Transcript

Kai Li

Division of Computer Science

University of Central Florida

Mobile Data Collection Networks for Wireless Sensor Networks*

Traditional Wireless Sensor Networks

Wireless Sensor Networks are composed of a large number of small devices (irreplaceable in many applications), called wireless sensors, which are normally distributed in an ad hoc manner. Wireless sensors gather information, such as

pressure, humidity, temperature, speed etc. Wireless sensors typically share some common

characteristics, such as small size, low power, low cost etc.

Applications

MilitaryBattle damage assessment, nuclear,

biological and chemical attack detection, etc. Environmental

Forest fire detection, habitat monitoring, etc. Health applications

Patients monitoring, drug administration, etc. Industry

Production temperature, humidity, pressure control

Wireless Sensor Networks

Internet

Sink/Base Station

Wireless Sensor

...

Data Collection in Traditional WSNs Data Collection is of paramount importance

sensing data needs to be routed to the sink or base-station (sometimes further transmitted over the Internet through them) for further analysis or applications.

Data transmission over the ad hoc network formed by resource-constrained sensorsdata generated at each sensor can only reach their

neighbors within communication range data go through multiple sensors on their way to the

sink

Data Collection Issues in traditional WSNsCommunication is a major energy consumer for those energy-constrained sensors Multi-hop communication

→ sensors assume dual roles: data source and data forwarder

Fixed routing path (towards static sink)→ sensors in the neighborhood of the sink will deplete their energy faster (“energy hole problem”), which render the WSN dysfunctional prematurely

WSNs with Mobile Elements

Adding Mobile Elements is considered to be a promising solution to the aforementioned problem. Existing approach includes

Mobile Sink Approach

Mobile Messenger Approach

Mobile Sink Approach

Mobile Sink

Sinks moves to different locations in the network field during WSN lifetime

Sojourn for a time interval at each location

When sojourning at each site, routing path of sensors are updated and traffic is redirected towards the current sink site

Mobile Sink Approach

AdvantagesThe “neighborhood” of the sink does not remain

unchanged any more, thus distributing the burden of those sensors over the whole network, preventing premature cessation of network operation.

LimitationsSensors still do multi-hop communicationMobile sinks are not feasible for some applications

(e.g. it’s not possible for them to have access to Internet in harsh environments)

Not scalable for large scale WSNs

Mobile Messenger Approach

Sink

Mobile Messenger

Sinks are static Mobile messengers start out

from sink site, following a path, to visit each sensor

Sensors upload their data to the messenger (in a single hop ) when they approach.

Mobile messengers go back to he sink to deliver the collected data

Mobile Messenger Approach

Advantages sensors transmit data in a single hop, and do not

forward data for other sensorslow communication overhead w.r.t. routing energy consumption at each sensor is greatly

reduced. Limitations

every sensor has to wait a long time for the messenger to approach, thus resulting in long or even unpredictable latency

long wait may result in sensor buffer overflows, thus reducing data delivery ratio

Our Approach—the MDCNet

We propose a new data collection paradigm—the Mobile Data Collection Network (MDCNet) for WSNs that featuresEnergy efficiency (single-hop

communication model)Short latency (compared with mobile

messenger approach)High data delivery ratio

MDCNet is a self-deployed mesh network

formed by Mobile Relay Nodes (MRNs) (e.g. mini robot, autonomous vehicles), each serving a certain number of sensors

with partial and intermittent connection among MRNs (MRN only communicate with other neighboring MRNs when it needs to transmit data)

through which data could be uploaded by sensors in a single hop and electronically transmitted towards the sink or base-station

MDCNet - A new data collection paradigm

MDCNet - A new data collection paradigm

A Conceptual View of MDCNet

Mobile Relay Node

Sensor

MDCNet - A new data collection paradigm

The MDCNet is designed with the following three major considerations the number of sensors each MRN serves should

be balanced to reduce sensor contentionsensor’s data should be collected in a timely

manner to avoid data loss caused by sensor buffer overflows

data relay among MRNs should conform to a reliable protocol to guarantee safe arrival at the sink

Each of the above three requirements is satisfied by corresponding techniques

Load-balanced Area Partitioning Deterministic Area Partitioning (DAP) Adaptive Search and Conquer (ASC)

Local Data Collection Protocol

Data Relay Protocol

MDCNet - A new data collection paradigm

Load-balanced Area Partitioning: DAP approach

𝑅√2

𝑅

2𝑅

Assumption sensor locations are known

a priori Centralized administration

of MRN deployment is possible

Simple partition Evenly divide the region into

several parts Associate each partition

with a mobile relay node MRN moves back and forth

in a snake-like pattern to collect data from sensors

The Adaptive Search and Conquer (ASC) approach has the following characteristics

It assumes no knowledge of sensor locations

No centralized deployment (i.e. decentralized self-deployment) is required

MRNs cooperatively and incrementally search and conquer different regions until the whole WSN has been covered

Load-balanced Area Partitioning: ASC approach

2R𝐿

𝐿

1 2

3L+2R

L+2R

Load-balanced Area Partitioning: ASC approach These Target Areas will be explored by other MRNs, upon their receipt of the NOTICE message from the MRN that claimed the bottom left region as its Service Area4th Expansion by 2R

2nd Expansion by 2R

3rd Expansion by 2R1st Expansion by 2R

After conquer the area as its service area, the MRN will move in a snake-like pattern the service area to collect data from sensors

MRNs set a random timer in the beginning, the MRN whose timer expires first will be the first one to start out and at the same time send out a TIMEOUT message. Others will cancel their timer upon receipt of this message.

The sensor is not served within a predefined time frame . (This is to make sure that a sensor does not get repetitive service when MRN is within its communication range )

Local Data Collection Protocol

Mobile Relay Node Sensor

time

4. Start sending data packet

...

1. HELLO message

2. ACK message

If satisfy service requirement, then stop and set a wait timer

3. START message

5. FINISH message

Cancel timer &receive data

Move& broadcast

timeout

End Session

Data Relay ProtocolData relay hierarchy of DAP

O(Sink Location)

1 2 3

654

87 9

1

54 2

7 8 6 6 3

Sink

Data Relay ProtocolIn the ASC approach, the data relay hierarchy is automatically established as MRNs cooperatively search the sensor field.

1

42 3

8 5 6 7 9

Sink

O(Sink Location)

128673954

Data Relay ProtocolMRN (child)

time

...

HELP message

Ready messagestop and set a wait timer

start sending data packet Cancel timer &receive data

stop serving & seek help

MRN (parent)

FINISH messageResume serving sensors Session end

transmit data

Serving sensors

timeout

Simulation Environment

Simulation Environment: NS2 Network Topology: 100m by 100m Sensor Nodes

data generation rate:10bit very 0.1 secondsbuffer capacity: 10KBcommunication radius: 7mrandom distribution

Mobile Relay Nodes:moving speed: 2m/scommunication radius: 40m

Performance Metrics

Data delivery ratioratio of the data packets delivered to the sink and the data packets generated by the sensors

Latencysensors’ average service interval by mobile relay nodes

Deployment time (for ASC approach)average searching time of mobile relay nodes

Effect of Sensor Density

DAP cannot dynamically adjust the size of its service area with the increase of number of sensors (i.e. its load keep increasing)

ASC tries to keep given workload (number of sensors to serve), and adjust its service area size accordingly

When there are less than 300 sensors, MRN has not reach full load. Thus, in our setting 300

is the full load point

When sensors are very sparse, the 1st MRN takes a long time to conquer a

service area, which dominates the deployment

timeAs sensors density

increases, more MRNs are dispatched, which

contributes to the gradual increase in

deployment time

Effect of Load factor (ASC approach)

When load factor exceeds 60, the number of partitions can not decrease any more (i.e. at least 4 parts)

Taking all factors (latency, data delivery ratio, cost in terms of number of MRNs needed) into account, the optimal load factor in our setting should be between 40 to 50.

performance does not degrade

anymore, because partition

number has reached

minimum

Too many sensors per

MRN. They are overloaded

Latency shows rapid increase

around 50, as a result of overload

Conclusion and Future Work A Mobile Data Collection Network has many

advantages: Single-hop communication saves sensors energy to the

largest extent Electronic transmission of sensing data over MDCNet

contributes to shorter latency Self-deployment and distributed cooperation of MRNs is fit for

large scale WSNs

Future Work Further reduce assumptions such as location awareness (i.e.

GPSs) Generalization to irregular-shaped service areas Consideration of obstacles and/or constrained path


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