M. Guo et al. (Eds.): ISPA 2006, LNCS 4330, pp. 231–245, 2006. © Springer-Verlag Berlin Heidelberg 2006

A Service Differentiation Mechanism for Improving the Performance of IEEE 802.15.4 Sensor Networks*

Tae-Yoon Kim 1, Sungkwan Youm 2, Eui-Jik Kim 2, and Chul-Hee Kang 1

1 Department of Electronics Engineering, Korea University 1, 5-ga, Anam-dong, Sungbuk-gu, 136-701, Seoul, Korea {2000kty, chkang}@widecomm.korea.ac.kr

2 Samsung Electronics Co., LTD 416, Maetan3-dong, Paldal-gu, Suwon-si, Gyenggi-do, Korea

{sk.youm, euijik.kim}@samsung.com

Abstract. In the sensor networks, each device generates data of different sizes in the home networking and the industrial application according to their roles in the networks. In this paper, we propose a mechanism that provides differentiated services for the IEEE 802.15.4 sensor networks to improve the total throughput and the fairness of the channel. To provide differentiated services for each and every device, our mechanism adds different sizes of backoff period according to the size of packet that is generated by the device. The mathematical model based on the discrete-time Markov chain is presented and is analyzed to measure the performances of the proposed mechanism. Simulation results are also given to verify the accuracy of the analytical model. Finally, the analytical results show the improvement in the throughput and the fairness of the network which applies our mechanism.

1 Introduction

For the last few years, the researches on wireless sensor networks have been increased significantly. Terms such as pervasive computing and smart spaces are being used for describing future computing and communications. These concepts are adapted to our personal and business domains being densely populated with miniature sensors, which are constantly monitoring the environment and reporting the data to each other or to some central base stations. Sensor networks cover from small applications such as health monitoring to large applications like environment surveillance. In other words, it can be used widely in practical applications from home networking to industrial applications. The recent IEEE 802.15.4 standard for the low rate wireless personal area networks is considered as one of the technology candidates for wireless sensor networks, since it supports small, cheap, energy-efficient devices operating on battery power that require little infrastructure to operate, or none at all [1, 2].

Applications of Sensor networks are mainly used for measurement of industries and have been grown with industrial development. In this reason, requirements of * This research was supported by the MIC (Ministry of Information and Communication),

Korea, under the ITRC (Information Technology Research Center) support program supervised by the IITA (Institute of Information Technology Assessment).

232 T.-Y. Kim et al.

sensor networks are increased continuously. Moreover, demands for large scale sensor networks which can interact with not a few of devices are also increased because of development of instruments and machines. But there are a few problems with IEEE 802.15.4 sensor network even though many suitable aspects for sensor networks with IEEE 802.15.4 are mentioned before. IEEE 802.15.4 sensor network did not have enough channel resource or bandwidth to adapt to large scale sensor networks. And a few problems may occur due to low channel data-rate of the standard in the network which supports many devices. It is easy to exceed channel data-rate when a few number of devices that have long size packets or those with short inter-arrival rate increase in the network. For instance, in case of IEEE802.15.4 sensor network using 868-868.6MHz band, if there are equal to or more than only 5 devices that generates 512bits of data per two super-frames, total data rate of them exceeds data rate of a channel which is 20kbps. So there can be lots of collisions and performance of the network may be decreased easily.

Like previously mentioned, IEEE 802.15.4 sensor network can be used in various areas. Therefore, each device in the IEEE 802.15.4 sensor network generates different data of different sizes according to their roles in the network. In this point of view, we propose a mechanism that provides differentiated services for IEEE 802.15.4 sensor networks to improve the performance of the network by using the aspect that each device generates different size of data respectively.

We present the mathematical model for the proposed mechanisms based on IEEE 802.15.4 sensor networks, which is based on the previous works of analyzing IEEE 802.15.4 [2, 3] and IEEE 802.11[4]. We consider the beacon-enabled mode with slotted CSMA-CA algorithm in our model and assume the saturation conditions, i.e. each and every device always has packets waiting to be transmitted, for the performance analysis. The mathematical model is based on the discrete-time Markov chain in which each component of an element in state space is representing the situation of the head packet in the queue of a device. By analyzing the Markov chain, we obtain the access probability for the device and the probability that the medium is idle. Moreover, we obtain the saturation throughput and the drop probability.

2 A Survey of Legacy 802.15.4

In the beacon enabled networks, the PAN coordinator set superframes as a cycle of its channel time. Each superframe begins with the transmission of a network beacon in an active portion and an optional inactive portion. In the active portion of superframe, the coordinator interacts with its PAN and may enter a power saving mode during the inactive portion. The superframe duration, SD, is equal to the duration of the active portion of the superframe, which cannot exceed the beacon interval, BI. In the active portion, each superframe is divided into sixteen uniformly sized slots. The beacon frame is transmitted at the beginning of slot 0 which is followed by the contention access period (CAP) of the active portion. In each slot in CAP, the channel access mechanism is contention based using CSMA-CA access mechanism.

In legacy IEEE 802.15.4, the basic time unit of MAC protocol is the duration of so-called backoff period. In slotted CSMA-CA, there are channel access opportunities at the boundary of each backoff period. The actual duration of backoff period depends

A Service Differentiation Mechanism for Improving the Performance of IEEE 233

on the frequency band in which 802.15.4 WPAN is operating. The standard allows the PAN to use either one of three frequency bands: 868-868.6, 902-928 and 2400-2483.5 MHz. As in the case of other contention based access control schemes, the transmission will be attempted only when the medium is idle, but withheld if the channel is busy due to packet transmission or collision.

Now we define three parameters to describe CSMA-CA protocol. NB denotes the number of times that the algorithm is required to backoff due to the unavailability of medium during channel assessment. Let CW be the contention window, i.e. the number of backoff periods that need to be clear of channel activity before the packet transmission can begin. Finally, BE denotes the backoff exponent which is related to the number of backoff periods that a device should wait before attempting to assess the channel.

When packet arrives in the queue of device, MAC sublayer of the device sets the two parameters NB and CW by zero and 2, respectively. If the device operates on battery power, BE is set to 2 or to the constant macMinBE, whichever is less. Otherwise, it is set to macMinBE (the default value of which is 3). Then the algorithm locates the boundary of next backoff period. In next step, the algorithm attempts to avoid collisions by generating random waiting time in the range of [0,2 1]BE − . When

the waiting period is over, MAC sublayer needs to perform CW clear channel assessment (CCA) procedures, transmit the frame, and optionally wait for the acknowledgment. If the remaining time within the CAP area of the current superframe is suitably long to accommodate all of these, MAC sublayer will perform the first CCA to see whether the medium is idle. If the remaining time is not sufficient, MAC sublayer will pause until the next superframe. If the channel is busy, the values of NB and BE are increased by one (but BE cannot exceed macMaxBE, the default value of which is 5), while CW is reset to 2. If the number of retries is below or equal to macMaxCSMABackoffs (the default value of which is 5), the algorithm generates random waiting time according to current values of NB and BE, otherwise the algorithm terminates with a channel access failure status. The failure will be reported to the higher protocol layers, which can then decide whether to attempt the transmission as a new packet again or not. If the channel is idle during CCA procedures, the value of CW is decreased by one, and the channel is reviewed once more. When the value of CW becomes zero, the packet transmission may begin, provided the remaining number of backoff periods in the current superframe suffices to handle both the packet and the subsequent acknowledgment. If this is not the case, the packet transmission is postponed until the beginning of the next superframe.

3 Service Differentiation Mechanism

Every sensor node has different role in the network and generates different data according to their roles respectively. In other words, every device in the network can generate different sizes of packet. We are proposing a mechanism that divides every device into multiple groups according to their packet sizes and gives different services to every group to enhance performance of the network. Before describing the mechanism in detail, we first state several assumptions and a definition of service. We are considering the IEEE 802.15.4 sensor network model that operates in the

234 T.-Y. Kim et al.

beacon-enable mode with slotted CSMA-CA algorithm. In this paper we only consider contention access period (CAP) and analyze the proposed mechanism in the saturation mode. When the transmitted packet collides, the packet is dropped and the device tries to transmit a new packet in the head of the queue. Packet size of each device will not be changed because the roles of devices will not change from early stage of network forming phase commonly in sensor network. We define the service differentiation as giving different amounts of channel resources to devices in the network with probability. In the following we describe the proposed mechanism in detail.

3.1 Service Differentiation Mechanism Based on Packet Size

There are plenty of collision occurrences in networks like the IEEE 802.15.4 Sensor network which have low data-rate or channel resource. So it is effective to reduce collision occurrences for enhancing performance of the networks. There are two methods which reduce collision occurrences in the networks. First method is giving differentiated services to the devices in the networks. Second method is reducing wasted time made by collisions of large packet. To satisfy both methods we make a new mechanism which is a new operation role of all devices in IEEE 802.15.4 sensor network.

All devices within the network are divided into multiple groups according to size of packet generated by them initially. Namely, devices that generate packets of similar size are gathered into a group. In the next, every group is given additional backoff periods for service differentiation based on their average packet size. The longer an average packet size is generated by the group, more number of the additional backoff period they must take. In this paper, we express the additional backoff period of the ‘g’ group as [ ]T g for mathematical analysis, and all devices which are included in the same group get equal number of additional backoff period.

[ ]T g can be obtained from the average number of slots that is taken to transmit packet of the device in the ‘g’ group. So the size of [ ]T g is in proportion to the average packet size of the ‘g’ group.

A device in ‘g’ group will perform the first clear channel assessment (CCA) procedure, and if a channel is sensed busy, it adds the additional backoff period as many as [ ]T g . More specifically, the device in ‘g’ group will initially choose a

random waiting period according to backoff exponent (BE) before the CCA procedure in every backoff stage. The device performs the first CCA procedure when the waiting period is over. If the channel is sensed idle as a result of the first CCA procedure, the device performs a second CCA procedure like legacy IEEE 802.15.4 standard. However, if the channel is sensed busy after the first CCA procedure, the device adds backoff period as long as [ ]T g unlike legacy mechanism which makes

the device enter the second CCA procedure directly. When the additional waiting period becomes zero, the device enters second CCA procedure and it will transmit packet if channel is idle. However, if the channel is sensed busy during the second CCA procedure, the device will enter the next backoff stage and will generate a new random waiting time to delay the transmission of packets. The mechanism will work again equally in every backoff stage. So this mechanism enables every device to receive differentiated service accordingly as the average packet size of their groups

A Service Differentiation Mechanism for Improving the Performance of IEEE 235

because more number of additional backoff period a device take, it have to wait more time in stochastically before transmit packets than others.

From our mechanism, it is possible to give different contention rate to each group through service differentiation. It can reduce the total collision rate of the sensor network, because the devices which receive better services will compete with the smaller number of devices than legacy mechanism that have the same contention level. Also, devices that receive worse services will yield channel access to better serviced devices and support them to access channel without a hitch. And it is also possible by using our mechanism to give lower service to the device which would like to transmit the longer sized packet. There will be fewer collisions generated during transmissions of longer size packets, which can reduce the wasted time generated by collisions. In other words, there would be more opportunities to transmit packets if the occupied time of the channel generated by collisions is reduced, which can enhance the performance of IEEE 802.15.4 sensor network.

Total throughput of the network can be enhanced by two methods we mentioned. In addition, when we defined that fairness of network is generally examined by throughput of each device, proposed mechanism also can enhance the fairness of the network. Because proposed mechanism gives more channel resource to groups which are generate packets of short size, their performance will be improved more than other groups which are generate packets of long size. In this reason, the differences between

00, 2, 1W − 0, 2,1 0, 2, 0

0,1, [ ] 1T g − 0,1,1 0,1, 0

0, 0, 0

1,1, [ ]T g

11, 2, 1W − 11, 2, 2W − 1, 2,1 1, 2, 0

1,1, [ ] 1T g − 1,1,1 1,1, 0

1, 0, 0

,1, [ ]m T g

, 2, 1mm W − , 2, 2mm W − , 2,1m , 2, 0m

,1, [ ] 1m T g − ,1,1m ,1, 0m

, 0, 0m

1, 0, 0m +

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

01 /W

11 /W

1 / mW

gα1 gα−

gβ1 gβ−

gα1 gα−

gβ1 gβ−

gα1 gα−

gβ1 gβ−

00, 2, 2W −

0,1, [ ]T g

00, 2, 1W − 0, 2,1 0, 2, 0

0,1, [ ] 1T g − 0,1,1 0,1, 0

0, 0, 0

1,1, [ ]T g

11, 2, 1W − 11, 2, 2W − 1, 2,1 1, 2, 0

1,1, [ ] 1T g − 1,1,1 1,1, 0

1, 0, 0

,1, [ ]m T g

, 2, 1mm W − , 2, 2mm W − , 2,1m , 2, 0m

,1, [ ] 1m T g − ,1,1m ,1, 0m

, 0, 0m

1, 0, 0m +

1

1

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1

1

1

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1

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1

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1

1

1

1

1

1

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1

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01 /W

11 /W

1 / mW

gα1 gα−

gβ1 gβ−

gα1 gα−

gβ1 gβ−

gα1 gα−

gβ1 gβ−

00, 2, 2W −

0,1, [ ]T g

Fig. 1. Markov Chain Model

236 T.-Y. Kim et al.

total throughputs of groups can be decreased. More detailed explanations about the proposed mechanism are presented in following sessions with the flowchart and the Markov chain model of the mechanism.

4 Analytical Model

To analyze the proposed scheme, we introduce the following three random variables for a given device in the priority ‘g’ group. Let ( , )n g t , ( , )c g t , and ( , )b g t be the

stochastic processes representing the value of NB, CW, and the value of the backoff period, respectively, at time t. Note that NB represents the backoff stage within the range of [0, 1]m + , m macMaxCSMABackoffs= whose default value is 4 in IEEE

802.15.4 standard. Furthermore, throughout this paper, ‘g’ means gth group, and gives the different priorities taking integer values in [0, ]G , where ( 1)G + is the

number of groups with different packet size in the network. The process {( ( , ), ( , ), ( , ))}n g t c g t b g t forms a multi-dimensional Markov process defining the

state of the packet at the backoff unit boundaries. Since we are assuming that each device has its own priority according to their group which is not changeable, each of the processes ( , )n g t , ( , )c g t , ( , )b g t can be simplified as ( )n t , ( )c t , ( )b t . ( )n t

belongs to the range of [0, 1]m + in integer value. ( )c t may be 0, 1, or 2. Value of

( )b t are differed according to the value of ( )c t .

0 ~ 1, [0 , ] , ( ) 1( )

[ ] , [0 , ] , ( ) 2iW i m if c t

b tT g g G if c t

− ∈ =⎧= ⎨ ∈ =⎩

(1)

where 0 2BEW = , 02iiW W= .

Like previously mentioned, [ ]T g means size of additional backoff period of group

‘g’. Note that [ ]T g is drawn by

[ ] ( ) ( /1 )gH L ACK ACKT g T T T t Unit backoff periods sγ= + + + + × (2)

where HT , gLT , γ , ACKT and ACKt denote the time to transmit the header (including

MAC header, PHY header), the average time to transmit the packet of devices in group ‘g’, propagation delay, the time to transmit the ACK, the time to receive first bit of ACK.

The state transition diagram of these states is illustrated in Fig. 1. For the simplicity of the notations, we use the transition probabilities ( , , 1| , , )P i j k i j k− instead

of ( ( 1) , ( 1) , ( 1) 1 | ( ) , ( ) , ( ) )P n t i c t j b t k n t i c t j b t k+ = + = + = − = = = .

We assume that there is a total number of devices, n , which is composed of ln ,

[0, ]l G∈ devices in group l with their l st priority. Furthermore, we assume that

each of them always has a packet ready to be transmitted. Then the one-step transition probabilities are given as follows:

A Service Differentiation Mechanism for Improving the Performance of IEEE 237

0 0(0, 2, | ,0,0) 1/ , [0, ], [0, 1],P k i W i m k W= ∈ ∈ −

0 0(0, 2, | 1,0,0) 1/ , [0, 1],P k m W k W+ = ∈ −

( , 2, 1 | , 2, ) 1, [0, ], [1, 1],iP i k i k i m k W− = ∈ ∈ −

( ,1, 1 | ,1, ) 1, [0, ], [1, [ ]],P i k i k i m k T g− = ∈ ∈

( ,1,0 | , 2,0) , [0, ],gP i i i mα= ∈ (3)

( ,0,0 | ,1,0) , [0, ],gP i i i mβ= ∈

( ,1, [ ] | , 2,0) 1 , [0, ],gP i T g i i mα= − ∈

1 1( 1,2, | ,1,0) (1 ) / , [0, 1], [0, 1],g i iP i k i W i m k Wβ + ++ = − ∈ − ∈ −

( 1,0,0 | ,1,0) 1 ,gp m m β+ = −

Note that all of the states are positive recurrence and the system is stable. Therefore, there exist the stationary probabilities , ,{ }i j kb of the discrete-time Markov

chain which can be defined as

, , lim { ( ) , ( ) , ( ) }, [0, 1], [0, 2]i j kt

b P n t i c t j b t k i m j and→∞

= = = = ∈ + ∈ (4)

0 ~ 1, [0 , ] , 1

[ ] , [0 , ] , 2iW i m if j

kT g g G if j

− ∈ =⎧= ⎨ ∈ =⎩

Due to the chain regularities, the following relationships hold:

,0,0 0,0,0 (1 ) , [0, ],ii gb b i mβ= − ∈

,2, 0,0,0

(1 )( ), [0, ], [0, 1],

igi

i k ii g

W kb b i m k W

W

ββ

−−= ∈ ∈ −

,1, 0,0,0

(1 )(1 ), [0, ], [1, [ ]],

ig g

i kg

b b i m k T gα β

β− −

= ∈ ∈ (5)

,1,0 0,0,0

(1 ), [0, ],

ig

ig

b b i mβ

β−

= ∈

1

1,0,0 0,0,0

(1 ),

mg

mg

b bββ

+

+

−=

Sum of all the stationary probabilities in the Markov chain will become 1. So the value of 0,0,0b can be obtained through the following normalization:

1 [ ]

,0,0 ,2, ,1, ,1,0 1,0,00 0 0 0 1 0

1iW T gm m m m

i i k i k i mi i k i k i

b b b b b−

+= = = = = =

+ + + + =∑ ∑∑ ∑∑ ∑ (6)

and subsequently we can obtain 0,0,0b by substituting Eq. (5) into Eq. (6).

0,0,0 00 0

1

2 /{ ( 2 1)(1 ) 2( [ ](1 ) 1 ) (1 )

2(1 ) }

m mi i i

g g g g gi i

mg

b W T gβ β α β β

β= =

+

= + − + − + + −

+ −

∑ ∑ (7)

238 T.-Y. Kim et al.

By substituting Eq. (7) into each equation in Eq. (5), we obtain the stationary probabilities , ,{ }i j kb .

With these stationary probabilities, we find the probability that the device transmits a packet at the boundary of a backoff period which will be denoted by τ . Let gτ be

the probability that a device in the group ‘g’ start transmission during a generic slot time. Then we have

,0,00

m

g ii

bτ=

=∑ . (8)

Since all groups have different priority, elements like [ ]T g , gα and gβ are

different according to group. gα and gβ means the probabilities that the device

senses channel is idle in the first and second CCA procedure respectively. And also these probabilities mean that the channel is idle at the end of backoff counting or

other 0,

( 1)G

g ii i g

n n= ≠

− + ∑ devices are not transmitting during CCA procedures of the

device in the group ‘g’. Assuming the average slot times that are used by devices in the network to transmit packets is T , gα can be described by

1

00,

1 (1 (1 ) (1 ) ) , [0, ],g i

G Gn n

g g i lli i g

T g G n nα τ τ−

== ≠

= − − − − ∈ =∑∏ . (9)

Because of gβ is depend on gα , gβ can be obtained from Eq. (9). So gβ can be

described as

1

0,

1

00,

(1 ) (1 )

1 (1 (1 ) (1 ) ) , [0, ],

g i

g i

Gn n

g g ii i g

G Gn n

g i lli i g

T g G n n

β τ τ

τ τ

−

= ≠

−

== ≠

= − −

+ − − − − ∈ =

∏

∑∏. (10)

5 Performance Analysis

5.1 Throughput

Let IP be the probability that the channel is idle because of all devices in network

don’t start transmission. So this probability can be calculated as followed:

00

(1 ) , .l

G Gn

I l lll

P n nτ==

= − =∑∏ . (11)

Let sP and ,s gP be the probabilities that a successful transmission occurs by a

device in any priority group and a successful transmission occurs by device in the

A Service Differentiation Mechanism for Improving the Performance of IEEE 239

priority ‘g’ group in a time slot, respectively. Then these probabilities are calculated as followed:

0 0 00

(1 ) ,1 1

h

GG G Gnl l l l

s h I jl l jhl l

n nP P n n and

τ τττ τ= = ==

= − = =− −∑ ∑ ∑∏ (12)

1,

00,

(1 ) (1 ) , [0, ], .1

g i

G Gn g gn

s g g g g i I jji i g g

nP n P g G n n

ττ τ τ

τ−

== ≠

= − − = ∈ =− ∑∏ (13)

Let BP be the probability that there is at least one transmission in the considered

slot time. Then it is given by

00

1 1 (1 ) , .l

G Gn

B I l lll

P P n nτ==

= − = − − =∑∏ (14)

Then B sP P− is the probability that the channel is sensed busy because of the collision

generated from any priority groups. Using these equations from Eq. (11) to Eq. (14), we can calculate the normalized

saturation throughput for the ‘g’ group, gS .

,

( )

( )

( )

g

s g g

I s s B s c

E payload transmitted in a slot timeS

E length of a slot time

P L

P PT P P Tδ

=

=+ + −

(15)

Here sT is the average time when the channel is busy because of a successful

transmission, and cT is the average time when the channel is busy by each station

during a collision. δ is the duration of an empty slot time. gL means average payload

sizes of devices in ‘g’ group. sT and cT can be expressed by

( )s H E L ACK ACKT T T T tγ= + + + + (16)

( ),c H E L

T T T γ∗= + + (17)

where *( ) ( *), , , , , ,H E L ACK ACK E LT T T t L L and Tγ denote the time to transmit the

header (including MAC header, PHY header), time to transmit average payload size of all devices in the network, propagation delay, the time to transmit the ACK, the time to receive first bit of ACK from the receiver device, payload size of each device in the network, payload size of each device in the network during a collision, the average time to transmit payload during a collision and the symbol E stands for expectations.

5.2 Packet Drop Probability

In this paper we are assuming that if a collision occurs, the packet is dropped and next packet of boundary of queue will be prepared for transmission. We are assuming this for the simplicity of analysis. Therefore, for the group ‘g’, the probability to be

240 T.-Y. Kim et al.

dropped in a time slot equals to the probability that there are at least two devices which occur collision, which can be expressed as followed:

1

, ,0,

2 0

(1 ) (1 (1 ) )

(1 ) , [0, ], ,

g l

g

g

Gn n

d g c g g g g ll l g

n Gg n kk

g g jk j

P P n

ng G n n

k

τ τ τ

τ τ

−

= ≠

−

= =

= = − − −

⎛ ⎞+ − ∈ =⎜ ⎟

⎝ ⎠

∏

∑ ∑ (18)

6 Analytical and Simulation Results

In this section we compare the analytic and simulation results to verify the accuracy of the analytical model of the proposed mechanism and present the performance analysis of that mechanism. The analytic results show the effect of the proposed mechanism. Simulations are performed using a Matlab-version6.5 simulator. The the analytic results without losing the comprehensive analysis of the model. The following assumptions are applied with the saturation mode which is considered in this paper. We assume that the packet sizes of devices in each group are constant. In addition, we assume that packets for ACK are not collided.

Table 1. The parameter sets used in the analytical analysis and simulation

Group 1 26 bytes Group 2 52 bytes Packet

payload Group 3 104 bytes

Channel bit rate 20 kbits/sec ACK 40 bits

MAC header 200 bits macMaxCSMABackoffs 4

PHY header 48 bits Unit backoff period 20 symbols Modulation symbol 1 Data bit in 860MHz band

Table 2. Comparison of throughputs on the legacy 802.15.4 with varying number of devices (unit: bits/sec)

The number of devices for each group

Analysis Simulation

Groups Groups Groups G1 G2 G3 G1 G2 G3 G1 G2 G3 5 5 5 667.3 1,334.6 2,669.3 660.1 1,342.3 2,753.7

10 10 10 509.5 1,019.1 2,038.3 523.7 986.0 2,015.9 15 15 15 423.5 847.1 1,694.3 407.0 848.7 1,632.2 20 20 20 367.1 734.4 1,468.8 370.2 710.2 1,430.9 25 25 25 326.9 653.9 1,307.7 339.5 669.1 1,257.0

A Service Differentiation Mechanism for Improving the Performance of IEEE 241

Table 3. Comparison of throughputs on the proposed mechanism with varying number of devices (unit: bits/sec)

The number of devices for each group

Analysis Simulation

Groups Groups Groups G1 G2 G3 G1 G2 G3 G1 G2 G3 5 5 5 667.3 1,334.6 2,669.3 660.1 1,342.3 2,753.7

10 10 10 509.5 1,019.1 2,038.3 523.7 986.0 2,015.9 15 15 15 423.5 847.1 1,694.3 407.0 848.7 1,632.2 20 20 20 367.1 734.4 1,468.8 370.2 710.2 1,430.9 25 25 25 326.9 653.9 1,307.7 339.5 669.1 1,257.0

In order to compare the network’s performance of using the proposed mechanism and that of using the legacy mechanism, we made two analytic models for the both mechanisms. Analytic model of the legacy mechanism is made from the previous work of analyzing IEEE 802.15.4 [2] with a little modifying. All devices in the network are divided into multiple groups based on packet size of each device. But there is no priority for each group and all groups have the same opportunities for accessing to the channel. Analytic model for the proposed mechanism are presented in previous session. For verifying the accuracy of the analytic models, the comparisons of throughputs with a varying number of devices within each group are presented in Table 2 and Table 3. The packet size of each group is set by Table 1. As shown in the Table 2 and Table 3, the results of simulation are almost the same as those of analytic results. All simulation results in Table 2 and Table 3 are obtained with 97.89% and 98.24% Confidential Rates respectively. In the table the Confidential Rate (CR) between analytical and simulation results are given, which are calculated using the following equation:

[1 100%

[ ]anal sim

anal

E S SCR

E S

⎛ − ⎞= − ×⎜ ⎟⎝ ⎠

.

Since the differences between the analytical and simulation results are negligible, in the remained figures we present the analytical results only. In each figure from Fig. 2 to Fig. 5, x axis denote the number of devices at each group. We assume the number of devices in each group is all the same in the figures of analytical results. For example, if x is 5, there is the total number of 15 devices because we there are three groups in each figure with characteristics listed in Table 1. And we named the proposed mechanism as SDiPS(Service Differentiation by Packet Size).

τ in Fig. 2 represents the probabilities of trying transmission for each group characterized by the packet sizes. In the figure, y axis denote τ at each group. The value of τ is drawn by many elements of the network such as the number of devices in each group, the priority of the group, the size of backoff period of each device and so on. In brief, τ for each group in the SDiPS is different each other as we can see from Fig. 2 because the device of every group in the SDiPS has different opportunity to transmit packet by different number of additional backoff periods. We analyzed that the lowered τ values are drawn from lowered probability of sensing idle channel

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during CCA procedure of the device which is one of the effects of service differentiation. And we expect that there will be more lowered τ values if there is more degree of service differentiations. SDiPS’s lowered τ value means there are lower competitions for obtaining an access to the channel than the legacy mechanism and it can relief tension of the channel. Especially, the devices of groups with long packet size try a transmission with low probabilities. We think it is important factor to use channel resources efficiently.

Fig. 2. τ (Probability of trying transmission)

With previous τ values, we already know that the channel access attempts are alleviated due to the service differentiation in the SDiPS. As a result of that, the collision probabilities of each group in the SDiPS shown in Fig. 3 are decreased in compared with the legacy mechanism. And the low access attempts of the group with long packet size result in fewer occurrences of collision during the transmissions of long size packets in the SDiPS. Therefore, using the SDiPS can reduce an average collision time. And it enables the devices in the network to make better use of channel resources.

Fig. 3. Collision probability

The throughputs of each group in the legacy mechanism are different because the packet sizes are different while successful transmission probabilities of each device are the same, in Fig. 4. The total throughput of the SDiPS that sum up throughputs of each group is improved because the decrease of total collision probability presented in

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Fig. 3. And the reducing collision occurrences during transmit large size packet can generate spare time to transmit more data during the same time. The throughput of the group with short packet size is improved since the group is given more opportunities by the service differentiation in the SDiPS.

Fig. 4. Throughput

The throughput difference shows that the fairness property is improved after applying the SDiPS in Fig. 5. The throughput difference subtracts the throughput of group 3 from that of group 1. The decrease of throughput difference means that all devices share the channel resource well. And it decreases as the number of device increase, which means that using the SDiPS is more useful for the fairness when there are more devices in the channel.

Fig. 5. Throughput Difference

Table 4. Gain between the total throughputs of the legacy mechanism and the SDiPS

The number of devices for each group Analysis

Group1 Group2 Group3 Proposed Legacy Gain 5 5 5 5,347.7 4,671.3 1.1447

10 10 10 4,123.0 3,567.0 1.1558 15 15 15 3,447.2 2,965.0 1.1626 20 20 20 3,001.7 2,570.4 1.1678 25 25 25 2,680.5 2,288.5 1.1713

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Finally gain between the total throughputs of the legacy mechanism and the SDiPS are showed in Table 4. Gain is obtained from dividing SDiPS total throughput by total throughput of legacy network. As number of each device increase, the gain is also increased nearly from 14% to 17%. This means SDiPS is helpful to sensor network which interact with many devices in it. And we think that the results of this paper deserve to be considered with industrial development.

7 Conclusion

In this paper, we propose a mechanism for the IEEE 802.15.4 sensor networks which provides differentiated services to each and every device by adding different size of backoff period on each device according to the size of packet generated by the device. The mathematical model based on the discrete-time Markov chain is provided for analyzing the performance of the proposed mechanism. The comparison of analytical and simulation results are given to verify the accuracy of the numerical model. The analytical results of several performance measurements are given to analyze the effect of the proposed mechanism on the IEEE 802.15.4 sensor networks.

We could summarize the following benefits on IEEE 802.15.4 sensor network when proposed mechanism is applied to the network. First, the throughput of IEEE 802.15.4 sensor network can be improved. The collision probability can be reduced by providing contention rate differently to each device. Moreover, the wasted time generated by collision can be reduced by reducing the occurrences of collision during the transmissions of long size packets. Also, these profits of proposed mechanism are more effective as the number of devices increase. Second, the fairness property is improved because there are remarkable increases of opportunities to transmit short packets, while there are not marked increases of those to transmit long packets. Therefore the mechanism can decrease throughput differences between group of short packet and group of long packet. This means that all devices share the channel resource more equally.

However, there is a short cut of using our mechanism when all devices in network generate similar or the same sizes of packets. In that situation, our mechanism can not provide service differentiation quite well to devices in the network and there may be not much improvement. As for further work, the delay characteristics should be analyzed for each group in order to estimate how much time is taken for the devices to use the proposed mechanism to transmit packets.

References

1. Standard for part 15.4, Wireless medium access control (MAC) and physical layer (PHY) specifications for low rate wireless personal area networks (WPAN), IEEE Std 802.15.4, IEEE, New York, NY. (2003)

2. Misic, J., Shafi, S., Misic, V.B.: The Impact of MAC Parameters on the Performance of 802.15.4 PAN, Elsevier Ad hoc Networks, Vol. 2. (2004) 351-371

3. Eui-Jik Kim, Meejoung Kim, Sung-kwan Youm, Seokhoon Choi, and Chul-Hee Kang.: Priority-Based Service Differentiation Scheme for IEEE 802.15.4 Sensor Networks, will be published on Elsevier AEU, (2006)

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4. Bianchi, G.: Performance Analysis of the IEEE 802.11 Distributed Coordination Function, IEEE Journal on Selected Areas in Communications, Vol. 18. (2000) 535-547

5. Robinson, J.W., Randhawa, T.S.: Saturation Throughput Analysis of IEEE 802.11e Enhanced Distributed Coordination Function, IEEE Journal on Selected Areas in Communications, Vol. 22. (2004) 917-928