Performance evaluation of data transport over differentnode density of zigbee sensor network

Journal of Science and Technology, Vol. 47, 2020

PERFORMANCE EVALUATION OF DATA TRANSPORT OVER DIFFERENT-

NODE DENSITY OF ZIGBEE SENSOR NETWORK – AN OPNET SIMULATION

STUDY

ONG MẪU DŨNG

Faculty of Electronics Technology, Industrial University of Ho Chi Minh city,

[email protected].vn

Abstract. In this paper, we analyze the performance of different node density of Wireless Sensor Network

(WSN) operating under the IEEE Standard 802.15.4 in the beacon-enabled mode. The motivation for

evaluating the beacon-enabled mode is due to its flexibility for WSN applications as compared to the non-

beacon enabled mode. The analysis is based on an accurate OPNET simulation model which supports

slotted Carrier Sense Multiple Access Mechanism with Collision Avoidance (CSMA/CA) mechanism and

Guaranteed Time Slot (GTS). The performance of the slotted CSMA/CA sensor network is evaluated and

analyzed for different network settings to understand the impact of the protocol attributes, including super-

frame order (SO), beacon order (BO), data packet size and maximum back-off number. Through the

simulation results, high SO provides better network throughput, otherwise results in lower average latency.

We also found that the MAC overheads on small MAC Service Data Unit (MSDU) are more significant

than the overheads on large MSDU. And the back-off mechanism results in longer delays when the network

traffic is heavy.

Keywords. Wireless sensor network, ZigBee network, network performance.

1

INTRODUCTION

During the last decade there has been an explosion of devices using sensor technologies for control and

monitoring purposes. Wired sensors are now intended to be replaced with wireless technologies and

wireless sensor networks have aroused much research interest. Most technologies designed so far, such as

Bluetooth and Wi-Fi, primarily focus on the ability to support higher data rates and wider operating range,

which have a direct impact on the power requirements, cost factor, size, complexity and feasibility [1].

ZigBee is a new wireless technology guided by the IEEE802.15.4 Personal Area Network (PAN) standard.

It is primarily designed for the wide ranging automation applications and to replace the existing non-

standard technologies. Compared to Long Range (LoRa) wireless radio frequency (RF) technology, the

main features of ZigBee are low power consumption, low cost, low data rate, self-organization and flexible

topologies [2][3].

Till this time, few accurate simulations and implementations have been done for ZigBee protocol. The

OPNET Modeler is an industry leading discrete-event network modeling and simulation environment

[4][5][6]. Two IEEE802.14.5 OPNET simulation models were researched. The first model is developed by

the National Institute of Standards and Technology (NIST) [7]. This model implements only the first two

levels of the International organization of Standardization (ISO)/ Open System Interconnection (OSI) stack

and a few functions of the upper layer. Instead of using the accurate OPNET wireless library, it uses its

own radio channel model and only supports un-slotted CSMA/CA MAC protocols. Compared to the NIST

simulation model, the model developed by OPEN-ZB implements the both the application layer and the

battery module [8]. Since the OPEN-ZB simulation model provides more features and uses the accurate

OPNET wireless library, we used this model to evaluate the performance of the ZigBee sensor network.

Last but not least, from the best of our knowledge, there has not reported about the impact of node-

density on Quality of Service (QoS) of ZigBee sensor network. And it is critical to have analytical model

using parameters such as node-density, back-off number, retransmission limit, and packet size for the

scalable-node ZigBee sensor network [9]. For better presentation of our results, we collect and classify all

simulation results from OPNET, export them to spreadsheet to illustrate the final simulation results.

PERFORMANCE EVALUATION OF DATA TRANSPORT OVER DIFFERENT-NODE

91

DENSITY OF ZIGBEE SENSOR NETWORK – AN OPNET SIMULATION STUDY

This paper divides into following primary sections. Section 2 will introduce the general concept of

IEEE802.15.4 protocol and cover some relevant features of this protocol. Further details about the

simulation models and simulation environment setup are explained in Section 3. Section 4 shows the

collected simulation results based on simulation scenarios. Finally, Section 5 concludes this paper.

2

RELEVANT FEATURES OF THE IEEE802.15.4 PROTOCOL

The IEEE802.15.4 standard specifies the physical layer and MAC sub-layer for Low-Rate Wireless

Personal Area Networks (LR-WPAs) [9]. The ZigBee standard is guided by the IEEE802.15.4 protocol and

specifies the network and application layers [10][11]. According to [10], three different types of nodes can

be used in a wireless sensor network: the coordinator, the router and the end device. The coordinator

performances like the root of a tree. It initiates the network format and exchanges the parameters used by

the other nodes to communicate. There is only one coordinator in each network. The router participates in

multi-hop routing of messages and managers the routing tables. Both the coordinator and the router are

called Full Function Devices (FFDs). On the other hand, the end device, which is also referred as Reduced

Function Devices (RDFs), is only responsible for collecting data from sensors and sending them to FFDs.

2.1 IEEE802.15.4 physical and MAC layers

The physical layer is responsible for data transmission and reception using a certain radio channel. The

IEEE802.15.4 is currently operating in three frequency bands: 868MHz band at a data rate of 20kbps in

Europe, 915MHz band at 40kbps in the North America, and 2.4GHz band at a data rate of 250kbps in

worldwide [10].

Table 1. ZigBee physical layer specifications.

Attribute

Gross data rate

2450MHz band

250 kbps

915MHz band

40 kbps

868MHz band

20 kbps

Number of Channel

Modulation

16

O-QPSK

10

BPSK

1

BPSK

Chip pseudo-noise sequence

Bit per symbol

32

4

15

1

15

1

Symbol period

Access scheme

16 micro-sec

DSSS

24 micro-sec

DSSS

49 micro-sec

DSSS

Figure 1: Frame structure of the beacon signal [10].

The Medium Access Control (MAC) protocol supports two operation modes that can be selected by a

coordinator in the Personal Area Network (PAN): beacon enabled mode and non-beacon enabled mode. In

beacon-enabled mode, the beacon frames are periodically generated and sent by the PAN coordinator to

identify its PAN and synchronize devices that are associated with it. When beacon enabled mode is selected,

the PAN coordinator uses super-frame structure to communicate the end devices which are associated to

that PAN. Each super-frame begins with the transmission of a network beacon followed by an active portion

92

PERFORMANCE EVALUATION OF DATA TRANSPORT OVER DIFFERENT-NODE

DENSITY OF ZIGBEE SENSOR NETWORK – AN OPNET SIMULATION STUDY

and an optional inactive portion as shown in fig. 1. Therefore, the Beacon Interval (BI) is the time between

two consecutive beacon frames.

The active period, referred to the Super-Frame Duration (SD), is divided into 16 equally sized time slots.

Data can be transmitted during these time slots. The BI and the SD are determined by two parameters, the

Beacon Order (BO) and the Super-Frame Order (SO) respectively.

퐵퐼=푎퐵푎푠푒푆푢푝푒푟푓푟푎푚푒 퐷푢푟푎푡푖표푛×2^퐵푂for 0≤퐵푂≤14

푆퐷=푎퐵푎푠푒푆푢푝푒푟푓푟푎푚푒퐷푢푟푎푡푖표푛×2^푆푂for 0≤푆푂≤퐵푂≤14

(1)

(2)

In these two equations (1) and (2), the “aBaseSuperframeDuration” refers to the minimum duration of

the super-frame. This duration is 15.36ms if the assumption of 250kbps in the 2.4GHz frequency band is

made [3]. Each active period can be further divided into a Contention Access Period (CAP) and an optional

Contention Free Period (CFP). Slotted Carrier Sense Multiple Access mechanism with Collision Avoidance

(CSMA-CA) can be used within the CAP.

The CFP is activated when a device sends to the PAN coordinator a request. Upon receiving the request,

the PAN coordinator checks whether there are sufficient resources to allocate the requested time slots.

These slots are referred to as Guaranteed Time Slots (GTS). In non-beacon enabled mode, super-frame

structure is not used and the un-slotted CSMA/CA mechanism is used. Therefore, GTS is not provided by

the non-beacon enabled mode. In this paper, we only interest with the beacon-enabled mode due to its

flexibility for Wireless Sensor Network (WSN) applications as compared to the non-beacon enabled mode.

2.2 Slotted CSMA/CA mechanism

The slotted CSMA/CA mechanism is based on a basic time unit called Back-off Period (BP) and is used in

beacon-enabled mode during the CAP. The BP is the basic time unit of the MAC protocol. The access to

the channel can only occur at the boundary of the back-off slots. The back-off slot boundaries must be

aligned with the super-frame slot boundaries. When a device wants to transmit frames during the CAP, it

first locates the boundary of the next back-off slot and then waits for a random number of the back-off slots.

If the channel is busy, following this random back-off, the device will wait for another random number of

back-off slots before trying to access the channel again. This can be repeated for several times. If the channel

is idle, the device can begin transmitting on the next available back-off slot boundary.

There are three parameters in the slotted CSMA/CA mechanism, the Back-off Exponent (BE), the

Contention Window (CW) and the Number of Back-offs (NB). The BE enables the computation of the

back-off delay, which is a random variable between 0 and (2^퐵퐸−1). The CW represents the number of back-

off period and the NB represents the number of times that the slotted CSMA/CA mechanism was required

to back-off while attempting to access the channel.

3

IEEE802.15.4 SIMULATION MODELS

3.1 OPEN-ZB simulation model features

As shown in fig. 2a about the OPNET simulation model of IEEE802.15.4, the physical layer consists of the

IEEE802.15.4 compliant radio transmitter and receiver, which are operating at 2.4GHz frequency band with

the data rate of 250kbps. The transmission power of the transmitter and the receiver is set to 1mW.

The MAC layer implements the slotted CSMA/CA and the GTS mechanisms. When the GTS is active,

the GTS data traffic generated from the application layer is stored in a buffer with a specified capacity and

dispatched to the network. The MAC layer also managers the generation of beacon frames when the node

is a PAN coordinator.

PERFORMANCE EVALUATION OF DATA TRANSPORT OVER DIFFERENT-NODE

93

DENSITY OF ZIGBEE SENSOR NETWORK – AN OPNET SIMULATION STUDY

The application layer consists of three parts, a traffic source, a GTS traffic source and a traffic sink. The

traffic source and the GTS traffic source can generate both the unacknowledged and acknowledged data

frames during the CAP and CFP periods. The traffic sink receives data frames from lower layers and

performs network statistics. The batter module computes and energy consumption and the remaining energy

levels.

Figure 2b: User-defined attributes.

Figure 2a: IEEE802.15.4 OPNET simulation model.

3.2 User-defined attributes

This section introduces some important user-defined attributes of our simulation model. As shown in fig.

2b, the MSDU Size attribute specifies the size of the MAC Service Data Unit. Since the MAC header is

104 bits and the maximum allowed size of the overall frame is 1016 bits, the MSDU Size value can be from

0 to 912 bits. The Maximum Back-off Number attribute specifies the maximum number of retransmissions

that the slotted CSMA/CA mechanism will attempt before the mechanism terminates with a channel access

failure status. The range of this value is from 0 to 5.

The Minimum Back-off Exponent attribute specifies the minimum value of the BE in the slotted

CSMA/CA. As mentioned in previous section, the BE is related to how many back-off periods a device

must wait before attempting to access the channel activity.

The BO and SO attributes are related only to the PAN coordinator. The setting of BO and SO must

satisfy the relationship 0 ≤ 푆푂 ≤ 퐵푂 ≤ 14. If SO is equal to BO, then according equations (1) and (2) from

Section 2, the Beacon Internal is equal to the super-frame duration. Therefore, the super-frame is always

active. According to the IEEE802.15.4 standard, the super-frame will not be active following the beacon if

SO is equal to 15. Thus, in order to operate in beacon-enabled mode, the SO and BO attributes in the PAN

coordinator must be set to a value between 0 and 14.

The GTS Permit attribute allow the PAN coordinator to accept or reject the GTS allocation request from

end devices. This attribute only applies to the PAN coordinator. From the end device side, each device can

94

PERFORMANCE EVALUATION OF DATA TRANSPORT OVER DIFFERENT-NODE

DENSITY OF ZIGBEE SENSOR NETWORK – AN OPNET SIMULATION STUDY

specify the time when the GTS allocation and deallocation requests are sent to the PAN coordinator by

setting the Start Time and Stop Time attributes.

4

SIMULATION AND RESULTS

Our objective is to evaluate the performance of the ZigBee wireless sensor network. The performance of

the un-slotted CSMA/CA mechanism was evaluated in [7] by using the NIST simulation model, however

the slotted CSMA/CA mechanism was not addressed. In order to carry out this task, we developed a

simulation environment for the IEEE802.15.4 slotted CSMA/CA mechanism using the OPNET simulator.

We consider a typical star wireless sensor network with one PAN coordinator surrounded by numbers of

identical nodes within the radio coverage. The node density is sequentially simulated as

1,2,3,4,5,10,20,30,40,100,130 and 150 RDFs end-nodes, respectively. One of our provision network

topology simulation with 40 ZigBee end-nodes is pictured in fig. 3.

Figure 3: Example of star topology with 40 ZigBee end-nodes inside 100m²room.

We particularly interest in three performance parameters, the average end-to-end delay, the network

output load and the probability of success. The end-to-end delay is the transmission delay between two

consecutively received packets. The probability of success is the probability of the packets being

successfully received during the CAP. In order to understand the impact of the protocol attributes, including

the super-frame order, beacon order, maximum back-off number and the frame size, on the network

performance, we set up four primary simulation scenarios as follows.

(i) The purpose of the first scenario is to evaluate the impact of the network load.

(ii) The second scenario is to evaluate the impact of super-frame order and beacon order.

(iii) The third scenario is to evaluate the impact of the frame size.

(iv) And the last scenario is to evaluate the impact of maximum back-off number.

Unless it is mentioned differently, following settings apply to all the simulation scenarios.

.

BO and SO are always set to equal

Maximum Back-off Number is set to 4

Minimum Back-off Exponent is set to 3

Only acknowledge data frame are generated

GTS are enabled

MSDU Inter-arrival Time and MSDU Size are constants

PERFORMANCE EVALUATION OF DATA TRANSPORT OVER DIFFERENT-NODE

95

DENSITY OF ZIGBEE SENSOR NETWORK – AN OPNET SIMULATION STUDY

.

Simulated period is 50 seconds

Buffer size is 1000 bits

4.1 Impact of number of end devices

In order to evaluate the impact of the network load on the performance of ZigBee wireless sensor network,

the average delay, the probability of success and the network throughput are collected as functions of the

number of end devices in the network. In this scenario, each identical end device sends packets with a

packet size of 100 bits (MSDU size) and a constant generation interval (MSDU Inter-arrival Time) of 0.1s

during the CAP. The GTS is enabled from the 0.2s to 1.5s of the simulation period and it sends packets

with a packet size of 100 bits and a constant generation interval of 0.2s during the CFP. The super-frame

order and beacon order are set to 7. The arrival data rate is defined as MSDU size over MSDU Inter-arrival

Time. Thus, the arrival data rates are 1kbps during the CAP and 0.5kbps during the CFP. Since GTS is

enabled only at the beginning of the simulation period (from 0.2s to 1.5s), the arrival data rate is 1kbps after

1.5s. When we increase the number of end devices in the network, we increase the network load

accordingly.

Figure 4a: Average delays as a function of

the number of end devices.

Figure 4b: Average network throughputs as a function

of the number of end devices.

Figures 4a and 4b present the impact on the end-to-end delay and the network throughput when step-

by-step increasing the end-device number from 1 to 150. Figures 4a and 4b show that initially both the

network throughputs and the delays increase with the number of end devices. When the number of end

devices reaches 50, the curves become flat. The floor level of the network throughput is about 32kbps and

the delay is about 0.016s. The floor level is determined by the data rate limitation of the IEEE802.15.4.

Although theoretically the IEEE802.15.4 protocol can provide a capacity of 250kbps, our simulation results

show that in fact the data rate is limited to 32kbps, which is 12.8% of the theoretical value.

To further investigate the difference between the theoretical value and the simulation value, the

percentage of successful acknowledged transmission packets are captured. As shown in fig. 5, the

percentage is 100% when there is only one end device in the network. When more end devices are added

to the network, more packets are dropped during the transmission due to the heavy network load and the

limited buffer size. From the simulation result, we can observe that a network with 150 end nodes (each

node has a data arrival rate of 1kbps) is able to successfully transmit 75% of the generated data.

96

PERFORMANCE EVALUATION OF DATA TRANSPORT OVER DIFFERENT-NODE

DENSITY OF ZIGBEE SENSOR NETWORK – AN OPNET SIMULATION STUDY

Figure 5: Average successful acknowledged transmission packets for different numbers of end nodes.

4.2

Impact of SO and BO

The objective of this part is to evaluate the impact of super-frame order and beacon order on the

performance of slotted CSMA/CA. The results are collected based on different values of SO and BO. We

consider a network with 20 end devices and each of them has a data arrival rate of 3.5kbps.

From fig. 6a, as we expected, low SO values produce lower network throughput. This is basically due

to two reasons. First, the overhead of the beacon frame is more significant for lower SO values because

beacons are more frequent. Second, in case of lower SO values, there are more collisions at the start of each

super-frame. Furthermore, although the increase in the super-frame order from 0 until 4 has significant

impact on the network throughput, the increase of SO from 5 to 14 has little impact on the network

throughput. If SO equals to 4 as a threshold value, for SO values above the threshold, the probability of

collisions is quite low. As a result, it leads to higher network throughputs but no further increases.

Figure 6a: Network output load as a function of

different BO, SO values.

Figure 6b: The average delay as a function of

different SO, BO values.

PERFORMANCE EVALUATION OF DATA TRANSPORT OVER DIFFERENT-NODE

97

DENSITY OF ZIGBEE SENSOR NETWORK – AN OPNET SIMULATION STUDY

Figure 6b shows the average delay as a function of different SO, BO values. It is basically consistent

with the network throughputs. There are more collisions in the beginning of a new super-frame due to the

high probability of Clear Channel Assessment (CCA). Therefore, the back-off delays will not increase too

much due to this frequent collision in case of low SO values. For high super-frame orders, the back-off

algorithm will have less impact and the end-to-end delay will not be further increased.

4.3

Impact of packet size

This part studies the impact of packet size on the performance of slotted CSMA/CA. According to the

IEEE802.15.4 standard specification, the size of the MAC header is 104 bits because only 16-bit short

addresses are used for communication. The maximum allowed size of the overall frame is equal to 1016

bits. Thus, the MSDU size is limited to 912 bits. In order to generate the constant data arrival rate when

varying the MSDU size, for each configuration, we vary the inter-arrival times as well. The following table

shows the corresponding settings of MSDU sizes and intervals.

Table 2: MSDU size and interval settings

MSDU Size (bit)

MSDU Interval (s)

Data Arrival Rate (bps)

100

200

300

400

500

600

700

800

900

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

500

As shown in fig. 7, the network output loads increase when large MSDUs are generated. When the MSDU

size is small, the impact of the MAC header on the network throughputs is significant. We can observe that

there is only 21kbps network throughput when the MSDU size is 100 bits as compared to the 36kbps

network throughput when the MSDU size is 900 bits. A great amount of the network bandwidth is wasted

by carrying MAC headers. When the MSDU size becomes larger, we need less MAC headers to frame the

generated data. Consequently, more bandwidth is used to carrying data and results in a higher network

throughput.

Figure 7: Network output load as a function of packet size.

4.4

Impact of maximum Back-off Number

This part investigates the impact of maximum back-off number on the performance of slotted CSMA/CA.

Our preliminary studies show that the maximum back-off number has no impact on the network

performance when the network load is light because the retransmission occurs very quickly. In order to

study the impact on a heavy network, we consider a network with 30 end nodes and each node sends packets

with a data arrival rate of 0.7kbps. As shown in fig. 8a, the delay is about 0.005s when no retransmission is

allowed. Then it increases abruptly to reach 0.03s when five retransmissions are allowed. Therefore, we

98

PERFORMANCE EVALUATION OF DATA TRANSPORT OVER DIFFERENT-NODE

DENSITY OF ZIGBEE SENSOR NETWORK – AN OPNET SIMULATION STUDY

can conclude that the node has to wait for a longer time before attempting to retransmit in case of heavy

traffic load.

Figure 8a: Simulation values of delay as a function of

maximum back-off number

Figure 8b: Simulation values of Network Output Load

as a function of maximum back-off number

Figure 8b shows the impact on the network output load when increasing the maximum back-off number.

We can observe that if the maximum back-off number becomes larger (bigger than 1) the network output

load reaches a higher level. When we use a small back-off value, such as 0 or 1, all the nodes which sense

a collision will try to retransmit after a short interval. Consequently, the collision probability is high and

the packets may be dropped. When a high back-off value is used, the retransmission interval becomes longer

and as a result, the total number of successful transmissions increases.

5

CONCLUSIONS

In this paper we have evaluated the performance of the slotted CSMA/CA mechanism deployed by the

IEEE802.15.4 protocol in beacon-enabled mode. We built a simulation environment to evaluate the impact

of the following parameters on the performance of slotted CSMA/CA: (i) the network load, (ii) the beacon

order and the super-frame order, (iii) the packet size, and (iv) the maximum back-off number. The

simulation results show that that high super-frame orders provide better network throughput than lower

super-frame orders. On the other hand, low SO values result in lower average delays. The MAC overheads

on small MSDUs are more significant than the overheads on large MSDUs. The back-off mechanism results

in longer delays when the network traffic is heavy. The actual data transmission rate of the IEEE802.15.4

protocol cannot reach the theoretical value of 250kbps due to the finite buffer size and traffic collisions.

REFERENCES

[1] Liu, Yongkang, et al. “Wireless Network Design for Emerging IoT Applications: Reference Framework and Use

Cases”, Proceedings of the IEEE 107.6 (2019): 1166-1192.

[2] Arora, Vishal Kumar, et al. “On QoS evaluation for ZigBee incorporated Wireless Sensor Network (IEEE802.15.4)

using mobile sensor nodes”, Journal of King Saud University-Computer and Information Sciences (2018).

[3] Mishra, Rakesh Kumar, et al. “An Addressing Scheme for Massive Sensor Networks”, IFIP International

Conference on Computer Information Systems and Industrial Management. Springer, Cham, 2019.

[4] OPNET Technologies, Inc., Opnet Modeler, http://www.opnet.com

[5] Chen, Min, Yiming Miao, and Iztok Humar. “Introduction to OPNET Network Simulation”. OPNET IoT

Simulation. Springer, Singapore, 2019. 77-153.

[6] Chen, M.: OPNET Network Simulation, Press of Tsinghua University, ISBN 7-302-08232-4 (2004)

[7] National Institute of Standards and Technology (NIST), http://www.nist.gov/

[8] IEEE 802.15.4 OPNET simulation model, http://www.open-zb.net

[9] Mekki, Kais, et al. “A comparative study of LPWAN technologies for large-scale IoT deployment”, ICT express

5.1 (2019): 1-7.

PERFORMANCE EVALUATION OF DATA TRANSPORT OVER DIFFERENT-NODE

99

DENSITY OF ZIGBEE SENSOR NETWORK – AN OPNET SIMULATION STUDY

[10] IEEE 802.15.4 Standard-2003, “Part 15.4: Wireless Medium Access Control (MAC) and Physical layer (PHY)

Specifications for Low Rate Wireless Personal Area Networks (LR WPANs)”, IEEE SA Standards Board, 2003

[11] ZigBee Alliance, “ZigBee Specification”, http://www.ZigBee.org/

ĐÁNH GIÁ HIỆU SUẤT VẬN CHUYỂN DỮ LIỆU QUA MẠNG CẢM BIẾN ZIGBEE

VỚI MẬT ĐỘ NODE KHÁC NHAU- NGHIÊN CỨU TRÊN MÔ PHỎNG OPNET

Tóm tắt. Trong bài báo này, chúng tôi phân tích hiệu suất của mạng cảm biến không dây có số lượng node

khác nhau hoạt động theo tiêu chuẩn IEEE802.15.4 với chế độ beacon. Nguyên nhân đánh giá theo chế độ

beacon là do tính linh hoạt đối với nhiều ứng dụng trong mạng cảm biến không dây (WSN) so với chế độ

non-beacon. Phân tích dựa trên mô hình chính xác trong mô phỏng OPNET hỗ trợ cơ chế đa truy cập tránh

xung đột (CSMA/CA) và khe thời gian được đảm bảo (GTS). Hiệu suất của mạng cảm biến CSMA/CA

theo khe thời gian được đánh giá và phân tích thông qua việc cài đặt các thông số mạng khác nhau để hiểu

tác động của các thuộc tính giao thức, bao gồm thứ tự siêu khung (SO), thứ tự beason (BO), kích thước gói

dữ liệu và số lượng backoff tối đa. Thông qua kết quả mô phỏng, thông số SO lớn cung cấp thông lượng

mạng tốt hơn, ngược lại dẫn đến độ phản hồi trung bình thấp hơn. Chúng tôi cũng nhận thấy rằng overhead

trên MAC Service Data Unit (MSDU) nhỏ có ý nghĩa quan trọng hơn so với trên MSDU lớn. Và cơ chế

backoff dẫn đến sự chậm trễ lâu hơn khi lưu lượng mạng tăng cao.

Từ khóa. Mạng cảm biến không dây, mạng ZigBee, hiệu suất mạng.

Ngày nhận bài: 30/03/2020

Ngày chấp nhận đăng: 17/08/2020

Performance evaluation of data transport over differentnode density of zigbee sensor network – an opnet simulation study