic strength of India does not allow of such an infrastructure and an alternative could be to use smart-phones (augmented with various sensors) to design low-cost (possibly not the best) solutions

Collaboration and management plan: Past Experience (Research) A Secure Decentralized Disaster Management

Information Network using Rapidly Deployable Wireless and Mobile Computing Technologies  -- A DIT Funded project successfully accomplished by Prof. Somprakash Bandyopadhyay (IIM Calcutta), Dr. Siuli Roy (HIT, Kolkata) and Mr. Sujoy Saha, NIT Durgapur

Work on directional antenna, DIT funded projects on peer-to-peer networks, Vodafone funded projects on mobile communication networks (Prof. Niloy Ganguly)

The communication was setup among three island near gosaba using 802.11 enabled with optilink devices configured in point to multipoint bridge with 15dbi antenna which was found to be able to cover near about 7 to 8 km range in line of sight. Using this link voice communication was established with NGOs as shown in figure.

Collaboration and management plan: Past Experience (Field work)

Collaboration and management plan: On-going work IIT Kharagpur

Comparison of infrastructure for disaster management after calamities in Japan, Pakistan, Haiti and India

Information dissemination in DTN using bipartite networks 

Online social media for gathering situational updates (jointly with BESU Shibpur )

SensoSaur - Landmark based location tracking Collaborative download framework

IIM Kolkata

Collaboration and management plan: On-going work NIT Durgapur

Layered architecture for post-disaster communication Disaster management services - Android application Google map based user interface for disaster

management BESU Shibpur

Using online social media for gathering situational updates (jointly with IIT Kharagpur)

Installing smart-phone based DTN in disaster-hit region HIT Kolkata

Wireless sensor networks – tracking miners and the mining environment, agro-parameter monitoring system, pollution monitoring system, traffic congestion detection system

Impact on curriculum

Study groups Planet-lab installation Tweet collection on social media PG level electives:

Wireless Networks for Crisis Management: IIM Kolkata + KGEC

ICTs for Disaster Management: IIM Kolkata + Heritage Institute of Technology (HIT)

Distributed Systems and Unreliability: IIT KGP + BESU

Impact on curriculum

Disaster related database development Building computer solutions Refresher course (through AICTE) Recruitment of new faculty members Summer/winter training programmes Measure to attract good MS/PhD students

Societal sensitivity development Through the established banners of

Initiative for Community Action (INCA) – IIM Kolkata National Service Scheme -- IIT Kharagpur

A structured list of members (User-Groups) NGOs Government agencies Community based organizations Victims of disaster

First User-Group meeting already held at IIM Kolkata on March 30, 2012

Four workshops for sensitization planned to be held at IIT KGP and IIM Kolkata

References http://cse.iitkgp.ac.in/resgrp/cnerg/disaster_dtn

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