A guide for the selection of routing protocols in WBAN for healthcare applicationsV. Bhanumathi* and C. P. Sangeetha

IntroductionWireless body area networks (WBANs) include a collection of body sensor nodes that are low power, invasive or non-invasive, light-weight devices which are either worn on the body or implanted inside the body. The architecture of WBAN [1] can be considered as three different tiers, namely: Tier-1 as Intra-BAN, Tier-2 as Inter-BAN and Tier-3 as Extra-BAN as shown in Fig. 1. In Tier-1, the body sensor nodes collect the data and send to the coordinator. In Tier-2, the coordinator processes the received data and sends the

Abstract

In the present scenario, the term wireless body area network (WBAN) is becoming an integral part of human day to day life due its wide variety of applications, especially in the field of healthcare systems. To design such a reliable body area network system, there are a number of factors to be considered both in hardware and software levels. One of such factors still developing is the design and the analysis of routing proto-cols in the network layer. Routing protocols are a set of protocols which can identify and maintain the routes in the network so that the data can be exchanged between the nodes efficiently. Hence, routing protocol plays a vital role in the wireless sensor networks for reliable communication between the sensor nodes. In this paper, differ-ent routing protocols for body area networks are surveyed and observed that they are affected by factors like energy, network topology, various quality of services (QoS) in the nodes, node temperature, transmission range of nodes, human posture, etc. An evocative taxonomy of protocols is presented such as cluster-based, cross-layered, postural movement based, QoS aware and temperature-aware routing protocols. From the survey, it is found that the selection of a routing protocol is application dependent. For example, the energy efficient protocols like reinforcement learning based routing with QoS support or wireless autonomous spanning tree protocol can be used for daily health monitoring systems due to its high packet delivery ratio. If the system is for in vivo networks, routing algorithm for network of homogeneous and Id-less biomedi-cal sensor nodes or mobility-supporting adaptive threshold-based Thermal-aware energy-efficient multi-hop protocols are the suitable ones. For critical and emergency cases, where accuracy with little delay is the major concern, the protocols like critical data routing, reliability aware routing, data-centric multi objective QoS-aware rout-ing protocol, etc. can be rightly chosen. This entire survey paper can be used by the researchers as a reference for studying various WBAN routing protocols, especially in the field of medical health care systems.

Keywords: Quality of service, Routing protocols, Wireless body sensor networks

Open Access

© The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

REVIEW

Bhanumathi and Sangeetha Hum. Cent. Comput. Inf. Sci. (2017) 7:24 DOI 10.1186/s13673-017-0105-6

*Correspondence: vbhanu_02@yahoo.com Anna University Regional Campus, Coimbatore, Tamil Nadu, India

Page 2 of 19Bhanumathi and Sangeetha Hum. Cent. Comput. Inf. Sci. (2017) 7:24

information towards the sink node. From the sink node the packets are transmitted to the corresponding health-center through internet or other communication techniques.

According to the survey conducted by the Economic and Social Affairs Department of United Secretariat [2], after 10 years people with age above 65 will be approximately 15% of total world population. As, older people are more exposed to medical health issues, the need for low cost health monitoring devices [3] becomes a major part human life.

WBAN is actually a subset of conventional wireless sensor networks (WSNs), which can be used for early detection of various diseases, for real-time patient monitor-ing of elderly people, etc. The body sensor node is either worn on the body surface or implanted inside the body. The sensed data is sent to the Base Station and is then for-warded to the sink node. The sink node is responsible for sending the information to its corresponding healthcare center.

The reliability and efficiency of WBAN depend on how the system responds quickly and accurately, to send and receive the data between the nodes, which eventually depends on the selected routing protocols or algorithms. The process of sending infor-mation from either an in-body or an on-body sensor node includes the radiation emitted from wireless transceivers which is similar to WSNs.

Although the routing protocols that are used in WSNs have been under study for past few years, these protocols cannot be used for WBANs due to its stringent requirements. For WSNs, the main focus is on minimal routing overhead and maximal throughput than reduced energy consumption [4]. Also, WSNs are mostly homogenous networks, the WBANs are heterogeneous too [5].

In this article, a comprehensive review of the existing recent routing protocols/algo-rithms is discussed. “The required evaluation metrics for healthcare applications” sec-tion discusses the performance metrics that should be considered for WBANs. The classification of the existing routing protocols is explained in “Classification of routing protocols” and “Future challenges and comparative analysis of routing protocols” sec-tions gives the future challenges and a comparative analysis of different selected proto-cols. Finally, “Conclusions” concludes the survey.

EEG Hearing

Glucose

Blood pressure

Coordinator

Sink node

Internet

Physician Hospital

Data Server Emergency

Tier - 1 Tier - 2 Tier - 3

Vision

ECG

Fig. 1 Wireless body area network architecture

Page 3 of 19Bhanumathi and Sangeetha Hum. Cent. Comput. Inf. Sci. (2017) 7:24

The required evaluation metrics for healthcare applicationsIn order to identify the important metrics that have to be considered in WBANs during the design process, a general overview about the routing challenges in WBANs should be studied. The certain routing issues and challenges include network topology, postural body movements, limited resources, quality of service metrics, radiation and interfer-ence, global network lifetime, heterogeneous environment, etc. By analyzing all these factors we can conclude and list the important performance metrics to be considered while implementing the whole WBAN. The following section defines the metrics:

• Network lifetime defines the total operation time of the network until the last node is dead.

• Path loss is the difference between the transmitted power at the source node and received power at sink node.

• Stability period is the time before first node die. • Residual energy is the difference between initial energy and used energy during the

operation of the network. • End-to-end delay is the average time taken by a data packet to reach the sink from

the source node. • Packet delivery ratio is determined by number packets obtained at the sink divided

by the number of packets send from the source.

Classification of routing protocolsThe classification of routing protocols can be done in different categories that correlate with the routing challenges of WBAN. The following section gives an overview about the existing protocols, which can be categorized as Cluster-based, Cross-layered, Postural movement based, quality of services (QoS) aware and Temperature-aware routing algo-rithms [6] as shown in Fig. 2.

Cluster‑based routing protocols

In both WSNs and WBANs, the limited energy source is the main constraint to be ana-lyzed. Hence, several efficient cluster based schemes are proposed for both networks to minimize the power consumption and maximize the network lifetime [7]. While com-paring hybrid indirect transmission [8] to power-efficient gathering in sensor infor-mation systems [9] and low-energy adaptive clustering hierarchy (LEACH) [10], it consumes less amount of energy if the number of nodes are small. However, AnyBody [11] protocol is better than LEACH, as the numbers of clusters remain constant with an increase in the number of nodes, but LEACH does not. Also, the installation cost is also less with AnyBody. The Table 1 shows an overview of the existing cluster-based protocols.

Cross‑layered routing protocols

These protocols use the concept of cross layering [13] which is already addressed in WSNs, where each layer (adjacent or non-adjacent) in the protocol stack shares their information unlike in the strict layered model. In WBANs, we can utilize the cross layer-ing concept between network and medium access control (MAC) layers for routing and

Page 4 of 19Bhanumathi and Sangeetha Hum. Cent. Comput. Inf. Sci. (2017) 7:24

thereby can upgrade the overall network performance. Table 2 shows the different cross-layered routing protocols. Considering the detailed analysis of cross layered protocols, Cascading Information retrieval by controlling access with distributed slot assignment (CICADA) [14] and time zone coordinated sleep scheduling [15] have less power con-sumption. Wireless autonomous spanning tree protocol (WASP) [16] has better packet delivery ratio and CICADA has less delay.

Postural movement based routing protocols

The body postural movements affect the network topology of the network, which results in link disconnection. The researchers introduced a cost function that is periodically

ARBA

QPRR

DARE

SIMPLE

CO-LAEEBA

Two-Hop

MLAEEBA

RAR

ZEQoS

TEEN

Multi-hop

CDR

WBAN Routing Protocols

Clustered Cross layered Postural Temperature QoS aware

QPRD

QRP

EAWD

EPR

Gateway

AMR

EBRAR

DMQoS

RACOON

Heuristic

Modified Dijkstras Global

LOCALMOR

EERS

EAR

RLQRP

QoS

M2E2

RE-ATTEMPT

MATTEMPT,

TMQoS

THSR

LTRT

HPR

RAIN

LTR,

TARA

ATTEMPT

CBBAP

AnyBody

HIT

WASP

TICOSS

CICADA

BioComm ETPA

PSR

Opportunistic

PRPLC

DVRPL

OBSFR

Relay Based

LAEEBA

ENSA

Energy Efficient

Fig. 2 Classification of routing protocols

Table 1 clustered routing protocols in body area networks

Sl. no. Protocol [ref. no.] Goal Performance metrics Compared with

1 Cluster based body area protocol (CBBAP) [12]

To enhance the overall energy efficiency of WBAN

Throughput, residual energy, number of live nodes

LEACH

2 AnyBody protocol [11] To divide the network into clusters and to efficiently send packets from source to sink

Number of clusters, average cluster size, number of transmitted messages to setup

LEACH

3 Hybrid indirect transmis-sion (HIT) [8]

To maintain longer network life

Network longevity, network delay, average energy dissipation, average energy dis-sipation × average delay product

LEACH, PEGASIS, direct

Page 5 of 19Bhanumathi and Sangeetha Hum. Cent. Comput. Inf. Sci. (2017) 7:24

updated for choosing the best route to forward packets to the sink. The protocols listed in Table 3 are the existing postural movement based routing protocols. Among the dis-cussed protocols, on-body store and flood routing (OBSFR) [18] has better performance in reducing the packet delivery delay, but opportunistic postural movement based rout-ing protocol has lower energy consumption than others.

QoS aware routing protocols

Presently, there are a number of diverse QoS aware protocols available in WSNs, which cannot be as such implemented in WBANs, but by considering its unique curbs it can. In WBANs different data types require different QoS [24]. Hence the proposed proto-cols should be aware of different types of QoS metrics for various types of data. The vari-ous QoS aware routing protocols are shortlisted as given in Table 4.

The comparative analysis has shown that energy-aware peering routing protocol (EPR) [45], QoS-aware peering routing protocol for delay sensitive data (QPRD) [41] and QoS aware peering routing protocol for reliability sensitive data (QPRR) [38] have less power consumption when compared to other protocols. Some protocols do not consider energy consumption, while others. One of the most used QoS aware protocols is data-centric multi objective QoS-aware routing protocol (DMQoS) [50] because it can decrease the delay for delay-sensitive information, and similarly, it can provide reliable routing for reliable-sensitive information. The other QoS-aware protocols are used or selected for a particular network, according to the data type and its QoS requirements.

Temperature‑aware routing protocols

The antenna radiation, its absorption and interference are the major challenges to be considered while designing a body sensor network, since the radiated fields cause a temperature rise of node’s electronic circuitry. The field of radiation also has a strong

Table 2 Cross layered protocols in body area networks

Sl. no. Protocol [ref. no.] Goal Performance metrics Compared with

1 Biocomm and Biocomm-D [17]

To optimize the overall performance of the in vivo network

Maximum temperature rise, average energy con-sumption, packet delivery delay, percentage of injected packets dropped, cumulative network throughput

Shortest hop routing, hotspot preventive routing

2 Cascading informa-tion retrieval by controlling access with distributed slot assignment (CICADA) [14]

To introduce less delay and low energy con-sumption

End to end delay –

3 TImezone coordinated sleep scheduling (TICOSS) [15]

To improve 802.15.4 through the division of the network into time zones

Network lifetime IEEE 802.15.4 without TICOSS

4 Wireless autonomous spanning tree proto-col (WASP) [16]

To reduce power consumption, network delay and packet loss rate

End to end delay CSMA with fixed routing

Page 6 of 19Bhanumathi and Sangeetha Hum. Cent. Comput. Inf. Sci. (2017) 7:24

impact on the human body [57] that may damage the human tissues due to its continu-ous exposure. The goal of all temperature-aware protocols is to decrease the temperature rise of in-body sensor nodes by avoiding routing through hotspots. Table 5 discusses the existing temperature-aware protocols. From the comparison of different protocols, it is seen that LTRT [58] performs much better than others while TARA [59] performs worst. In terms of temperature rise, HPR [60] shows less temperature rise in comparison with others. Finally, the latest M2E2 protocol [61] has proved that it is the best one among all thermal aware protocols, suitable for heterogeneous, multimode, energy efficient body sensor networks.

Future challenges and comparative analysis of routing protocolsThe scope of this article is to open up new research areas in WBAN domain for routing protocol designs. Among all the routing protocols, the cluster based protocol HIT [8] aims at maximizing the network lifetime, but it does not consider the packet delivery ratio which is an important QoS metric. The second one, AnyBody [11] protocol consid-ers the delivery ratio, but does not consider average delay, mobility and energy consump-tion. It leads to poor security measures. In order to optimize the performance of sensor networks for some specific applications, it is necessary to include the aforementioned metrics also in the design considerations.

The cross layered concept is attaining great significance and interest among research-ers due to its flexibility and effectiveness in sensor networks. The future research work aims at improving the reliability of CICADA [14] which performs better in terms of energy efficiency and average delay when compared to other cross layered protocols.

Table 3 Postural routing protocols in body area networks

Sl. no.

Protocol [ref. no.] Goal Performance metrics Compared with

1 Energy efficient thermal and power aware rout-ing (ETPA) [19]

To reduce the node’s temperature and to prevent the hotspot formation

Packet hop count, packet delivery ratio, packet delay, average tem-perature rise of nodes in the network, scalability, depletion time of the first node mobility

PRPLC

2 Prediction based secure and reliable routing framework (PSR) [20]

To provide secure and reliable routing from various data attacks

Packet dropping rate, authentication cost

Backbone protocol

3 Opportunistic routing [21] To increase the network lifetime from the motion of body parts

Average energy consump-tion per bit

Single hop, multi hop

4 Distance vector routing with postural link costs (DVRPLC) [22]

To decrease end to end delay

Average delay, packet delivery ratio, packet hop count

Probabilistic proto-col (PROPHET), opportunistic protocol, UTILITY

5 On-body store and flood routing (OBSFR) [18]

To provide better rout-ing delay and hop count

End-to-end packet delay (PD), number of transmissions per packet (NTPP), packet delivery ratio (PDR)

PROPHET, on-body store and flood routing (OBSFR)

6 Probabilistic routing with postural link costs (PRPLC) [23]

To reduce end to end delay

Average delay, packet delivery ratio

PROPHET, OBSFR

Page 7 of 19Bhanumathi and Sangeetha Hum. Cent. Comput. Inf. Sci. (2017) 7:24

Tabl

e 4

QoS

aw

are

rout

ing

prot

ocol

s in

 bod

y ar

ea n

etw

orks

Sl. n

o.Pr

otoc

ol [r

ef. n

o.]

Goa

lPe

rfor

man

ce m

etri

csCo

mpa

red

with

1Effi

cien

t nex

t hop

sel

ectio

n al

gorit

hm

(EN

SA-B

AN

) [25

]To

impr

ove

the

over

all Q

oS p

erfo

rman

ce

of th

e ne

twor

k us

ing

link

cost

func

tion

Ener

gy c

onsu

mpt

ion,

pac

kets

forw

arde

d, e

nd-t

o-en

d de

lay,

pac

ket d

eliv

ery

ratio

DM

QoS

2En

ergy

effi

cien

t rou

ting

algo

rithm

[26]

To m

axim

ize

the

wor

king

life

time

of th

e ne

twor

kCo

vera

ge d

ista

nce,

resi

dual

ene

rgy,

co

mm

unic

atio

n co

unt n

ode

criti

calit

y–

3M

ulti-

hop

prot

ocol

usi

ng c

ost f

unct

ion

[27]

To b

oost

the

netw

ork

perf

orm

ance

and

life

time

by

opt

imum

resi

dual

ene

rgy

and

dist

ance

Num

ber o

f dea

d no

des,

resi

dual

ene

rgy,

dat

a pa

cket

s se

nt a

nd re

ceiv

ed to

sin

k, d

elay

Old

ene

rgy

awar

e m

ulti-

hop

4C

ritic

al d

ata

rout

ing

(CD

R) [2

8]To

forw

ard

the

criti

cal d

ata

pack

ets

with

bet

ter

relia

bilit

y al

ong

with

redu

ctio

n in

tem

pera

ture

ris

e of

the

in-b

ody

sens

or n

odes

Pack

et lo

ss ra

tio, p

acke

t suc

cess

ratio

, on-

time

pack

et d

eliv

ery

ratio

, ene

rgy

cons

umpt

ion

TMQ

oS, L

TRT

5Th

resh

old

sens

itive

ene

rgy

effici

ent s

enso

r ne

twor

k pr

otoc

ol (T

EEN

) [29

]To

mon

itor a

nd re

cord

crit

ical

dat

a of

the

pa

tient

’s bo

dy p

aram

eter

sEn

ergy

con

sum

ptio

n, fa

lse

acce

ptan

ce ra

te, f

alse

re

ject

ion

rate

, tim

e se

rved

–

6A

dapt

ive

rout

ing

and

band

wid

th a

lloca

tion

pr

otoc

ol (A

RBA

) [30

]To

enh

ance

ban

dwid

th u

tiliz

atio

n an

d ro

utin

g in

BA

N, b

ette

r net

wor

k lif

etim

eRe

sidu

al e

nerg

y, th

roug

hput

Opt

imal

sol

utio

n

7Re

lay

base

d ro

utin

g pr

otoc

ol [3

1]Fo

r net

wor

k lif

etim

e m

axim

izat

ion

and

end-

to-

end-

dela

y (E

2ED

) min

imiz

atio

nRe

mai

ning

ene

rgy,

no.

of d

ead

node

s, no

. of

dro

pped

pac

kets

, pac

ket a

rriv

al ra

teSi

ngle

-hop

Mul

ti-ho

pC

H-r

otat

e

8Li

nk-a

war

e an

d en

ergy

effi

cien

t sch

eme

for b

ody

area

net

wor

ks (L

AEE

BA) [

32]

To ro

ute

data

with

min

imum

pat

h-lo

ss o

ver t

he

link

in W

BAN

Stab

ility

per

iod,

resi

dual

ene

rgy,

net

wor

k lif

etim

e,

path

-loss

, del

ay s

prea

d, th

roug

hput

SIM

PLE,

M-A

TTEM

PT

9Co

oper

ativ

e lin

k-aw

are

and

ener

gy e

ffici

ent

prot

ocol

for W

BAN

(Co-

LAEE

BA) [

33]

To s

elec

t bet

ter r

outin

g pa

th w

ith m

inim

um

path

-loss

in c

oope

rativ

e lin

ks in

WBA

NSt

abili

ty p

erio

d, re

sidu

al e

nerg

y, p

ath-

loss

, th

roug

hput

LAEE

BA, S

IMPL

E, M

-ATT

EMPT

10Tw

o-ho

p tr

ansm

issi

on s

chem

e [3

4]To

ext

end

netw

ork

lifet

ime

and

to im

prov

e th

e ne

twor

k st

abili

ty o

f WBA

NA

vera

ge re

sidu

al e

nerg

y, n

umbe

r of p

acke

ts p

er

prio

rity

leve

l, to

tal e

nerg

y, n

umbe

r of d

ead

node

s

Dire

ct tr

ansm

issi

on, T

PDS

11M

odifi

ed L

AEE

BA: l

ink

awar

e an

d en

ergy

effi

cien

t sc

hem

e fo

r BA

N (M

LEEB

A) [

35]

To u

pgra

de th

e LE

EBA

pro

toco

l by

incr

easi

ng

thro

ughp

ut a

nd d

ecre

asin

g de

lay

PDR,

end

to e

nd d

elay

, thr

ough

put

LEEB

A

12Re

liabi

lity

awar

e ro

utin

g (R

AR)

[36]

To e

nhan

ce re

liabi

lity

for r

elia

bilit

y co

nstr

aint

da

ta p

acke

tsPa

cket

loss

ratio

, ave

rage

PD

R, a

vera

ge e

nerg

y co

nsum

ptio

nRA

R w

ith re

lay

node

s, TM

QoS

13Za

hoor

ene

rgy

and

QoS

-aw

are

rout

ing

prot

ocol

(Z

EQoS

) [37

]To

pro

vide

bet

ter Q

oS b

y se

lect

ing

the

best

ro

utin

g pa

ths

Ener

gy c

onsu

mpt

ion,

suc

cess

ful t

rans

mis

sion

ra

te, p

acke

ts fo

rwar

ded

and

rece

ived

DM

QoS

, NoR

outin

g

Page 8 of 19Bhanumathi and Sangeetha Hum. Cent. Comput. Inf. Sci. (2017) 7:24

Tabl

e 4

cont

inue

d

Sl. n

o.Pr

otoc

ol [r

ef. n

o.]

Goa

lPe

rfor

man

ce m

etri

csCo

mpa

red

with

14Q

oS a

war

e pe

erin

g ro

utin

g pr

otoc

ol fo

r rel

iabi

lity

sens

itive

dat

a (Q

PRR)

[38]

To e

nhan

ce th

e re

liabl

e de

liver

y of

em

erge

ncy

BAN

dat

a fo

r ind

oor h

ospi

tal c

omm

unic

atio

nSu

cces

sful

tran

smis

sion

rate

, net

wor

k tr

affic

load

, ov

eral

l ene

rgy

cons

umpt

ion,

late

ncy

DM

Qos

, NoR

outin

g

15D

ista

nce

awar

e re

layi

ng e

nerg

y effi

cien

t pro

toco

l (D

ARE

) [39

]To

ach

ieve

bet

ter n

etw

ork

lifet

ime

for m

onito

ring

patie

nts

in m

ulti-

hop

body

are

a ne

twor

ksRe

sidu

al e

nerg

y, P

DR,

num

ber o

f pac

kets

se

nt to

sin

kM

-ATT

EMPT

16St

able

incr

ease

d-th

roug

hput

mul

ti-ho

p pr

otoc

ol

for l

ink

effici

ency

(SIM

PLE)

[40]

To b

oost

the

netw

ork

stab

ility

per

iod

and

pack

et

deliv

ered

to s

ink

Net

wor

k lif

etim

e, s

tabi

lity

perio

d, th

roug

hput

, re

sidu

al e

nerg

y, p

ath

loss

ATTE

MPT

17Q

oS-a

war

e pe

erin

g ro

utin

g pr

otoc

ol fo

r del

ay

sens

itive

dat

a (Q

PRD

) [41

]To

less

en th

e en

d to

end

del

ayTr

affic

load

, suc

cess

ful t

rans

mis

sion

rate

, num

ber

of p

acke

ts ti

meo

utD

MQ

oS

18Q

-lear

ning

bas

ed ro

utin

g pr

otoc

ol (Q

RP) [

42]

To d

esig

n a

pow

er e

ffici

ent a

nd re

duce

d ho

p co

unt b

ody

sens

or n

etw

orks

Resi

dual

ene

rgy,

ave

rage

hop

cou

ntPS

R, E

BRA

R

19A

dapt

ive

mul

tihop

tree

-bas

ed ro

utin

g (A

MR)

pr

otoc

ol [4

3]To

ass

ess

seve

ral n

ode

and

netw

ork

para

met

ers

in

ord

er to

enh

ance

net

wor

k pe

rfor

man

ce

usin

g fu

zzy

logi

c

Net

wor

k lif

etim

e, P

DR,

nor

mal

ized

resi

dual

en

ergy

Shor

test

pat

h tr

ee, r

ecei

ved

sig-

nal s

tren

gth

indi

cato

r, ba

tter

y

20G

atew

ay s

elec

tion

algo

rithm

[44]

To a

dapt

ivel

y se

lect

the

gate

way

nod

e fo

r bal

anc-

ing

the

load

am

ong

the

node

sN

etw

ork

lifet

ime

No

ener

gy a

nd in

depe

nden

t en

ergy

har

vest

ing

devi

ce

21En

ergy

-aw

are

peer

ing

rout

ing

prot

ocol

(EPR

) [45

]To

enh

ance

BA

N re

liabi

lity

and

to re

duce

net

wor

k tr

affic

and

pow

er c

onsu

mpt

ion

Traffi

c lo

ad, e

nerg

y co

nsum

ed a

nd s

aved

, buff

er

over

flow

, pac

kets

forw

arde

d an

d re

ceiv

edD

MQ

oS

22En

ergy

-aw

are

topo

logy

des

ign

(EAW

D) [

46]

To re

duce

the

tota

l ene

rgy

cons

umpt

ion

and

inst

alla

tion

cost

by

wire

less

sen

sors

and

rela

ysTo

tal e

nerg

y co

nsum

ed, i

nsta

llatio

n co

st–

23En

ergy

-bal

ance

d ra

te a

ssig

nmen

t and

ro

utin

g pr

otoc

ol (E

BRA

R) [4

7]To

less

en th

e to

tal e

nerg

y co

nsum

ed in

the

netw

ork

at th

e ex

pens

e of

hig

h ne

twor

k ut

ility

, ad

aptiv

e re

sour

ce a

lloca

tion

Nor

mal

ized

resi

dual

ene

rgy,

rout

ing

tree

siz

eEB

RAR-

SP, E

BRA

R-PD

, EBR

AR-

PE

24En

ergy

-effi

cien

t rou

ting

sche

me

(EER

S) [4

8]To

pro

vide

ada

ptiv

e tr

ansm

issi

on p

ower

for s

enso

r no

des,

esta

blis

h an

ene

rgy-

effici

ent p

ath

Pack

et re

cept

ion

ratio

, ave

rage

hop

cou

nt, c

ol-

lect

ion

dela

y, a

vera

ge n

umbe

r of t

rans

mis

sion

s pe

r pac

ket,

ener

gy c

onsu

mpt

ion

per p

acke

t, pe

r ho

p, o

verh

ead

Colle

ctio

n tr

ee p

roto

col (

CTP

)

25M

odifi

ed D

ijkst

ra’s

glob

al ro

utin

g al

gorit

hm [4

9]To

yie

ld b

ette

r net

wor

k lif

etim

e in

WBA

NN

etw

ork

lifet

ime

ratio

, ene

rgy

per b

it ra

tioO

ppor

tuni

stic

rout

ing,

tran

smit

pow

er a

dapt

atio

n, m

in.

ener

gy p

acke

t for

war

ding

, use

of

ded

icat

ed re

lays

Page 9 of 19Bhanumathi and Sangeetha Hum. Cent. Comput. Inf. Sci. (2017) 7:24

Tabl

e 4

cont

inue

d

Sl. n

o.Pr

otoc

ol [r

ef. n

o.]

Goa

lPe

rfor

man

ce m

etri

csCo

mpa

red

with

26D

ata-

cent

ric m

ulti

obje

ctiv

e Q

oS-a

war

e

rout

ing

prot

ocol

(DM

QoS

) [50

]To

ach

ieve

bes

t QoS

ser

vice

s fo

r diff

eren

t dat

a ty

pes

Ave

rage

end

-to-

end

dela

y, o

n-PD

R, a

vera

ge

ener

gy c

onsu

mpt

ion

per p

acke

t, op

erat

ion

ener

gy o

verh

ead

MM

SPEE

DLO

CA

LMO

RD

ARA

27Ra

ndom

con

tent

ion-

base

d re

sour

ce

allo

catio

n pr

otoc

ol (R

ACO

ON

) [51

]To

pro

vide

bet

ter t

he q

ualit

y of

ser

vice

for m

ulti-

user

mob

ile w

irele

ss b

ody

area

net

wor

ksPa

cket

late

ncy,

pow

er c

onsu

mpt

ion,

pa

cket

col

lisio

n, u

ser c

apac

ityBo

dyQ

oS

28H

euris

tic a

dapt

ive

rout

ing

algo

rithm

[52]

To m

ake

mul

ti-ho

p W

BAN

ene

rgy

effici

ent

Life

time,

sta

ndar

d de

viat

ion

of re

mai

ning

pow

er,

aver

age

end

to e

nd d

elay

, pac

ket l

oss

Opt

imal

sch

eme

29En

viro

nmen

t-ad

aptiv

e ro

utin

g al

gorit

hm (E

AR)

[5

3]To

ach

ieve

bet

ter n

etw

ork

lifet

ime

and

relia

ble

com

mun

icat

ion

for h

eter

ogen

eous

net

wor

ksN

umbe

r of a

live

node

s, am

ount

of c

olle

cted

dat

a in

the

coor

dina

tor

Hop

-cou

nt b

ased

met

hod,

en

ergy

-bas

e m

etho

d

30Lo

caliz

ed m

ulti-

obje

ctiv

e ro

utin

g pr

otoc

ol

(LO

CA

LMO

R) [5

4]To

con

side

r the

traffi

c di

vers

ity ty

pica

l for

bio

med

i-ca

l app

licat

ions

and

to p

rovi

de a

diff

eren

tiatio

n ro

utin

g fo

r diff

eren

t qua

lity

of s

ervi

ce (Q

oS)

met

rics

Pack

et re

cept

ion

ratio

, end

to e

nd d

elay

, pac

kets

re

ceiv

ing

with

in d

eadl

ine

SPEE

D, M

MSP

EED

, GFW

, EA

GFS

31Re

info

rcem

ent l

earn

ing

base

d ro

utin

g w

ith Q

oS

supp

ort (

RL-Q

RP) p

roto

col [

55]

To a

ttai

n de

sira

ble

QoS

in re

spec

t of t

hrou

ghpu

t an

d en

d to

end

del

ayA

vera

ge e

nd to

end

del

ay, a

vera

ge P

DR,

nod

e m

obili

ty, n

etw

ork

traffi

c lo

adQ

oS-A

OD

V

32Q

oS a

war

e ro

utin

g se

rvic

eTo

pro

vide

ser

vice

with

prio

ritiz

ed ro

utin

g, u

ser

spec

ific

QoS

End

to e

nd d

elay

, pac

ket d

eliv

ery

ratio

–

Page 10 of 19Bhanumathi and Sangeetha Hum. Cent. Comput. Inf. Sci. (2017) 7:24

Tabl

e 5

Tem

pera

ture

aw

are

rout

ing

prot

ocol

s in

 bod

y ar

ea n

etw

orks

Sl. n

o.Pr

otoc

ol [r

ef. n

o.]

Goa

lPe

rfor

man

ce m

etri

csCo

mpa

red

with

1M

2 E2 pro

toco

l [61

]To

redu

ce e

nerg

y co

nsum

ptio

n an

d in

crea

se li

fe ti

me,

to

redu

ce li

nk h

otsp

ot n

etw

ork

in h

eter

ogen

eous

W

BSN

s

Pack

ets

sent

to B

S, n

umbe

r of d

ead

node

s, to

tal e

nerg

y of

net

wor

k, n

umbe

r of c

lust

er h

ead

M-A

TTEM

PT

2Re

liabi

lity

enha

nced

-ada

ptiv

e th

resh

old

base

d th

erm

al

unaw

are

ener

gy-e

ffici

ent m

ulti-

hop

prot

ocol

(RE-

ATTE

MPT

) [62

]

To m

axim

ize

the

netw

ork

lifet

ime

and

to re

mov

e th

e de

ficie

ncie

s of

ATT

EMPT

pro

toco

lA

vera

ge ra

te o

f dea

d no

des,

num

ber o

f pac

kets

sen

t to

sink

, pac

kets

dro

pped

and

thro

ughp

utAT

TEM

PT

3Th

erm

al-a

war

e m

ulti

cons

trai

ned

intr

a bo

dy Q

oS ro

ut-

ing

prot

ocol

(TM

QoS

) [63

]To

ens

ure

the

requ

ired

QoS

dem

ands

alo

ng w

ith

mai

ntai

ning

the

tem

pera

ture

of e

ach

node

to a

des

ir-ab

le le

vel

Ener

gy e

ffici

ency

, ave

rage

tem

pera

ture

rise

, del

ay re

li-ab

ility

, max

imum

tem

pera

ture

rise

, pac

kets

mee

ting

dead

line

LTRT

, TA

RA

4M

obili

ty-s

uppo

rtin

g ad

aptiv

e th

resh

old-

base

d th

erm

al-a

war

e en

ergy

-effi

cien

t mul

ti-ho

p pr

otoc

ol

(M-A

TTEM

PT),

ATTE

MPT

[64]

To s

ense

the

link

hot-

spot

, to

forw

ard

the

data

aw

ay

from

suc

h lin

ksN

umbe

r of d

ead

node

s, th

roug

hput

, num

ber o

f clu

ster

he

ads

per r

ound

, tot

al e

nerg

y of

net

wor

kM

ulti-

hop

5Th

erm

al-a

war

e sh

orte

st h

op ro

utin

g al

gorit

hm (T

HSR

) [6

5]To

redu

ce th

e no

de’s

tem

pera

ture

and

to p

reve

nt th

e fo

rmat

ion

of h

otsp

otM

axim

um te

mpe

ratu

re ri

se, a

vera

ge d

elay

, pac

kets

dr

oppe

dLT

R, S

HR,

HPR

, TA

RA

6H

otsp

ot p

reve

ntin

g ro

utin

g (H

PR) a

lgor

ithm

[60]

To p

reve

nt th

e fo

rmat

ion

of h

otsp

ots

and

to re

duce

th

e av

erag

e pa

cket

del

iver

y de

lay

Max

imum

tem

pera

ture

rise

of a

ny n

ode,

ave

rage

pa

cket

del

iver

y de

lay,

tota

l num

ber o

f pac

kets

dr

oppe

d

TARA

, SH

R

7Ro

utin

g al

gorit

hm fo

r net

wor

k of

hom

ogen

eous

and

Id

-less

bio

med

ical

sen

sor n

odes

(RA

IN) [

66]

To b

e us

ed in

an

in v

ivo

netw

ork

of h

omog

eneo

us a

nd

id-le

ss b

iom

edic

al s

enso

r nod

esM

axim

um te

mpe

ratu

re ri

se o

f nod

es, a

vera

ge e

nerg

y co

nsum

ptio

n pe

r nod

e, p

erce

ntag

e pa

cket

del

iver

y,

aver

age

pack

et d

eliv

ery

dela

y

Cont

rolle

d-FL

OO

D

8Le

ast t

otal

-rou

te te

mpe

ratu

re ro

utin

g pr

otoc

ol (L

TRT)

[5

8]To

redu

ce te

mpe

ratu

re c

ause

d by

bio

med

ical

sen

sors

im

plan

ted

in h

uman

bod

ies

Ave

rage

tem

pera

ture

rise

and

hop

cou

nt p

er a

rriv

al

pack

etLT

R, A

LTR

9Le

ast t

empe

ratu

re ro

utin

g pr

otoc

ol (L

TR),

adap

tive

leas

t tem

pera

ture

rout

ing

prot

ocol

(ALT

R) [6

7]To

redu

ce th

e am

ount

of h

eat p

rodu

ced

in th

e ne

twor

kA

vera

ge te

mpe

ratu

re ri

se, d

elay

, pow

er c

onsu

mpt

ion,

pa

cket

s dr

oppe

d, li

fetim

e of

net

wor

ksTA

RA, S

HR

10Th

erm

al-a

war

e ro

utin

g al

gorit

hm (T

ARA

) [59

]To

est

imat

e th

e te

mpe

ratu

re v

aria

tion

of n

eigh

bor

node

s an

d di

rect

pac

kets

nea

rby

the

hots

pot r

egio

nM

axim

um te

mpe

ratu

re ri

se, a

vera

ge te

mpe

ratu

re ri

se,

dela

y pe

rfor

man

ceSh

orte

st h

op

Page 11 of 19Bhanumathi and Sangeetha Hum. Cent. Comput. Inf. Sci. (2017) 7:24

When IEEE 802.15.4 standard networks are used, it will be good if the TICOSS [15] pro-tocol is redesigned for reducing the average delay which is not considered in the existing one. If the entire network performance is to be optimized, the choice will be the Bio-comm protocols along with new techniques to reduce the node temperature. Hence, the scope for research in this area is very much wide enough to work with. The comparative analysis of postural movement protocols has shown that, none of them considered the thermal effects of nodes and QoS issues together. Therefore, the future protocols could be proposed in such a way that, it could achieve better QoS parameters along with tech-niques to reduce the node temperature rise and methods to counter security attacks. The survey on QoS aware protocols unveils various research areas for future work because of its importance. Every new protocol, which has been designed, is meant for addressing the limitation of the previous one. For example, in routing service framework [56] and reinforcement learning based routing with QoS support [55] the energy consumption is not considered, but it is taken into account in the remaining protocols.

In almost, all the existing QoS aware protocols, only the QoS metrics are exam-ined, without concentrating on the human body movements and temperature rise of implanted devices. The proposed temperature aware protocols perform better by reduc-ing the temperature rise due to radiation from antenna and other node circuitry. Along with the thermal issue and power consumption, it will be better if these protocols can also address the routing issues like shortest path as in QoS aware.

Table 6 summarizes the comparison between some of the routing protocols used in WBAN. From the analysis, it is seen that almost all the protocols have considered dif-ferent QoS metrics for their performance analysis. Hence, choosing the protocol for a WBAN system depends on the particular application of the system; whether it should be energy efficient, good reliable one or it should reduce the temperature of the node cir-cuitry. Table 7 lists the pros and cons and the application domain of each protocols used in body area networks. This table helps to choose a particular protocol based on the QoS requirements. For example, if the application of the proposed system is patient moni-toring in hospitals, then the protocols like WASP [16] or TICOSS [15] can be selected due to its high packet delivery ratio and low average delay. If the sensors are implanted within the body, then the protocols like Co-LEEBA [33], TARA [59], or routing algo-rithm for network of homogeneous and Id-less biomedical sensor nodes (RAIN) [66] can be chosen. If the network is heterogeneous one, then M-ATTEMPT or M2E2 can be used.

ConclusionsWireless body area network is a part of wireless sensor network, with a number of nodes deployed within and on the surface of human body to measure different bio-logical parameters for a particular application. In this survey article, various existing routing protocols that are used in WBANs are categorized and briefly analyzed from the available articles between the years 2002–2016. It is seen that the routing proto-col plays a vital role in the design process of every efficient, reliable, low cost wireless

Page 12 of 19Bhanumathi and Sangeetha Hum. Cent. Comput. Inf. Sci. (2017) 7:24

body sensor networks. Based on the structure and nature of networks, the routing protocols for WBANs are categorized as cluster-based, cross-layered, postural move-ment based QoS aware and temperature-aware protocols. It is observed that there is no strict classification of protocols is possible since most of them aims or results in achieving the challenges of sensor networks. It is also concluded that each protocol is application dependent, i.e., the protocols used for daily monitoring and the criti-cal medical cases are different. The future directions for each group of protocols are also presented which helps the researchers to focus on their interested area. Also, a comparative study of different protocols has been examined so that an appropriate protocol can be selected according to the targeted application. This survey will ben-efit the researchers to study the existing routing protocols for WBANs in the field of healthcare systems.

The Future work includes the design and implementation of a body sensor prototype with a newly designed routing protocol, which will be highly energy efficient and reliable one for rehabilitation of old age people using a microcontroller based system with suit-able sensors.

Table 6 Comparative analysis of routing protocols

* Not applicable

Sl. no. Routing protocol

Type of  protocol

Average delay

Energy consumption

Packet delivery ratio

Average temperature rise

1 HIT [8] Clustered Very Low Low * *

2 AnyBody [11] Clustered * * Very high *

3 WASP [16] Cross-layered Low Low Very high *

4 CICADA [14] Cross-layered Low Low * *

5 TICOSS [15] Cross-layered * Low High *

6 Routing service framework [56]

QoS-aware * * Moderate *

7 RL-QRP [55] QoS-aware High * High *

8 ZEQoS [37] QoS-aware * High High *

9 RL-QRP [55] QoS-aware Low Low High *

10 ENSA-BAN [25] QoS-aware Very low Low Very high *

11 Co-LEEBA [33] QoS-aware * Low High *

12 DMQoS [50] QoS-aware Low Moderate High *

13 LOCALMOR [54] QoS-aware Low Low High *

14 TARA [59] Temperature-aware Very High High Low Low

15 LTRT [58] Temperature-aware * * Very high Low

16 RAIN [66] Temperature-aware Moderate Low High Low

17 M-ATTEMPT [64] Temperature-aware Low Low High Low

18 M2E2 [61] Temperature-aware Low Very low Very high Low

19 TMQoS [63] Temperature-aware Very low Very low High Moderate

20 ETPA [19] Postural High Low High Low

21 PSR [20] Postural Low High Moderate *

Page 13 of 19Bhanumathi and Sangeetha Hum. Cent. Comput. Inf. Sci. (2017) 7:24

Tabl

e 7

Pros

and

 con

s an

d th

e ap

plic

atio

n do

mai

n of

 rout

ing

prot

ocol

s

Sl. n

o.Ro

utin

g pr

otoc

olPr

osCo

nsA

pplic

atio

n do

mai

n

1H

IT [8

]Re

quire

s on

ly 2

5% o

f the

tim

e re

quire

d by

PE

GA

SIS

and

LEA

CH

for d

ata

colle

ctio

n, n

etw

ork

long

evity

is 1

.05

and

1.44

tim

es th

at o

f PEG

ASI

S an

d LE

AC

H re

spec

tivel

y

Not

men

tione

d fo

r a s

peci

fic m

edic

al a

pplic

atio

n,

the

term

s se

curit

y, fa

ult-

tole

ranc

e an

d re

liabi

lity

of th

e ne

twor

k ne

ed to

be

addr

esse

d

Mic

ro s

enso

r net

wor

ks, b

io m

edic

al s

ensi

ng li

ke

EEG

and

EM

G s

igna

ls, b

io e

lect

ric c

ompu

ter

inte

rfac

es

2A

nyBo

dy [1

1]A

sel

f-or

gani

zing

pro

toco

l, m

aint

ains

con

stan

t nu

mbe

r of c

lust

ers

with

incr

easi

ng n

umbe

r of

node

s. PD

R is

app

roxi

mat

ely

100%

The

met

rics

like

netw

ork

dela

y an

d en

ergy

co

nsum

ptio

n ar

e no

t ana

lyze

d. H

ence

can

not

cons

ider

ed fo

r crit

ical

med

ical

app

licat

ions

Perio

dic

patie

nt m

onito

ring

in h

ospi

tals

3W

ASP

[16]

Min

imiz

es th

e co

ordi

natio

n ov

erhe

ad, t

hrou

gh-

put o

btai

ned

is 9

4%. I

t can

min

imiz

e th

e de

lay

by re

duci

ng th

e nu

mbe

r of l

evel

s in

the

span

-ni

ng tr

ee a

nd a

lso

the

ener

gy c

onsu

mpt

ion

Mob

ility

is n

ot s

uppo

rted

, hen

ce c

anno

t be

used

fo

r dyn

amic

sen

sor n

etw

ork

appl

icat

ions

For i

ndoo

r hos

pita

l pat

ient

mon

itorin

g

4C

ICA

DA

[14]

Enha

nced

mob

ility

is s

uppo

rted

, gen

erat

ion

of

the

sche

me

is e

asie

r, en

d to

end

del

ay is

abo

ut

110

ms,

node

s w

ake

up o

nly

to tr

ansm

it an

d re

ceiv

e da

ta, h

ence

dis

sipa

tion

of e

nerg

y is

m

inim

ized

It do

es n

ot s

uppo

rt tr

affic

from

the

sink

to

the

node

sFo

r sen

sors

whe

re c

ompu

tatio

nal r

esou

rces

are

sc

arce

5TI

COSS

[15]

Dou

bles

the

netw

ork

lifet

ime

for h

igh

traffi

c sc

e-na

rios,

PDR

is h

ighe

r tha

n 92

%. L

ifetim

e of

4 m

in

per J

oule

for T

ICO

SS w

ith 8

02.1

5.4

and

2 m

in

per J

oule

with

802

.15.

4 al

one,

sav

es e

nerg

y du

e to

tim

ezon

e co

ordi

nate

d sl

eepi

ng m

echa

nism

Not

sui

tabl

e fo

r del

ay to

lera

nt n

etw

orks

and

als

o it

is n

ot a

n ap

plic

atio

n sp

ecifi

c pr

otoc

olCo

ntin

uous

vita

l sig

n m

onito

ring,

for a

mbi

ent

sens

or n

odes

pla

ced

thro

ugho

ut a

site

6Ro

utin

g se

rvic

e FR

AM

EWO

RK

[56]

Prov

ides

prio

ritiz

ed ro

utin

g se

rvic

e, u

ser s

peci

fic

QoS

sup

port

for s

mal

l sca

le n

etw

orks

Not

con

side

red

ener

gy c

onsu

mpt

ion,

whi

ch is

on

e of

the

maj

or c

onst

rain

ts o

f sen

sor n

etw

orks

Dyn

amic

, sm

all s

cale

wire

less

bod

y ar

ea n

etw

orks

7RL

-QRP

[55]

Use

s in

depe

nden

t dis

trib

uted

rein

forc

emen

t le

arni

ng a

ppro

ach

for Q

oS ro

ute

calc

ulat

ion,

PD

R ab

ove

90%

Ave

rage

del

ay is

hig

her (

abov

e 20

0 m

s), e

nerg

y co

nsum

ptio

n is

not

con

side

red,

not

suffi

cien

t fo

r glo

bal o

ptim

izat

ion

in la

rge

scal

e ne

twor

ks

Dyn

amic

, sm

all s

cale

wire

less

bod

y ar

ea n

etw

orks

8ZE

QoS

[37]

Suita

ble

and

effec

tive

for a

ll da

ta ty

pes

like

ordi

-na

ry, d

elay

and

relia

bilit

y se

nsiti

ve p

acke

ts, 8

4%

cons

iste

nt th

roug

hput

No

cons

ider

able

impr

ovem

ent i

n te

rms

of e

nerg

y co

nsum

ptio

nH

ospi

tal B

AN

com

mun

icat

ion

9RL

-QRP

[55]

Fits

wel

l in

dyna

mic

env

ironm

ents

usi

ng o

ptim

al

rout

ing

polic

y. G

ood

perf

orm

ance

dur

ing

heav

y tr

affic

cond

ition

s, av

erag

e de

lay

is le

ss th

an

200

ms

Not

sui

tabl

e fo

r lar

ge s

cale

net

wor

ks li

ke m

ulti

agen

t sys

tem

sD

ynam

ic b

io-m

edic

al s

enso

r net

wor

ks

Page 14 of 19Bhanumathi and Sangeetha Hum. Cent. Comput. Inf. Sci. (2017) 7:24

Tabl

e 7

cont

inue

d

Sl. n

o.Ro

utin

g pr

otoc

olPr

osCo

nsA

pplic

atio

n do

mai

n

10EN

SA-B

AN

[25]

Alo

ng w

ith a

ll Q

oS re

quire

men

ts, i

t con

side

rs

the

ener

gy c

onsu

mpt

ion

of n

odes

to im

prov

e th

e ne

twor

k pe

rfor

man

ce. A

ppro

x. 9

6% P

DR

com

pare

d to

DM

QoS

can

be

achi

eved

, ave

rage

de

lay

is le

ss th

an 1

6 m

s

Alth

ough

it is

a Q

oS a

war

e ro

utin

g pr

otoc

ol, t

he

body

mov

emen

t is

not c

onsi

dere

dCo

ntin

uous

pat

ient

mon

itorin

g se

nsor

net

wor

ks

11Co

-LEE

BA [3

3]It

is a

link

aw

are

rout

ing

prot

ocol

. Pat

h lo

ss is

re

duce

d du

e to

the

use

of d

iffer

ent p

ath

loss

m

odel

s. W

ith th

e di

scon

tinuo

us d

ata

tran

smis

-si

on, i

t pro

vide

s be

tter

life

tim

e. It

max

imiz

es

the

thro

ughp

ut to

36

Mbp

s co

mpa

red

to o

ther

pr

otoc

ols

with

a th

roug

hput

of a

vera

ge 2

Mbp

s

Max

imiz

es th

e th

roug

hput

at t

he c

ost o

f in

crea

sed

dela

yIm

plan

ted

sens

ors,

mon

itorin

g of

age

d pe

ople

12D

MQ

oS [5

0]U

ses

mod

ular

arc

hite

ctur

e fo

r del

ay c

ritic

al a

nd

relia

bilit

y cr

itica

l pac

kets

, end

to e

nd d

elay

is

less

than

120

ms

whe

n co

mpa

red

to o

ther

QoS

aw

are

prot

ocol

s of

260

ms.

PDR

is a

bove

92%

fo

r var

ying

traffi

c flo

ws

The

estim

atio

n of

sev

eral

tuni

ng p

aram

eter

s is

no

t ana

lytic

al. T

hey

are

fixed

thro

ugh

diffe

rent

si

mul

atio

n ex

perim

ents

Reso

urce

-con

stra

ined

bod

y ar

ea n

etw

orks

13LO

CA

LMO

R [5

4]Th

is ro

utin

g al

gorit

hm c

an b

e us

ed a

long

with

an

y M

AC

pro

toco

l with

AC

K m

echa

nism

, con

-si

dere

d th

e di

vers

ity o

f dat

a tr

affic

like

regu

lar,

dela

y- s

ensi

tive,

relia

bilit

y-se

nsiti

ve a

nd c

ritic

al

traffi

c, e

nd to

end

del

ay is

less

than

200

ms,

Pack

et re

cept

ion

ratio

n is

abo

ve 8

5%

Scal

abili

ty o

f the

pro

toco

l with

hig

her n

umbe

r of

sens

or n

odes

sho

uld

be in

vest

igat

edD

iver

se tr

affic

biom

edic

al a

pplic

atio

ns

14TA

RA [5

9]H

andl

es d

ata

tran

smis

sion

in th

e pr

esen

ce o

f te

mpe

ratu

re h

ot s

pots

, rou

tes

pack

ets

thro

ugh

low

tem

pera

ture

are

a, h

as lo

ad b

alan

cing

cap

a-bi

lity,

sm

alle

r ave

rage

tem

pera

ture

rise

Hig

her p

acke

t los

s du

e to

larg

er d

elay

(gre

ater

th

an 4

00 m

s), u

niqu

e ha

rdw

are

ids

for n

odes

he

nce

this

alg

orith

m fa

ils to

ope

rate

in id

-less

se

nsor

nod

es, h

omog

eneo

us a

nd n

ot e

mer

-ge

ncy

supp

orte

d

Impl

ante

d se

nsor

net

wor

ks a

nd a

pplic

atio

ns li

ke

retin

al p

rost

hesi

s an

d ca

ncer

det

ectio

n

15LT

RT [5

8]O

ptim

izat

ion

of ro

utin

g is

acc

ompl

ishe

d, v

ery

high

pac

ket d

eliv

ery

ratio

, whi

ch is

clo

se to

10

0%, S

mal

ler a

vera

ge te

mpe

ratu

re ri

se

The

anal

ysis

is d

one

only

on

the

aver

age

tem

-pe

ratu

re ri

se a

nd p

acke

t los

s ra

teIm

plan

ted

bio

-med

ical

net

wor

ks, c

ardi

ac p

atie

nt

mon

itorin

g ap

plic

atio

ns

Page 15 of 19Bhanumathi and Sangeetha Hum. Cent. Comput. Inf. Sci. (2017) 7:24

Tabl

e 7

cont

inue

d

Sl. n

o.Ro

utin

g pr

otoc

olPr

osCo

nsA

pplic

atio

n do

mai

n

16RA

IN [6

6]Ro

utes

the

data

effi

cien

tly to

war

ds th

e si

nk in

an

id-le

ss b

iom

edic

al s

enso

r net

wor

ks, p

reve

nts

the

form

atio

n of

hig

h te

mpe

ratu

re z

ones

in th

e ne

twor

k, m

axim

um te

mpe

ratu

re ri

se in

crea

ses

slow

ly th

an C

FLO

OD

pro

toco

l, PD

R is

gre

ater

th

an 9

0%, t

he a

vera

ge e

nerg

y co

nsum

ptio

n is

le

ss th

an 1

000

ener

gy u

nits

com

pare

d to

300

0 un

its o

f CFL

OO

D

Ave

rage

pac

ket d

eliv

ery

dela

y is

slig

htly

hig

her

than

CFL

OO

D p

roto

col,

PDR

is s

light

ly lo

wer

th

an C

FLO

OD

pro

toco

l

In-v

ivo

netw

ork

of h

omog

eneo

us a

nd id

-less

bi

omed

ical

sen

sor n

odes

17M

-ATT

EMPT

[64]

Mob

ility

sup

port

ed, g

reat

er n

etw

ork

lifet

ime

(29.

5%),

bett

er s

tabi

lity

perio

d (g

reat

er th

an

20%

) and

29%

bet

ter r

esul

ts fo

r suc

cess

fully

re

ceiv

ed p

acke

ts w

hen

com

pare

d to

mul

tihop

co

mm

unic

atio

n, e

nerg

y effi

cien

t and

em

er-

genc

y su

ppor

ted

A m

ovin

g no

de n

eeds

a n

ew p

aren

t and

the

new

pa

rent

may

refu

se th

is re

ques

t, an

alys

is o

f ave

r-ag

e/m

axim

um te

mpe

ratu

re ri

se is

not

incl

uded

Het

erog

eneo

us a

nd h

omog

eneo

us w

irele

ss b

ody

area

net

wor

ks

18M

2 E2 [61]

Mob

ility

and

mul

ti-m

ode

supp

orte

d, e

nerg

y effi

-ci

ent a

nd e

mer

genc

y su

ppor

ted,

thro

ughp

ut is

ab

ove

100M

bps

whe

n co

mpa

red

to 5

0 M

bps

of

M-A

TTEM

PT

Requ

ires

mor

e ha

rdw

are

than

the

othe

r pro

toco

lsH

eter

ogen

eous

wire

less

bod

y se

nsor

net

wor

ks

19TM

QoS

[63]

Tabl

e-dr

iven

pro

toco

l with

hig

h ne

twor

k lif

etim

e,

low

end

to e

nd d

elay

whi

ch is

less

than

130

ms,

abov

e 85

% re

liabi

lity,

can

mee

t the

QoS

de

man

ds a

long

with

mai

ntai

ning

the

tem

pera

-tu

re o

f the

nod

es to

an

acce

ptab

le le

vel,

uses

a

hots

pot a

void

ance

mec

hani

sm

Ave

rage

tem

pera

ture

rise

is h

ighe

r in

orde

r to

mee

t the

des

ired

QoS

dem

ands

In-v

ivo

wire

less

bod

y ar

ea n

etw

orks

20ET

PA [1

9]M

obili

ty s

uppo

rted

, It s

olve

s th

e lin

k di

scon

nec-

tion

prob

lem

due

to b

ody

mov

emen

ts a

long

w

ith a

redu

ctio

n in

tem

pera

ture

rise

, PD

R is

up

to 9

5%

The

aver

age

dela

y is

slig

htly

hig

her t

han

PRPL

C

in o

rder

to b

alan

ce th

e te

mpe

ratu

re ri

se in

the

netw

ork

Wire

less

bod

y ar

ea n

etw

ork

with

long

last

ing

com

-m

unic

atio

n an

d sc

arce

reso

urce

s

21PS

R [2

0]It

prov

ides

relia

ble

and

secu

re c

omm

unic

atio

n ag

ains

t dat

a in

ject

ion

atta

cks,

PDR

up to

80%

, sh

orte

r rou

ting

dela

y

Use

s A

CK

tech

niqu

es fo

r mea

surin

g lin

k qu

ality

an

d if

the

num

ber o

f AC

Ks is

larg

e, it

may

co

nsum

e a

lot o

f net

wor

k re

sour

ces,

as a

who

le,

netw

ork

lifet

ime

is le

ss

Relia

ble

and

secu

re w

irele

ss b

ody

area

net

wor

ks

Page 16 of 19Bhanumathi and Sangeetha Hum. Cent. Comput. Inf. Sci. (2017) 7:24

AbbreviationsWBAN: wireless body area network; QoS: quality of services; RL-QRP: reinforcement learning based routing with Qos support; WASP: wireless autonomous spanning tree protocol; RAIN: routing algorithm for network of homogeneous and Id-less biomedical sensor nodes; M-ATTEMPT: mobility-supporting adaptive threshold-based thermal-aware energy-effi-cient multi-hop protocols; CDR: critical data routing; RAR: reliability aware routing; DMQoS: data-centric multi objective QoS-aware routing protocol; LEACH: low-energy adaptive clustering hierarchy; CBBAP: cluster based body area protocol; HIT: hybrid indirect transmission; PEGASIS: power-efficient gathering in sensor information systems; MAC: medium access control; CICADA: cascading information retrieval by controlling access with distributed slot assignment; TICOSS: time zone coordinated sleep scheduling; OBSFR: on-body store and flood routing; ETPA: energy efficient thermal and power aware routing; PSR: prediction based secure and reliable routing framework; DVRPLC: distance vector routing with postural link costs; PRPLC: probabilistic routing with postural link costs; ENSA-BAN: efficient next hop selection algorithm; TEEN: threshold sensitive energy efficient sensor network protocol; ARBA: adaptive routing and bandwidth allocation protocol; LAEEBA: link-aware and energy efficient scheme for body area networks; Co-LAEEBA: cooperative link-aware and energy efficient protocol for WBAN; MLEEBA: modified LAEEBA: link aware and energy efficient scheme for BAN; ZEQoS: Zahoor energy and QoS-aware routing protocol; QPRR: QoS aware peering routing protocol for reliability sensi-tive data; DARE: distance aware relaying energy efficient protocol; SIMPLE: stable increased-throughput multi-hop proto-col for link efficiency; QPRD: QoS-aware peering routing protocol for delay sensitive data; QRP: Q-learning based routing protocol; AMR: adaptive multihop tree-based routing; EPR: energy-aware peering routing protocol; EAWD: energy-aware topology design; EBRAR: energy-balanced rate assignment and routing protocol; EERS: energy-efficient routing scheme; MDGRA: modified Dijkstra’s global routing algorithm [49]; RACOON: random contention-based resource allocation proto-col; EAR: environment-adaptive routing algorithm; LOCALMOR: localized multi-objective routing protocol; RE-ATTEMPT: reliability enhanced-adaptive threshold based thermal unaware energy-efficient multi-hop protocol; TMQoS: thermal-aware multi constrained intra body QoS routing protocol; M-ATTEMPT: mobility-supporting adaptive threshold-based thermal-aware energy-efficient multi-hop protocol; THSR: thermal-aware shortest hop routing algorithm; HPR: hotspot preventing routing; LTRT: least total-route temperature routing protocol; LTR: least temperature routing protocol; ALTR: adaptive least temperature routing protocol; TARA: thermal-aware routing algorithm.

Authors’ contributionsVB conducted the survey work, analyzed the schemes and drafted the manuscript. CPS participated in literature review and helped to draft the manuscript. Both authors read and approved the final manuscript.

Authors’ informationV. Bhanumathi received the Bachelor Degree in Electronics and Communication Engineering from Madras University, Master Degree in Communication Systems from Anna University, Chennai and Ph.D. in Information and Communica-tion Engineering from Anna University, Chennai. She is currently working as an Assistant Professor in the Department of Electronics and Communication Engineering, Anna University, Regional Campus, Coimbatore. She has published her works in various International Journals and conferences. Her areas of interest are Wireless Communication, VLSI Design, Network Security, and Digital Communication.

C. P. Sangeetha received her Bachelor Degree in Electronics and Communication and Master Degree from Cochin University of Science and Technology, Kerala. She is currently doing her Ph.D. in Information and Communication Engineering, Anna University, Chennai. She has worked as a Lecturer in Electronics and Communication Engineering, Toc H Institute of Science and Technology, Cochin for 8 years. She has published a number of papers in various International Journals and conferences. Her areas of interest include wireless sensor networks and mobile communications.

AcknowledgementsWe would like to thank the editors and the reviewers for their noble comments and constructive criticisms for improve-ment of the manuscript.

Competing interestsThe authors declare that they have no competing interests.

Publisher’s NoteSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Received: 24 December 2016 Accepted: 25 June 2017

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