dynamic route construction based on measured characteristics of radio propagation in wireless sensor...

8/13/2019 Dynamic Route Construction Based on Measured Characteristics of Radio Propagation in Wireless Sensor Networks

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International Journal of Advanced Computer Science, Vol. 2, No. 3, Pp. 85-98, Mar. 2012.

ManuscriptReceived:

17, Dec., 2011

Revised:14, Jan., 2012

Accepted:11, Feb., 2012

Published:15, Apr., 2012

Keywordswireless sensor

network,

route

construction,

transmission

power control

Abstract In this paper, we propose a

dynamic route construction method based

on measured characteristics of radio

propagation in a real environment. Our

method first measures characteristic of

radio propagation for each link, and

determines a communication route fromevery node to the sink node and its

transmission power based on the measured

characteristics. While operating the system,

our method dynamically reconstructs

communication routes according to the

change in the characteristics of radio

propagation. We conduct experiments to

verify that our method can construct

efficient communication routes in terms of

energy-efficiency and quality of

communication even when the

characteristics of radio propagation

dynamically changes.

1. IntroductionRecent rapid advances in wireless communication

technologies have led to great interest in wireless sensor

networks (WSNs), which have been constructed only by

using sensor devices with wireless communication facilities

(sensor nodes) [1]. In WSNs, it is general that nodes are

equipped with poor devices due to several constraints such

as size and cost. In particular, since nodes work on limited

battery power, energy efficiency is one of the most

important issues. Therefore, many studies to reduce power

consumption have been conducted [2-4]. Among them,

controlling the transmission power of each node has beenone of the hottest research issues in recent years [5-6]. In

particular, there have been many studies on constructing

energy-efficient routes by controlling the transmission

power of individual node. However, since most of them

have assumed an ideal environment in which radio signalstransmitted by nodes propagate equally in all directions,

they do not work in real environments. This is because radio

waves generally have complicated propagation

This research was supported by Grant-in-Aid for Young Scientists (B)

(23700078) of JSPS, and for Scientific Research (S)(21220002) of MEXT,

Japan.

Akimitsu Kanzaki ([email protected]_u.ac.jp), Takahiro Hara, &

Shojiro Nishio, Osaka University, Japan.

Yasuhiro Nose, NTT DATA CORPORATION, Japan.

characteristics such as shadowing and fading. Moreover,

such characteristics become more complicated due to the

presence of obstacles such as walls and desks.

In [7], we have proposed RCPDS (Route Construction

based on Packet Delivery ratio and received Signal strength),

which constructs routes and controls transmission powers

based on the measured characteristics of radio propagation.RCPDS determines the route and transmission power of

every node based on the packet delivery ratiosand average

RSSIsfor all links measured in a real environment. Here, the

packet delivery ratio is defined as the ratio of the number of

packets correctly received by the receiver to that of all

packets transmitted from the transmitter. The average RSSIis defined as the average of the RSSIs (Received Signal

Strength Indicator) of correctly received packets. We have

also carried out some experiments in a real environment and

verified that RCPDS can construct an efficient route in

terms of energy-efficiency and quality of communication.

RCPDS determines routes and transmission powers of

nodes before starting the operation of a WSN assuming thatthe characteristics of radio propagation do not change. Thus,

it may not work in a dynamic environment in which the

characteristics of radio propagation dynamically change due

to appearances or removals of obstacles. In this paper, we

propose D-RCPDS (Dynamic Route Construction based onPacket Delivery ratio and Signal to noise ratio), that

dynamically constructs routes according to the change in the

characteristics of radio propagation. In D-RCPDS, each

node monitors the packet delivery ratios and SNRs (Signal

to Noise Ratios) from its neighboring nodes to itself. Aneighboring node is defined for each node as a node whose

transmitted packets are overheard. When the quality of

communication from a neighboring node deteriorates, the

node reconstructs the route from the neighboring node. In

addition, when the quality of communication becomes

excessively better than the requirement specified by theapplication, D-RCPDS tries to find another route that is

more energy-efficient while satisfying the requirement.

The rest of this paper is organized as follows. In

Section 2, we present the assumed environment in this

paper. In Section 3, we discuss related work including

RCPDS which is a basis of our method. The details ofD-RCPDS are explained in Section 4. We present the result

of an experiment to evaluate the efficiency of D-RCPDS in

Section 5. Finally, we conclude the paper in Section 6.

Dynamic Route Construction Based on Measured

Characteristics of Radio Propagation in WirelessSensor Networks

Akimitsu Kanzaki, Yasuhiro Nose, Takahiro Hara, & Shojiro Nishio


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International Journal Publishers Group (IJPG)

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2. AssumptionIn this paper, we assume a monitoring application which

measures a rough distribution of the sensor data in the

whole target region. Each node sends packets to the sink

node via a single-hop or multi-hop route. The applicationspecifies the required packet delivery ratio. This indicates

that routes of all nodes must achieve a packet delivery ratio

equal to or larger than this ratio. For example, when a user

wants to gather 70% of the data acquired by all nodes, the

required packet delivery ratio becomes 0.7. Here, the packetdelivery ratio of a multi-hop route is defined as the product

of the packet delivery ratios of all links on the route. For

example, when the packet delivery ratio of link from nodeA

to node B ( PDR ) and that from B to S ( PDR )correspond to 0.8 and 0.9 as outlined in Fig. 1, the packet

delivery ratio of the multi-hop route fromA to S(PDR) isderived as their product, i.e., 0.72 (= 0.8 0.9).

Fig. 1 Packet Delivery Ratio of a Multihop Communication Route.

Each node can control its own transmission power from

discrete n levels. In addition, each node appends its

identifier and a sequence number, which is incremented

every time the node transmits a packet, to all packets.

Moreover, each node is always able to receive the packets

transmitted from its neighboring nodes.

3. Related workThis section briefly presents some conventional studies

on route construction by controlling transmission power in

WSNs and a radio propagation model that these studies

assume. Also, we discuss the problems of these

conventional studies. Then, we present some studies on the

characteristics of radio propagation and transmission powercontrol in WSNs. In addition, we briefly present RCPDS,

which is a basis of our proposed method.

A.Existing Route Construction MethodsThere have been many studies on route construction by

controlling the transmission power of individual nodes [6],

[8-11]. For instance, in GPER (Geographic Power Efficient

Routing) [6], each node constructs a route to the destination

node to minimize the total transmission power consumed by

all nodes on the route. In addition, there are many studies on

clustering nodes in the network to improve

energy-efficiency [8-9], [11]. These methods form multiple

clusters in a network, in each of which a cluster head and

cluster member(s) exist. When gathering readings, members

in a cluster send their readings to the cluster head. Each

cluster head aggregates the received readings and sends

them to the sink node. By doing so, the number of packet

transmissions at each node can be decreased. As a result, thepower consumption in the entire network can be reduced.

These conventional methods assume the radio

propagation model [5-6], [12-14] in which the relationship

between the transmission power required to perform a

communication and the distance between the sender and the

receiver is represented by the following equation:

= :constant. (Equ. 1)Here, denotes the distance between the sender and

the receiver, and denotes the transmission powerrequired to perform a communication between the nodes. is the power loss constant and is typically between 2 and 4depending on the distance between nodes [15]. In this

model, the propagation of radio signals is modeled as a

simple equation only using the distance from the

transmitter. In other words, this model assumes that radio

signals propagate equally in all directions. However, such a

simple model cannot be applied to real environments.

B.Link Quality QuantificationThere have been some studies on measuring the

characteristics of radio propagation in real environments.

ETX (Expected Transmission Count) [16-18] is one of

the well-known metrics among those studies. To calculate

the ETX of the link between nodesA andB, both end nodes

periodically broadcast probe packets (packets for

measurement) and calculate the packet delivery ratios of

links from another to themselves. After that, the ETX of the

link is calculated by the following equation:

ETX = 1

!" !". (Equ. 2)

Here, !"denotes the packet delivery ratio of thelink fromA toB and !" denotes that fromB toA. Forexample, assume that nodes A and B have transmitted 10

probe packets. If node B has correctly received nine probe

packets from node A and node A has correctly received

eight probe packets from nodeB, the ETX between nodesA

andBbecomes 1.39 (= 1 0.9 0.8# ).STLE (Short-Term Link Estimator) [19-20] is a metric

that estimates the characteristics of radio propagation in a

short term. To derive the STLE, each node overhears

packets transmitted from its neighboring nodes. When the

node overheard consecutive h packets from a neighboring

node, it determines that the present quality ofcommunication from the neighboring node to itself is good.In [20], it is concluded that an appropriate value for h is

between 3 and 5 in a real environment.

C. Transmission Power ControlSome transmission power control methods based on the

measured characteristics of radio propagation have also

been proposed in recent years. For example, ATPC

(Adaptive Transmission Power Control) [10] controls the

transmission power of the sender of a link based on the

measured characteristics of radio propagation. Specifically,the transmission power of the sender is determined based on

the RSSI measured by the receiver. This method achieveseffective packet transmissions in terms of energy-efficiency

and quality of communication between a pair of nodes.

S Sink node

9.0=BSPDR8.0=ABPDR

)9.08.0(72.0 ==ASPDR

B

A


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87

However, these studies only consider the characteristics of

radio propagation of a link (i.e., one-hop communication

between a pair of nodes).

D.RCPDSRCPDS [7] determines the route and the transmission

power of every node based on the measured characteristics

of radio propagation.

First, each node broadcasts several probe packets with

each transmission power to measure the characteristics of

radio propagation. The nodes that receive the probe packets

calculate the packet delivery ratios and the average RSSIs

from the transmitter to themselves for each transmission

power.

Next, the sink node collects information on the packet

delivery ratios and average RSSIs for all links (pairs of

nodes). After that, the sink node determines the route andthe transmission power of each node according to the

following procedure:

1. Deriving the packet delivery ratio model (PDR model)

First, the sink node classifies the gathered information on

packet delivery ratios for all links by their average RSSIs,

and sets the confidence packet delivery ratiofor each RSSI.

Here, the confidence packet delivery ratio for an RSSI is

defined as the lowest packet delivery ratio among top k[%]

of those for the corresponding RSSI. For example, when the

sink node gathered information on 100 packet delivery

ratios with the average RSSI of $90[dbm], and k is set as95[%], the confidence packet delivery ratio for RSSI of

$90[dbm] becomes the 95th largest packet delivery ratio.By doing so, the sink node derives the PDR (packet deliveryratio) model, that show the confidence packet delivery

ratios for all observed RSSIs as shown in Fig. 2.

Fig. 2 PDR Model in RCPDS.

2. Determining initial link powers

Next, the sink node sets the confidence packet delivery

ratio for each link according to its average RSSI. After that,the sink node sets the temporal transmission power called

the initial link powerfor each link. The initial link power of

a link is defined as the minimum transmission power of the

transmitter that achieves the maximum confidence packet

delivery ratio.

3. Constructing routes

After setting the initial link powers of all links, the sink

node constructs routes from all nodes by applying the

Dijkstra algorithm [21] in which links whose confidence

packet delivery ratios are more than or equal to the ratio

specified by the application, and their initial link powers are

edges and their costs in the directed graph. After this step, atree-shaped topology in which a root is the sink node and a

branch is the wireless link is constructed. Each node sets the

path to the root on the tree-shaped topology as its route

(communication route from itself to the sink node).

4. Adjusting transmission powers

Finally, the sink node adjusts the transmission power of

each node in order to further reduce the energy consumption

while keeping the confidence packet delivery ratio more

than that specified by the application.

By doing so, RCPDS constructs energy-efficient routeswhile keeping high quality of communication. However, as

described in Section 1, RCPDS assumes a static

environment and determines routes and transmission powers

before starting operation of a WSN. Thus, it does not work

well in an environment in which the characteristics of radio

propagation dynamically change.

4. D-RCPDSIn a real environment, the characteristics of radio

propagation dynamically change due to a variety of effects

such as appearances or removals of obstacles. D-RCPDS

detects such dynamic changes in the characteristics of radio

propagation and reconstructs routes by the autonomousbehaviors of nodes. Specifically, each node continuously

monitors the packet delivery ratio and SNR from each of its

neighboring nodes. When a node detects that the quality of

communication from a neighboring node deteriorates or

becomes excessively good, it reconstructs the route of the

neighboring node.

D-RCPDS consists of two phases, the initialization phase

and the operation phase. During the initialization phase,

D-RCPDS determines the route and the transmission power

of every node before starting operation of a WSN. During

the operation phase, D-RCPDS dynamically changes routes

according to the change in the characteristics of radio

propagation.In what follows, we show the details of the above two

phases in D-RCPDS. Here, in this section, we assume a

situation in which the required packet delivery ratio equals

0.7 for the purpose of explanation. In addition, we set the

number of levels (the number of transmission powers that

each node can set) to eight (Lv1,Lv2, ..., Lv8), and assumethat the actual transmission power is proportional to each

level for simplicity.

A.Initialization PhaseDuring the initialization phase, the initial route and

transmission power of each node are determined before

starting operation of a WSN. Here, these are basicallydetermined according to RCPDS except that D-RCPDS uses

0

0.2

0.4

0.6

0.8

1

-95 -85 -75 -65 -55

Confidencepacket

deliveryratio

RSSI[dBm]


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SNR instead of RSSI for deriving the PDR model. The

reason for using SNR is that we have confirmed from one

preliminary experiment that using SNR works better than

using RSSI. After this phase, the confidence packet delivery

ratio is set for each link on the routes.

In addition, in order to accommodate the change in thecharacteristics of radio propagation during the operation

phase, each node maintains the following information.

1) Routing Table: Each node holds the routing table,

which includes routing information of itself and all its

neighboring nodes. The routing information of a node

consists of the transmission power, the total transmission

power, and the route ratio of the node. Here, the total

transmission power of a node is defined as the sum of

transmission powers of all nodes on the route from itself to

the sink node. The route ratio of a node is defined as the

confidence packet delivery ratio of that route. For example

in Fig. 3, the routing table held by node Cconsists of therouting information of itself, that is, 7 as the transmission

power (%&), 14 and 0.81 as the total transmission power(%%&) and the route ratio (""&). In addition, this tableconsists of routing information of its neighboring nodes, A,

B,D and S(the sink node). In this figure, the level and the

number on each edge respectively denote the transmission

power of the sender and the confidence packet delivery ratio

of the link.

2) Required Link Ratio: When a node has at least one

child on the tree-shaped topology constructed during this

phase, it records the confidence packet delivery ratio from

each child to itself, as the required link ratio (

"'()*). For

example in Fig. 3, node C sets the confidence packetdelivery ratio from its child (node A) to itself (0.9) as the

required link ratio "'()*+,- .

Fig. 3 Initial Setting of Each Node in D-RCPDS.

3) Reception Window: In order to monitor the

characteristics of radio propagation, each node recordsinformation on the overheard packets for each neighboring

node to the reception window. The reception window of a

node consists of the PCK (PaCKet) window and the PDR(Packet Delivery Ratio) window.

The PCK window manages the sequence numbers of the

latestD overheard packets from each neighboring node and

the SNR measured when each packet is overheard. In

addition, each node calculates the cumulative packet

delivery ratio and the average SNR for each neighboring

node every time it overhears a packet from the neighboring

node. These values are calculated by the following

equations:

c/at23 PDR = !4567$ 456;a?3 @AR =

B 4C"


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prove packet updates the route ratio of the deteriorated node

in its routing table. In addition, when the node is not a childof the deteriorated node, it becomes a candidate of the

parent of the deteriorated node. We call such a node a

candidate node. The procedure of a candidate node consists

of the following five steps:

(a) Broadcasting Probe Packets.

(b) Calculation of Confidence Packet Delivery Ratio.

(c) Calculation of Required Candidate Link Ratio.

(d) Determination of Candidate Link Power.

Fig. 7 Characteristics of Radio Propagation Measurement.

1.It derives the average SNR from the deteriorated node toitself with each transmission power using the received

probe packets. After that, it derives the confidencepacket delivery ratio for each calculated average SNR

based on its holding PDR model. For example in Fig.

7(b), nodes B, C and D that receive the probe packetsfrom node A derive confidence packet delivery ratios

from nodeA to themselves.

2.It calculates the required candidate link ratio, "d=


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4. Notification of the change of route

The deteriorated node broadcasts a change notification

packet in order to notify the change of its parent,

transmission power and the total transmission power. Thispacket includes information on the identifiers of its new

parent and child(ren), and the updated transmission powerand total transmission power.

On receiving this packet, each node updates the routing

information for the deteriorated node. Specifically, it

updates the transmission power and the total transmissionpower in the routing information to those in the received

packet. In addition, when the node holds the routing

information for a child of the deteriorated node, it calculates

the sum of the total transmission power of the deteriorated

node and the transmission power of the child. Then, it

updates the transmission power of the child in its routingtable to the calculated value. Moreover, each node clears the

PCK window for the deteriorated node. This is because the

packet delivery ratio from the deteriorated node may changedue to the change in the transmission power.

When the node was the parent of the deteriorated nodebefore detecting the deterioration in quality of

communication, it recognizes that the deteriorated node is

no longer its child. Thus, it clears "


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and that of the cumulative confidence packet delivery ratio

and its own route ratio. These values denote the expected

route ratio of the transmitter if the node becomes its parent.

Then, each node checks whether the following two

conditions are satisfied:

Both of the calculated ratios become larger than theroute ratio of the transmitter recorded in the routing

table.

The sum of its own total transmission power and the

transmission power of the transmitter recorded in the

routing table becomes smaller than the total transmission

power of the transmitter recorded in the routing table.

When both of these conditions are satisfied, the node

determines that more energy-efficient route can be

constructed if it becomes the parent of the transmitter. Thus,

the node becomes a candidate node and notifies the

transmitter that the node can be the new parent. In this

section, we call the node that received this notification thewasting node. Here, this notification includes information

on the total transmission power of the candidate node. For

example in Fig. 10, node D derives the cumulative packet

delivery ratio and the cumulative confidence packet

delivery ratio from nodeA as 1.0 and 0.9. In this case, node

D recognizes that a more energy-efficient route can be

constructed when node A sets itself as the parent because

both of the following two conditions are satisfied:

The product of the cumulative packet delivery ratio from

nodeA and its own route ratio (0.8I = 0.8I 1.0) andthat of the cumulative confidence packet delivery ratio

from node A and its own route ratio (0.bNI = 0.9 0.8I) are larger than the route ratio of nodeA recordedin its routing table (0.73)

The sum of its own transmission power (7) and the total

transmission power of node A recorded in its routingtable (6) becomes less than the present total transmission

power of nodeA (20).

Thus, node D becomes a candidate node and sends a

notification to nodeA.

Fig. 10 Detection of More Energy-Efficient Route.

On receiving this notification, the wasting node

calculates the expected total transmission power of itself

when it sets the candidate node as its parent. Then, when thecalculated value is less than the present one, it sets the

candidate node as its parent. After that, the wasting node

transmits a change notification packet in the same way as in

step 4 in Section 4-B-1).

When the calculated total transmission power becomes

equal to or more than the present total transmission power,the wasting node determines that the candidate node holds

wrong information for itself in its routing table. Thus, the

wasting node sends the information on its present

transmission power and total transmission power to the

candidate node. On receiving this information, the candidate

node corrects the record for the wasting node in its routing

table.

3) Detection of Excessive Transmission Power: Even

when a more energy-efficient route cannot be found, it is

possible that a node can suppress its transmission power

while satisfying the required quality of communication. Forexample, when an obstacle on a link in a route is removed,

it becomes possible for the sender of the link to suppress the

transmission power. In D-RCPDS, each node tries to detect

such links and suppress the transmission powers.

First, similar to the procedure described in Section 4-B-2),each node continuously derives the cumulative packet

delivery ratio and the cumulative confidence packet

delivery ratio from each child. When both of the above

values become larger than the required link ratio for the

child by P during the predefined period %h , the nodedetermines that the child can suppress the transmissionpower while keeping the required quality of communication

and notifies the child of that fact. Similar to Section 4-B-2),

we call the node that received this notification the wasting

node. On receiving this notification, the wasting node

decreases its transmission power by one level. For examplein Fig. 11, the sink node recognizes that the cumulative

packet delivery ratio !"` and the cumulativeconfidence packet delivery ratio O!"` have beenrespectively 1.0 and 0.97, which are larger than the sum of

" 0.85 + 0.1

cPDRDS = 0.97 > 0.85 + 0.1

during TH

Rlink,DS = 0.85


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When the wasting node has child(ren), it sends a power

change packet to all its children in the same way as in step 4in Section 4-B-1).

C.DiscussionDuring the operation phase, D-RCPDS reconstructs

routes according to the dynamic change in the

characteristics of radio propagation. Here, using the

procedures in the operation phase, D-RCPDS can also

handle the exit or join of a node.

When a node exits from the network, the node no longer

transmits packets. Thus, the parent of the exited node can

recognize the exit when the node has not received any

packet from the exited node during a long period. In such a

case, the parent notifies the exit of its child by flooding a

packet which includes the identifier of the exit node. On

receiving this packet, each node that sets the exited node asits parent reconstructs its route starting with the broadcast of

probe packets as described in Section 4-B-1).On the other hand, when a node newly joins the network,

it first broadcasts prove packets which include the required

packet delivery ratio as its route ratio. By doing so, the

route and the transmission power of the node aredetermined by the same way as described in Section 4-B-1).

Next, we discuss the effects of parameters in D-RCPDS.

In D-RCPDS, each node detects the change in the quality of

communication based on the cumulative packet delivery

ratio and the cumulative confidence packet delivery ratio. In

some environments, these values frequently change due to

frequent movement of objects and the change in the strength

of noises. In such environments, since each node frequentlyreconstructs a route, its overhead such as transmissions of

probe packets becomes large. This causes not only the waste

of energy but a large number of packet collisions due toradio interferences. As a result, the energy-efficiency and

the quality of communication in the network deteriorate. To

avoid such a situation, D-RCPDS introduces % , %:, %hand % , as the periods for detecting the change in the

quality of communication, and eliminates the influences of

frequent changes in the quality of communication. However,

the larger these periods are set, the larger the delays for

detecting the changes in the characteristics of radio

propagation become.

Finally, we discuss the reversibility of the procedures inthe operation phase. When the quality of communication

deteriorates, D-RCPDS simultaneously redetermines both of

the parent and the transmission power of a node. On the

other hand, for the situation when the quality of

communication becomes excessively good, D-RCPDS

separately performs the procedures to change each of theparent and the transmission power of a node. Thus, the

procedures of route reconstruction in D-RCPDS are not

reversible. In other words, D-RCPDS does not uniquely

determine the route and transmission power of every node

according to an environment.

5. EvaluationThis section presents the results of experiments we

carried out to evaluate the effectiveness of D-RCPDS. In the

experiments, we made an environment where the

characteristics of radio propagation dynamically changesdue to the appearance and removal of an object. We

deployed nine MICAz MOTEs [22] and the sink node in our

laboratory (shown in Fig. 12). The required packet delivery

ratio was set as 0.7. Each node can control its own

transmission power from discrete 15 levels from

$LI[dBm] to 0[dBm] (Although the transmission power ofMICAz Mote can be set from 29 levels, the datasheet [23]

only shows the specific information on 8 of them. In

TABLE 1, the specific transmission powers which were not

shown in the datasheet are estimated by using those shownin the datasheet.) [24]. In such an environment, we compare

the performances of three methods described in Section

5-B.

Fig. 12 Experimental Environment.

A.Experimental ProcedureIn the experiment, we made two different situations: case

1) appearance of an objectand case 2) removal of an object.In what follows, we present the details of each procedure.

1) Case 1: Appearance of an object: First, each node

broadcasted probe packets to measure the characteristics of

radio propagation between each pair of nodes. Second, we

stored these measured results at the sink node and then

determined the route and the transmission power of each

node by using three methods described in Section 5-B.Then, we changed the environment where we assumed an

object appeared. Specifically, we inserted node F into an

aluminium box. By doing so, we changed the characteristics

of radio propagation between the sink node and nodeF.

After that, each node sent a packet every 10[sec] to the

sink node during two hours along the communication routedetermined by each method. We call this packet a data

packet and that transmitted for reconstructing a

communication route as a control packet.

2) Case 2: Removal of an object: First, we inserted

node F into an aluminium box, and determined the initial

routes in the same way as described in Section 4-A.Then, we changed the environment where we assumed an

object was removed by removing the aluminium box.


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After that, each node sent data packet every 10 [sec] to

the sink node during two hours along the communication

route determined by each method.

TABLE 1

TRANSMISSION POWERS OF MICAZ MOTE.

Level Transmission Power [dBm]Lv15 0Lv14 $0.ILv13 $1Lv12 $LLv11 $_Lv10 $KLv9 $ILv8 $NLv7 $bLv6 $8Lv5 $10Lv4 $1LLv3 $1ILv2 $18Lv1 $LI

B.Evaluation MethodsIn the experiments, we compare the performances of the

following three methods:

1) D-RCPDS: D-RCPDS first measured the packet

delivery ratios and the average SNRs of all links for all

transmission powers. After that, the route and the

transmission power of each node were determined based on

the measured results. More specifically, the packet delivery

ratios and the average SNRs of links were measured by

broadcasting 100 probe packets from each node at the rate

of 2 packets per 1[sec] for each transmission power. These

measurements were conducted before the experiment and

the results were stored at the sink node.

The threshold, k, for constructing PDR model was set as0.9. The sizes of PCK and PDR windows were respectively

set as 40 and 100. The parameter V in Equ. 5 was set as 0.8.The periods for detecting changes in the characteristics of

the quality of communication, % , % , %h and % wererespectively set as 50[sec], 300[sec], 50[sec] and 10[sec].

Other parameters,N, I, U,L, YandPwere respectively set

as 2, 10[msec], 3, 0.05, 2,000[sec] and 0.1.

2) Static RCPDS: This method consists only of the

initialization phase in D-RCPDS. Specifically, the initial

route and transmission power of each node were determinedin the same way in D-RCPDS. However, no route

reconstruction was conducted even when the characteristics

of radio propagation changed.

Note that this method is different from RCPDS proposed

in [7].

3) SP (Single Power) Method: This method performsneither the transmission power control nor the route

reconstruction. Specifically, we set all nodes to have the

same transmission power. The transmission power was set

to Lv15 and the shortest (minimum hop count)

communication routes with packet delivery ratios higher

than the required packet delivery ratio were determined.

C.Evaluation Criteria

We evaluated the following three criteria in the

experiment:

The average packet delivery ratio

The average of packet delivery ratios from all nodes to

the sink node measured every 500[sec]. The data transmission power

The sum of transmission powers of nodes in the entirenetwork consumed for transmission of data packet every

500[sec] calculated by the following equation:

j 5


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ratio from node F to the sink node in Fig. 17. From this

result, the packet delivery ratio from node F to the sinknode with Static RCPDS becomes much less than the

required ratio. On the other hand, with D-RCPDS, both of

the average packet delivery ratio and the packet delivery

ratio from node Fbecome larger than the required ratioduring almost entire period after elapsing 500[sec]. This is

because, as shown in Fig. 15, node F changes its parent

from the sink node to node G. The average packet delivery

ratio with the SP method is always larger than the required

ratio. This is because the appearance of the aluminium box

did not affect the quality of communication with the

maximum transmission power.

Fig. 13 PDR Model Derived in the Initialization Phase of case 1.

(a) D-RCPDS, Static RCPDS

(b) SP method

Fig. 14 Communication Routes and Transmission Powers at the Starting

Time of case 1.

Fig. 18 plots the data transmission powers. The

horizontal axis denotes the elapsed time since theexperiment started. From this result, we can see that the data

transmission power with D-RCPDS is less than not onlythat with the SP method but that with Static RCPDS during

almost entire period of the experiment. Comparing Fig.

14(a) and Fig. 15, not only nodeFand its children but othernodes such as nodes C and D change their parents and

transmission powers. This indicates that D-RCPDS found

more energy-efficient routes than those constructed in the

initialization phase according to the procedures described inSections 4-B-2) and 4-B-3).

Fig. 15 Communication Routes and Transmission Powers in D-RCPDS at

the Ending Time of case 1.

Fig. 16 Average Packet Delivery Ratio in case 1.

Fig. 17 Packet Delivery Ratio from NodeFin case 1.

Fig. 18 Data Transmission Power in case 1.

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2) Case2: Removal of an Object: Fig. 19 shows the

PDR model derived in the initialization phase of D-RCPDS.Fig. 20 outlines the constructed routes and the transmission

powers of nodes in D-RCPDS and Static RCPDS when the

experiment started. Moreover, Fig. 21 outlines those in

D-RCPDS when the experiment ended.

Fig. 19 PDR Model Derived in the Initialization Phase of case 2.

Fig. 20 Communication Routes and Transmission Powers in D-RCPDS andStatic RCPDS at the Starting Time of case 2.

Fig. 21 Communication Routes and Transmission Powers in D-RCPDS at

the Ending Time of case 2.

Fig. 22 Average Packet Delivery Ratio in case 2.

Fig. 22 plots the average packet delivery ratios. The

horizontal axis denotes the elapsed time since theexperiment started. From this result, we can see that the

average packet delivery ratios with all methods satisfy the

required ratio during almost entire period of the experiment.

This is because no deterioration in the quality ofcommunication occurred in the experiment.

Fig. 23 plots the data transmission powers. The

horizontal axis denotes the elapsed time since the

experiment started. From this result, we can see that the data

transmission power with D-RCPDS becomes less than that

at the starting time of the experiment. In particular, from the

result in Fig. 24, the data transmission power of node Fdrastically decreases due to the removal of the aluminium

box. Node F in D-RCPDS started changing its parent by

receiving a notification from the sink node at 410[sec]. In

addition, it decreases its transmission power by receiving a

notification from its parent (the sink node) at 460[sec],

3,470[sec] and 6,550[sec].

Fig. 23 Data Transmission Power in case 2.

Fig. 24 Data Transmission Power of nodeFin case 2.

3) Total Transmission Power: Fig. 25 shows the total

transmission powers in the entire periods of the above twoexperiments. From this result, we can see that the

transmission powers with D-RCPDS and Static RCPDS are

lower than that with the SP method. In particular,

D-RCPDS reduces the transmission power to about 48[%]

even though it needs to exchange control packets. This

indicates that D-RCPDS can construct effectivecommunication routes in terms of both of quality of

communication and energy-efficiency even in an

environment where the characteristics of radio propagation

dynamically changes.

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Fig. 25 Total Transmission Power.

6. SummaryA. Conclusion

In this paper, we have proposed D-RCPDS, which is adynamic route construction method based on the measured

characteristics of radio propagation. D-RCPDS reconstructs

the communication route to the sink node by theautonomous behaviors of nodes when the characteristics of

radio propagation change.

We also conducted experiments in a real environment

where the characteristics of radio propagation dynamically

change and demonstrated that D-RCPDS could construct

effective communication routes that achieve the required

packet delivery ratio during almost entire period of the

experiment.

B.Future WorkIn the initialization phase, we do not take into account

any overhead such as delay in the measurement and power

consumption for collecting information. However, such

overhead cannot be ignored especially in dense WSNs with

a massive numbers of nodes. In addition, the sink node mustperform numerous calculations for determining the initial

route and transmission power of each node in an

environment where an enormous number of nodes are

deployed. Therefore, we plan to consider an effective

protocol to measure and collect characteristics of radio

propagation and to reduce the number of calculations at thesink node.

As described in Section 4-C, D-RCPDS can

accommodate the exit and join of a node. Thus, we plan to

define the detailed procedures and verify the effectiveness

of these procedures in a real environment.

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Akimitsu Kanzaki received his B.E., M.E.,

and Ph.D. in Information Science andTechnology from Osaka University in Japan,

in 2002, 2004, and 2007, respectively. He iscurrently an Assistant Professor at theDepartment of Multimedia Engineering of

Osaka University. His research interests

include wireless networks and communicationprotocols. Dr. Kanzaki is a member of IEEE, IEICE, IPSJ, andDBSJ.

Yasuhiro Nose received his B.E. and M.E. inInformation Science and Technology from

Osaka University in 2008 and 2010,

respectively.

Takahiro Hara received his B.E, M.E, and

Dr.E. degrees in Information SystemsEngineering from Osaka University, Osaka,Japan, in 1995, 1997, and 2000, respectively.

Currently, he is an Associate Professor of the

Department of Multimedia Engineering,Osaka University. He has published morethan 300 international Journal and conference

papers in the areas of databases, mobile computing, peer-to-peer

systems, WWW, and wireless networking. He served and isserving as a Program Chair of IEEE International Conferences onMobile Data Management (MDM 2006 and 2010) and AdvancedInformation Networking and Applications (AINA 2009), and

IEEE International Symposium on Reliable Distributed Systems

(SRDS 2012). He guest edited IEEE Journal on Selected Areas inCommunications, Sp. Issues on Peer-to-Peer Communications andApplications. His research interests include distributed databases,

peer-to-peer systems, mobile networks, and mobile computingsystems. He is a senior member of IEEE and ACM and a member

of three other learned societies.

Shojiro Nishio received his B.E., M.E., and

Ph.D. degrees from Kyoto University inJapan, in 1975, 1977, and 1980, respectively.He has been a full professor at Osaka

University since August 1992. He served as aVice President and Trustee of Osaka

University from August 2007 to August 2011.He also acted as the Program Director in the

Area of Information and Networking, Ministry of Education,Culture, Sports, Science and Technology (MEXT), Japan from

April 2001 to March 2008. His research interests includedatabase systems and multimedia systems for advanced networks

such as broadband networks and mobile computing environment.Dr. Nishio has co-authored or co-edited more than 55 books, andauthored or co-authored more than 600 refereed journal or

conference papers. He served as the Program Committee

Co-Chairs for several international conferences including DOOD1989, VLDB 1995, and IEEE ICDE 2005. He has served and iscurrently serving as an editor of many international journalsincluding IEEE Trans. on Knowledge and Data Engineering,

VLDB Journal, ACM Trans. on Internet Technology, and Data &Knowledge Engineering. Dr. Nishio has received numerousawards during his research career, including a Medal with PurpleRibbon from the Japanese government in 2011. He is also a fellow

of IEEE, IEICE and IPSJ, and is a member of five learned

societies, including ACM.

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