robust real-time ieee802.15.4 mac protocol in multi-hop

International Journal of Engineering & Computer Science IJECS-IJENS Vol:13 No:04 1

130304-2626-IJECS-IJENS © August 2013 IJENS I J E N S

Robust Real-time IEEE802.15.4 MAC Protocol in

Multi-Hop Mesh Network for Distribution Smart

Grid-AMI Hikma Shabani, Musse Mohamud Ahmed, Sheroz Khan, Shihab Ahmed Hameed and Mohamed Hadi Habaebi

Department of Electrical and Computer Engineering, Kulliyyah of Engineering

International Islamic University Malaysia, P.O.BOX.10, Kuala Lumpur, 50728, Malaysia

E-mail: [email protected]

Abstract-- The success of Smart Grid will be based on grid-

integrated real-time communication between various grid

elements in generation, transmission, distribution and loads.

Merit to the ZigBee/IEEE802.15.4std low cost, low power, low

data rate, short range, simplicity and free licensed spectrum that

makes wireless sensor networks (WSNs) the most suitable

wireless technology for smart grid applications. This paper

focuses at the distribution layer from advanced metering

infrastructure (AMI) gateways at the consumer premises to the

distribution point where a multi-hop mesh network is built for

large coverage data exchange. While beacon-enabled mode is

adopted for energy efficient operations, IEEE802.15.4std does not

define any mechanisms to enable beacon mode in mesh network.

Therefore, in this paper, a modified Zigbee WSN MAC protocol

for real-time multi-hop mesh network topology is developed. The

protocol performance is evaluated using NS-2 simulation and the

preliminary results are encouraging.

Index Term-- Smart Grid, Mesh Network, AMI, WSN, ZigBee,

MAC sub-layer, Superframe, real-time.

I. INTRODUCTION

The current power grid is designed long time ago and the grid

components are near the end of their normal life span. Hence,

the capacity limitations of electricity distribution, lack of

automated analysis, and slow response time due to mechanical

switches, poor visibility, growing population and demand for

more energy, and equipment failures have contributed to the

blackouts happening over the past 40 years [1]. As a result,

the Energy Independence and Security Act of 2007 gives a

start for the smart grid implementation in the United States [2]

with many countries following suit.

The smart grid is a modern electric power grid

infrastructure using the innovative transmission and

distribution networks to deliver electricity to end-users more

efficiently to almost close to the maximum transmission

capacity of network. In smart grid, the electricity delivery

system monitors, protects and automatically optimizes the

operation of its interconnected devices from generation to

distribution systems via transmission grid [3]. The cornerstone

of a smart grid is the ability for various entities to interact via

bidirectional communication network. The distribution smart

grid AMI comprises of key components such as smart meters,

AMI gateways known as neighborhood area network (NAN)

gateways and repeaters [4]. Hence, wireless sensor networks

(WSNs) provide a feasible and cost-effective sensing and

communication solution for smart grid. To enable large scale

deployments, the sensing nodes must collaborate to efficiently

route data over long distances from source to destination [5].

Thus, multi-hop mesh networks offer flexibility and robustness

by enabling path formation from any source to any destination

mostly through intermediate nodes within the network. ZigBee

is one of the promising standards for WSNs due to its

simplicity, mobility, robustness, low bandwidth requirements,

low cost of deployment, easy network implementation. In

addition to that, its operation is within the range of 2.4GHz

unlicensed industrial, scientific and medical (ISM) radio

spectrum and as being a protocol based on the IEEE

802.15.4std [6].

The IEEE 802.15.4 MAC sub-layer permits two modes for

transmitting and receiving data: the asynchronous beaconless

and synchronous beacon-enabled mode. Mainly, the

asynchronous beaconless mode requires nodes to listen for

other nodes’ transmission at all the times, which can drain

battery power faster. Moreover, the beaconless mode does not

provide any guarantee for data delivery and all transmissions

are done after executing an un-slotted carrier-sense-multiple

access with collision avoidance (CSMA/CA). On the other

hand, the beacon-enabled mode supports the transmission of

beacon packets between transmitter and receiver providing

synchronization among nodes after performing the slotted

CSMA/CA algorithm. Hence, the synchronization allows

devices to sleep between coordinated transmission, which

results in energy efficiency and prolonged network lifetime

[7]. However, the current IEEE802.15.4std specification

restricts the beacon-enabled mode to star or cluster tree

topologies only. Whereas the first is one-hop limited, which

reduces network coverage, the second does not provide the

scalability and robustness enabled by mesh topologies [8].

Hence, in this paper, a robust real-time IEEE802.15.4 MAC

protocol for beacon-enabled mode based multi-hop mesh

network for large coverage, better power efficiency, improved

scalability, robust and collision free network to ensure the QoS

and real-time control of the distribution smart grid components

is designed.

The rest of the paper is organized as follows. In section II,

the IEEE 802.15.4 Slotted CSMA/CA protocol is highlighted.



Section III presents the problem definition and the scope.

Section IV depicts the methodology whereas in Section V, the

CSMA/CA Analytical Model for Multi-hop Mesh Network is

presented. Finally, Section VI presents the simulation results

whilst section VII presents the conclusion and perspectives.

II. IEEE 802.15.4 SLOTTED CSMA/CA PROTOCOL

There are two types of node in an IEEE 802.15.4 network: Full

Function Devices (FFDs) and Reduced Function Devices

(RFDs). FFDs known as beacon-enabled devices can operate

either as Personal Area Network Coordinators (PANc), Cluster

Head (CH) or Routers whereas RFDs called beaconless

devices can only operate as end devices. A network includes at

least one FFD, operating as the PANc and the other devices

can either act as end devices forming a star topology around

the coordinator, as routers creating a mesh topology or as a

combination of CHs and end devices creating a cluster-tree

topology [9].

The network operation consists of a Contention Access

Period (CAP) in which a transmitting node competes with

other nodes using slotted CSMA/CA mechanism to access to

the channel and a Contention Free Period (CFP) which

contains Guaranteed Time Slot (GTS) that provides certain

guarantees on eventual time and packet delivery in the network

[10].

In the slotted CSMA/CA channel access mechanism,

each time a node wishes to transmit data during the CAP must

initially sense the radio medium to determine whether the

channel is available or not. If the channel is idle, the node

transmits; otherwise for a busy channel, a random number of

backoff slots should be waited. After the random delay, a two

slot clear channel assessment (CCA) is carried out [11].

There are three key parameters in IEEE 802.15.4

CSMA/CA: Number of Backoff (NB) that is the number of

times the CSMA/CA algorithm is required to delay while

attempting the current transmission. NB is initialized to 0

before every new transmission and it is set to certain

boundaries, beyond which the transmission would be aborted

to avoid too much overheads. Contention Window (CW) that

is a content counter length defining the number of slot periods

that need to be clear of activity before the transmission can

start. It is initialized to 2 before each transmission attempt and

reset to 2 each time the channel is assessed to be busy. Finally,

Backoff Exponent (BE) is related to how many slot periods a

device must wait before attempting to assess the channel [12].

Even though, the CSMA/CA is similar to the IEEE 802.11

CSMA/CA in using binary exponential backoff, 802.15.4

differs from 802.11 in that, a backoff counter value of the

device decreases regardless of the channel status, and the

device monitors the channel, i.e. performs clear channel

assessment (CCA) twice when the value reaches zero [13].

III. PROBLEM DEFINITION AND SCOPE

Wireless mesh networks are the most popular choice for

deploying advanced metering infrastructure (AMI) extensively

used all over the world where the Smart Grid initiative is

gaining momentum. The primary purpose of deploying these

networks is to allow utilities to facilitate automated meter

readings and acquire periodic data which is highly granular.

This data can be used to provide demand response programs.

Such systems require highly reliable communications between

head end systems and metering devices [14]. This paper

focuses at the distribution layer where data exchange occurs

between AMI gateways at the house hold in multi-hop mesh

topology to the distribution point or ZigBee Network

Coordinator (ZNC).

According to IEEE802.15.4std, all the communications

have to go through the neighbor nodes (FFDs) and the data has

to be stored in the neighbor nodes until being advertised in the

beacon of the next superframe [15]. Therefore, it has been

shown that with the usage of guaranteed time slot (GTS), the

real-time data is sent at the end of the superframe to the PAN

coordinator and the reception is done using slotted CSMA/CA

which may not guarantee the immediate access to the medium.

The other limitations are related to the current superframe

structure itself. Hence, even if the node has reserved a GTS, it

can contend for channel access in the CAP period which

decreases the performance of the other nodes. The scheduling

of the contention free period (CFP) at the end of the active

portion of the supeframe is another additional limitation of

superframe structure of IEEE802.15.4std. This scheme gives

the normal data a faster channel access than the real-time data,

since the real-time data may wait until the end of the CAP to

get a deterministic channel access [16].

Moreover, since in Wireless Sensor Networks (WSNs) it

is recommended to set a low duty cycle (high sleep time) for

power saving purpose, the data may be kept in the network

coordinator for at least a time equal to the inactive period

duration which is given by equation (1) [17]

(1)

Furthermore, if the Duty Cycle (DC) is not set properly

(e.g. too short) the transmission latency may increase; since

during sleep time, data may have to wait until the active

portion of the next superframe to start the transmission [18].

The DC is calculated as the ratio between the superframe

duration (SD) and the beacon interval (BI) that can be related

to Beacon Order (BO) and Superframe Order (SO) via the

following equation (2) [19]

( ) (2)

Where:

𝑂 𝑂



IV. METHODOLOGY

This robust real-time IEEE802.15.4 MAC protocol is based on

the combination of the modified Enhanced superframe

structure developed in [7] integrating the beacon collision

avoidance technique as suggested in [20]. To the best of the

authors’ knowledge, there are no citations reporting to develop

WSN standards for smart grid distribution systems.

In mesh networks, each beacon enabled node requires the

list of its two hops neighbor nodes which is achieved by using

two commands, namely, MLME-NEIGHBOUR_SCAN to

obtain its neighbor’s beacons and MLME-NLIST_REQ to

request the neighbors’ neighbor list. A Reserved Broadcast

Duration Slot (RBDS) in the active superframe is used as time

reference to compute the beacon offset of beacon enabled

nodes [20]. The superframe of the proposed robust real-time

IEEE802.15.4 MAC protocol is shown in the following Fig. 1

RBDS

B CFP CAP B+1

A.

B.

time Active Inactive

Period (SD) Period

Beacon Interval (BI)

Fig. 1. IEEE 802.15.4 Superframe structure of RBDS model

The above proposed structure has similar periods as the model

developed in [7] with the following modifications:

1) A new time slot labeled reserved broadcast duration slot

(RBDS) has replaced the PRTPU of the model (Fig. 1)

developed in [7]

2) The RBDS is located before the beacon and at the

beginning of the SD. The RBDS is used by all nodes

(FFDs) to send critical real-time data while GTS is used

to send normal real-time data.

This new structure gives the following improvements:

1) Nodes with critical real-time data can access the channel

faster than those having normal data, since they don’t need to

wait for the end of the CAP to send their data.

2) The normal real-time nodes do not need to contend for

the channel access in the CAP, since they send all their data in

the CFP period that is placed at the beginning of the

superframe.

3) The third improvement is very important since it is

related to the energy-delay tradeoff. In this technique, the real-

time data is sent and received in the same superframe. The

node (FFD) uses the following ALGORITHM I (given below

in a pseudo code) to create the neighbors and neighbor’s

neighbor list.

ALGORITHM I

- Send MLME-NEIGHBOR_SCAN at the beginning of

superframe to create a list of neighbors

If Find an empty slot (entry) in the neighbor table

Record the beacon transmission time of each neighbor

in the neighbor table. Send MLME-NLIST_REQ to request the neighbors’

neighbor list in the broadcast active superframe duration

If Find an empty slot (entry) in the neighbors’

neighbor list

Record the short address and slot offset in the

neighbor table

keep RBDS in the allocated slot offset

Else

Return “no mesh network”

Else

Start beacon as described in IEEE802.15.4std

The node (FFD) uses ALGORITHM II (given in a pseudo code)

to send sensed data. The node (FFD) will wait until data is

sensed while different backoff exponent “BE” are used to

differentiate between the sensed data so that:

. If there is no real-time

data all nodes will use the standard backoff. Since all nodes

(FFDs) will receive the Beacon and RBDS and will know the

types of sensed data (Critical real-time data packets are sent in

the RBDS, normal real-time data list is sent in the GTS, and no-

real time data is sent in the beacon).

ALGORITHM II

- If node has real-time data

If “Critical data” sent in RBDS with

Else

“Normal data” sent in GTS with

- Else

Start the CAP as described in IEEE802.15.4std

10 1 0

2 3 4 5 6 7 8 9 12 13 14 11 15

GTS1 GTS2



V. CSMA/CA ANALYTICAL MODEL FOR MULTI-HOP MESH

NETWORK

In this section, we attempt to introduce a queuing theory model

for the new MAC protocol at hand. Let N be the maximum

number of identical nodes or routers (FFDs) operating on a

transmission range of device with range since nodes further

than two hops do not cause collision in the mesh network [20].

For the sake of energy efficiency no acknowledgement is

implemented whilst it is supposed that the packet arrival process

has no after effect. This analytical model is based on the

modification of the Markov chain models for slotted CSMA/CA

developed in [21] and [22].

Let ( ) be the stochastic process representing the backoff

stages if ( ( ) ∈ * , … ,𝑀+) with 𝑀 the maximum number of

backoff (𝑁 ) or the transmission stages if ( ( ) ), and

( ) be the stochastic process representing the length of backoff

or transmission duration counters of a device at time . The

MAC sub-layer delays for a random number of complete

backoff periods in the range of , , - where

backoff exponent ( 𝑀 ). Hence, when the length of backoff counter is decremented

to zero, the states * ( ), ( ) + and * ( ), ( ) + correspond to the first and second channel assessment ( 𝐴 ) and ( 𝐴 ), respectively. If two consecutive clear channel

assessments ( 𝐴) are idle, the node starts the transmission of

packet. And if 𝐴 fails due to busy channel, the value of both

𝑁 and is incremented by one up to

𝑀 𝑥 𝑀𝐴 𝑘 and 𝑀 𝑥 , respectively. The

transmission fails if 𝑁 > 𝑀 𝑥 𝑀𝐴 𝑘

The idle state * ( ) , ( ) + represents the sleep

period when the node has no packet to send. However, in this

analysis, it is assumed that a node always has a packet available

for transmission. Finally, the state * ( ) , ( ) , . . . , 𝐿 + represents the transmission state where 𝐿 is the

packet transmission duration measured in slots. The randomly

picked backoff window size at stage can take either value in

the set * ,𝑊 + where the value zero indicates immediate

sensing and the delay window (𝑊 ) is initially defined as

𝑊 and doubled at any stage until 𝑊 𝑊 with ( 𝑀 𝑥 𝑀 ) 𝑁 [23]

Let 𝛼 be the probability of assessing the channel busy

during the 𝐴 and 𝛽 be the probability of assessing it busy

during 𝐴 , assuming that it was idle in 𝐴 . Fig. 2

illustrates the proposed 2-D-Markov chain model for robust real-

time IEEE802.15.4 MAC protocol for multi-hop mesh network

with states represented by * ( ), ( )+ at a given time .

Fig. 2. 2-D Markov model for CSMA/CA mechanism of IEEE 802.15.4 robust real-time multi-hop mesh

,

, ,

, ,

𝑀, 𝑀,

,𝐿

𝛼

𝛼

𝛼

𝛽

𝛽

𝛽

𝛼

𝛼

𝛼

𝛽

𝛽

𝛽

𝛾

𝛾

,𝑊

,𝑊

𝑀,𝑊𝑀

𝛾

𝛾

𝛾

𝛾

𝑃𝑓



From Fig.2, the following transition probabilities are obtained.

1. 𝒑*𝒊, 𝒌|𝒊, 𝒌 + 𝟏+ (𝟏 𝜸), 𝒊 ∈ (𝟎,𝑴), 𝒌 𝑾𝒊 𝟏 (3)

Where 𝛾 .

/ is the probability that there is not an available

empty slot offset [20].

2. 𝒑*𝟎, 𝒌|𝒊, 𝟎+ (𝟏 )(𝟏 )(𝟏 𝜸)

𝟐, 𝒊𝝐(𝟎,𝑴), 𝒌 𝑾𝟎

( )

3. 𝒑*𝒊, 𝒌|𝒊 𝟏, 𝟎+ *, (𝟏 ) -(𝟏 𝜸) 𝜸+

𝟐, 𝒊 ∈ (𝟏,𝑴), 𝒌 𝑾𝒊

(5)

4. 𝒑*𝟎, 𝒌|𝑴, 𝟎+ (𝟏 )(𝟏 )(𝟏 𝜸)

𝟐+

𝟐, 𝒌𝝐(𝟎,𝑾𝑴)

(6)

Where 𝑃 *,𝛼 + ( 𝛼)𝛽-( 𝛾) + 𝛾+ is the probability

for transmission failure

Let the stationary probability of being in the state * , 𝑘+ be

, 𝑃{( ( ), ( )) ( , 𝑘)}, ∈ ( ,𝑀), 𝑘 ∈ ( ,𝑊 ).

Specifically, , 𝑃{( ( ), ( )) ( , )} and

, 𝑃{( ( ), ( )) ( , 𝑘)}

Therefore,

, ( 𝛼) , (7)

, 𝛼 , + 𝛽 , (8)

, ( 𝛼) , (9)

Then substituting equation (9) into (8), , leads to

, 𝛼 , + 𝛽 ( 𝛼) , (𝛼 + 𝛽 𝛼𝛽) , (10)

The general state probability formula can be obtained as

{ , ,

, ( 𝛼) ,

Where 𝛼 + 𝛽 𝛼𝛽

Due to the Markov chain regularities, the following relations

are obtained.

, ( )

{( 𝛼)( 𝛽)( 𝛾)∑ , + 𝑃

}, (12)

, ( )

, , ∈ ( ,𝑀), 𝑘 ∈ ( ,𝑊 ) (13)

Let be the probability that a node performs 𝐴 in a

random chosen time slot when the backoff counter reaches

zero, that is regardless of backoff stage and independent across

nodes. Since the probabilities must sum to 1, the equation (14)

is obtained as follow:

∑ ∑ , + ∑ ,

+ ∑ ,

+∑ ,

∑ , {𝑊

+ ( 𝛾), + ( 𝛼)( + ( 𝛽)𝐿)-}

(14)

By taking into account interaction between node according to

[23], the expressions for 𝛼, 𝛽 and are obtained as follow:

𝛼 𝐿 0 ( ( 𝛾)) ( )

1 ( 𝛼)( 𝛽) (15)

𝛽 [

( ( ))

] 0 ( ( 𝛾)) ( )

1 (16)

∑ , [ ( ) ]( )

,

(17)

Hence, the network operating point parameters , 𝛼 and 𝛽 are

obtained by solving the three non-linear equations (15), (16)

and (17).

VI. SIMULATION RESULTS AND ANALYSIS

This model is validated by using NS-2 simulator (version 2.34)

[22]. In this section, the analytical model is used to study the

energy consumption and throughput behavior of IEEE

802.15.4 multi-hop mesh network. TABLE I shows different

parameters used for this model.

TABLE I

General Simulation Settings

Radio Parameters

𝐴

5

𝑊

𝑊

𝑊

. 𝑊

. 6 𝑊

Variable and fix parameters

𝑀 𝑥 𝑀𝐴 𝑘

𝑀

𝑀 𝑥

𝑊

𝑘 𝑃

5,

,

5

.

⁄

Packets

𝑀𝐴

𝐿

𝑀𝐴 +

(11) for 𝑖 ∈ ( ,𝑀)



A. Throughput Analysis

The network throughput that is the number of occupied slots

for a successful frame transmission under the saturation

condition is given in the equation (18) in which the impact of

duty cycle on throughput is considered:

𝐿𝑁 ( 𝛾), ( 𝛾)- ( )( 𝛼)( 𝛽) ( ) (18)

After twice successive sensing channel idles, the node can

occupy the channel alone and transmit the pending frame

without the interference brought by any other node. For the

low Duty Cycle( .56 ), 𝑂 and 𝑂 are set to be

and respectively to ensure the energy conservation. Hence,

from Fig. 3 it can be seen that the analytical results of

throughput are compared with the simulation results.

Fig. 3. Throughput vs. Number of nodes (BO=10, SO = 4)

B. Power Consumption and Delay Analysis

In energy consumption analysis, factors such as the slots used

for periodical beacon transmission/reception( ), the CAPs

in active and inactive portions and finally, the sleep-to-idle

transition time ( ) which is .6 backoff slots [24]

Therefore, the average power consumption of each node

can be obtained as follow:

𝑃 +

,𝐿( 𝛼)( 𝛽)( 𝛾) +

( 𝛾)( 𝛼)𝑃 - (19)

Fig. 4. Power Consumption vs. Number of nodes

For end to end delay, this model is compared with the IEEE

802.15.4 MAC standard and the simulation results are shown

in Fig. 5, 6 and 7. No analytical model is developed for the

delay in this paper and it would be further investigated in

future works

The graph in Fig. 5 shows the influence of the duty cycle

on the end-to-end delay for a higher number of nodes.

Fig. 5. End-to-end delay vs. Duty Cycle (51nodes, SO = 4)

In Fig. 6, the impact of BO to data delivery delay is depicted.

Fig. 6. End-to-end delay vs. Beacon Order (51nodes, SO = 4)

0

0.05

0.1

0.15

0.2

0.25

5 10 15 20 25 30 35 40 45 50

Thro

ugh

pu

t

Number of nodes

Analytical Simulation

0

0.5

1

1.5

2

2.5

5 10 15 20 25 30 35 40 45 50

Po

we

r C

on

sum

pti

on

pe

r n

od

e

(mW

)

Number of nodes

Analytical Simulation

0

5000

10000

15000

20000

1 5 6 11 16 21 26 31 36 41 46 51

En

d-t

o-e

nd

dela

y (

ms)

Duty Cycle (%)

IEEE802.15.4std Smart model

0

500

1000

1500

2000

5 6 7 8 9 10 11 12 13 14

En

d-t

o-e

nd

dela

y (

ms)

Beacon Order (BO)




Finally, the Fig. 7 shows an end-to-end delay for different

traffic loads (different number of nodes) for a duty cycle (DC)

of 1.56% (BO = 10, SO = 4).

Fig. 7. End-to-end delay vs. Number of nodes

As shown in the Fig. 3&4, the simulation results validate the

theoretical analysis well. Hence, from Fig. 3, the network

throughput keeps growing with the increase of number of

nodes which demonstrates good scalability of the proposed

IEEE 802.15.4 MAC protocol model for multi-hop mesh

network networks. Furthermore, from Fig. 4, it is observed that

as the number of nodes increases, a successful transmission of

every bit of data requires less energy. Finally, it can be seen

that the developed model provides a better delay performance

than the original GTS mechanism of the IEEE 802.15.4

standard for different levels of duty cycle (Fig. 5), beacon

order (Fig. 6) and node number (Fig. 7).

VII. CONCLUSION AND PERSPECTIVES

In this paper, an analytical model for robust real-time IEEE

802.15.4MAC protocol for multi-hop mesh network is

developed. The validity of the analytical model is

demonstrated by the fact that its predictions closely match the

simulation results. The presented results are encouraging and

open many research perspectives. As it is crucial to test the

proposed model in real world environment, in the future

works, this model will be implemented on real-sensors using

the iLive platform [25] with the Atmel open MAC stack

protocol since it provides an open source implementation of

the IEEE 802.15.4 standard [26].

ACKNOWLEDGEMENT

The authors wish to thank the International Islamic University

Malaysia (IIUM) and the Renewable Energy Research Group

(RERG), Faculty of Engineering.

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