Sử dụng giao thức RPL cho việc ảo hóa trong mạng cảm biến không dây

To cover the diverse requirements imposed by different applications, ROLL has specified in [7] a set of link and node routing metrics and constraints which can be static or dynamic suita

Using RPL Routmg protocol for Virtualization of Wireless Sensor Networks

Sii dung giao thiic RPL cho ao hoa trong mang cam bi^n khong day

Thu Ngo-Quynh

School of Information and Communication Technology Hanoi University ofScience and Technology

No 1, Dai Co Viet Str., Hai Ba Trung, Ha Noi, Viet Nam

Received: November 01, 2013; accepted: August 25, 2014

Abstract

Virtualization of Wireless Sensor Wefivorics (WSN) is a new concept that can provide a common platfomi upon which new federated sensor network architectures can be built, expenmented and evaluated A Virtualized Sensor Network (VSN) is formed by a subset of sensor nodes of a physical WSN that is dedicated to a certain task or an application at a given time In this paper, we investigate the requirements that virtualization imposes on the routing procedure of the involved WSNs and propose to implement RPL routing protocol for this virtualization purpose In addition, we consider a special application case of virtualization and investigate the operation of RPL in this case for establishing different instances per application We also present how different QoS levels can be offered by adjusting routing metncs of RPL scheme Our approach is validated using computer simulations

Keywords: Virtualization, Routing protocol, Wireless sensor nehvorks

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1 Introduction

Nowaday, WSN is working as isolated islands

and most of the sensed data is not shared among

different administrative domains Reasons for using

dedicated sensor networks include the limited

sensing, processing and communication abilities of

the nodes, severe power constraints and most of all,

the lack of algorithms, protocols and techniques for

deploying complex sensor networks Under a wide

vanety of conditions (large scale network of

thousands nodes, crowded urban area or difficult

terrains), independent sensor networks dedicated to a

deployment technique That is why it is necessary to

deploy a WSN that is capable of sharing their

physical resources or exchanging information over

geographically isolated areas This concept is called

Virtual Sensor Networking [I]

In principle, a Virtual Sensor Network (VSN)

consists of sensor nodes providing the ability to be

leveraged by a multitude of different administrative

Corresponding Author, Tel- (+84) 912,528.824

domains, platforms, communication protocols and services In a virtualized sensor networks, new

applications can be served without requiring installing new sensors but just reusing existing ones For this important purpose of VSN, the most

objective of VSN is tbe resource virtualization In

other words, network and node resources play a very significant role for virtualization of WSN Given dial the VSN system will consist of heterogeneous devices with different capabilities anil communication resources, resource virtualization missions are:

Communication resources/connectivity: As the

heterogeneous devices of the system may also differ

in their communication capabilities, to optitmse the overall network performance, routing can take advantage of the heterogeneous neighbours capabilities Thus, the sensor transmission range or the supported wireless interface will be considered as

are made

- Dynamic resource control: The (heterogeneous)

devices included in a VSN may be battery or mains

powered As the energy consumption depends on a

nmnber of operational parameters, these may be

tuned dynamically to prolong the network lifetime,

- Hardware node resources: affect the complexity of

the routing protocol that can be executed For

example, given that security is one of the key

requirements, the implementation of trust logic can be

distributed among nodes in a proportional to

hardware resources manner

- Security services virtualization: Different security

levels have to be supported to improve tbe probability

of reaching tbe destination for special purpose

messages These messages may include alarm-related

messages, service discovery messages which are of

higher priority (more vital) in some applications than

regular messages carrying sensed data

- Energy level/node status: To improve the network

nodes to report their status and energy level is

included This information is also valuable for the

routing protocol, since taking into account the

neighbor's energy levels significant reduction in the

energy consumption rate can be achieved The fact

that it is a requirement to exchange such information

in VSN, can and will be exploited also at the routing

layer to prolong the network lifetime

Scalability and mobility: To benefit from the

virtualization of the wireless sensor nodes and

network, all the nodes involved in the VSN have to

cooperate for trust building and routing purposes

Although virtualization targets the reduction of the

already installed sensors, m this imcontrolled

environment, the number of nodes in the

neighbourhood can fluctuate Thus, it is mandatory

for the relevant protocols to support both scalability

and mobility

From this point of view, virtualization of WSN

aims at exploiting the dynamic symbiotic

relationships of application and virtualization

requirements that will produce a carefully crafted

platform of sensor nodes [2] [3], In other words, a

requirement of energy efficiency, seamless

connectivity, operational reliability and security [4]

[5] In order to satisfy this requirements,

virtualization process will influence the design

support of layer 3 (routing) of the protocol stack

significanfly In addition, when designed

appropriately, VSN routing protocol can affects

achieved quality of service (QoS) for different

applications Furthermore, we realize that over a

same WSN infrastructure, different applications

require different QoS levels but satisfymg this is not

always a straightforward task In order to overcome this problem, we can think about choosing appropriate routing metrics of the routing protocol for handling traffic of these applications differently

A routing protocol satisfying the above requirements of virtualization is IPv6 Routing

Directed Acyclic Graphs (DAG) and defines the rules

parent in the DAG, thus forming a tree To cover the diverse requirements imposed by different applications, ROLL has specified in [7] a set of link and node routing metrics and constraints (which can

be static or dynamic) suitable to Low Power and

protocol offers an additional feature which is very crucial for supporting virtual networks over LLNs: it supports the construction of multiple routing trees with the same or different destination (root) node based on different routing metrics, which form the so-called routing instances In other words, different routing paths firom the sensor nodes towards the sink node can be constructed to service different applications optimizing a different performance aspect each time For example, for e-health application, high reliability and low latency are required while for temperature and condition control applications, extended network lifetime is far more important than reliability For this reason, we anticipate that the adoption of RPL protocol brings

virtualization comes into the scene

Routing design plays an important role for VSN but to the best of our knowledge, the research of impact of virtualization on routing, especially on RPL protocol is rarely investigated recently In addition, there is also no research study that proposes a virtualized routing solution based on RPL that can provide different QoS for different applications in VSN In this paper, we consider a special case of virtualization and investigate the operation of RPL in this case for establishing different instances per application We also present how different QoS levels can be offered by adjusting routing metrics of RPL scheme Our approach is validated using computer simulations

The rest of the paper is organized as follows: in section I! we describe the steps that need to be carried out for virtualization purpose of an application that monitors the crossing of animal and sliding of rock

In section III we provide simulation results to show how the different adopted metrics can lead to different performance aspect optimization over the same sensor network Finally, conclusions are dra-wn

in section IV

2 R P L Protocol

In this paper, we consider here a geographical

application case of two VSNs for monitoring the

crossing of animal (VSNi) and sliding of rock

(VSN2), where virtualization requires an efficient use

of resources

their ranks are set up equal to received rank plus 1 Based on this information, nodes can select their parents, siblings and prefer-parent

Fig 1 Rock sliding and animal crossing [8]

More concretely, we will examine how RPL

operates in order lo establish two instances for these

two applications: one instance for rock sliding and

one instance for animal crossing over a same physical

sensor infrastructure

In order to accomplish this mission, RPL needs

to perform foilowmg steps:

Step 1: Root broadcasts DIO message in order

to establish DAG for the first instance In this step,

the DIO message contains Rankld^I instanceld^l

and DAGId=l and only nodes belong to VSNi can

receive this DIO message

All nodes that receive this message will join to

instance numbered 1, set up root as their preferparent

equation:

Rankld^Rankld of root + /

Fig 2 Operation of P ' step

These nodes continue to broadcast DIO message

to their neighbors with the same instanceld and

ranks

Step 2 Nodes continue to broadcast DIO

message for the first instance

Fig 3 Operation of 2"'' step

Step 3 Root broadcasts DIG message in order to

create second instance Sinular to the first step, root continues to broadcast DIO message to all its neighbors in both VSNi and VSN2 for establishing second instance with the following information:

Rankld=! Instanceld=2 andDAGId=l

This step is similar to tbe step when establishing the first instance

Fig 4 Operation of 3"* step

Step 4 Nodes continue to broadcast DIO

message of the second instance in order to select parents, siblings and prefer-parent

Fig 5 Operation of 4 * step

Step 5 This step helps to transmit data to the

root When received DATA message, root will check

links are dead, the simulation is terminated If no,

nodes will continue lo transmit data lo the root In the

following figure, instance 1 is presented by black line

while instance 2 is presented by orange line More

VSNi while instance 2 consists nodes belong to both

VSNi and VSN2

Fig 6 Operation of 5* step

Step 6 This step is for updating rank, parents,

sibling and prefer-parent Periodically, nodes need to

update information relating rank, parents, sibling and

prefer-parent by sending DIO message

Fig 7 Operation of 6"" step

3 Performance evaluation

In this section, we consider two routing metrics:

hop count and residual energy and evaluate network

lifetime of VSNs when setting these metrics for

object fimclions of RPL Finally, we examine a

topology, where RPL needs to provide different

quality of service levels for these sliding rock and

crossing animal applications by using the above

routing metrics (hop-count and residual energy)

From the case descnbed m the above section,

we realize that VSNi contains nodes that are

distributed in a mountainous area in order to monitor

the animal crossing while VSN2 monitor the sliding

of rock in a more dangerous area Because of

different geographical conditions of these two VSNs,

it is easier to remove or change the sensors of VSNj

maintain the network lifetime of VSN2 than VSNi

object fimctions for RPL Tbe above steps of RPL

scheme were implemented in OMNET++ simulator

We simulate here two VSNs, each has hundred nodes

that are distributed randomly in an area of

3.1 Scenario 1 The first scenario will contain only one instance that covers nodes of both VSNi and VSN2, but the routing metrics for this instance is hop count or node energy We evaluate the network lifetime of this scenario in these two cases in order to know which routing metric can provide better network lifetime The following figure plots the number of dead nodes

in two cases

Fig 8 Number of dead nodes From this figure, we realize that using hop count

as routing metric provides higher number of dead nodes than energy It can be explained easily because when using hop count, routing decision of RPL does

foilowmg figure presents network lifetime of the

metric of RPL Clearly, the first node dead parameter

of case using node energy is 188 rounds, and much more better than the first node dead parameter of case using hop c o u n t - 61 rounds

JJ

Fig 9 Network lifetime of P ' scenario 3.2 Scenario 2

The purpose of this scenario is to provide different QoS levels for two applications: rock sliding and animal crossing through virtualization From the

better network lifetime, we can select node energy as routing metric for RPL, while VSNi can use hop count for object function of RPL In this scenario, instance numbered 1 is transmitted within VSN| only while instance numbered 2 is transmitted within both

of two VSNs and present in the following figure:

J

Fig 10 Number of dead nodes of 2'"' scenario

From the above figiu-e, we realize that the

number of dead nodes VSN? is smaller than VSNi

More concretely, the network lifetime of two VSNs

are presented in the following figure by two metrics,

first node dead and total live round Total live round

is the network operation time until all nodes are out

rounds

First node dead is the number of round when

first node in the network runs out of energy

The first node dead of VSNi is after 60 rounds,

while for VSN2 it is after 114 rounds The total live

round of VSNi is only 174 rounds while the total live

roimds of VSN2 is 322 Obviously, the network

lifetime of VSN2 is better than VSN| or the quality of

service of VSN2 is better than VSNi This feature can

count as routing metric for RPL object fimction,

while instance 2 of VSN2 covers nodes of both VSNs

and utilizes node energy for RPL object fimction

That is why it is possible to use routing metrics of

RPL for providing different quality of service levels

for different applications in case of virtualization

4 Conclusion

In this paper, we investigate the impact of

virtualization on routing procedure of WSN We also

geographical context and provide this QoS

differentiation by setting object fiinctions for the RPL

protocol Via simulation, the QoS requirements are

satisfied by using hop count and node energy for

object function of RPL protocol

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J Fig 11 Network Hfetime of 2""* scenano

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