Ad Hoc Networks - Indian Institute of Technology Delhiweb.iitd.ac.in/~swadesd/pubs/JNL/UWN-AdHoc2013.pdf · networks with imprecise propagation delay information Priyatosh Mandala,

Ad Hoc Networks 11 (2013) 1443–1455

Contents lists available at ScienceDirect

Ad Hoc Networks

journal homepage: www.elsevier .com/locate /adhoc

A receiver synchronized slotted Aloha for underwater wirelessnetworks with imprecise propagation delay information

Priyatosh Mandal a, Swades De b,⇑, Shyam S. Chakraborty c

a Centre for Development of Telematics, New Delhi, Indiab Electrical Engineering Department, Indian Institute of Technology Delhi, New Delhi, Indiac Technology and Education Consultant, Helsinki, Finland

a r t i c l e i n f o

Article history:Available online 23 February 2011

Keywords:Underwater random access protocolReceiver synchronized slotted AlohaPropagation delay uncertaintyMany-to-one access protocol

1570-8705/$ - see front matter � 2011 Elsevier B.Vdoi:10.1016/j.adhoc.2011.01.019

⇑ Corresponding author. Tel.: +91 11 2659 1042; faE-mail addresses: [email protected] (P

[email protected] (S. De), [email protected] (S.S

a b s t r a c t

In a wireless network, where propagation delay is high but known, slotted Aloha (S-Aloha)is synchronized with respect to the receiver’s time slots. Since the transmitter knows thepropagation delay to its receiver, after a frame is generated, the transmitter introduces asuitable delay before its transmission, such that the frame arrives exactly in a slot at thereceiver. However, in an underwater wireless network, due to significantly less signalpropagation speed, the channel dynamics has a significant effect on the time dispersionof propagation speed. Due to this uncertainty in propagation speed, even if the transmit-ter–receiver distance is exactly known, it is likely that a perfect synchronization at thereceiver is not possible.

In this paper, we first show that, even a little-less-than-perfect synchronization at thereceiver reduces the throughput of receiver synchronized S-Aloha (RSS-Aloha) to that ofpure Aloha. We modify the RSS-Aloha for underwater by accommodating the error in delayestimate while deciding the receiver-end slot size. Via probabilistic analysis, supported bysimulations, we show that our proposed modified protocol offers a gradual increase inthroughput as the propagation delay uncertainty decreases. We also show that thethroughput of our proposed modified protocol is consistently higher compared to thetransmitter synchronized S-Aloha when operating under the same propagation delayuncertainty. However, when the uncertainty is high, delay performance of the modifiedRSS-Aloha remains poorer than that of the transmitter synchronized S-Aloha in a systemwith smaller nodal communication range.

� 2011 Elsevier B.V. All rights reserved.

1. Introduction

Short-range underwater wireless ad hoc networks(UWN) are aimed at remotely monitoring various aquaticactivities, such as marine biological and zoological lives,geological changes, and underwater human activities.Despite some similarities in UWN and terrestrial radio fre-quency (RF) wireless sensor networks, such as, limitedchannel bandwidth, high bit error rate caused by the wire-less channel, and limited battery power of sensor nodes,

. All rights reserved.

x: +91 11 2658 1606.. Mandal), swades-. Chakraborty).

UWN performance is significantly different due to its sen-sitivity to propagation delay variations.

Underwater signal propagation speed v(z,n,h) (in m/s) ismodeled as [1]:

vðz; n; hÞ ¼ 1449:05þ 45:7h� 5:21h2 þ 0:23h3

þ ð1:333� 0:126hþ 0:009h2Þðn� 35Þþ 16:3zþ 0:18z2;

where h ¼ H10 ; H is the temperature in �C, n is the salinity in

ppt, and z is the depth in km. From this expression it can benoted that the signal propagation speed is a function of theoperating conditions. Besides, water current and turbu-lence may add to the variable signal propagation speed

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1444 P. Mandal et al. / Ad Hoc Networks 11 (2013) 1443–1455

between different transmitter–receiver pairs. Thus, even iftwo transmitters have the same spatial separation from acommon receiver in a possibly three-dimensional under-water environment, they are likely to encounter differentpropagation delays, however small it could be.

Generally, in centralized underwater wireless networks,the nodes deployed for sensing and communication pur-poses collect and send the field data to a gateway node,which further forwards them to the shore via wireless orwire-connected links. Communication from the fieldsensor nodes to the gateway is in the form of many-to-one access mechanism. This many-to-one connectivityand normally-sporadic sensed data from the field nodessuggest that some kind of random access protocol wouldbe suitable for the field nodes to gateway communication.However, pertaining to the distinctly different signal prop-agation characteristics, RF multi-access communicationprotocols are not directly applicable [2–6].

Noting that the inter-nodal propagation delay inunderwater communications is rather long, several vari-ants of underwater access protocols have been proposedand studied in recent literature [7–10,6]. In context of re-ceiver distance dependent propagation delay, pure Alohaand transmitter synchronized slotted Aloha (S-Aloha) per-formances have been studied, and different variants ofconventional transmitter synchronized S-Aloha (whichwe call mTSS-Aloha-uw) have also been proposed andstudied [11–13]. In [12] an optimum guard band fortransmitter synchronized S-Aloha was analyzed, where itwas called PDT-ALOHA. In [13], a different approach tofinding optimum slot size in transmitter synchronizedS-Aloha was analyzed, where the modified protocol wascalled mS-Aloha-uw. In this paper for consistency innomenclature, the mS-Aloha-uw is called mTSS-Aloha-uw. It was noted in [13] that the performance ofmTSS-Aloha-uw variants degrade as the propagation de-lay increases. Moreover, in all these studies the impactof propagation delay uncertainty on the protocolperformance has not been investigated.

Our current work is motivated by receiver-initiated/synchronized underwater wireless many-to-one multi-access communication protocol variants (e.g., [6,14]). Notethat, in practice Aloha protocol variants may not be usedfor actual data communication (because of its limitedthroughput), and some kind of (contention-free) reserva-tion protocols may be more suitable. Yet, as demonstratedin the prior underwater multi-access protocol studies[15,16,9,17,18,14], the initial communication phase forthe resource reservation purpose is expected to be ran-dom-access (Aloha or S-Aloha) based.

We observe that, satellite to earth stations many-to-onemulti-access communications also encounter a signifi-cantly large propagation delay, where, among severalvariants of random access protocols, receiver synchronizedS-Aloha (which we call RSS-Aloha) was proposed [19]. ThisRSS-Aloha protocol works best as long as the synchroniza-tion at the receiver is perfect. The error in receiver-endtime synchronization in RF based satellite communicationsmay be insignificantly small, where the propagation delayuncertainty can be disregarded because of relatively veryhigh electromagnetic signal communication speed. How-

ever, in underwater environment, perfect receiver-endsynchronization is more difficult, as the temporal and spa-tial variation of underwater signal propagation speed can-not be insignificant. In fact, a few recent underwatercommunication studies have accounted for a finite uncer-tainty in inter-nodal signal propagation delay [20–22]. Itmay be pointed here that, to the best of our knowledge,the effect imperfect receiver-end synchronization on S-Aloha performance in satellite communications as well asin underwater networks and its remedies have not beenstudied before.

In this paper we investigate modified S-Aloha protocolsfor many-to-one underwater wireless environment withlarge and variable propagation delay, and aim at maximiz-ing the system performance. Intuitively, to accommodatethe error in synchronization, the slot size can be increasedbeyond the frame transmission time. For a given frame gen-eration rate per unit time, this increase in slot size will re-duce the inter-slot frame collisions, however at the cost ofmore intra-slot frame collisions. It needs to be studiedhow the trade-off between inter-frame collision and in-tra-frame collision vulnerability would work in case of re-ceiver-end synchronized S-Aloha, and an optimum slotsize would be of interest to achieve a higher systemperformance.

Our specific contributions in this paper are as follows:

(a) We investigate the impact of propagation delay esti-mation error on the RSS-Aloha performance andshow that, a little error in delay estimate causessharp degradation of RSS-Aloha-uw (RSS-Aloha forUWN) throughput to that of pure Aloha.

(b) We propose to improve the RSS-Aloha-uw protocolperformance by optimally accommodating the prop-agation delay estimation error in deciding the recei-ver-side slot size. The proposed modified protocol iscalled modified RSS-Aloha-uw, or mRSS-Aloha-uw.

(c) With Gaussian approximation of propagationdelay variation, we analyze and compare the mRSS-Aloha-uw with a transmitter synchronized modifiedS-Aloha (which we call mTSS-Aloha-uw), anddemonstrate that mRSS-Aloha-uw performs betterwith respect to the mTSS-Aloha-uw in terms ofthroughput. Our results also show that, at a smallercommunication range, the mRSS-Aloha-uw delay per-formance can be poorer compared to the mTSS-Aloha-uw, when the propagation delay uncertaintyis high.

The remainder of the paper is organized as follows.Related works on propagation delay intensive many-to-one multi-access protocols and the synchronization relatedstudies are surveyed in Section 2. Performance analysis ofRSS-Aloha-uw is provided in Section 3. Our proposedmRSS-Aloha-uw is presented and its performance is ana-lyzed in Section 4. Section 5 contains the throughput per-formance study of the modified TSS-Aloha-uw underpropagation delay uncertainty. Delay performance of themodified S-Aloha protocols are formulated in Section 6.Numerical and simulation results are discussed in Section7. In Section 8 we conclude the paper.

P. Mandal et al. / Ad Hoc Networks 11 (2013) 1443–1455 1445

2. Related work

Several variants of underwater MAC protocols havebeen proposed in recent literature. In this section webriefly survey the protocols that explicitly address thecluster or gateway based communications, and also theones that address synchronization issues.

Different time synchronization protocols for underwa-ter sensor network were studied in [23–26]. In [23], syn-chronization was proposed using a two phase protocol. Inphase I, clock skew of the nodes are adjusted with respectto the clock of the beacon node. In phase II, a two wayhandshake between a synchronized node and the beaconnode is initiated. It was assumed that, during the shortmessage exchange in phase I, propagation delay is fixed.In [24], time synchronization is initiated by the clusterhead by broadcasting short packets to its local neighbors.These nodes reply to the reference packets with timestamps of receipt and their respective response instants.The cluster head then estimates the clock skew and clockoffset of a node using linear regression. The approach in[25] uses a global node to initiate synchronization bytransmitting multiple synchronization messages. Usingthe synchronization messages the local nodes estimatetheir clock skews using linear regression. The clock offsetsare adjusted afterward by a two way message exchange.This protocol also considers the propagation delay is fixedduring the short message exchange period. In [26], havinga reference node is not necessary. Any node synchronizesits clock with respect to its neighbor nodes by short mes-sage exchanges. The frequency of a node’s clock synchroni-zation is decided by a profile manager, which checks if thenumber of messages from all neighbors are received withcertain confidence limit.

The underwater multi-access protocol variants pro-posed in [15] use RTS/CTS (request to send/clear to send)handshake, where the initial phase is Aloha based. Severalother one-to-one underwater communication protocols in[16,9,17,18,14] also use some variants of handshaking thatare Aloha or S-Aloha based. The gateway based many-to-one communication in [6] uses RTS from non-gatewaynodes to gateway node through the control channel for re-source reservation, and data channel is used for CTS fromgateway to non-gateway nodes and for DATA from non-gateway nodes to gateway node.

The basic Aloha and S-Aloha protocol performanceswere studied and a guard time based variant of S-Alohawas proposed in [11]. Analytic performance evaluation ofthe Aloha protocols and different variants of transmittersynchronized S-Aloha protocol were independently stud-ied in [12,13]. In these studies, the error in propagation de-lay estimate was not accounted. In [22], a TDMA basedMAC protocol in single hop underwater sensor networkswas proposed considering variability of propagation delay,where the optimal guard time is computed after everynodes communication.

In addition to the time-synchronization MAC protocols,CDMA (code division multiple access) based protocols havealso been studied recently, some of which also have con-textual similarities with Aloha protocols. In [27], a CDMA

MAC protocol was proposed, which uses RTS-CTS for hand-shaking. In [28], transmitter controlled direct sequenceCDMA distributed MAC protocol was proposed that incor-porates closed loop distributed algorithm to set optimaltransmit power and code length to minimize near-fareffect.

In our present work, the proposed protocol is not a res-ervation based medium access scheme. Instead, we investi-gate the synchronization and optimal guard time allocationissues in the underwater S-Aloha protocols which can beused in the control (channel reservation) stage of the reser-vation based protocols. To this end, we take a re-look at thereceiver synchronized S-Aloha concept in satellite-to-earthstation communications [19]. Although the current studyapplies to gateway based many-to-one communicationscenarios with propagation delay uncertainty, the proposedconcept can be extended to one-to-one random accessprotocols as well.

3. Receiver synchronized S-Aloha

In this section, we study the performance of RSS-Alohawithout as well as with propagation delay uncertainty,where slot size is the same as a (fixed size) frame transmis-sion time. Before we proceed, the generic assumptions anddefinitions on the system performance, that are usedthroughout the paper, are briefly mentioned.

Assumption. The transmitters are uniformly randomdistributed around the receiver’s communication range R,and each node knows the distance to the receiver.Variability of underwater inter-nodal propagation delay,i.e., propagation delay uncertainty, is Gaussian distributed[20,21].

Definition 1. Access performance is measured in terms ofnormalized system throughput, defined as the average num-ber of successful frames in the network per frame trans-mission time.

Definition 2. Frame success rate is measured in terms ofdelay per successful frame, defined as the time taken to suc-cessfully deliver a frame.

3.1. Receiver synchronized S-Aloha without propagation delayuncertainty (RSS-Aloha)

In this case, perfectly synchronized reception is possibleif the transmitter knows its distance to the receiver andwaits appropriately before sending a frame. Thus, theframe will arrive exactly at a time slot, where the slot sizeis equal to the frame transmission time. The waiting timeduration at the transmitter Tw can be defined as:Tw = tr � (ta + Tp), where tr is the start time instant of thenearest next time slot after time (ta + Tp), ta is the frame ar-rival time instant at the transmitter, and Tp is the transmit-ter-to-receiver propagation delay which is known from thetransmitter–receiver distance and the average speed of the

Fig. 1. Frame transmission approach in RSS-Aloha.

Fig. 2. Collision vulnerability concept.


underwater acoustic signal. The case of time synchronizedreception depicted in Fig. 1, where tr = t2.

From the receiver’s perspective this concept is depictedin Fig. 2. Consider, the number of frames that arrive during[t2, t3] is m and the total number generated during [t1, t3] isn. Here the vulnerability duration is jt2 � t3j = T = Tt, frametransmission time. We have [29, Ch. 3]:

Pr m out of n frames arrive during ½t2; t3�½ �

¼n

m

� �pmð1� pÞn�m

;

where p ¼ jt2�t3 jjt1�t3 j

¼ Ttjt1�t3 j

. Frame arrival rate in the system isk ¼ n

jt1�t3 j. The window jt1 � t3j can be increased arbitrarily

so that n ?1 and p ? 0, keeping the product np = kTt aconstant. Thus, the above equation can be approximated as:

PnðmÞ � e�np ðnpÞm

m!¼ e�kTt

ðkTtÞm

m!:

So the frame success probability is Pnð0Þ ¼ e�kTt , and thenormalized system throughput is:

gRSS�Aloha ¼ kTte�kTt ; ð1Þ

which is the same as the conventional S-Aloha throughputof a system with negligible propagation delay.

3.2. Receiver synchronized S-Aloha with propagation delayuncertainty (RSS-Aloha-uw)

In underwater wireless environment, due to signifi-cantly less signal propagation speed, the channel dynamics(caused by water current, temperature variation, etc.) has asignificant effect on the time dispersion of propagation de-lay, and the dispersion could be on the order of the averagepropagation delay. Due to this uncertainty in propagationdelay, perfect synchronization at the receiver, i.e., receivinga frame exactly at a slot boundary, is not possible.

Looking from the receiver’s perspective, as long as itsframe reception duration does not overlap with any otherframe arrivals, the frame will be successful. Thus, a frameof size Tt, whose reception starts at time t + Tp, will be suc-cessful if no additional arrival at the receiver occurs during

the interval from t + Tp � Tt to t + Tp + Tt, i.e., for the dura-tion 2Tt. Referring to Fig. 2, the vulnerability duration inthis case is: jt2 � t3j = T = 2Tt.

Proceeding similarly as in Section 3.1, we have theframe success probability, Pnð0Þ ¼ e�2kTt . Hence, the nor-malized system throughput of RSS-Aloha-uw is:

gRSS-Aloha-uw ¼ kTte�2kTt ; ð2Þ

which is same as the throughput of Aloha-rf or Aloha-uw.Thus, even due to a little imperfection in receive side syn-chronization, the S-Aloha performance degrades to that ofpure Aloha.

4. A Modified Receiver Synchronized S-Aloha for UWN(mRSS-Aloha-uw)

In this section we propose to modify the slot size ofRSS-Aloha-uw protocol to achieve an improved systemperformance. Consider, a frame reaches at the receiver attime tr. The arrival instant is assumed Gaussian distributed[20,21] as: tr �Nðtg ;r2ðrÞÞ, where tg is the start time of atime slot at the receiver and r2(r) is the variance, which is afunction of transmitter–receiver distance r.

We propose to increase the slot size of mRSS-Aloha-uwprotocol as, Ts = Tt + 2kr(r), with k P 0 and rðrÞ 6 T ðmaxÞ

p . kis termed as slot size increment coefficient, and T ðmaxÞ

p ¼ Rv is

the maximum propagation delay to the receiver. rðrÞ 6TðmaxÞ

p is a practical assumption that the delay uncertaintyis upper bounded by the maximum possible inter-nodaldelay. The factor 2 on right-hand side of the modified slotdefinition is to accommodate worst case errors due tojointly overshooting and undershooting a slot boundary.

By Gaussian approximation of arrival time uncertaintydistribution, the success probability PðmRSÞ

s of a frame desig-nated for slot i is primarily determined by the frames thatare designated for slot i ± j, where 1 6 j 6 d3rðrÞTs

e. Clearly, fork P 1 and any value of T ðmaxÞ

p , PðmRSÞs in a slot will be gov-

erned by the designated frames that are its two-slot neigh-bors. If 0 6 k < 1, 3rðrÞ

Tscan be greater than 2, and hence PðmRSÞ

s

is affected by more than two-slot neighbors. In the follow-ing analysis of PðmRSÞ

s , we consider only two-slot neighborvulnerability, which is likely to introduce some error inanalysis for 0 6 k < 1. However, as we will see from thenumerical results in Section 7, the range 0 6 k < 1 is of lessimportance, as the optimum mRSS-Aloha-uw slot size isachieved only for k P 1. Considering vulnerability causedby up to two-slot neighbors, PðmRSÞ

s can be approximatelywritten as:

PðmRSÞs ¼

Z R

0

Z ðiþ2ÞTs

ði�2ÞTs

X1ni¼0

Pr ni arrival in slot ið Þ"

�Yni

i¼0

1� Pr y� Tt 6 xiðriÞ 6 yþ Ttð Þf g#

�X1

nip2¼0

Pr nip2 arrival in slot i� 2� �2

4

�Ynip2

ip2¼0

1� Pr y� Tt 6 xip2ðrip2Þ 6 yþ Tt

� �n o35


�" X1

nip1¼0

Pr nip1 arrival in slot i� 1� �

�Ynip1

ip1¼0

1� Pr y� Tt 6 xip1ðrip1 Þ 6 yþ Tt

� �n o#

�" X1

nin1¼0

Pr nin1 arrival in slot iþ 1� �

�Ynin1

in1¼0

1� Pr y� Tt 6 xin1 ðrin1 Þ 6 yþ Tt� �� #

�" X1

nin2¼0


�Ynin2

in2¼0

1� Pr y� Tt 6 xin2ðrin2Þ 6 yþ Tt

� �� #

� Prðyi ¼ yÞ Prðri ¼ rÞ: ð3Þ

By the assumption of Gaussian delay distributionwe have: yiðriÞ �NðiTs;r2

i Þ; xiðriÞ �NðiTs;r2i Þ; xip2 ðrip2 Þ �

Nðði� 2ÞTs; r2ip2Þ; xip1 ðrip1 Þ � Nðði� 1ÞTs;r2

ip1Þ; xin1 ðrin1 Þ �

Nððiþ 1ÞTs;r2in1Þ:xin2 ðrin2 Þ �Nððiþ 2ÞTs;r2

in2Þ. Hence, for a

uniformly random nodal distribution, the expression (3)becomes:

PðmRSÞs ¼

Z R

r¼0

Z ðiþ2ÞTs

ði�2ÞTs

X1ni¼0

e�kTsðkTsÞni

ni!

"

�Yni

k¼0


�X1

nip2¼0

e�kTsðkTsÞ

nip2

nip2 !

Ynip2

ip2¼0

1� Prðy� Tt 6 xip2ðrip2 Þ 6 yþ TtÞ

n o24

35

�X1

nip1¼0

e�kTsðkTsÞ

nip1

nip1 !

Ynip1

ip1¼0

1� Prðy� Tt 6 xip1 ðrip1 Þ 6 yþ TtÞn o2

435

�X1

nin1¼0

e�kTsðkTsÞnin1

nin1 !

Ynin1

in1¼0

1� Prðy� Tt 6 xin1 ðrin1 Þ 6 yþ TtÞ� 2

435

�X1

nin2¼0

e�kTsðkTsÞnin2

nin2 !

Ynin2

in2¼0

1� Prðy� Tt 6 xin2 ðrin2 Þ 6 yþ TtÞ� 2

435

� 1ri

ffiffiffiffiffiffiffi2pp e

�12

y�i�Tsri

� �2

dy2rdr

R2 : ð4Þ

In practice, the mean as well as variance of propagationdelay are functions of transmitter–receiver distance[20,21]. Accordingly, the frame arrival time at the receiveris also Gaussian distributed with distance dependentparameters. The arrival time of a frame destined to thereceiver in slot i is Gaussian distributed as: xiðriÞ �NðiTs;r2ðriÞÞ, where the variance is dependent on trans-mitter–receiver distance ri. Using the arrival time distribu-tion, the probability expressions in (4) can be simplified as:

Pr y� Tt 6 xiðriÞ 6 yþ Ttð Þ

¼Z R

0Prðy� Tt 6 xiðri ¼ rÞ 6 yþ TtÞ � Prðri ¼ rÞ

¼Z R

0

12

erfyþ Tt � iTs

rðrÞffiffiffi2p

!� erf

y� Tt � iTs

rðrÞffiffiffi2p

!" #rdr

R2 ,P1;

Pr y� Tt 6 xip1ðrip1Þ 6 yþ Tt

� �¼Z R

0Pr y� Tt 6 xip1

ðrip1¼ rÞ 6 yþ Tt

� �� Prðrip1

¼ rÞ

¼Z R

0

12

erfyþ Tt � ði� 1ÞTs

rðrÞffiffiffi2p

!"

� erfy� Tt � ði� 1ÞTs

rðrÞffiffiffi2p

!#rdr

R2 ,P2;

Pr y� Tt 6 xip2ðrip2Þ 6 yþ Tt

� �¼Z R

0Pr y� Tt 6 xip2

ðrip2¼ rÞ 6 yþ Tt

� �� Prðrip2

¼ rÞ

¼Z R

0

12

erfyþ Tt � ði� 2ÞTs

rðrÞffiffiffi2p

!"

� erfy� Tt � ði� 2ÞTs

rðrÞffiffiffi2p

!#rdr

R2 ,P3;

Pr y� Tt 6 xin1 ðrin1 Þ 6 yþ Tt� �¼Z R

0Pr y� Tt 6 xin1

ðrin1¼ rÞ 6 yþ Tt

� �� Prðrin1

¼ rÞ

¼Z R

0

12

erfyþ Tt � ðiþ 1ÞTs

rðrÞffiffiffi2p

!"

� erfy� Tt � ðiþ 1ÞTs

rðrÞffiffiffi2p

!#rdr

R2 ,P4;

Pr y� Tt 6 xin2ðrin2Þ 6 yþ Tt

� �¼Z R

0Pr y� Tt 6 xin2

ðrin2¼ rÞ 6 yþ Tt

� �� Prðrin2

¼ rÞ

¼Z R

0

12

erfyþ Tt � ðiþ 2ÞTs

rðrÞffiffiffi2p

!"

� erfy� Tt � ðiþ 2ÞTs

rðrÞffiffiffi2p

!#rdr

R2 ,P5:

For a known r(r), the above integrations can be solvedto compute the frame success probability in (4). However,since the nature of distance dependence on r(r) is notknown yet, for a closed form analytic solution on systemthroughput, below consider a special case of constant r.

We consider r ¼ aTðmaxÞp a constant, where 0 6 a 6 1.

Thus, simplifying and using the identities: erfðxÞ ¼R x0 e�t2 dt, and

R ba

1rffiffiffiffi2pp e�

12

x�lrð Þ2 ¼ 1

2 erf b�lrffiffi2p

� �� erf a�l

rffiffi2p

� �h i, we

have from (4),

PðmRSÞs ¼

Z R

r¼0

Z ðiþ2ÞTs

ði�2ÞTs

e�kTsðP1þP2þP3þP4þP5Þ

� 1rffiffiffiffiffiffiffi2pp e�

12

y�iTsrð Þ2 dy

2rdr

R2

¼Z ðiþ2ÞTs

ði�2ÞTs

e�kTsðP1þP2þP3þP4þP5Þ � 1rffiffiffiffiffiffiffi2pp e�

12

y�iTsrð Þ2 dy:

Hence, the normalized system throughput is:

gmRSS�Aloha�uw ¼ kTtPðmRSÞs : ð5Þ


Note that, for a given uncertainty in propagationdelay (i.e., the standard deviation r), the frame successprobability, and hence system throughput can beoptimized by suitably adjusting the slot size incrementcoefficient k.

5. Performance of modified transmitter synchronizedS-Aloha with propagation delay uncertainty (mTSS-Aloha-uw)

We now evaluate the throughput performance of trans-mitter-end synchronized Aloha (which we call mTSS-Aloha-uw) protocol. In this case, a frame is transmitted ata slot boundary defined at the transmitters, and the trans-mitter-end slot size is optimally increased to accommodatethe distance dependent propagation delays to the receiver[11–13] to maximize the system throughput. The priorstudies of the protocol performance [12,13] however didnot consider the propagation delay uncertainty, i.e., itwas assumed that for a fixed distance away transmitterthe propagation delay is constant.

We analyze the mTSS-Aloha-uw performance under thesame assumption of Gaussian distributed propagationdelay uncertainty as in mRSS-Aloha-uw. For mTSS-Aloha-uw with the transmissions governed by the transmitter-end slot boundaries and the maximum propagationdelay to the receiver Tmax

p ¼ Rv 6 Tt , the slot size is modified

as Ts ¼ Tt þ dTmaxp , where 0 6 d 6 1. Note that, for

rðrÞ ¼ aTmaxp with 0 6 a 6 1, always r(r) 6 Tt. So, in this

case the frame success probability in a slot will be gov-erned by 3rðrÞ

Ts6 3 adjacent slots. Accordingly, the frame

success probability can be calculated similarly as in (3)with the new integration limits for y as (i � 3)Ts and(i + 3)Ts:

PðmTSÞs ¼

Z ðiþ3ÞTs

ði�3ÞTs

Z R

0

X1ni¼0

Pr ni arrival in slot ið Þ"

�Yni

i¼0


�X1

nip3¼0


4

�Ynip3

ip3¼0

1� Pr y� Tt 6 xip3 ðrip3 Þ 6 yþ Tt

� �n o35

�X1

nip2¼0


4

�Ynip2

ip2¼0

1� Pr y� Tt 6 xip2 ðrip2 Þ 6 yþ Tt

� �n o35

�X1

nip1¼0


4

�Ynip1

ip1¼0

1� Pr y� Tt 6 xip1ðrip1Þ 6 yþ Tt

� �n o35

�" X1

nin1¼0


�Ynin1

in1¼0

1� Pr y� Tt 6 xin1 ðrin1 Þ 6 yþ Tt� �� #

�" X1

nin2¼0


�Ynin2

in2¼0


� �� #

�" X1

nin3¼0


�Ynin3

in3¼0


� �� #

� Prðyi ¼ yÞ Prðri ¼ rÞ: ð6Þ

Here, since all the transmitters transmit according to theirown time slots, the mean of Gaussian distribution for thearrival slot i from an ri distance away transmitter is iTs +Tp(ri), where TpðriÞ ¼ ri

v is the propagation delay. InmTSS-Aloha-uw, the additional uncertainty is due to therandom distance ri to the receiver. Hence, accommodatingthe additional propagation delay to the receiver Tp(ri), thearrival time will be Gaussian distributed as: xiðriÞ �NðiTs þ TpðriÞ;r2ðriÞÞ, where r2(ri) is also a function oftransmitter–receiver distance ri.

In (6), Pr(y � Tt 6 xi(ri) 6 y + Tt) can be written as:

P1 ¼ Pr y� Tt 6 xiðriÞ 6 yþ Ttð Þ

¼Z R

0Pr y� Tt 6 xiðri ¼ rÞ 6 yþ Ttð Þ � Prðri ¼ rÞ

¼Z R

0

Z yþTt

y�Tt

1rðrÞ

ffiffiffiffiffiffiffi2pp e

�12

x� iTsþrvð Þ

rðrÞ

� �2

dx � 2rdr

R2 ,P11 � P12:

This above equation can be derived for known values ofTp(r) and r(r).

As in mRSS-Aloha-uw, since the nature of r(r) is un-known, by considering distance independent propagationdelay uncertainty, a compact expression for systemthroughput can be obtained.

With constant r approximation: rðrÞ ¼ r ¼ aRv , with

0 6 a 6 1, after simplification we have,

P11 ¼rffiffiffi2p

Tmaxp

!214

2ffiffiffiffipp b1e�b2

1 � a1e�a21

� �þ 2b2

1 � 1� �

erfðb1Þ��

� 2a21 � 1

� �erfða1Þ

�� r

ffiffiffi2p

ðTmaxp Þ

2 ðyþ Tt � iTsÞ

� b1 erfðb1Þ þe�b2

1ffiffiffiffipp � a1 erfða1Þ �

e�a21ffiffiffiffipp

!;

with a1 ¼ yþTt�iTs

rffiffi2p ; b1 ¼

yþTt�iTs�Tmaxp

rffiffi2p , and


P12 ¼rffiffiffi2p

Tmaxp

!214

2ffiffiffiffipp b2e�b2

2 � a2e�a22

� �þ 2b2

2 � 1� �

erfðb2Þ��

� 2a22 � 1

� �erfða2Þ

�� r

ffiffiffi2p

ðTmaxp Þ

2 ðy� Tt � iTsÞ

� b2 erfðb2Þ þe�b2

2ffiffiffiffipp � a2 erfða2Þ �

e�a22ffiffiffiffipp

!;

with a2 ¼ y�Tt�iTs

rffiffi2p ; b2 ¼

y�Tt�iTs�Tmaxp

rffiffi2p .

Similarly P2¼Prðy�Tt 6xip1 ðrip1 Þ6 yþTtÞ; P3¼Prðy�Tt

6xip2 ðrip2 Þ6 yþTtÞ; P4¼Prðy�Tt 6xip3 ðrip3 Þ 6 yþTtÞ; P5¼Prðy�Tt 6xin1 ðrin1 Þ6 yþTtÞ; P6 ¼ Prðy �Tt 6xin2 ðrin2Þ6 yþTtÞ, and P7¼Prðy�Tt 6xin3

ðrin3Þ6 yþTtÞ are found.

Now,Z ðiþ3ÞTs

y¼ði�3ÞTs

Z R

r¼0Prðyi ¼ yÞ Prðri ¼ rÞ

¼Z ðiþ3ÞTs

y¼ði�3ÞTs

Z R

r¼0

e�1

2y�ðiTsþr

vÞrðrÞ

� �2

rðrÞffiffiffiffiffiffiffi2pp dy

2rdr

R2

¼Z ðiþ3ÞTs

y¼ði�3ÞTs

Z R

r¼0

e�1

2y�ðiTsþr

vÞrðrÞ

� �2

rðrÞffiffiffiffiffiffiffi2pp dy

2rdr

R2

¼Z ðiþ3ÞTs

y¼ði�3ÞTs

ðI11 � I12Þdy;

where the second equality is obtained by constant rassumption. I11 and I12 are respectively:

I11 ¼rffiffiffi2p

e�c2 � e�d2� �ðTmax

p Þ2 ffiffiffiffi

pp ; I12 ¼

ðy� iTsÞ erfðdÞ � erfðcÞf gðTmax

p Þ2 ;

with c ¼ y�iTs

rffiffi2p and d ¼ y�iTs�R

vrffiffi2p .

After substituting and simplifying, PðmTSÞs in (6) can be

written as:

PðmTSÞs ¼

Z ðiþ3ÞTs

y¼ði�3ÞTs

e�kTsðP1þP2þP3þP4þP5þP6þP7Þ � I11 � I12ð Þdy;

and hence the normalized system throughput is:

gmTSS�Aloha�uw ¼ kTtPðmTSÞs : ð7Þ

6. Delay performance

Consider that any transmitter will know the outcome ofits transmission after a delay which is the round-trip prop-agation delay between the transmitter and the receiver.Since this propagation delay in underwater applicationsis large, we assume that the processing and decision mak-ing time is rather negligible, so as soon as the transmitterknows the outcome it will transmit or retransmit a frameimmediately. With a uniform random distribution ofnodes, the probability density function of transmitter–receiver distance is:

friðrÞ ¼ 2r

R2 ; 0 6 ri 6 R

where R is the communication range of the nodes(assumed same for all nodes).

From (6), the average round trip propagation delay iscomputed as 4R

3v, where v is the average propagation speedof underwater acoustic signal. So, the average delay pertransmission can be written as:

D1 ¼Ts

2þ 4R

3v ;

where Ts2 is the average time a transmitter waits after a new

frame is generated. Note, for example, Ts = Tt + 2kr(r) formRSS-Aloha-uw, and Ts ¼ Tt þ dTmax

p for mTSS-Aloha-uw,as defined in Sections 4 and 5, respectively.

Denote the probability of success of a transmission as p.p ¼ PðmRSÞ

s for mRSS-Aloha-uw, where PðmRSÞs is given by 4,

and p ¼ PðmTSÞs for mTSS-Aloha-uw, where PðmTSÞ

s is givenby (6). With no limit on the number of retries, the averagenumber of transmissions per successful frame is, N ¼ 1

p.So, the average delay per successful frame is given by,

D ¼ D1N ¼ Ts

2þ 4R

3v

� �1p: ð8Þ

7. Results and discussion

For simulation based performance evaluation we con-sidered a single cell scenario with one receiver and multipletransmitters at varying distances within the communica-tion range of the receiver. Based on the estimate ofpropagation delay to the receiver, a frame transmission in-stant is deferred such that it arrives in a slot. But due topropagation delay uncertainty, the actual time of arrivalof a frame at the receiver varies around the estimatedarrival instant, which we have approximated as Gaussiandistributed. To highlight the relative performance of differ-ent protocol variants at the MAC layer, the frame failureevents were simulated only due to MAC level contentions,including that due to propagation delay uncertainty. Also,since the current analytical study does not involve otherprotocol layers, we chose to use our developed C baseddiscrete event simulation model for creating a randomnetwork and verifying the analytical results. The analyticalresults were obtained in SCILAB using the expressionsdeveloped in Sections 4–6.

In simulations, 200 randomly located nodes were takenaround the receiving node. In each iteration, a randomlylocated transmitter was chosen, and the other neighboringtransmitters’ activities were controlled by varying the(Poisson distributed) frame arrival rate k. Different valuesof delay variance r2 were taken to study its impact on aprotocol performance.

Following the underwater modem specifications [30],the parameters considered are: channel rate 16 kbps,acoustic signal speed v = 1500 m/s, frame size F = 40 Bytes,and (unless otherwise stated) transmission range R = 20 m.We particularly chose to use very short frame size (as inRTS (36 Bytes or 44 Bytes) and CTS (38 Bytes)), as we antic-ipate that the proposed modified S-Aloha protocol could beuseful for short (RTS/CTS or alike) control messagingpurposes.


7.1. Performance of RSS-Aloha-uw

In Fig. 3, analytic and simulation based results on sys-tem throughput performance of RSS-Aloha with respectto frame arrival rate are shown. As observed in the analy-sis, with perfect synchronization, i.e., without any propaga-tion delay uncertainty, the system performs identically asin S-Aloha system without any propagation delay. Thus,as long as the propagation delay can be perfectly esti-mated, there is no impact of propagation delay on theS-Aloha performance. However, as shown in the secondplot, when there is some uncertainty in the propagationdelay estimation, the performance drops down to that ofbasic Aloha system. This result holds for any non-zerovalues of propagation delay uncertainty. Thus, the resultsverify that, without perfect synchronization the benefit oftime slotting vanishes if the slot size Ts is the same as theframe transmission time Tt.

7.2. Graceful degradation of mRSS-Aloha-uw performance

In Fig. 4, throughput performance of our proposedmRSS-Aloha-uw is shown at different values of propaga-tion delay uncertainty. In this study, to decide the slot sizeTs = Tt + 2kr, k was chosen 1.0. r ¼ aTmax

p ¼ nTt where a ischosen such that 0 6 n 6 1. The analytic observationsmatch well with the simulation results. The results alsoshow that the throughput of mRSS-Aloha-uw at a = 0.1(or n = 0.067) is more than the throughput at a = 0.5 (orn = 0.333), confirming a graceful degradation of mRSS-Alo-ha-uw performance as the propagation delay uncertaintyincreases.

Further, in Fig. 5, throughput performance of mRSS-Aloha-uw is shown with modified slot size Ts = Tt + 2kr

0 0.5 1 1.50

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

Frames per frame tr

Nor

mal

ized

sys

tem

thr

ough

put,

η

Fig. 3. System throughput of RSS-Aloha with as well as without perfect syncsynchronization, r = 0.005Tt. R = 20 m.

and with Tmaxp � Tt . Two different r values (r < Tt, and

r > Tt) were considered to verify if the analytic formulationof mRSS-Aloha-uw throughput holds good at a highervalue of r. The two numerical values are: r ¼0:00075Tmax

p ¼ 0:005Tt and r ¼ 0:45Tmaxp ¼ 3Tt . The

matched simulation results with both r confirm that thesimplifying assumption apparently does not have anybearing on the system performance. The plots also confirmthat the throughput of mRSS-Aloha-uw is independent ofthe inter-nodal propagation delay.

7.3. Optimum slot size in mRSS-Aloha-uw

Fig. 6 shows the impact of slot size increment coeffi-cient k on the maximum system throughput in mRSS-Aloha-uw at various values of r. The results demonstratethat, with a larger r a smaller k is required. This is because,when r is large, a smaller k is able to increase the slot sizesufficiently to accommodate the straying frames within aslot.

The results demonstrate further that, irrespective ofthe value of r, at a very low value of k, i.e., when mRSS-Aloha-uw approaches to RSS-Aloha-uw, the system tendsto behave as a pure Aloha system. Further, as k is increased,beyond a certain high value, the system performance actu-ally decreases. This indicates that, some increase in slotsize Ts is required to compensate the uncertainty of propa-gation delay, thereby reducing the inter-slot frame colli-sions. But, since the increase in Ts also invites additionalwaiting and hence more probability of overlapping arrivalsin a slot (i.e., more intra-slot collision), beyond a certainlarge Ts, the gain from accommodating propagation delayuncertainty is superseded by the loss due to collisions. To

2 2.5 3 3.5 4ansmission time, λTt

RSS−Aloha (perfect sync) :simRSS−Aloha (perfect sync) :anaRSS−Aloha (imperfect sync) :simRSS−Aloha (imperfect sync) :ana

hronization. Ts = Tt. Propagation delay uncertainty in case of imperfect

0 0.5 1 1.5 2 2.5 3 3.5 40

0.05

0.1

0.15

0.2

0.25

0.3

0.35

Frames per frame transmission time, λTt

Nor

mal

ized

sys

tem

thr

ough

put,

η

sim:σ=0.067Ttana:σ=0.067Ttsim:σ=0.333Ttana:σ=0.333Ttsim:σ=0.599Ttana:σ=0.599Tt

Fig. 4. Performance of mRSS-Aloha-uw with k = 1 at different levels of propagation delay uncertainty. R = 20 m.

0 0.5 1 1.5 2 2.5 3 3.5 40

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

Frames per frame transmission time, λTt

Nor

mal

ized

sys

tem

thr

ough

put,

η

sim:σ=0.005 Ttana:σ=0.005 Ttsim:σ=Ttana:σ=Tt

Fig. 5. Performance of mRSS-Aloha-uw with Tmaxp > Tt . k = 1, R = 200 m.


quantify the maximum achievable gain associated withmRSS-Aloha-uw, let us define throughput gain as:

Gain ¼ gmaxmRSS�Aloha�uw � gmax

RSS�Aloha�uw

gmaxRSS�Aloha�uw

� 100:

By inspection of the plots in Fig. 6, a higher gain isachieved in mRSS-Aloha-uw with respect to RSS-Aloha-uw at a smaller value of propagation delay uncertainty.For example, for r = 0.00067Tt, a maximum gain of 98% isachieved at k � 2, whereas, r = 0.0067Tt, a maximum gain

of 61% is achieved at k � 1.5. The observation on through-put gain of mRSS-Aloha-uw with respect to RSS-Aloha-uwis more clearly demonstrated in Fig. 7.

7.4. Relative throughput performances of mRSS-Aloha-uw andmTSS-Aloha-uw

Relative throughput performance of mRSS-Aloha-uwwith respect to mTSS-Aloha-uw at different slot sizeincrement coefficient in Fig. 6 shows that, although at

0 0.5 1 1.5 2 2.5 30.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

Slot size increment coefficient

Max

imum

sys

tem

thro

ughp

ut, η

max

mRSS−Aloha−uw: σ=0.00067TtmRSS−Aloha−uw: σ=0.0067TtmTSS−Aloha−uw: σ=0.00067TtmTSS−Aloha−uw: σ=0.0067Tt

Fig. 6. Relative performance of mRSS-Aloha-uw and mTSS-Aloha-uw at different slot size increment coefficient (k or d). R = 20 m.

0 0.1 0.2 0.3 0.4 0.5 0.6 0.70

10

20

30

40

50

60

70

80

90

100

σ / T t

Perc

enta

ge th

roug

hput

gai

n

Fig. 7. Maximum throughput gain in mRSS-Aloha-uw with respect RSS-Aloha-uw, as a function of standard deviation of propagation delay uncertainty(normalized with respect to Tt).


lower values of slot size increment coefficient both syn-chronization approaches have increasing trends of perfor-mance, mTSS-Aloha-uw has increasing lower throughput.At higher values of the coefficient, mTSS-Aloha-uw per-formance degrades fast, as the slot size increases in thiscase at a faster rate compared to that in mRSS-Aloha-uw. As a result, in mTSS-Aloha-uw intra-frame collision

vulnerability overrides the benefit of reduced inter-framecollisions.

Fig. 8 compares the maximum system throughput per-formances of mTSS-Aloha-uw and mRSS-Aloha-uw using(5) and (7), respectively. The plots clearly demonstratethat, when operating in a propagation delay intensivecommunication environment, although transmitter-end

0 0.1 0.2 0.3 0.4 0.5 0.6 0.70.18

0.2

0.22

0.24

0.26

0.28

0.3

0.32

0.34

0.36

σ / T t

Max

imum

sys

tem

thro

ughp

ut,η

max

mRSS−Aloha−uwmTSS−Aloha−uw

Fig. 8. Maximum throughput comparison at different delay uncertainties.


synchronization with optimally increased slot size(mTSS-Aloha-uw) performs better than the case with Ts =Tt, receiver-end synchronization with an optimal slot size(mRSS-Aloha-uw) has a consistently higher throughputperformance with respect to mTSS-Aloha-uw.

A comparative maximum throughput performance ofmRSS-Aloha-uw and mTSS-Aloha-uw at a constant propa-gation delay uncertainty r and different Tmax

p (whereTmax

p 6 Tt) in Fig. 9 shows that, beyond very small valuesof Tmax

p mTSS-Aloha-uw performance degrades sharply

5 10 150.2

0.22

0.24

0.26

0.28

0.3

0.32

Transmissio

Max

imum

sys

tem

thro

ughp

ut,η

max

Fig. 9. Maximum throughput comparison at d

below that of mRSS-Aloha-uw. The mRSS-Aloha-uw per-formance remains unaffected because the optimum slotsize in this case is independent of Tmax

p . This Tmaxp indepen-

dence of optimum slot size in mRSS-Aloha-uw also impliesthat, at very low Tmax

p a fixed-r dependent slot size is largerthan Tmax

p -dependent slots, and this larger slot does nothelp reduce inter-frame collisions compared to the in-creased intra-frame collisions. As a result, the throughputperformance of mRSS-Aloha-uw is a little poorer than thatof mTSS-Aloha-uw at very low Tmax

p . Note that, the

20 25 30n range, R (m)

mRss−Aloha−uwmTss−Aloha−uw

ifferent transmission ranges. r = 0.01Tt.

5 10 15 20 25 300.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

Transmission range, R (m)

Del

ay p

er s

ucce

ssfu

l fra

me,

D (s

ec)

mTSS−Aloha−uw: σ=0.1TtmTSS−Aloha−uw: σ=0.001TtmRSS−Aloha−uw: σ=0.1TtmRSS−Aloha−uw: σ=0.001Tt

Fig. 10. Delay comparison at different transmission ranges.


performance of mRSS-Aloha-uw at very low Tmaxp can be

improved if r is an increasing function of Tp.

7.5. Delay performance

The delay performances of mRSS-Aloha-uw andmTSS-Aloha-uw per successful frame delivery, as devel-oped in Section 6, are compared in Fig. 10. The resultsare based on maximum throughput (as expressed in (4)and (7)) for a given propagation delay uncertainty r andwith an optimum time slot increment coefficient k.

Two observations can be drawn from the plots. First,since the node deployment density is kept constant, withthe increase in nodal communication range, the numberof contending nodes (i.e., the overall frame arrival rate k)increases, causing more collision vulnerability. Thus, irre-spective of the propagation delay uncertainty, the delayper successful frame increases. The rate of increase of delayin mTSS-Aloha-uw is more because, the increase in Tmax

p

further contributes to the increase in slot size, whereasTmax

p does not have an impact in deciding the mRSS-Alo-ha-uw slot size. Second, while at a lower propagation delayvariance r2 the mRSS-Aloha-uw always offers lower (bet-ter) delay performance, at a higher r and for a shortertransmission range mTSS-Aloha-uw has an effectively low-er delay performance. A similar trend was also seen inFig. 9. This is because, although the average number oftransmission attempt per success N ¼ 1

p

� �in mTSS-

Aloha-uw is always higher than that of mRSS-Aloha-uw(cf. Fig. 7), the slotting definitions of the two schemesdictate that the slot size in mTSS-Aloha-uw is lower (dueto a small R) than that of the mRSS-Aloha-uw (due to afixed r).

8. Conclusion

In this paper, we have presented a theoretical frame-work for throughput performance computation of receiversynchronized S-Aloha in underwater wireless networks(RSS-Aloha-uw) with a random inter-nodal signal propaga-tion delay and delay uncertainty. We have shown that,when using conventional slotting concept, if the propaga-tion delay cannot be estimated perfectly, the performanceof RSS-Aloha-uw degrades to that of basic Aloha. Wehave proposed and analyzed a modified RSS-Aloha-uw(mRSS-Aloha-uw) and have shown that, by optimallyincreasing the slot size, a graceful degradation of systemperformance can be achieved as the propagation delayuncertainty increases. Via analysis and simulations, wehave further compared the proposed mRSS-Aloha-uw witha transmitter-end synchronized modified S-Aloha under asimilar network environment setting, and verified thatmRSS-Aloha-uw offers a consistently higher throughputperformance. The delay performance studies have shownthat, while at a lower propagation delay uncertaintymRSS-Aloha-uw always offers a lower (better) delay, whenthe uncertainty is high, the delay performance of mRSS-Aloha-uw can be poorer in a system with smaller nodalcommunication range.

Although the S-Aloha protocols may not be used for datacommunication phase because of low throughput, the res-ervation based random access protocols are normally pre-ceded by S-Aloha based control message exchange phase.To improve the user experience as well as for resource effi-ciency, it is also important to maximize the control phaseperformance. Our proposed modified S-Aloha protocol isexpected to be useful in such applications in uncertainpropagation delay intensive environments.


Acknowledgments

This research was partly supported by the Dept. of Sci-ence and Technology (DST) under Grant No. SR/S3/EECE/054/2007 and the Council of Scientific and Industrial Re-search (CSIR) under Grant No. 22/448/07/EMR-II.

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Priyatosh Mandal received his B.Sc. inMathematics (with Honors) from JadavpurUniversity, in 1998, M.C.A. from JawaharlalNehru University, New Delhi, in 2001, and M.Tech in Information Technology from GGSIPU,Delhi, in 2004. He has been working with theSignalling Group in Centre for Development ofTelematics (C-DOT), New Delhi, India as aSenior Research Engineer since 2001. Cur-rently he is a part-time Ph.D. student in theElectrical Engineering Department at IITDelhi. He has more than 8 years of work

experience in the field of SS7 and Sigtran protocols. His research interestsare in performance analysis of communication protocols.

Swades De received his B.Tech in Radiophys-ics and Electronics from the University ofCalcutta, India, in 1993, M.Tech in Optoelec-tronics and Optical Communication from theIndian Institute of Technology (IIT) Delhi, in1998, and Ph.D. in Electrical Engineering fromthe State University of New York at Buffalo, in2004. Before moving to IIT Delhi in 2007, hewas an Assistant Professor of Electrical andComputer Engineering at NJIT (2004–2007).He also worked as a post-doctoral researcherat ISTI-CNR, Pisa, Italy (2004), and has 5 years

industry experience in India in telecommunication hardware and soft-ware development (1993–1997, 1999). His research interests includeperformance study, resource efficiency in multihop wireless and high-
speed networks, broadband wireless access, and communication andsystems issues in optical networks.
http://www.link-quest.com/html/uwm_hr.pdf

http://www.link-quest.com/html/uwm_hr.pdf

Documents

Ad Hoc Networks - Indian Institute of Technology Delhiweb.iitd.ac.in/~swadesd/pubs/JNL/UWN-AdHoc2013.pdf · networks with imprecise propagation delay information Priyatosh Mandala,