PERFORMANCE OF TCP CONGESTION CONTROL IN UAV NETWORKS OF VARIOUS RADIO PROPAGATION MODELS

Transcription

1 PERFORMANCE OF TCP CONGESTION CONTROL IN UAV NETWORKS OF VARIOUS RADIO PROPAGATION MODELS Jun Peng Elecrical Engineering Deparmen, Universiy of Texas Rio Grande Valley, Edinburg, Texas, USA ABSTRACT Unmanned aerial vehicles (UAVs) have recenly become popular for boh recreaional and commercial use and UAV neworks have hus sared o arac he aenion of researchers in area of he compuer communicaion and neworking. One imporan opic in UAV neworks is congesion conrol because congesion causes packe losses and delays which resul in he wase of all ypes of nework resources such as bandwidh and power. Alhough here are sudies on he performance of TCP congesion conrol in wireless neworks, hey focus on erresrial neworks of wo dimensions in general. In his paper we sudy he performance of TCP congesion conrol in hree dimensional UAV neworks. In paricular, we invesigae how TCP congesion conrol performs in such ype of nework using various radio propagaion models. Our daa on he average flow hroughpu, packe delay, and packe loss rae in UAV neworks show ha TCP congesion conrol improves he nework performance of UAV neworks in general, bu i faces challenges when he link losses become severe. Our sudy hus shows ha invesigaion on new congesion conrol schemes is silled needed for he emerging UAV neworks. KEYWORDS Congesion conrol, TCP, unmanned aerial vehicles (UAV), proocols, radio propagaion 1. INTRODUCTION Unmanned aerial vehicles were mainly used by he miliary bu hey have become popular for boh civil and commercial use recenly because relevan hardware and sofware has become more advanced bu coss less a he same ime. For example, various ypes of UAVs can be purchased for jus hundreds of dollars in he marke and hey come equipped wih advanced sofware and hardware. Some of hese UAVs have high qualiy cameras preinsalled on hem and people in all professions sar o ake advanage of hem. Some examples are realor using hem o ake aerial images and videos of properies for sale and enhusiasic amaeur phoographers aking picures of heir favorie scenes from he sky. The use of UAVs for aking aerial images and videos no only saves he huge cos of rening a plane or helicoper bu also are faser o deploy and more friendly o he environmen. Oher areas where UAVs have been widely invesigaed and used include law enforcemen, propery surveillance, search and rescue in disasers, scienific research and oher applicaions where erresrial access is limied or impossible [1]. UAVs will evenually need o communicae wih each oher for all kinds of reasons such as coordinaion and collaboraions. When here are more and more UAVs in he sky, i will become necessary for hem o avoid collision among hemselves. Alhough equipping hem wih radars can help, he exra cos and weigh may make hem no ideal for such a purpose. Some UAVs have already had GPS unis insalled on hem and hus heir locaion informaion may be used for DOI: /ijcnc

2 collision avoidance if he UAVs can communicae wih each oher in he sky in real ime. There will also likely be some applicaions ha need a big number of UAVs working ogeher o achieve a goal. For example, when a large geographical area needs o fully surveilled wihou inerrupion for a period of ime, one of he bes soluion would be a group of UAVs collaboraing wih each oher on he job and relaying daa back o he Inerne. UAV neworking will hus become more imporan in he near fuure. Researchers in he area of compuer communicaion and neworking have been invesigaing various opics a all layers of UAV neworks. Asadpour e al. [2] sudied he performance of IEEE n inerfaces in UAV neworks and hey found ha n performed poorly in highly mobile scenarios. Cai e cal. [3] proposed a medium access conrol (MAC) proocol for UAV adhoc neworks wih fullduplex radios. They proposed a oken-based echnique o updae informaion in he nework for efficienly handling he high mobiliy of UAVs. Ollero e al. [4] presened a plaform ha enables auonomous aerial vehicles o cooperae wih ground wireless sensor-acuaor neworks. Alshbaa e al. [5] used he approach of cross layer design o deal wih he high dynamics in UAV neworks. Alshbaa e al. [6] also proposed an adapive medium access conrol proocol for UAV neworks using direcional anennas. Gu e al. [7] proposed a rouing scheme for muli-layer ad hoc neworks ha use UAVs in heir backbones. Gu e al. [8] also presened a muliple access proocol for such ype of nework. One imporan opic in UAV neworking ha has no been widely invesigaed is congesion conrol. UAVs are widely used for capuring video and image daa in all ypes of applicaions. When hose daa need o be sen over a UAV nework, here will be heavy raffic on many links in he nework which will likely cause congesion. If congesion occurs bu is no deal wih in a UAV nework, i will resul in packe losses and delays and hus grealy degrade he performance of he nework. The TCP congesion conrol is widely used in boh wired and wireless neworks. Alhough here is work invesigaing he performance of TCP congesion conrol in wireless neworks [9], [10], [11], mos invesigaion focused on erresrial neworks having wo dimensions in general. In his paper we sudy he performance of TCP congesion conrol in UAV neworks of hree dimensions. I is well known ha link losses in wireless neworks cause performance problems for TCP congesion conrol. We hus invesigaed UAV neworks having various link models in our sudy, which are he free space model, he wo-ray ground model, and he shadowing model. Our conclusion is ha TCP congesion conrol can improve he nework performance of UAV neworks, bu when he link losses are severe, i faces significan challenges. I is hus sill needed o design effecive congesion conrol schemes for he emerging UAV neworks. The res of he paper is organized as follows. Secion 2 inroduces he basic idea of TCP congesion conrol. Secion 3 presens he hree radio propagaion models ha we use in our sudy. Secion 4 shows our resuls on he performance of TCP congesion conrol in UAV neworks of various link models. Secion 5 summarizes our findings. 2. TCP CONGESTION CONTROL TCP congesion conrol is based on he approach of addiive-increase muliplicaive-decrease (AIMD) rae conrol, as shown in Figure 1 where he congesion window basically deermines he rae of he TCP connecion. TCP congesion conrol does no reply on he nework for assisance in is rae conrol. Insead, i infers he congesion saus in he nework by monioring he packe losses ha a TCP connecion experiences. When here are no packe losses, TCP increases is rae linearly, which is o explore for free bandwidh ha migh be available on he pah of he connecion. When a packe loss even is deeced, TCP cus is rae by half o alleviae he congesed saus on is pah. If no more packe losses are deeced afer he rae cu, i sars o 2

3 increase is rae linearly again, since raffic on he connecion s pah is dynamic and free bandwidh may become available any ime. This AIMD approach has been proven effecive in wired neworks where congesion causes he mos packe losses. Figure 1. The AIMD approach of congesion conrol [12] When he TCP proocol is used in wireless neworks, is congesion conrol faces he challenge of link losses caused by link impairmens such as inerference and fading. Since TCP congesion conrol inerpres all losses as being caused by congesion, TCP cus is rae by half whenever a packe loss even is deeced, be i caused by congesion or link impairmens. Depending on he characerisics of he link impairmen in quesion, he decrease of he TCP rae may be helpful or harmful. If he link impairmen is severe and lass long, he reducion of TCP rae may acually help he siuaion because he effecive bandwidh of he affeced link would have decreased acually. However, when he link impairmen is low in severiy and shor in duraion, he halving of TCP rae may resul in a much lower connecion hroughpu han ha he pah can suppor. Emerging UAV neworks have hree dimensions in heir node deploymen and hus have more link complexiy han wo dimensional erresrial wireless neworks. I is herefore necessary o invesigae how TCP congesion conrol would perform in UAV neworks. 3. THE THREE RADIO PROPAGATION MODELS In his secion we inroduce he hree radio propagaion models we use in our sudy. As inroduced earlier, link losses pose challenges o TCP congesion conrol. Differen link models inroduce differen link characerisics in UAV neworks The Free Space Propagaion Model The free space radio propagaion model assumes, as is name indicaes, ha he ransmier and he receiver are in free space wihou obsacles. The propagaion formula is as follows [9]: Pr Ar A = (1) P d 2 λ 2 3

4 where P r is he signal power a he receiving anenna, anenna, A is he effecive area of he receiving anenna, r P is he signal power a he ransmiing A is he effecive area of he ransmiing anenna, d is he disance beween he ransmiing anenna and he receiving anenna, and λ is he wavelengh of he signal. When we have an isoropic anenna, he effecive area is λ / 4π. Equaion 1 hus becomes: P r P 2 λ = (2) 2 ( 4πd ) In a general case where we have an anenna gain ha is no 1 for boh he ransmiing anenna and he receiving anenna, Equaion 1 becomes: P r P 2 λ = G G (3) r 2 ( 4πd ) where G is he anenna gain of he ransmiing anenna and receiving anenna. G r is he anenna gain of he Noe ha Equaions 1 o 3 only apply, in general, under he following condiion [9]: 2 2a d (4) λ where a is he larges linear dimension of eiher of he anennas The Two-Ray Ground Propagaion Model The wo-ray ground propagaion model [10] assumes ha here are wo signal pahs from he ransmier o he receiver. One is he direc line-of-sigh pah while he oher is he reflecion pah from he ground. The formula is as follows: Pr P 2 2 hr 4 h = G G (5) r d where h is he heigh of he ransmiing anenna and h r is he heigh of he receiving anenna. Noe ha Equaion 5 applies under he following condiion: 4πh hr d (6) λ 4

5 3.3. The Shadowing Model Due o mulipah propagaion effecs, he received power a a receiving anenna is no a deerminisic funcion of he communicaion disance as shown in he wo models inroduced earlier. Insead, he received power flucuaes as a random variable. The shadowing model [10] beer reflecs his characerisic of he received signal power han he oher wo models inroduced earlier. The pah loss is usually expressed in db as follows in he he shadowing model: d ( β db d (7) 0 [ P r d) Pr ( d ] = 0 ) 10 log + X db where d 0 is a reference disance, β is he pah loss exponen, variable having a zero mean and a sandard deviaion of shown in Tables 1 and 2, respecively. 4. SIMULATION RESULTS δ db X db is a Gaussian random. The ypical values of β and δ are Afer inroducing TCP congesion conrol and he hree radio propagaion models ha we use in our sudy in preceding secions, in his secion we invesigae how TCP congesion conrol performs in UAV neworks of various link models. The ns2 neworking simulaion plaform [15] does no fully suppor he simulaion of hree dimensional neworks. In our sudy we hus modified he ns2 package for simulaing hree dimensional UAV neworks. The hree dimensional es bed has he same size for is widh, lengh, and heigh, which is 500 meers. UAVs are configured o fly freely in his defined space of hree dimensions following he random waypoin model. The UAVs in he es bed are configured o have he IEEE air inerface using is defaul seings in he simulaor. During each simulaion some UAVs se up TCP connecions wih some oher UAVs a random imes. Rouing in he es bed is done by he DSR proocol [16]. Table 1 Typical value of β in differen environmen Environmen β Oudoor, free space 2 Oudoor, shadowed urban area In building, line-of-sigh In building, obsruced 4-6 Table 2 Typical value of δ in differen environmen Environmen δ Oudoor 4-12 Office, hard pariion 7 Office, sof pariion 9.6 Facory, line-of-sigh 3-6 Facory, obsruced 6.8 5

6 The es bed used in our simulaions has fify UAV nodes flying in i. We varied he number of TCP flows in he nework for each radio link model. In paricular, we varied he number of TCP flows in he es bed from 10 o 35 for each model. In each simulaion we colleced daa o calculae he average hroughpu of he TCP flows, he average loss rae of he TCP packes, and he average delay of he TCP packes in he nework. The resuls are shown in Figures 2 o 10. Figure 2. The average TCP flow rae for he free space model Figure 3. The average TCP packe delay for he free space model 6

7 Figures 2 o 4 show he resuls for TCP flows in he UAV nework using he free space link model. Figure 2 presens he average TCP flow rae in he nework versus he number of TCP flows in he nework. As menioned earlier, he number of TCP flows varies from 10 o 35 in our simulaions. There are wo lines in he figure. One is for he TCP proocol wih is congesion conrol enabled, while he oher is for he TCP proocol wih is congesion conrol disabled. As shown in he figure, he average TCP flow rae, in general, increases firs wih he increase of he number of TCP flows in he nework and hen sars o decease as he number of TCP flows increases furher. This rend is rue for boh cases shown in he figure, wih congesion conrol and wihou congesion conrol. However, one hing is obvious in Figure 2 is ha when he TCP congesion conrol is disabled for he flows in he nework, he average TCP flow rae is significanly lower. Therefore Figure 2 shows ha TCP congesion conrol does improve he nework performance in he case of our UAV nework wih free space link loss model. Figure 4. The average packe loss rae for he free space model The resuls in Figure 2 are corroboraed by he resuls shown in Figures 3 and 4. Figure 3 shows he average packe delay in he nework using he free space link model. The average package delay, in general, increases wih he number of TCP flows in he nework because he raffic load is higher when here are more TCP flows in he nework. Moreover, when he congesion conrol of TCP is disabled, he average packe delay is much higher han ha when he congesion conrol is enabled. These delay resuls hus corroborae he hroughpu resuls shown earlier. Figure 4 presens he average packe loss rae for TCP flows in he nework using he free space link model. As shown in he figure, he packe loss rae, in general, increases when here are more TCP flows in he nework because a higher raffic load resuls in more and severer congesion evens in he nework. As in he case of average packe delay, he average packe loss rae is much higher when he TCP congesion conrol is disabled in he nework. These packe loss resuls hus also demonsrae ha TCP congesion conrol does improve he nework performance in a UAV nework where he free space link model is used, as he flow hroughpu and packe delay resuls show earlier. 7

8 Fig. 5. The average TCP flow rae for he wo-ray ground model Fig. 6. The average packe delay for he wo-ray ground model Figures 5 o 7 show he same kinds of resuls for he TCP flows in he UAV nework as hose in he previous hree figures, bu he wireless link model in he nework has changed o he wo-ray ground model inroduced earlier. As shown in Figure 5, he average TCP flow rae increases firs and hen decreases as he number of TCP flows in he nework increases from en o hiry five, which is similar o he rend shown in Figure 2. Addiionally, he average flow rae is much higher when he TCP congesion conrol is enabled in he nework, which is also similar o wha shown Figure 2. These hroughpu resuls are also corroboraed by he packe delay and loss resuls presened in Figures 6 and 7, respecively. Figure 6 demonsraes ha when TCP 8

9 congesion conrol is disabled, he average packe delay becomes much higher as compared ha when he TCP congesion conrol is enabled. In addiion, Figures 7 presens ha when he TCP congesion conrol is disabled, he average packe loss rae is much higher han ha when i is enabled. Therefore, in he case of he UAV nework using he wo-ray ground link model, TCP congesion conrol sill significanly improves he performance of he nework. Figure 7. The average packe loss rae for he wo-ray ground model Figures 8 o 10 presen he average flow hroughpu, packe delay, and packe loss rae, respecively, for he case where he shadowing link model is used in he UAV nework. Alhough hese resuls sill demonsrae ha TCP congesion conrol improves he performance of he nework in general, he improvemen becomes much less significan as compared wih ha in he oher wo cases of link models, he free space loss model and he wo-ray ground model. As shown in Figure 8, he average flow rae of TCP flows in he nework follows he same rend as ha in he oher wo cases. However, he average flow rae in he case of disabled TCP congesion conrol is very close o ha in he case of enabled TCP congesion conrol. Similarly, he average packe delay and loss resuls in Figures 9 and 10, respecively, show ha he performance improvemen generaed by TCP congesion conrol is much smaller as compared wih hose shown in he wo earlier cases of he free space loss model and he woray ground model. I hus demonsraes ha when he link losses are severe in an UAV nework, TCP congesion conrol may face significan challenges. In summary, TCP congesion conrol can improve he nework performance of an UAV nework, bu i faces significan challenges when he link losses in he nework become severe. I is herefore imporan o invesigae more effecive congesion conrol schemes for emerging UAV neworks. 9

10 Figure 8. The average TCP flow rae for he shadowing model Figure 9. The average packe delay for he shadowing model 10

11 5. CONCLUSION In his paper we sudy he performance of TCP congesion conrol in UAV neworks using various link models. Alhough earlier sudies show ha TCP congesion conrol may face challenges in wireless neworks, hey are mainly done for wo dimensional wireless neworks. Wih UAVs becoming more and more popular for boh recreaional and commercial applicaions, more research effors are needed in he area of hree dimensional wireless neworks. We invesigaed hree dimensional UAV neworks using hree link models which are he free space model, he wo-ray ground model, and he shadowing model. In paricular, we sudied how TCP congesion conrol impacs on he nework performance in such ype of nework. Our resuls on average flow hroughpu, packe delay, and packe loss rae comprehensively show ha TCP congesion conrol improves, in general, he nework performance of an UAV nework. However, when he link losses become severe, TCP congesion conrol faces significan challenges in UAV neworks. I is herefore needed o develop new congesion conrol schemes for emerging UAV neworks. Figure 10. The average packe loss rae for he shadowing model ACKNOWLEDGEMENTS The auhors would like o hank everyone who offered suppor o his projec and he publicaion of is resuls. 11

12 REFERENCES [1] T. H. Cox, C. J. Nagy, M. A. Skoog, and I. A. Somers, Civil UAV Capabiliy Assessmen, NASA, [2] M. Asadpour, D. Giusiniano, K. A. Hummel, and S. Heimlicher, Characerizing N Aerial Communicaion, in Proceedings of he Second ACM MobiHoc Workshop on Airborne Neworks and Communicaions, 2013, pp [3] Y. Cai, F. Yu, J. Li, Y. Zhou, and L. Lamon, Medium Access Conrol for Unmanned Aerial Vehicle (UAV) Ad-Hoc Neworks Wih Full-Duplex Radios and Mulipacke Recepion Capabiliy, Vehicular Technology, IEEE Transacions on, vol. 62, pp , Jan [4] A. Ollero, M. Bernard, M. La Civia, L. van Hoesel, P. Marron, J. Lepley, and E. de Andres, AWARE: Plaform for Auonomous self-deploying and operaion of Wireless sensor-acuaor neworks cooperaing wih unmanned AeRialvehiclEs, in Safey, Securiy and Rescue Roboics, 2007, IEEE Inernaional Workshop on, Sep 2007, pp [5] A. Alshbaa and L. Dong, Adapive MAC proocol for UAV communicaion neworks using direcional anennas, in Neworking, Sensing and Conrol (ICNSC), 2010 Inernaional Conference on, April 2010, pp [6] A. Alshbaa and L. Dong, Cross layer design for mobile Ad-Hoc Unmanned Aerial Vehicle communicaion neworks, in Neworking, Sensing and Conrol (ICNSC), 2010 Inernaional Conference on, April 2010, pp [7] D. Gu, G. Pei, H. Ly, M. Gerla, and X. Hong, Hierarchical rouing for muli-layer ad-hoc wireless neworks wih UAVs, in MILCOM 2000, vol. 1, 2000, pp [8] D. Gu, H. Ly, X. Hong, M. Gerla, G. Pei, and Y.-Z. Lee, C-ICAMA, a cenralized inelligen channel assigned muliple access for muli-layer ad-hoc wireless neworks wih UAVs, in Wireless Communicaions and Neworking Confernce, 2000, IEEE, vol. 2, 2000, pp [9] G. Holland and N. Vaidya, Analysis of cp performance over mobile ad hoc neworks, Wirel. New., vol. 8, no. 2/3, pp , Mar [10] M. Gerla, K. Tang, and R. Bagrodia, Tcp performance in wireless muli-hop neworks, in Mobile Compuing Sysems and Applicaions, Proceedings. WMCSA 99. Second IEEE Workshop on, Feb 1999, pp [11] G. Xylomenos, G. C. Polyzos, P. Mahonen, and M. Saaranen, Tcp performance issues over wireless links, IEEE Communicaions Magazine, vol. 39, no. 4, pp , Apr [12] Kurose and Ross, Compuer Neworking - A Top-Down Approach, Pearson, [13] H. T. Friis, A noe on a simple ransmission formula, in Proceedings of he I.R.E. and Waves and Elecrons, 1946, pp [14] T. S. Rappapor, Wireless Communicaions, Principles and Pracice, Prenice Hall, [15] The nework simulaor - ns-2. [Online]. Available: hp:// [16] D. B. Johnson, D. A. Malz, and Y.-C. Hu, The Dynamic Source Rouing Proocol for Mobile Ad Hoc Neworks (DSR), IETF Inere draf,draf-ief-mane-dsr-10.x, July AUTHOR Jun Peng received his Ph.D. degree from he Deparmen of Elecrical, Compuer & Sysems Engineering a Rensselaer Polyechnic Insiue, Troy, New York, Unied Saes. He is currenly an associae professor a he Elecrical Engineering Deparmen of Universiy of Texas Rio Grande Valley, Edinburg, Texas, Unied Saes. His research ineress are in compuer and communicaion neworks. 12