ENERGY-CONSERVING ON-DEMAND ROUTING FOR

MULTI-RATE MULTI-HOP NETWORKS

Tsung-Han Lee , Alan Marshall, Bosheng Zhou

School of Electrical and Electronic Engineering, Queen's University of Belfast, Belfast, UK

Keywords: Energy efficiency, ad-hoc routing, energy-conserving, multi-rate.

Abstract: We present a novel scheme for conserving energy in multi-rate multi-hop wireless networks such as 802.11.

In our approach, energy conservation is achieved by controlling the rebroadcast times of Route Request

(RREQ) packets during path discovery in on-demand wireless routing protocols. The scheme is cross-layer

in nature. At the network layer, the RREQ rebroadcast delay is controlled by the energy consumption

information, and at the Physical layer, an energy consumption model is used to select both the rate and

transmission range. The paper describes the energy-conserving algorithm at the network layer (ECAN),

along with simulation results that compare the energy consumption of Ad-hoc On-Demand Distance Vector

routing (AODV) with and without ECAN.

1 INTRODUCTION

Many Mobile terminals such as PDAs, smart mobile

phones and laptops are usually powered by batteries,

which necessarily provide limited amounts of

energy. Therefore, techniques to reduce energy

consumption in wireless ad-hoc networks are

attracting a lot of attention. The most well known

technique to conserve energy is to employ power

saving mechanisms which allow a mobile node to go

to sleep mode whenever the wireless network

interface is idle (J. Gomez et al., 2001). However

such mechanisms may not be always a good idea, as

they can partition the wireless network. A node must

turn its radio on not only to receive packets, but also

to participate in transmitting any higher-level

routing and control protocols. An alternative

approach is to reduce the route control and

signalling load by using the network layer

information related to the routing protocol to extend

route lifetimes (Bosheng Zhou et al., 2004).

Due to the physical properties of communication

channels, there is a direct relationship between the

rate of communication and the energy consumption

of mobile devices. Since distance is one of the

factors that determines wireless channel quality (e.g.

BER and SNR), long-range communication should

occur at low rates, and high-rate communication

should take place over short range. These multi-rate

and multi-range capacities provide a number of

different trade-off points (Gavin Holland et al.,

2001). For example, with a high communication rate

and short communication range, there is a trade-off

between the number of relay nodes in routing path

and the energy consumption of entire wireless

network. In this work, we focus on how to balance

these objectives. We propose a framework for

conserving energy in multi-rate multi-hop wireless

networks (IEEE 802.11 Work Group, 1999). The

framework is cross-layer in nature and operates in

the Physical and Network layers. Dynamic

adjustment of transmission rate can produce efficient

data communication for multi-hop wireless networks

in the Physical layer, while a cross-layer routing

algorithm in Network layer is used to provide a

balance between the minimum transmission energy

consumed and a fair distribution of energy

consumed across the nodes involved in a route. This

goal is achieved by controlling the rebroadcast delay

of Route Request (RREQ) packets. Within the

framework, we have designed a mechanism to

estimate the end-to-end energy consumption in the

routes through a multi-rate multi-hop network. This

is used to adaptively control the RREQ rebroadcast

delay in the wireless routing protocol.

The rest of the paper is organized as follows.

Section 2, we present our proposed energy-

conserving algorithm in detail. Section 3 describes

156

Lee T., Marshall A. and Zhou B. (2005).

ENERGY-CONSERVING ON-DEMAND ROUTING FOR MULTI-RATE MULTI-HOP NETWORKS.

In Proceedings of the Second International Conference on e-Business and Telecommunication Networks, pages 158-161

DOI: 10.5220/0001414501580161

 SciTePress

the simulation results and performance comparison.

Finally, we conclude the paper in Section 4.

2 SYSTEM MODEL OF

NETWORK LAYER

The routing protocol for multi-hop and ad-hoc

wireless networks proposed in this paper is called

ECAN (Adaptive Energy-Conserving routing

Algorithm in Network layer). ECAN attempts to

reduce routing control overhead and processing

requirement so as to minimize power utilization.

2.1 Energy-Conserving Algorithm in

802.11 Network-layer (ECAN)

Generally in on-demand routing protocols (C. E.

Perkins and E.M. Royer, 1999)(S. Ni et al., 1999), a

source floods a RREQ packet to search for a path

from source to destination. The destination node

receives the RREQ packet and unicasts RREP

(Route-reply) packets back to the source to set up

the path. ECAN uses a “rebroadcast time” control

mechanism, coupled with information on the battery

levels of nodes, to select desirable routes and reduce

the routing overhead. ECAN does not implement

any supplementary control packets to obtain energy

information for power aware routing. The RREQ

rebroadcast time is defined using the total energy

cost of a path. The rebroadcast control mechanism is

then executed to determine whether or not to

rebroadcast the RREQ.

ECAN

is the combined multi-hop energy

consumption by nodes on the path and K

cout

is the

hop count number that the RREQ packet has

registered. When an intermediate node has

determined the rebroadcast delay of a RREQ, it then

enters a competing procedure to rebroadcast the

RREQ. The main parameters of our energy model

are:

z P

[mJ/sec]: the power required to transmit

data.

z P

[mJ/sec]: the power required to receive

data.

z P

[mJ/sec]: the power required to sense

radio.

z P

[mJ/sec]: the power required in idle mode.

There are three energy dissipation scenarios that can

be considered, as shown in figure 1: (i) Direct

Transmission Model (Single-hop). (ii) Direct

transmission (Single-hop) with a neighbour node

Model. (iii) Multi-hop Simple Relay Model (k-hop).

We denote the complete multi-hop energy

consumed by nodes on the path, E

ECAN

, as

(

)

t×++=

∑

P P P E

RXcirc

TXcirc

ECAN

(1)

Where t is the total transmitting time. P

TXcirc

is the

energy expended by the circuitry in transmit mode

and P

RXcirc

is the energy expended in receive mode.

ECAN

E is the total energy consumption at k-hop

scenario.

i) In the direct transmission model (Fig.1a).

Figure 1 provides a model for P

and P

for

IEEE 802.11 RTS/CTS/DATA/ACK handshake.

DIFSRSSIFSR

ACKDATA

MAC

PHY

CTSRTS

ECAN

TPTP

ratebasic

PPPE

×+×+

+++++

×∆++=

)

(

)2()(

(2)

The H

PHY

and H

MAC

are the frame headers of the

PHY and MAC layers respectively. The basic_rate is

the basic data transmission rate, which is defined in

the 802.11 standard. γ is the current data

transmission rate. ∆P is the energy different between

the P

TXcirc

and the P

RXcirc

. Thus,

PPPP

TXcirc

∆+==

ii) Direct transmission (Single-hop) with a

neighbour node Model.

In this scenario (Figure. 1b), A transmits data to

B and C as a neighbour node in RTS/CTS cover

range of node A.

SIFSACKDATACTSNAV

DIFSRSNAV

RTS

ECAN

ABC

ECAN

TTTTT

TPTPTPE

PPPP

+++=

×+×+×=

∆++=

(3)

iii) Multi-hop Simple Relay k-hop Model

ECAN

is the multi-hop simple relay k-hop

model (Figure 1c). We assume that a node i has n

neighbour nodes within transmission range, we

Figure 1: an illustration of RTS/CTS of Energy

Consumption in DCF

Source

Destination

Others

Deferred Medium Access

RTS

SIFS

CTS

DATA

ACK

DIFS

Sending

Reveiving

SIFS

(a)

(b)

(c)

RTS

CTS

NAV(RTS)

NAV (CTS)

ACK

DATA

ENERGY-CONSERVING ON-DEMAND ROUTING FOR MULTI-RATE MULTI-HOP NETWORKS

157

obtain the weighting factor of the multi-hop

energy consumption

)(

ECAN

E in node i.

)(

)()(

)()1(

)

(

)2(

)(

NAV

RDIFSRS

RTS

SIFSRDIFSRS

ACKDATATX

CTSRTSTX

ACKDATA

MAC

PHY

CTSRTS

ECAN

TPTPTPn

TkPTkP

TTPk

ratebasic

PPk

⋅+⋅+⋅×+

×+×+

+××+

+++++×

∆+×=

(4)

SIFSACK

MAC

PHY

DATACTSNAV

DATA

ratebasic

TTT

and

+++++=

Where L is the data frame size and γ is the data

transmission rate.

2.2 Rebroadcast time control

mechanism

The goal of ECAN is to control the rebroadcast time

and to reduce routing overhead whenever a node is

low on battery power. This strategy will prolong the

wireless network lifetime. R

xRREQ

is the signal

strength of RREQ packet.

A node determines its rebroadcast time T

RREQ

follows.

Output:

RREQ packet Mi(E

ECAN

(γ) , K

cout

Begin

Receive a RREQ packet

if the RREQ packet come from a new neighbour

node than

n = n + 1, n is the number of neighbour.

if (R

xRREQ

> ReceiveSensitivity (11Mbps)) than

γ = 11Mbps

else if (ReceiveSensitivity (5.5Mbps) < R

xRREQ

< ReceiveSensitivity (11Mbps)) than

γ = 5.5Mbps

else if (ReceiveSensitivity (2Mbps) < R

xRREQ

< ReceiveSensitivity (5.5Mbps)) than

γ = 2Mbps

else

γ = 1Mbps

()

1)11(

)(

tanh

max

+×

×=

coutECAN

coutECANi

RREQ

KMbpsE

) , K(EM

βσ

max

is the maximum delay of RREQ packet.

ECAN

(11Mbps) is the energy consumption at

11Mbps data rate, α is a constant variable for RREQ

delay. Tanh(β) is a hyperbolic tangent function. σ 

[0,0.99] when β  [0,4]. T

RREQ

increases rapidly

when β approaches 4 so as to differentiate

rebroadcast delay between high priority nodes. In

this paper, we set these parameters as T

max

= 20 ms,

= 5 ms.

3 SIMULATION RESULTS

To evaluate its performance, we have implemented

ECAN based on the well-known AODV wireless

routing protocol. A simulation environment was

developed using the Qualnet developing library

(Qualnet simulator). Using this, the performance of

AODV was compared with and without ECAN. The

bandwidth of the wireless channel varied from

1Mbps to 11Mbps, which is chosen by SINR (Signal

to Interference and Noise Ratio). The data packet

size is 1024 bytes. The traffic pattern is constant bit

rate, with a 10s inter-packet arrival time. The

simulation scenario consisted of 64 nodes that are

grid distributed and 200m apart. Table 1 gives the

simulation parameters.

Transmit mode (P

) 1400 mW

Receive mode (P

) 900 mW

Idle mode (P

) 600 mW

Sense mode (P

) 600 mW

Transmit power level 15 dBm

Initial energy of nodes 4000 mAh / 10V

1 Mbps = -93 dBm

2 Mbps = -89 dBm

5.5 Mbps = -87 dBm

Receive sensitivity

11 Mbps = -83 dBm

Figure 2(a) illustrates the energy consumption of

each scheme. It shows that AODV with ECAN using

a higher transmission rate will decrease the duration

of transmission, and effectively reduce to 75%

energy consumed of native AODV in receive and

transmit mode. In ECAN, the link with higher

transmission rate and lower energy consumption has

the higher priority to be selected. This simulation

result demonstrates that AODV with ECAN

mechanism will conserve more energy than AODV.

The performance of ECAN against route length

is shown in Figure 2(b). The results show that the

average route length of ECAN scheme is around

20% less than native AODV. This is because the

ECAN scheme aims at finding the route that has

lower energy consumption and higher performance

route rather than the native AODV.

Table 1: Simulation parameters

ICETE 2005 - WIRELESS COMMUNICATION SYSTEMS AND NETWORKS

158

Figures 2(c) shows result conserving the RREQ

routing overhead. It may be seen that the routing

overhead of native AODV increases much more

rapidly than AODV with ECAN. The routing

overhead of RREQs forwarded is only 80% of that

of native AODV. The reason for the lower routing

overhead is that a large amount of rebroadcasts are

avoided in the route discovery procedure.

Analysis of the overall network performance

shows that the average End-to-End delay is only

29% that of native AODV. This is because ECAN

aims to find the more stable and higher transmission

rate routes by using the received SINR.

From the above results, we can conclude that

AODV with ECAN performs more efficiently than

native AODV in terms of higher throughput, lower

End-to-End delay, and reduced routing overhead.

Furthermore, the results show that it saves much

more network bandwidth and energy.

4 CONCLUSIONS

We have designed a cross-layer approach to energy

conservation for multi-rate multi-hop routing. The

ECAN uses two algorithms and is applied in the

Physical and Network layers. First, algorithm

achieves energy conservation by uses the highest

data transmission rate. The second algorithm adapts

RREQ rebroadcast times based on the total energy

consumption cost of a path. In our system model,

ECAN only requires the current transmission SINR

from Physical layer, which can be obtained with the

use of only RREQ packets. When RREQ packets are

broadcast, the rebroadcast time is determined by a

rebroadcast control mechanism.

Simulation results show that ECAN achieves

energy saving without causing throughput

degradation. This improvement is due to the fact that

ECAN makes a compromise between the multi-rate

transmission and fair energy consumption.

This paper describes research that is applied in the

Physical and Network layers. An interesting area of

future research will be to extend the approach for

MAC layer specific information such as TPC

(Transmission Power Control) to further optimize

energy consumption.

ACKNOWLEDGMENT

This work is supported by the UK funding body

EPSRC, under the project GR/S02105/01

“Programmable Routing Strategies for Multi-Hop

Wireless Networks”.

REFERENCES

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Figure 2: Simulation results in the 64 nodes wireless multi-hop networks

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