A Multimedia Cross-Layer Protocol for Underwater Acoustic Sensor Networks

Transcription

1 2924 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 9, NO. 9, SEPTEMBER 2010 A Multmeda Cross-Layer Protocol for Underwater Acoustc Sensor Networks Daro Pompl, Member, IEEE, and Ian F. Akyldz, Fellow, IEEE Abstract Underwater multmeda acoustc sensor networks wll enable new underwater applcatons such as multmeda coastal and tactcal survellance, undersea exploratons, pcture and vdeo acquston and classfcaton, and dsaster preventon. Because of the dfferent applcaton requrements, there s a need to provde dfferentated-servce support to delay-senstve and delay-tolerant data traffc as well as to loss-senstve and losstolerant traffc. Whle research on underwater communcaton protocol desgn so far has followed the tradtonal layered approach orgnally developed for wred networks, mproved performance can be obtaned wth a cross-layer desgn. Hence, the objectve of ths work s twofold: 1) study the nteractons of key underwater communcaton functonaltes such as modulaton, forward error correcton, medum access control, and routng; and 2) develop a dstrbuted cross-layer communcaton soluton that allows multple devces to effcently and farly share the bandwdth-lmted hgh-delay underwater acoustc medum. Index Terms Underwater wreless communcatons, underwater sensor networks, cross-layer routng and MAC algorthms, optmzaton. I. INTRODUCTION UNDERWATER Acoustc Sensor Networks (UW-ASNs) [1] consst of sensors deployed to perform collaboratve montorng tasks over a body of water. UW-ASNs enable applcatons for oceanographc data collecton, polluton montorng, offshore exploraton, and asssted navgaton. Wreless acoustc communcaton s the typcal physcal layer technology n underwater networks because of the propagaton lmtaton of rado frequency and optcal waves [2]. A sgnfcant surge n research on underwater sensor networks n the last few years has resulted n ncreased nterest n the networkng communty for ths leadng-edge technology. Ths growng nterest can be largely attrbuted to new applcatons enabled by networks of small devces capable of harvestng nformaton from the underwater physcal envronment, performng smple processng on the extracted data, and transmttng t to remote locatons. Several archtectures, protocols, and solutons for underwater networkng have been proposed n [3], [4], [5], [6]. As of today, however, exstng works on UW-ASNs are mostly focused on enablng the measurement of scalar physcal phenomena lke temperature, water salnty, and presence of contamnants/pollutants n water. Furthermore, Manuscrpt receved February 1, 2010; revsed May 23, 2010; accepted June 2, The assocate edtor coordnatng the revew of ths paper and approvng t for publcaton was G. Xue. D. Pompl s wth the Department of Electrcal and Computer Engneerng, Rutgers, The State Unversty of New Jersey, 94 Brett Road, Pscataway, NJ (e-mal: pompl@ece.rutgers.edu). I. F. Akyldz s the drector of the Broadband Wreless Networkng Laboratory, School of Electrcal and Computer Engneerng, Georga Insttute of Technology, 75 5th Street, Atlanta, GA (e-mal: an@ece.gatech.edu). Dgtal Object Identfer /TWC /10$25.00 c 2010 IEEE most of these applcatons have n general very low bandwdth demands and are usually delay tolerant. In order to enable new applcatons such as multmeda coastal and tactcal survellance, undersea exploratons, pcture and vdeo acquston and classfcaton, and dsaster preventon, underwater sensor networks wll need to be able to retreve multmeda data orgnated from heterogeneous sources, and store, process, and fuse t whle t s beng transmtted. Many of the above applcatons, however, requre the underwater sensor network paradgm to be re-thought n vew of the need for mechansms to delver multmeda content wth a certan level of Qualty of Servce (QoS). As a matter of fact, mechansms to effcently meet applcaton-level QoS requrements, and to map them nto network-layer metrcs such as end-to-end delay, delay jtter, and packet error rate, have not been prmary concerns n manstream research on underwater sensor networks. There are several characterstcs of UW-ASNs that make QoS delvery of multmeda content a challengng task such as frequency-dependent transmsson loss, colored nose, multpath, Doppler frequency spread, hgh propagaton delay, sensor battery and resource constrants, varable channel capacty, and cross-layer couplng of functonaltes [1], [7]. In multhop wreless networks, n fact, there s a strct nterdependence among functons handled at all layers of the communcaton stack. Hence, the varous functonaltes amed at QoS provsonng should not be desgned separately when effcent solutons are sought. Whle most of research on underwater communcaton protocol desgn so far has followed the tradtonal layered approach, whch was orgnally developed for wred networks, mproved performance n wreless networks can be obtaned wth a cross-layer desgn [8], [9], especally n a harsh envronment such as the underwater. Gven our research experence n ths area, we clam that UW-ASNs requre for a cross-layer communcaton soluton to allow for an effcent use of the scarce resources such as bandwdth and battery energy. However, although we advocate ntegratng hghly specalzed communcaton functonaltes to mprove network performance and to avod duplcaton of functons by means of cross-layer desgn, t s mportant to consder the ease of desgn by followng a modular desgn approach. Ths wll also allow mprovng and upgradng partcular functonaltes wthout the need to re-desgn the entre communcaton system. Cross-layer nteractons need to be thoroughly studed and controlled, and no cross-layer dependency should be left unntended as ths may lead to poor system performance [10], [11]. For these reasons, we rely on the above-mentoned desgn gudelnes and propose a cross-layer communcaton soluton

2 POMPILI and AKYILDIZ: A MULTIMEDIA CROSS-LAYER PROTOCOL FOR UNDERWATER ACOUSTIC SENSOR NETWORKS 2925 for UW-ASN multmeda applcatons that s bult upon our prevous work on underwater routng [3] and Medum Access Control (MAC) [4] protocols. In partcular, the objectve of our work s twofold: 1) explore the nteracton of key underwater communcaton functonaltes such as modulaton, Forward Error Correcton (FEC), MAC, and routng; 2) develop a dstrbuted cross-layer soluton ntegratng hghly specalzed communcaton functonaltes that cooperate to allow multple devces to effcently and farly share the bandwdth-lmted hgh-delay underwater acoustc medum. To the best of our knowledge, ths work s the frst to propose a coherent cross-layer framework to optmze communcatons n UW-ASNs. The remander of ths artcle s organzed as follows. In Sect. II, we descrbe our desgn phlosophy for cross-layerng and we ntroduce our communcaton soluton. In Sect. III, we analyze the performance results. Fnally, n Sect. IV, we draw the man conclusons and outlne future research drectons. II. CROSS-LAYER COMMUNICATION SOLUTION A. Our Cross-layer Desgn Approach Three approaches to cross-layer desgn are possble: Parwse nteractons (e.g., [9], [12]). Resource allocaton problems are treated by consderng smple nteractons between two communcaton layers. A typcal example s the nteracton between the congeston control and power control mechansms [9]; another s the jont power control and schedulng problem, whch s addressed n [12]. Ths approach does not take nto account the tght couplng among functonaltes handled at all layers of the protocol stack typcal of mult-hop underwater networks. Heurstc approaches (e.g., [13]). Resource allocaton problems followng ths approach consder nteractons between several communcaton functonaltes at dfferent layers as t s not always possble to model and control the nteractons between functonaltes; solutons n these category rely on heurstcs, whch often lead to suboptmal performance. Resource allocaton frameworks (e.g., [8], [14]). Theseapproaches ntegrate dfferent communcaton functonaltes nto a coherent mathematcal framework and provde a unfed foundaton for cross-layer desgn and control n mult-hop wreless networks. Solutons n ths category try to reach optmalty based on an applcaton-dependent objectve functon, and provde gudelnes and tools to develop mathematcally sound dstrbuted solutons. In our work, we follow ths last desgn approach. Our objectve s to develop a resource allocaton framework that accurately models every aspect of the layered network archtecture, resultng n theoretcal and practcal mpacts beyond the prevously establshed results. By explotng our prevous experence n modelng underwater communcaton functonaltes, we develop a hghly specalzed cross-layer communcaton soluton that can adapt to dfferent applcaton requrements and seek optmalty n several dfferent stuatons. Our soluton reles on a dstrbuted optmzaton problem to jontly control the routng, MAC, andphyscal functonaltes n order to acheve effcent communcatons n the underwater envronment. In partcular, the proposed soluton combnes a 3D geographcal routng algorthm (routng functonalty), a novel hybrd dstrbuted CDMA/ALOHA-based scheme to access the bandwdth-lmted hgh-delay shared acoustc medum (MAC functonalty), and an optmzed soluton for the jont selecton of modulaton, FEC, and transmt power (physcal functonaltes). The proposed soluton s talored for the characterstcs of the underwater acoustc physcal channel, e.g., t takes nto account the very hgh propagaton delay, whch may vary n horzontal and vertcal lnks due to multpath, the dfferent components of the transmsson loss, the mparment of the channel, the scarce and range-dependent bandwdth, the hgh bt error rate, and the lmted battery capacty. These characterstcs lead to very low utlzaton effcences of the underwater acoustc channel and hgh energy consumptons when common MAC and routng protocols are adopted n ths envronment, as thoroughly analyzed n [3], [4]. The remander of ths secton s organzed as follows. In Sect. II-B, we group underwater multmeda applcatons nto four traffc classes and hghlght ther dfferent requrements. In Sect. II-C, we analyze the acoustc channel transmsson loss, avalable bandwdth, nose structure, and maxmum capacty, and descrbe the man physcal layer functonaltes dealt wth n ths work. In Sect. II-D, we present possble modulaton and FEC technques sutable for the underwater envronment, and evaluate ther performance. In Sect. II-E, we ntroduce the CDMA/ALOHA-based MAC and locaton-based routng functonaltes, whch are the core of our cross-layer soluton, and we dscuss how to ntegrate and control dfferent communcaton functonaltes n a dstrbuted manner. Fnally, n Sect. II-F, we detal the protocol operaton. Whle we present the dfferent functonaltes n solaton for the sake of presentaton clarty, the last sectons focus on ther coherent cross-layer ntegraton. B. Multmeda Traffc Classes We envson that underwater multmeda sensor networks wll need to provde support and dfferentated servce to applcatons wth dfferent QoS requrements, rangng from delay senstve to delay tolerant, and from loss senstve to loss tolerant. Hence, we consder the followng four traffc classes: Class I (delay-tolerant, loss-tolerant). It may nclude multmeda streams that, beng ntended for storage or subsequent offlne processng, do not need to be delvered wthn strct delay bounds. Ths class may also nclude scalar envronmental data or non tme-crtcal multmeda content such as snapshots. Class II (delay-tolerant, loss-senstve). It may nclude data from crtcal montorng processes that requre some form of offlne post processng. Class III (delay-senstve, loss-tolerant). It may nclude vdeo/ audo mult-level streams as well as meta-data assocated wth the stream that need to be delvered wthn strct delay bounds and that are, however, relatvely loss tolerant (e.g., vdeo streams can be wthn a certan level of dstorton). Ths class may also nclude montorng data from densely deployed scalar sensors whose montored phenomenon s characterzed by hgh temporal/spatal correlaton, or loss-tolerant snapshots of a phenomenon taken from several multple vewponts.

3 2926 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 9, NO. 9, SEPTEMBER 2010 Class IV (delay-senstve, loss-senstve). Ths class may nclude data from tme-crtcal montorng processes such as dstrbuted control applcatons. C. Physcal Layer Functonaltes The underwater transmsson loss descrbes how the acoustc ntensty decreases as an acoustc pressure wave propagates outwards from a sound source. The transmsson loss TL(d, f 0 )[db]that a narrow-band acoustc sgnal centered at frequency f 0 [khz] experences along a dstance d [m] can be descrbed by the Urck propagaton model [15], TL(d, f 0 )=χ 10 log 10 (d)+α(f 0 ) d. (1) In (1), the frst term accounts for geometrc spreadng 1, whch refers to the spreadng of sound energy caused by the expanson of the wavefronts. It ncreases wth the propagaton dstance and s ndependent of frequency. The second term accounts for medum absorpton, whereα(f 0 )[db/m] represents an absorpton coeffcent that descrbes the dependency of the transmsson loss on the central frequency f 0. Interestngly, the transmsson loss ncreases not only wth the transmsson dstance but also wth the sgnal frequency. As a result, gven a maxmum tolerated transmsson loss TL max [db], whch depends on the transmtter output power and the recever senstvty, a maxmum central frequency exsts for each range. In addton, because of the colored structure of the underwater ambent nose power spectrum densty (p.s.d.), N(f) [W/Hz] or [db re μpa /Hz] 2, the useful acoustc bandwdth B [khz] 3 depends on the transmsson dstance and on the central frequency. Hence, the desgn of the routng and MAC functonaltes of our cross-layer soluton (Sect. II-E) takes ths characterstc of the underwater channel nto account, whch can be stated as follows: agreater throughput may be acheved f data packets are relayed over multple shorter hops nstead of beng transmtted over one long hop. Moreover, the unque V structure of the underwater acoustc nose p.s.d. (whch has a mnmum of 20 db re μpa /Hz at about 40 khz), makes non trval the choce of the optmal bandwdth. Interestngly, when the central frequency s low, e.g., f 0 = 10 khz, a hgher relatve Sgnal-to-Nose-Rato (SNR) s acheved wth a narrow bandwdth (B = 3 as opposed to 9kHz); conversely, when the central frequency s hgh, e.g., f 0 = 100 khz, a hgher relatve SNR s acheved wth a wde bandwdth (B = 90 as opposed to 30 khz). Ths mples that f a hgh central frequency s selected, a large bandwdth can be used for communcaton, although a hgh transmt power would be needed to compensate for the hgher transmsson loss. Our communcaton soluton takes nto account ths unque characterstc, whch s caused by the pecular V structure of the nose p.s.d. and by the fact 1 There are two knds of geometrc spreadng: sphercal (omn-drectonal pont source, spreadng coeffcent χ = 2) and cylndrcal (horzontal radaton only, spreadng coeffcent χ =1). 2 A reference pressure of 1μP a s used to express acoustc source levels n db re μpa. Hence, 1 and 10 W correspond to 171 and 181 db re μpa. 3 We assume the band to be symmetrcal around the central frequency,.e., the band occupancy of bandwdth B at central frequency f 0 s [f 0 B/2,f 0 + B/2], whch for convenence wll be denoted as <f 0,B >. that the dfference between the slopes of N(f) and TL(d, f) decreases as the central frequency ncreases (e.g., postve for low frequences and negatve for hgh ones). In [7], the author assesses the bandwdth dependency on the dstance usng an nformaton-theoretc approach that takes nto account the underwater propagaton loss and ambent nose. The author defnes the bandwdth correspondng to optmal sgnal energy allocaton as the one that maxmzes the channel lnk capacty. However, n order to fnd the optmal sgnal power dstrbuton across the chosen band an a pror knowledge of the optmal reshold ( )atthe recever s requred, whch s often a non-realstc assumpton n practcal systems. In [7], a heurstcally pre-specfed value of 20 db s suggested for ths threshold. If we denoteby S(d, f) [W/Hz] the p.s.d. of the transmtted sgnal chosen for a dstance d,.e., the power dstrbuton across the chosen band <f 0 (d),b(d) >, the total transmtted power s P (d) = <f 0(d),B(d)> S(d, f)df and the sgnal to nose rato s, <f SNR(d, B(d)) = S(d, f) TL(d, f) 1 0(d),B(d)> df <f N(f)df. 0(d),B(d)> (2) By assumng that the nose s Gaussan and that the channel s tme-nvarant for some nterval tme, the channel transfer functon appears frequency-nonselectve n a narrow sub-band Δf centered around frequency f n whch the nose can be approxmated as whte (wth p.s.d. N(f )). Under these assumptons, the capacty C [bps] s gven by, C(d) = [ ] Δf log 2 1+ S(d, f ) TL(d, f ) 1. (3) N(f ) Accordng to the water-fllng prncple [16], maxmzng the capacty wth respect to S(d, f), subject to the constrant that the transmtted power be fnte, yelds to the optmal p.s.d S(d, f) =K(d) N(f) TL(d, f), f < f 0 (d),b(d) >, where K(d) [W/Hz] s a dstance-dependent constant. The SNR correspondng to ths optmal power dstrbuton s thus gven by, SNR(d, B(d)) = K(d) <f 0(d),B(d)> TL(d, f) 1 df <f 0(d),B(d)> N(f)df 1. Fgure 1(a) depcts the chosen central frequency f 0 and bandwdth B, whle Fg. 1(b) shows the assocated theoretcal capacty C when the fxed pre-specfed target ranges n [5, 30] db. Note that, whle the optmal central frequency f 0 (lower curve n Fg. 1(a)) s ndependent on the target, both the chosen bandwdth B and maxmum theoretcal capacty C depend on t. Consequently, fxng the SNR at the recever makes ther values suboptmal: hence, the words optmal and chosen. Fgure 1(c) depcts the p.s.d. of N(f) TL(d, f) and S(d, f), as well as the sgnal band occupancy, when the pre-specfed target s heurstcally set to 20 db, as suggested n [7]. Ths shows that, f the recever SNR s not consdered n the lnk optmzaton at the sender sde, suboptmal decsons are taken. In fact, the lnk (and thus the overall system) performance strongly depends on (4)

4 POMPILI and AKYILDIZ: A MULTIMEDIA CROSS-LAYER PROTOCOL FOR UNDERWATER ACOUSTIC SENSOR NETWORKS 2927 Optmal Central Frequency (f 0 ) and Bandwdth (B) [khz] Optmal Central Frequency and Bandwdth vs. Dstance (@ [db]) Optmal f [khz] 0 Optmal B =5 db Optmal B SNR =10 db th Optmal B =15 db Optmal B =20 db Optmal B =25 db Optmal B SNR =30 db th Capacty [kbps] Capacty vs. Dstance =5 db =10 db SNR =15 db th =30 db SNR =25 db th =30 db p.s.d [db re μpa /Hz] Power Spectral Densty (p.s.d.) of Nf*TL and Sf vs. Frequency (@ SNR =20 db) th Nf*TL p.s.d, dst=100 m Sf p.s.d, dst=100 m Nf*TL p.s.d, dst=1000 m Sf p.s.d, dst=1000 m Nf*TL p.s.d, dst=10000 m Sf p.s.d, dst=10000 m Dstance [m] 0 Dstance [m] Frequency [khz] (a) (b) (c) Fg. 1. (a): Optmal central frequency f 0 [khz] and chosen bandwdth B [khz] vs. dstance d [m], gvenafxed pre-specfed target [5, 30] db; (b): Chosen capacty C [kbps] vs. dstance d [m], gvenafxed pre-specfed target [5, 30] db; (c):p.s.d.ofn(f) TL(d, f) and S(d, f) [db re μpa /Hz] vs. frequency f [khz] at d =10 2, 10 3, 10 4 m when the pre-specfed target s heurstcally set to 20 db. the selected, as t s clear from Fgs. 1 and 2(a). 4 For these reasons, our cross-layer soluton jontly controls physcal transmsson, modulaton, and FEC functonaltes n such a way as to optmze the overall system performance,.e., ether by mnmzng the energy per successfully receved bt or by maxmzng the net bt rate. Among these objectve functons, the cross-layer soluton wll choose dependng on the applcaton requrements. In the next sectons, we present the man communcaton functonaltes of our cross-layer soluton. Wthout relyng on a pre-specfed, our algorthm jontly selects, n a dstrbuted manner, the optmal p.s.d. of the transmtted sgnal,.e., K, f 0,andB, and the best combnaton of modulaton and FEC technques as well as MAC and routng, wth the objectve of ether savng energy, thus prolongng the lfetme of the network n most scenaros 5 (Objectve 1), or maxmzng the network end-to-end throughput (Objectve 2), thus ncreasng the system performance. The actual objectve (1 or 2) would depend on the specfc applcaton requrements that need to be met, and s ether decded offlne durng the deployment phase or onlne through control sgnalng from the surface staton. In order to acheve the selected objectve, our crosslayer soluton nterfaces wth the modulaton functonalty by choosng the optmal transmtted power and number of bts per symbol, thus tradng power effcency for spectral effcency 6. Moreover, our soluton nterfaces wth the FEC functonalty and trades channel codng overhead,.e., the amount of redundancy ntroduced to protect the transmsson, for the level of protecton from nose nterference,.e., the bt error correctng capablty at the recever (Sect. II-D). Last, but not least, our soluton jontly decdes on the best next hop 4 The dscontnuty of the capacty as well as of the transmtted power n Fgs. 1(b) and 2(a) at 300 and 5000 m, respectvely, s caused by the mnmum frequency f 0 B/2 reachng zero. Consequently, because of the constrant on the band symmetry around the central frequency, the maxmum frequency reaches f 0 + B/2. 5 In the case of nhomogeneous network denstes, network topologes wth dfferent node degrees, and asymmetrc traffc patterns the maxmzaton of the network lfetme should be acheved not only through energy mnmzaton but also through load balancng. 6 By movng to a hgher-order constellaton, t s possble to transmt more bts per symbol usng the same bandwdth (hgher spectral effcency), although at the prce of hgher energy per bt requred for a target Bt Error Rate (BER) (lower power effcency). (routng functonalty) and how/when to access the channel and send the data to the chosen next hop (MAC functonalty) (Sect. II-E). D. Modulaton and FEC Interactons We consder several classes of modulaton schemes sutable for underwater communcatons such as PSK, FSK, and QAM (both n ther coherent and non-coherent versons), whose Bt Error Rate (BER) vs. SNR performance s reported n Fg. 2(b). Note that, whle BER plots usually refer to the receved bt SNR,.e., E b /N 0,wedefne the p.s.d. of an equvalent whte nose as N 0 =(1/B) <f 0,B> N(f)df and the receved bt energy as E b =(1/C) <f S(d, f) TL(d, f) 1 0,B> df. Hence, the equvalent bt SNR s E b /N 0 =(B/C) SNR. As far as the FEC functonalty s concerned, we consder block codes because of ther energy effcency and lower complexty compared to convolutonal codes [17], [18]. In fact, the lmted energy-consumpton requrements of UW- ASNs calls for energy-effcent low-complexty error control codng schemes. In [18], the energy consumpton profle of convolutonal codes s presented based on a μ-amps archtecture. It s shown that no convolutonal code provdes better energy effcency for BER > 10 5 than uncoded transmsson [18]. Smlarly, n [17], convolutonal and BCH (Bose, Ray-Chaudhur, Hocquenghem) 7 codes are compared n terms of energy effcency n a framework to optmze the packet sze n wreless sensor networks. Results of ths work reveal that BCH codes outperform the most energy-effcent convolutonal code by almost 15%. Consequently, we do not consder convolutonal codes n our work. Our framework, however, can be extended to support convolutonal codes as well as other codes such as turbo codes or Type I or II Automatc Repeat request (ARQ) schemes. A BCH block code s represented by (n, k, t), wheren s the block length, k s the payload length, and t s the error correctng capablty n bts. In our experments, we used BCH codes able to correct up to t = 10 bt errors. Fgure 2(c) depcts PER vs. BER for dfferent BCH(n,k,t) codes and for 7 A BCH code s a multlevel, cyclc, error-correctng, varable-length dgtal code used to correct multple random error patterns.

5 2928 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 9, NO. 9, SEPTEMBER Transmt Power vs. Dstance 10 0 Bt Error Rate (BER) vs. Sgnal to Nose Rato (SNR) 10 0 Packet Error Rate (PER) vs. Bt Error Rate (BER) (@ L P =100 Byte) Transmt Power [db re μpa ] SNR =5 db th =10 db SNR =15 db th =20 db =25 db SNR =30 db th BER BPSKco BFSKco BFSKnc DPSKnc 4 FSKco 4 FSKnc 8 FSKco 8 FSKnc 4 QAMco 8 QAMco 16 QAMco 32 QAMco 64 QAMco 128 QAMco 256 QAMco 1024 QAMco PER NO FEC BCH(63,57,1) BCH(63,52,2) BCH(63,45,3) BCH(63,39,4) BCH(63,33,5) BCH(127,85,6) BCH(127,78,7) BCH(127,71,8) BCH(255,183,9) BCH(255,175,10) Dstance [m] SNR [db] BER (a) (b) (c) Fg. 2. (a): Transmt power P [db re μpa ] vs. dstance d [m], gvenafxed pre-specfed target [5, 30] db; (b):bterrorrate(ber)vs.snr for dfferent coherent and non-coherent typcal underwater modulaton technques; (c): Packet Error Rate (PER) vs. BER for dfferent BCH(n,k,t) codes. the case of uncoded transmssons (NO FEC) computed as, { BLER(n, k, t) = n ) =t+1 BER (1 BER) n PER(L P,n,k,t)=1 [ 1 BLER(n, k, t) ] L Pk, (5) where BLER represents the BLock Error Rate and L P s the packet length, whch s set to 100 Byte. To qualtatvely understand how we capture the cross-layer nteractons between the modulaton and FEC functonaltes to mprove the lnk performance, let us consder the objectve of these functonaltes when they operate n solaton. The FEC functonalty performs the so-called channel codng,.e., ntroduces some controlled bt redundancy wth the objectve of reducng the PER at the recever gven a certan BER on the lnk. On the other hand, the modulaton functonalty decdes what the best modulaton scheme and ts constellaton should be ether ) to maxmze the lnk raw rate,.e., the rate of transmtted bts (hgh spectrum effcency), or ) to mnmze the lnk BER (hgh power effcency). It s clear that mproved performance can be acheved by jontly selectng the BCH code and the modulaton scheme. Hence, our crosslayer desgn s amed at maxmzng the lnk net rate,.e., the rate of successfully receved bts, by jontly decdng: 1) the modulaton scheme and ts constellaton (whch affect the lnk raw rate), 2) the transmt power (whch affects the BER), and 3) the FEC type and ts strength (whch affect the PER). Whle ths should provde an ntutve explanaton on the cross-layer operaton as far as the physcal layer functonaltes are concerned, n the the next sectons we ntroduce a rgorous mathematcal framework to capture the FEC/modulaton nteractons. E. MAC and Routng Interactons The MAC functonalty s based on a novel hybrd medum access scheme that combnes Drect Sequence Code Dvson Multple Access (DS-CDMA) for the data payload and a smple yet effectve ALOHA access for a control header, whch s transmtted back-to-back mmedately before the data packet to help the next hop set ts recever, as explaned n Sect. II-F. The MAC functonalty ncorporates a closedloop dstrbuted algorthm that nteracts wth the physcallayer functonalty (descrbed n Sect. II-C) to set the optmal transmt power and code length. The objectve s to let sgnals ( n arrve at the recever wth approxmately the same mean power, thus mnmzng the near-far effect 8, whch affects the overall performance of CDMA systems [19], [20]. DS-CDMA compensates for the effect of multpath, whch may heavly affect underwater acoustc channels especally n shallow water (.e., when the depth s up to 100 m), by explotng the tme dversty n the underwater channel. Ths leads to hgh channel reuse and low number of packet retransmssons, whch result n decreased battery consumpton and ncreased network throughput. In such a scheme, however, the major problem encountered s the Multuser Access Interference (MAI), whch s caused by smultaneous transmssons from dfferent users. In fact, the system effcency s lmted by the amount of total nterference and not by the background nose exclusvely [21]. Our MAC functonalty, n conjuncton wth other functonaltes such as FEC and modulaton, ams at achevng three objectves,.e., guarantee ) hgh network throughput, ) low channel access delay, and ) low energy consumpton. To do so, t uses locally generated chaotc codes to spread transmtted sgnals on the optmal band,.e., <f0,b >, whch guarantees a flexble and granular bt rate, bult-n secure protecton aganst eavesdroppng, transmtter-recever self-synchronzaton, and good auto- and cross-correlaton propertes. The dstrbuted closed-loop MAC functonalty ams at settng the optmal combnaton of transmt power and code length at the transmtter sde by relyng on local perodc broadcasts of MAI values from actve nodes. Sender needs to transmt on the shared medum a data packet to j, andletj receve enough power to correctly decode the sgnal wthout mparng ongong communcatons from h to k and from t to n. Because the system effcency s lmted by the amount of total nterference, t s crucalfor to optmze ts transmsson, n terms of both transmt power and code length, n order to lmt the near-far problem. These requrements are compactly expressed by the followng set of constrants, NIj (f) TL j (f)df [ ] P j mn ( ˆRk NI k ) TL k. w j Ω(BER j ) k K (6) 8 The near-far effect occurs when the sgnal receved by a recever from a sender near the recever s stronger than the sgnal receved from another sender located further. In ths case, the remote sender wll be domnated by the close sender.

6 POMPILI and AKYILDIZ: A MULTIMEDIA CROSS-LAYER PROTOCOL FOR UNDERWATER ACOUSTIC SENSOR NETWORKS 2929 In (6), NI j (f) [W/Hz] s the nose plus MAI p.s.d. at recever j, whle NI k [W] s the nose plus MAI power at nodes k K, wth K beng the set of nodes whose ongong communcatons may be affected by node s transmt power. In addton, w j and w tk k are the bandwdth spreadng factors of the ongong transmssons from to j and from t k to k, respectvely, where t k s the node from whch k s recevng data. The normalzed receved spread sgnal,.e., the sgnal power after despreadng, s ˆR k = R k w tk k Ω(BER tk k); where R k [W] s the user sgnal power that recever k s decodng and Ω() s the MAI threshold, whch depends on the target bt error rate. Fnally, n (6), P j [W] represents the power transmtted by to j, andtl j (f) and TL k are the transmsson losses from to j and from to k K, respectvely,.e., TL j (f) =TL(d j,f) and TL k = TL(d k,f 0k ), as n (1). The left constrant n (6) mposes that the SINR 1 at recever j be below a certan threshold,.e., the power P j transmtted by needs to be suffcently hgh to allow recever j to successfully decode the sgnal, gven ts current nose and MAI p.s.d. NI j (f). The rght set of constrants n (6) mposes that the SINR 1 at recevers k K be below a threshold,.e., the power P j transmtted by must not mpar ongong communcatons toward nodes k K. Consequently, to set ts transmt power P j and spreadng factor w 9 j, node needs to leverage nformaton on the MAI and normalzed recevng spread sgnal of neghborng nodes. Ths nformaton s broadcast perodcally by actve nodes. In partcular, to lmt such broadcasts, a generc node k transmts only sgnfcant values of NI k and ˆR k,.e., out of predefned tolerance ranges. Constrants (6) are ncorporated n the cross-layer lnk optmzaton problem P cross layer (, j) n (16). In our cross-layer soluton, the level of nterference at potental recevers,.e., ther MAI, s used not only by the MAC functonalty, but also by the routng functonalty to decde for the best next hop. Whle a routng functonalty mplemented n solaton would fnd the best path from the sender to the destnaton only consderng routng-layer metrcs, our cross-layer routng/mac soluton fnds the best path also consderng the nterference levels at the neghborng nodes (potental next hops): a longer path characterzed by a hgher number of hops (.e., a path that would lkely be suboptmal accordng to only routng-layer nformaton) may be chosen by our cross-layer soluton as the optmal one f the drect path (.e., the one that would guarantee the mnmum number of hops) were composed of nodes characterzed by hgh levels of MAI. A relable communcaton between these nodes, n fact, would requre longer codes and/or hgher transmt power. Also, gven the fact that the bandwdth of underwater acoustc channels ncreases when the range decreases (.e., shorter lnks provde hgher bandwdth, whch, n turns, leads to hgher data rates, as dscussed n Sect. II-C), our dstrbuted cross-layer soluton captures ths property by composng paths usng short lnks to explot ther hgher bandwdth, thus achevng better end-to-end performance (Sect. III). 9 We assume the spreadng factor to be proportonal to the chaotc code length,.e., w j = α c j. By proposng chaotc codes as opposed to pseudorandom sequences, a much hgher granularty n the code length can be acheved as code lengths do not need to be a power of 2. The proposed routng functonalty reles on a geographcal paradgm, whch s very promsng underwater for ts scalablty feature and lmted requred sgnalng, as shown n [3]. Accordng to our dstrbuted routng algorthm, a source or relay node wll select j as best next hop f arg j = arg mn j S P N OR max j S P N E (j) (Objectve 1) R (j) (Objectve 2), where E (j) [J/bt] (Objectve 1) represents the mnmum energy requred to successfully transmt a payload bt from node to the snk; and R (j) [bps] (Objectve 2) represents the maxmum net bt rate that can be acheved from node consderng every outbound lnks n the path towards the snk. In (7), S s the neghbor set of node and P N s the postve advance set, whch s composed of nodes closer to snk N than node,.e., j P N ff d jn <d N. The lnk metrcs E (j) and R (j) n (7) are, respectvely, the objectve functons (8) and (9) of the cross-layer lnk optmzaton problem P cross layer (, j). These metrcs take nto account the number of packet transmssons ˆN j T assocated wth the optmal lnk (, j ),gven the optmal combnaton of modulaton (Mj M) and FEC (Fj F,L F P j ) technques, and transmtted p.s.d. Sj (f) =K j NI j (f) TL j (f), f < f 0j,B j >. Moreover, they account for the estmated hop-path length ˆN Hop j from node to the snk gven j. The proposed optmzaton problem s a dstrbuted communcaton soluton for dfferent multmeda traffc classes that optmzes the transmsson consderng every feasble outbound lnk from,.e., (, j), j S P N, by choosng the optmal p.s.d. of the transmtted sgnal as well as band (K,f0,B ), modulaton (M ), FEC (F,L F P ), and code length (c ). The objectve s set dependng on the hghlevel applcaton requrements. We consder two alternate applcaton-dependent objectves,.e., Objectve 1: mnmze the average energy per bt successfully receved at the destnaton; andobjectve 2: maxmze the average lnk net bt rate, defned as the lnk bt rate R b dscounted by the number of transmssons N T. Whle the frst objectve s expected to lead to a long network lfetme, the second ams at achevng a hgh end-to-end throughput. In the followng, we cast the cross-layer lnk optmzaton problem. P cross layer(, j): Cross-layer Lnk Optmzaton Problem (7) Gven (offlne) : Eelec, b L H P,L P, Φ M (), Ψ F (), PERmax e2e,(m) Computed (onlne) : d j, d N,NI j,ni k, dj, q j, ΔD (m), ˆQj Fnd : Kj, f0j, Bj, Mj, Fj, L F P j, c j Objectve 1 : Mnmze E (j) OR Objectve 2 : Maxmze R (j) Subject to : (class-ndependent relatonshps) R b j = Π e2e j = = E b j Π e2e j (8) = R b j Π e2e 1 j η(mj) Bj c j, E b j =2E b elec + Pj R b j L P L P LH P ˆN LF j T P j (9) (10) ˆN Hop j (11)

7 2930 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 9, NO. 9, SEPTEMBER 2010 SINR j = K j <f 0j,B j > TLj(f) 1 df <f 0j,B j > NIj(f)df 1 (12) BER j =Φ M j ( SINR j ) PER j =Ψ F ( j L P,L F ) Pj,BER j ( ) ˆN Hop d N j =max, 1 <d j > N (class-ndependent set of constrants) P mn j where, P j = K j B j P mn j (c j,ber j) = (13) (14) (15) (c j,ber j) P j mn[pj max,p max ] (16) P max j <f 0j,B j > <f 0j,B j > NI j(f) TL j(f)df (17) NIj(f) TLj(f)df α c j Ω(BER j) (18) =mn k K [ ( ˆRk NI k ) TL k ]. (19) Notatons of class-ndependent relatonshps and constrants: L P = L H P + L F P j + LN P j [bt] s the fxed optmal packet sze, soluton of an offlne optmzaton problem presented n [3], where L H P s the header sze of a packet, whle L F P j s the varable FEC redundancy of each packet from to j. Eelec b = Eelec trans = Eelec rec [J/bt] s the dstance-ndependent energy to transt one bt, where Eelec trans s the energy per bt needed by transmtter electroncs (PLLs, VCOs, bas currents) and dgtal processng, and Eelec rec represents the energy per bt utlzed by recever electroncs. Note that Eelec trans does not represent the overall energy to transmt a bt, but only the dstance-ndependent porton of t. Ej b =2Eelec+P b j/rj b [J/bt] n (10) s the energy to transmt one bt from to j, when the transmtted power and the bt rate are P j [W] and Rj b [bps], respectvely. The second term, P j/rj, b sthedstance-dependent porton of the energy to transmt a bt. P max [W] s the maxmum transmttng power for node. BER =Φ M (SINR) represents the bt error rate, gven the SINR and the modulaton scheme M M, whle η(m) s the spectrum effcency of modulaton M. PER = ψ F (L P,L F P,BER) represents the lnk packet error rate, gven the packet sze L P, the FEC redundancy L F P,and the bt error rate (BER), and t depends on the adopted FEC technque F F. TL j s the transmsson loss (n absolute values) from to j, whch s computed accordng to the Urck model n (1). T ˆN j s the number of transmssons of a packet sent by. The relaton Nj T =(1 PER j) 1, whch approxmates the average number of transmssons such that the packet be correctly decoded at j, assumes ndependent errors among consecutve packets; ths assumpton holds when the channel coherence tme s shorter than the retransmsson tmeout,.e., the tme before retransmttng an unacknowledged packet, whch s the case n UW-ASNs. ˆN Hop j =max ( d N <d j > N, 1 ) s the estmated number of hops from node to the surface staton (snk) N when j s selected as next hop, assumng that the followng hops wll guarantee the same advance towards the surface staton. Ths estmate has three nce propertes: 1) t does not ncur any sgnalng overhead as t s locally computed and does not requre endto-end nformaton exchange, 2) ts accuracy ncreases as the densty ncreases, and 3) as the dstance between the surface staton and the current node decreases. <d j > N, whch we refer to as advance, s the projecton of d j onto the lne connectng node wth the snk. As descrbed n Sect. II-B, we envson that underwater multmeda sensor networks wll need to provde support and dfferentated servce to applcatons wth dfferent QoS requrements, rangng from delay senstve to delay tolerant, and from loss senstve to loss tolerant. Hence, n ths work we consder the followng four traffc classes: Class I (delaytolerant, loss-tolerant), Class II (delay-tolerant,loss-senstve), Class III (delay-senstve, loss-tolerant), and Class IV (delaysenstve, loss-senstve). Whle for loss-senstve applcatons a packet s locally retransmtted untl t s correctly decoded at the recever (or f the maxmum number of retransmssons s reached), for loss-tolerant applcatons packets are transmtted only once on each lnk and are protected unequally, dependng on the mportance of the data they are carryng for correct reconstructon. (addtonal class-dependent constrants) { ˆN j T =1 Class I = 1 ( ) 1 PER ˆNHop j j PERmax e2e,(m) Class II = { T ˆN j =(1 PER j) 1 Class III = Class IV = ˆN j T =1 1 ( ) 1 PER ˆNHop j j PERmax e2e,(m) ( ) + δ(γ) σ q j ΔD (m) ˆQ ˆN Hop j L P R b j j d j q j d j q j ˆN T j =(1 PER j) 1 ( + δ(γ) σ q j ΔD (m) ˆN Hop j ) ˆQ j L P. R b j Notatons of addtonal class-dependent constrants: PERmax e2e,(m) s the maxmum end-to-end error rate for packet m. ΔD (m) = D max ( t (m),now ) t(m) 0 [s] s the tme-to-lve of packet m arrvng at node, whered max [s] s the maxmum end-to-end delay, t (m),now s the arrvng tme of m at, and t (m) 0 s the tme m was generated, whch s tme-stamped n the packet header by ts source. T j = L P /Rj b + T q j [s] accounts for the packet transmsson delay and the propagaton delay assocated wth lnk (, j); to derve the last constrant for Classes III and IV, we consder a Gaussan dstrbuton for T j,.e., T j N (L P /Rj b + T q j,σq 2 j ); for the mathematcal dervaton of the constrant, due to lack of space we refer the nterested reader to [3]. ˆQ j [s] s the network queueng delay estmated by node when j s selected as next hop, computed accordng to the nformaton carred by ncomng packets and broadcast by neghborng nodes. Note that sender optmally decouples the routng decson, whch s based on (7), from the soluton of P cross layer (, j), whose output s the optmal metrc E (j) (or R (j) ), nput of the routng decson tself. Therefore, sender can optmally decouple the cross-layer algorthm nto two sub-problems (to be solved sequentally): 1) Mnmze the lnk metrc E (j) (or maxmze R (j) )for each of ts feasble next-hop neghbors (Algorthm 1 presents a possble space-search approach) (physcal functonaltes); 2) Pck as best next hop that node j assocated wth the best lnk metrc (MAC/ Routng functonaltes). Ths means that the generc node does not have to solve

8 POMPILI and AKYILDIZ: A MULTIMEDIA CROSS-LAYER PROTOCOL FOR UNDERWATER ACOUSTIC SENSOR NETWORKS 2931 a complcated optmzaton problem to fnd ts best route towards a snk. Rather, t only needs to sequentally solve the two aforementoned sub-problems wth no loss of optmalty. The frst sub-problem has a complexty O( S th M F ), where S th, M, and F are the number of dfferent thresholds, modulaton technques, and FEC schemes, respectvely, used n combnaton wth Algorthm 2. The second subproblem has a complexty O( S P N ),.e., proportonal to the number of the sender s neghborng nodes wth postve advance towards the snk. Moreover, ths operaton does not need to be performed every tme a sensor has to route a packet, but only when the channel or the traffc condtons,.e., the structure of the MAI n the neghborhood, have changed. Whle ths cross-layer approach - whch s the soluton of a local optmal problem - does not guarantee global optmalty as a sender does not have global knowledge of the network, t acheves the best possble performance gven the lmted nformaton at the sender. Algorthm 1 Cross-layer Lnk Optmzaton (gven, j, d j ) 1: E mn = [or R max =0] {ntalzaton} 2: for th=1 : S th do 3: for mo=1 : M do 4: for fe=1 : F do 5: 6: (SNR,K, f 0,B) Algorthm 2(d j, = th) PER = ψ fe( L P,L F P (fe), Φ mo (SINR) ) 7: Solve P cross layer, CalculateE (j) (8) [OR R (j) (9)] 8: f (E (j) <E mn) [ORR (j) >R max] then 9: E mn = E (j) [OR R max = R (j) ] 10: (fe,mo,k,f 0,B) =(fe,mo,k,f 0,B) 11: end f 12: end for {end FEC cycle} 13: end for {end modulaton cycle} 14: end for {end SNR cycle} Algorthm 2 Lnk Transmsson (gven d and ) 1: f 0 =argmn f [N(f) TL(d, f)] {optmal f 0} 2: K (0) =[mn f N(f)] TL(d, f 0) {ntalzaton} 3: stop =0,n=0 4: whle (stop == 0) do 5: n = n +1,FndB (n) s.t. K (n 1) N(f) TL(d, f) 6: Calculate SNR (n) from (4) usng K (n 1) and B (n) 7: f (SNR (n) ) then 8: stop =1 9: else 10: K (n+1) =(1+ε) K (n) {ε R + } 11: end f 12: end whle F. Protocol Operaton Algorthm 1 makes use of the soluton of Algorthm 2, whch provdes four communcaton parameters, the three defnng the transmt sgnal (.e., K, f 0, and B), and the assocated estmated SNR at the recever. Algorthm 1 wll use these parameters to fnd the best FEC/modulaton combnaton. Whle some teratons between the two algorthms are needed as they cannot be entrely decoupled, usng ths approach the complexty s reduced whle stll leadng to the optmal soluton of the cross-layer optmzaton problem. Once ths optmzaton problem has been solved at sender, andtheoptmal communcaton parameters (.e., K, f 0, B, M, F, L F P, c ) have been found, randomly accesses the channel by transmttng a short header called Extended Header (EH). The EH s sent usng a common chaotc code c EH known by all devces. Sender transmts to ts next hop j the short header EH. The EH contans nformaton about the fnal destnaton,.e., the surface staton, the chosen next hop j, and the parameters that wll use to generate the chaotc spreadng code of length c for the actual data packet that j wll receve from. Immedately after the transmsson of the EH, transmts the data packet on the channel usng the optmal communcaton parameters set by the cross-layer algorthm. Note that the protocol does not have to send control packets before the actual data packet s transmtted. Ths s because the packet - composed of the extra header EH and the actual data packet (payload plus standard header) - uses a hybrd MAC to access the channel,.e., t smultaneously accesses the channel usng ALOHA-lke MAC (for the extra header EH) and locally adaptng ts power and code length as n standard dstrbuted CDMA MAC schemes (for the data packet). Ths novel approach s motvated by the need to acheve hgh channel utlzaton effcences to compensate for the low-bandwdth shared medum and the huge propagaton delay affectng the underwater envronment (fve orders of magntude larger than n terrestral wreless networks). If no collson occurs durng the recepton of the EH,.e., f s the only node transmttng an EH n the neghborhood of node j, j wll be able to synchronze to the sgnal from, despread the EH usng the common code, and acqure the carred nformaton. Then, f the EH s successfully decoded, recever j wll be able to locally generate the chaotc code that used to send ts data packet, and set ts decoder accordng to the optmal communcaton parameters used by n such a way as to decode the data packet. Once j has correctly receved the packet from, t acknowledges t by sendng an ACK packet to j usng code c A. In case does not receve the ACK before a tmeout T out expres, for delay-tolerant and loss-senstve traffc classes t wll keep transmttng the packet untl a maxmum transmsson number s reached. If sender does not have updated nformaton about the MAI n j, t ncreases the code length every tme a tmeout expres to mprove the probablty that the packet be decoded. III. PERFORMANCE EVALUATION We compare here the performance acheved by our-cross layer soluton aganst that acheved by ndvdual communcaton functonaltes that do not share nformaton and operate n solaton (tradtonal layered approach). We compare results obtaned when the objectve functon of our cross-layer optmzaton problem s ether Objectve 1 (energy mnmzaton) or 2 (throughput maxmzaton). As far as the nteractons between physcal layer functonaltes are concerned, Fg 3 show the energy per bt E (j) [J/bt], transmt power P [db re μpa ], and net bt rate R (j) [kbps] versus dstance d [m] for the proposed cross-layer soluton when both Objectve 1 (OBJ.1) and 2

9 2932 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 9, NO. 9, SEPTEMBER 2010 Energy [J/bt] Transmt Energy vs. Dstance Cross layer (OBJ.1) BPSKco, NO FEC BFSKnc, BCH(63,57,1) 16 QAMco, BCH(63,45,3) 64 QAMco, BCH(63,39,4) Transmt Power [db re μpa ] Transmt Power vs. Dstance Cross layer (OBJ.1) BPSKco, NO FEC BFSKnc, BCH(63,57,1) 16 QAMco, BCH(63,45,3) Net Bt Rate [kbps] Net Bt Rate vs. Dstance Cross layer (OBJ.1) BPSKco, NO FEC BFSKnc, BCH(63,57,1) 16 QAMco, BCH(63,45,3) 64 QAMco, BCH(63,39,4) Dstance [m] Dstance [m] Dstance [m] (a) (b) (c) Fg. 3. Energy per bt E (j) [J/bt] (a), transmt power P [db re μpa ] (b), and net bt rate R (j) [kbps] (c) vs. dstance d [m] for the proposed cross-layer soluton (Objectves 1 and 2) and for four fxed FEC/modulaton combnatons. (OBJ.2) are consdered. The comparson s made aganst the four best fxed FEC/ modulaton combnatons: ) coherent BPSK/NO FEC, ) non-coherent BFSK/BCH(63,57,1), ) coherent 16-QAM/BCH(63,45,3), and v) coherent 16- QAM/BCH(63,39,4). As can be seen, our soluton outperforms competng fxed schemes when ether objectve s selected n terms of both energy and throughput. In partcular, n Fgs. 3(a) and 3(b), the curves assocated wth OBJ.1, representng the transmt energy and power, respectvely, for a payload bt to be successfully decoded at the recever, are always above any other curve assocate wth a fxed FEC/ modulaton combnaton. Moreover, the performance gan of our cross-layer soluton over the best FEC/ modulaton combnaton out of the four consdered ncreases as the dstance ncreases. The same concluson can be drawn lookng at Fg. 3(c), whch reports the net bt rate vs. dstance for our soluton as well as for the best four competng fxed schemes. Agan, the curve depctng the performance of our soluton when OBJ.2 s set as objectve functon of the optmzaton problem outperforms any of the other four curves whchever dstance s consdered. As far as the nteractons between MAC and Routng functonaltes are concerned, Fg. 4 report the average normalzed used energy, the normalzed successfully receved packets, and the average packet delay versus number of sensors. We consdered a varable number of sensors (from 10 to 50) randomly deployed n a 3D volume of 500x500x500 m 3. Performance results refer to the three cases of OBJ.1 and OBJ.2 for our cross-layer soluton, and the case where a CDMA-based MAC [4] and geographcally-based routng [3] run ndvdually. In Fgs. 4(a-b) our cross-layer soluton usng OBJ.1 outperforms the MAC+Routng case (for Class II); n Fg. 4(c) ths s agan the case when OBJ.2 s used (for Class III). These postve results are due to the fact that our soluton jontly optmzes the consdered communcaton functonaltes, thus explotng synerges that lead to mproved end-to-end system performance. Results show that by mnmzng at each node the energy to delver packets (.e., OBJ.1), n the cases n whch the network densty s not too nhomogeneous, the network topology has not very dfferent node degrees, and the traffc patter s not hghly asymmetrc, longer network lfetmes are experenced when our cross-layer soluton s used. Specfcally, the lfetme gan s n the 20 30% range dependng on the number of nodes, beng hgher for larger networks (number of nodes around 50) n whch there s greater flexblty on avalable end-to-end paths. In the other (less common) cases, the maxmzaton of the network lfetme should be acheved not only through energy mnmzaton, but also through load balancng. Ths s due to the fact that n such cases some nodes may be essental for the network to keep beng connected. Hence, a networkng strategy that would only try to save energy may possbly lead to the energy depleton of such nodes, whch n turn could result n a shorter network lfetme. IV. CONCLUSIONS AND FUTURE WORK We explored the nteracton of key underwater communcaton functonaltes and developed a cross-layer communcaton soluton that allows for the effcent utlzaton of the bandwdth-lmted hgh-delay underwater acoustc channel. We showed that end-to-end network performance mproves n terms of both energy and throughput when hghly specalzed communcaton functonaltes are ntegrated n a cross-layer module. As future work, we wll develop ad-hoc schedulng mechansms to smultaneously handle traffc classes wth dfferent QoS requrements and we wll ncorporate end-toend rate control functonaltes to provde far congeston avodance n dynamc condtons. REFERENCES [1] I. F. Akyldz, D. Pompl, and T. Meloda, Underwater acoustc sensor networks: research challenges, Ad Hoc Networks (Elsever), vol. 3, no. 3, pp , May [2] D. Pompl and I. F. Akyldz, A cross-layer communcaton soluton for multmeda applcatons n underwater acoustc sensor networks, n Proc. IEEE Internatonal Conference on Moble Ad-Hoc and Sensor Systems (MASS), Atlanta, GA, Sep [3] D. Pompl, T. Meloda, and I. F. Akyldz, Routng algorthms for delay-nsenstve and delay-senstve applcatons n underwater sensor networks, n Proc. ACM Conference on Moble Computng and Networkng (MobCom), Los Angeles, CA, Sep [4], A CDMA-based medum access control for underwater acoustc sensor networks, IEEE Trans. Wreless Commun., vol. 8, no. 4, pp , Apr [5] M. Molns and M. Stojanovc, Slotted FAMA: a MAC protocol for underwater acoustc networks, n Proc. MTS/IEEE Conference and Exhbton for Ocean Engneerng, Scence and Technology (OCEANS), Boston, MA, Sep

10 POMPILI and AKYILDIZ: A MULTIMEDIA CROSS-LAYER PROTOCOL FOR UNDERWATER ACOUSTIC SENSOR NETWORKS x 10 4 Average Normalzed Used Energy (LP=250Byte) 1 Normalzed Succesfully Receved Packets (LP=100Byte) 12 Average Packet Delay (LP=100Byte) Normalzed Used Energy [J/bt] MAC + Routng Cross layer (OBJ.1) Normalzed Succesfully Receved Packets MAC + Routng Cross layer (OBJ.1) Average Packet Delay [s] Cross layer (OBJ.1) MAC + Routng Number of Sensors Number of Sensors Number of Sensors (a) (b) (c) Fg. 4. (a): Average normalzed energy vs. no. of sensors for Class II (delay-tolerant, loss-senstve); (b): Normalzed successfully receved packets vs. no of sensors for Class II (delay-tolerant, loss-senstve); (c): Average packet delay vs. no. of sensors for Class III (delay-senstve, loss-tolerant). [6] I. Vaslescu, K. Kotay, D. Rus, M. Dunbabn, and P. 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Pompl, A trajectory-aware communcaton soluton for underwater glders usng WHOI mcro-modems, n Proc. IEEE Conference on Sensor, Mesh and Ad Hoc Communcatons and Networks (SECON), Boston, MA, June [12] U. C. Kozat, I. Koutsopoulos, and L. Tassulas, A framework for crosslayer desgn of energy-effcent communcaton wth QoS provsonng n mult-hop wreless networks, n Proc. IEEE Conference on Computer Communcatons (INFOCOM), Hong Kong S.A.R., PRC, Mar [13] A. Lachenmann, P. J. Marrón, D. Mnder, and K. Rothermel, An analyss of cross-layer nteractons n sensor network applcatons, n Proc. Conference on Intellgent Sensors, Sensor Networks & Informaton Processng (ISSNIP), Melbourne, Australa, Dec [14] B. Radunovc and J.-Y. L. Boudec, Rate performance objectves of multhop wreless networks, IEEE/ACM Trans. Moble Computng, vol. 3, no. 4, pp , Oct [15] R. J. Urck, Prncples of Underwater Sound. McGraw-Hll, [16] J. Proaks, Dgtal Communcatons. New York: McGraw-Hll, [17] Y. Sankarasubramanam, I. F. 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Wreless Commun., vol. 2, no. 6, pp , Nov Daro Pompl joned the faculty of the Department of Electrcal and Computer Engneerng at Rutgers, The State Unversty of New Jersey, as Assstant Professor n Fall He receved hs Ph.D. n Electrcal and Computer Engneerng from the Georga Insttute of Technology n June 2007 after workng at the Broadband Wreless Networkng Laboratory (BWN-Lab) wth Prof. I. F. Akyldz. In 2005, he was awarded Georga Insttute of Technology BWN-Lab Researcher of the Year for outstandng contrbutons and professonal achevements. He had prevously receved hs Laurea (ntegrated B.S. and M.S.) and Doctorate degrees n Telecommuncatons Engneerng and System Engneerng from the Unversty of Rome La Sapenza, Italy, n 2001 and 2004, respectvely. Hs research nterests nclude ad hoc and sensor networks, underwater acoustc communcatons, wreless sensor and actor networks, and network optmzaton and control. He s author and co-author of many nfluental papers n these felds. He s n the edtoral board of the journal Ad Hoc Networks (Elsever), and on the techncal program commttee of several leadng conferences on networkng. He s also a member of the IEEE Communcatons Socety and the ACM. Ian F. Akyldz s the Ken Byers Dstngushed Char Professor wth the School of Electrcal and Computer Engneerng, Georga Insttute of Technology and Drector of Broadband Wreless Networkng Laboratory. He s the Edtor-n-Chef of Computer Networks, Ad Hoc Networks, andphyscal Communcaton Journal (all wth Elsever). Dr. Akyldz s an IEEE Fellow (1995) and an ACM Fellow (1996). He served as a Natonal Lecturer for ACM from 1989 untl 1998 and receved the ACM Outstandng Dstngushed Lecturer Award for Dr. Akyldz receved the 1997 IEEE Leonard G. Abraham Prze award (IEEE Communcatons Socety) for hs paper enttled Multmeda group synchronzaton protocols for ntegrated servces archtectures, publshed n the IEEE Journal on Selected Areas n Communcatons (JSAC) n January Dr. Akyldz receved the 2002 IEEE Harry M. Goode Memoral award (IEEE Computer Socety) wth the ctaton for sgnfcant and poneerng contrbutons to advanced archtectures and protocols for wreless and satellte networkng. Dr. Akyldz receved the 2003 IEEE Best Tutoral Award (IEEE Communcaton Socety) for hs paper enttled A survey on sensor networks, publshed n IEEE Communcaton Magazne, n August Dr. Akyldz receved the 2003 ACM SIGMOBILE award for hs sgnfcant contrbutons to moble computng and wreless networkng. Hs current research nterests are n cogntve rado networks, sensor networks, and wreless mesh networks.