Aqua-TUNE: A Testbed for Underwater NetworksZheng Peng, Son Le, Michael Zuba, Haining Mo, Yibo Zhu, Lina Pu, Jun Liu and Jun-Hong Cui

Department of Computer Science and Engineering, University of Connecticut, Storrs, Connecticut 06269Email: {zhengpeng, sonle, michael.zuba, haining.mo, yibo.zhu, lina.pu, jul08003, jcui}@engr.uconn.edu

Abstract—In recent years, new challenges and emerging appli-cations have inspired increasing research interests in the area ofunderwater networks. However, field experiments are expensiveand not all the research work can be evaluated in real worldscenarios in a timely fashion. This motivates our interest ondeveloping an affordable, accessible and user friendly platformfor conducting field experiments. Aqua-TUNE, the Testbed forUnderwater NEtworks, is presented in this paper. It can beused to experimentally evaluate the algorithms and protocolsdeveloped for underwater networks in real world scenarios. Ourexperience with the testbed shows that it could be a valuable toolto encourage rapid progress in underwater networks.

I. INTRODUCTION

Underwater networks are wireless communication systemsthat are generally characterized by expensive equipment, highmobillity rates, sparse deployment and various energy require-ments [1]. The devices, which are often battery powered,can consist of autonomous underwater vehicles (AUVs) likevessles, sensors, network nodes and a variety of other devicesranging from computational to communication purposes. Thefundamental differences between underwater networks andterrestrial networks are within the communication channel andsignal characteristics. Unlike in ground-based networks, highfrequency electromagnetic waves do not work well in the waterdue to high absorption. For this reason, acoustic communica-tion becomes the most commonly used method. However, dueto the unique characteristics of acoustic channels, underwaternetworks face challenges at almost every layer of the protocolstack [2].

In the past few years, the area of underwater networkshas spurred a big wave of research efforts in both academiaand industry. Many algorithms and network protocols havebeen introduced. However, a majority of the work remainsin the stage of computer simulation due to many technicaland non-technical issues and challenges. In order to effectivelyevaluate the performance of underwater networks, experimentsare expected to be done in real world scenarios. Constructinga user friendly infrastructure is also critical for those whowish to efficiently develop, deploy and debug applications inrealistic underwater environments.

In this paper we will discuss our field testbed system, Aqua-TUNE, a Testbed for Underwater NEtworks, that is developedfor deployment and operation in lake based environments.Our system consists of both hardware and software modulesthat are easy to install and assemble while providing a lot offreedom for developers and engineers.

The testbed has a set of ready-to-deploy network nodes anda hybrid wireless network system to connect them together.

In terms of hardware, each network node consists of a sur-face platform, an electronic compartment and communicationdevices. The surface platform includes a small kayak, ananchor and a homemade system for easy deployment. Theelectronic compartment hosts most of the electronic devicessuch as a micro-controller, a radio frequency (RF) modem,a GPS receiver and batteries. The communication devicesinclude an acoustic modem, a transducer and an antenna. Thenetwork system is a hybrid of a multiple frequency shift keying(MFSK) underwater acoustic network, a frequency hoppingspread spectrum (FHSS) network and a direct sequence spreadspectrum (DSSS) network. The underwater data communica-tion is done via the underwater acoustic link while the abilitiesof online remote control and monitoring are convenientlyprovided by the other two networks. Additionally, dependingon the configurations and workload, the entire system canoperate from 70 hours to 7 days in a row without rechargingthe batteries.

The software system is based on a Linux implementationof Aqua-Net [3]. It is a generic architecture for underwatersensor networks aiming at delivering a powerful networkingsolution kit for underwater network researchers. It is designedin a way that provides robustness for users and easiness forprotocol or application developers.

Various algorithms and protocols are constantly being devel-oped in the laboratory environment and analysis often ends atthe simulation step. However, simulations can never fully con-sider the special characteristics of an environment, especiallythe aquatic world. The development of an underwater networktestbed is a costly, time consuming, and a labor intensiveprocess. It is often the case that most researchers do not havethe resources to effectively develop their own field testbed. Thegoal of Aqua-TUNE is to provide this affordable, accessible,and standardized platform to bridge the gap between modelingand simulation and the field experience.

The rest of the paper is organized as follows. Relatedwork in the development of underwater testbed systems isintroduced in Section II. The motivation of Aqua-TUNE, itscomponents, and its capabilities are presented in Section III,Section IV and Section V, respectively. Preliminary experi-mental results are presented in Section VI. Conclusions aredrawn and future work is presented in Section VII.

II. RELATED WORK

There has been limited progress in developing underwaternetwork testbeds. Researchers that have been developing thesesystems are mostly still in preliminary stages instead of a

final complete system. In this section we will introduce a fewtestbed systems that we are aware of in the field.

Goodney et al. [4] have made some progress on developing aflexible, configurable underwater sensing and communicationtestbed in Marina del Rey, California. The current system con-sists of two prototype testbed nodes which are designed basedupon existing underwater modems developed by WHOI [5].Future plans for this work are to address communicationlimitations while creating a more flexible node design. Thisincludes developing a software-based acoustic signal generatorto support a wide array of signal processing algorithms andcommunication protocols and to allow easy user integrationand testing of new algorithms.

Feng et al. [6] recently started work on an underwatermobile sensing network (UMSN) testbed. This testbed consistsof a surface station laptop computer, three AUVs and an RFmodem-based communication system to mimic underwateracoustic communication. The surface computer provides agraphical user interface (GUI) for human operators to easilyand remotely control each AUV via a wireless local areanetwork (WLAN). However, the pitfall of this work is thefact that no real acoustic communication is used; it is merelysimulated by RF modems.

B. Chen et al. [7] provide an out-of-water testbed thatemulates underwater acoustic communications using varioushardware modules. Their testbed consists of WHOI Micro-Modems, an audio interface to process audio signals, a gumstixmotherboard, and two desktop PCs. The main goal of thistestbed is to provide an emulator environment to evaluatethe performance of underwater vehicle formation and steeringalgorithms.

Aqua-Lab [8] is an underwater acoustic sensor networklab testbed developed by the Underwater Sensor Networks(UWSN) lab at the University of Connecticut. The goal ofAqua-Lab is to bridge the gap between real system implemen-tation and modeling/simulation environments. The design ofAqua-Lab is based around being able to appropriately mimicreal-world environments and hardware testing while providingan easy method for researchers to implement and use theirown protocols and tests. A web-based GUI is also providedfor easy access and configuration. This testbed provides re-searchers the ability to test, evaluate, and compare variousnetwork algorithms and protocols in a less-expensive lab basedenvironment while providing results that have been proven tobe consistent with real-world testing.

A good testbed system requires a good and user friendlysoftware developing platform. Aqua-Net [3] is an efficient,extendable, user friendly, and upgradable architecture frame-work for underwater sensor networks. It provides a layeredstructure while allowing for cross-layer optimization. Thislayered structure approach allows for easy integration ofnew solutions or protocols from multiple research groups orindustry companies. Additionally, the cross-layer design inAqua-Net is enabled by a translucent vertical layer that isaccessible for all protocols and applications. Aqua-Net hasproven itself to be a valuable networking solution kit that helps

to facilitate UWSN research and application development.Our literature review suggests that developing underwater

testbeds is still in its infancy. Existing technology may not besuitable to appropriately develop these underwater systems.We hope to provide new insight and progression in the devel-opment process by introducing Aqua-TUNE, our underwaterlake testbed system.

III. MOTIVATIONS AND GOALS

Recent years have witnessed a rapid growth in the areaof underwater networks. Building a cheap and efficient fieldtestbed for underwater networks is imperative. This is dueto the the difficulties in accurately modeling the specialcharacteristics of the water environment and underwater net-works in the lab. Without the help of field experiments, puretheoretical analysis and simulation face limitations. Moreover,new research topics are emerging from problems identifiedduring field experiment. A constraint posed by these problemsis that they can only be observed in real world environments.Furthermore, in academic studies, there are inconsistencies inthe different assumptions that researchers make due to theirperceptions of the underwater environment. This makes itdifficult to fairly compare and evaluate the performance ofalgorithms and protocols. This problem calls for the abilityto provide a standard field testbed platform to evaluate theseprotocols fairly.

Unfortunately, much research work in this area is still donein the lab and is rarely tested in the field. This is the resultof the high cost in conducting full scale field tests. With alarge scale network, node deployment and recovery can betime consuming and labor intensive. The costs of renting orusing a boat for deployment is also expensive. These issuesprovide motivation to develop an affordable, accessible andconvenient testbed for the research of underwater networks.The purpose of Aqua-TUNE is to provide a standardizedplatform for testing and to bridge the gap between modelingand simulation and the real world field experience.

Our current network testbed is designed for research pur-poses. The major goal is to build a platform in a realenvironment that can demonstrate the capacity of our un-derwater network. Our testbed design targets on low cost,simple to build modules and parts that are largely availableand convenient to deploy. The testbed should be small foreasy transportation, assembly and deployment. Since networkexperiments often involve a number of network nodes, eachindividual node should be of low cost to fit into an averagebudget. The components should also be easy to obtain forquick replacement.

Since our lab does experiments frequently, we focused onlakes and reservoir environments in our local area. Althoughthe shallow water adversely affects the acoustic communi-cation, lakes are very accessible with no interruption frommaritime activity. The lakes are usually calm and provide a lessharsh environment, making it perfect for our water operations.

IV. TESTBED OVERVIEW AND COMPONENTS

Aqua-TUNE consists of a number of network nodes. Eachnetwork node has a buoy, an electronic device compartment,an acoustic modem, a RF modem with an antenna and a GPSreceiver. The surface buoy can be used to carry the electronicsystem. This setup avoids the cost of waterproofing electronicswhen we deploy the acoustic modem devices underwater.The device compartment has a micro-controller which is usedfor computation and decision making. It also hosts the RFmodem and antenna in order to monitor the system statusand perform remote control operations. The GPS receiveris mainly used to provide the applications with geographicinformation which could be helpful in some scenarios. Theacoustic modem and its transducer are submerged in thewater to conduct underwater communications. Fig 1 shows acomplete node of Aqua-TUNE deployed in Mansfield HollowLake, Connecticut, USA. Each network node of Aqua-TUNEcosts less than 1,000 US dollars. In this section, we willdiscuss the system components in details.

Fig. 1. A Testbed Node in Operation

A. Buoys

In order to design a testbed for field experiments, severalthings need to be taken into consideration. The first is wherethe testbed will be deployed. The location of deployment willdecide the size of each individual node in the testbed. Largerbuoys are more stable and better suit the open seas where thewind and waves could be strong. However, they are not onlymuch more expensive to build but also more difficult to deploythan smaller buoys. Smaller buoys are easy to handle, savingcosts on heavy duty lifting equipment and ship time. They area better choice for lake tests launched by a smaller group ofpeople.

Another factor that affects design choice is how long thesystem is supposed to be deployed in the field. For longterm operations, people typically select moored buoys whichare anchored at fix location. Some buoys are even equippedwith solar panels to power their electronic devices. Many ofthese buoys also have special paint or coating that providechemical bonds with the buoy for high durability. Short termdeployments typically don’t need these sophisticated designs.The ease of handling would be preferable in these casesbecause it allows the system to be more quickly deployed orre-deployed when needed.

We compared various buoys from different manufacturesand concluded that many do not meet our requirements asdescribed in Section III. The cost of these buoys were tooexpensive or their size was too small. Additionally, manyof them take a long time to build. In the end, instead ofusing expensive buoys, we decided to use small scale kayaks.These kayaks can be purchased off the shelf and allow foreasy transportation. The particular model we chose is madeof plastic. This light-weight kayak can support up to 140 lbsof equipment. It has plenty of open space that can be usedfor storage of electronic devices. There are holes and hookson the sides of the kayak such that we can easily attach ropesand an anchor to it. We can conveniently deploy the networknodes by towing the kayaks to the locations of our choice. Inthis way, we can further reduce costs.

B. Micro-controllers

One of the goals of our research is to build a smartautonomous network system. Users only need to focus onapplications, and different network protocols can provide theservices needed by them. Each network node in the systemshould be able to make decisions based on available infor-mation and its own capacity to achieve the desirable goalsdefined by the researchers and developers. This is why micro-controllers are introduced into the testbed. They are the brainsin most of the decision making process. In order have a bettertestbed, a better brain is preferable.

Underwater sensor network is a challenging area. Advancedalgorithms are proposed to reduce energy consumption butrequire more computation power from processors and supportfrom advanced operating systems. When designing the testbed,we try to keep these broader perspectives in mind and supportany potential application that could benefit by our designchoice. The micro-controller we used is based on MarvellPXA270 with XScale microprocessor core. It is the fifthgeneration of the ARM architecture. Our system board has64 MB RAM, 16 MB flash memory and is running at 400MHz main frequency. It is capable of doing computationalextensive tasks such as data encryption and decryption. Withrelatively small form factor, the micro-controller offers a widerange of functions including microSD, Bluetooth and 802.11gwireless interfaces, USB, 10/100 Ethernet and RS232. As aresult, the testbed can host a variety of user applications. Ourmeasurements present that the peak power consumption isabout 1.5 W. We consider this to be affordable when the peak

power consumption of a typical acoustic modem can reach tensof watts [9], [5]. With techniques such as frequency scalingand duty cycle, this number can be further reduced to around50 mW.

Our system is running Embedded Linux, which is theoperating system designed and optimized for devices thathave limited resources, such as battery life, computationalpower and storage capacity. It is an open source platformthat could be customized by users to suit the need of aspecific application. Having an operating system can be costly.However, we argue that the introduction of an operating systemcan greatly reduce the overheads in research and development.As a variant of Linux, embedded Linux provides similar, if notthe same, features and has abundant resources. Researchers donot need to invent every wheel they need. Instead, there are alot of programming libraries and tools available to use rightout of the box. In short, with Embedded Linux, our testbedbecomes an advanced, customizable, developer friendly andever-developing platform that is ideal for developing under-water network applications.

C. Acoustic Modems

The current underwater communication method is mainlyacoustic communication. There are several commercial andnon-commercial acoustic modems available from differentmanufactures or institutions [9], [10], [11], [12]. The de factohardware interface between the acoustic modem and the hostmachine is an RS-232 serial port. With the same hardwareinterface, different acoustic modems communicate with themicro-controller in different ways. In the Aqua-Net networkarchitecture, different drivers could be developed for differentacoustic modems. The physical layer details are, by Aqua-Net design, transparent to various protocols such that networkprotocol researchers do not need to understand the details ofthe physical layer. On the other hand, some hardware specificfeatures are available to support cross-layer optimization forbetter system performance.

For our testbed, we use the underwater acoustic modemfrom a company located in Massachusetts, USA. This com-pany has years of experience in acoustic communication andtheir modems are used in worldwide subsea applications. Eachof the testbed nodes are equipped with an acoustic modemwhich is a completely self contained 2000-meter depth ratedsubsea modem with a built-in omnidirectional transducer. Thespecifications show an acoustic bit rate up to 2, 400 bps usingmultiple frequency shift keying (MFSK). Depending on thechannel condition, the communication range can reach 6 kmat some baud rates. In general, our experience shows that withlower acoustic bit rates, the modem works better in adversechannel conditions.

D. Radio Frequency Modems

Radio Frequency (RF) modem is a key component withinthe testbed, which helps build a monitoring and remote controlsubsystem and allows users to interact with the protocolsrunning on the micro-controllers conveniently.

1) RF Modem Selection: The RF link quality heavilydepends on the performances of the RF modems and the RFantennas. In our testbed, we used a long range 900 MHzindustrial Ethernet RF modem. The first reason for choosingthis modem is that it works at 900 MHz, which is a stableand free public frequency in the US. The second reasonis that it uses frequency hopping spread spectrum (FHSS)modulation which is considered reliable. Another reason isthat this modem has a dependable built-in ethernet protocolstack. This makes it possible to use a large number of existingsoftware or protocols such as SSH and FTP.

2) Antenna Selection: For antenna selection, We use FriisTransmission Equation to estimate the appropriate antennagain we need in the field test.

Pr

Pt= GtGr

(λ

4πR

)2

(1)

In Eq. 1, λ is the wave length, Pt is the transmission powerof the RF modem and Pr is its receive sensitivity. Then, giventhe transmit and receive antenna gain, Gt and Gr, we cancalculate the transmission range R.

Fig. 2. RF Modem Tests

According to our calculation, we picked a fiberglass omni-directional wireless antenna with a 6 db gain. Theoretically,it can reach a transmission range of 80 km. We tested it inthe town of Vernon, Connecticut, USA, as demonstrated inFig. 2, where the RF link is further challenged by obstaclesand interferences. Our test results showed that this antenna canwork reliably over 3.57 km while download speed can reach100 KB/s and the packet loss rate was almost 0. Additionally,in all the tests, power consumption was always stable at 0.96W, which means that the batteries can support our RF modemsfor almost a week without recharging. Though winds, hills andradio interference are degrading its performance, it still offers

satisfactory communication range. Taking all the above factorsinto consideration, the antenna we select should be reliableenough for our lake experiments.

E. Batteries

In the field experiments, all the electronic devices arepowered by batteries. If the micro-controllers are the brainsof the testbed, then the batteries are the heart of the system.Careful study on the power consumptions of the testbed andthe provision of a good power supply solution are the keys tosuccessful field experiments.

We first measured the power consumption of the micro-controller. During the test, all peripheral devices, e.g. aEthernet card, are connected and a program is developedto keep the micro-controller busy for testing purposes. Ourmeasurements indicate that the micro-controller’s maximalpower consumption is about 1.6 W. We also measured thepower consumption of the RF modem. As mentioned in aprevious section, at a distance of 3.57 km and a downloadspeed of 100 KB/s, the power consumption is about 0.96 W.Among all electronic devices, the acoustic modem has thehighest power consumption. According to the user manual, thepeak sending power is 20 W, almost an order of magnitudehigher than the total of all other equipment. Since the modemcarries its own battery pack which is stated to provide weeksof operating life time, we do not consider it when designingthe power supply solution.

In Aqua-TUNE, we use two sealed lead-acid rechargeablebatteries to power the whole system. Sealed lead-acid batteriesare popular because it has a mature and robust design. Thesebatteries can also work reliably in tough environments. This isnot the case for more expensive Lithium batteries that couldexplode in some conditions. Sealed lead-acid batteries area dependable and low cost solution for our field testbed ofunderwater networks. The total energy the two batteries canoffer is 184 WHr. This is enough for the whole system to run atpeak speed (i.e. 100% CPU usage) for 71 hours, almost threedays. Under normal system workload, the system can workfor 92 hours. We consider this to be sufficient for a lake test.With some simple frequency scaling or duty cycle techniques,the overall system life time can easily get much higher. Sincethe kayak has plenty of space for electronic devices, we donot see any limitation on doubling or tripling the number ofbatteries on each network node. The power supply solution ofAqua-TUNE can meet most of the experiment requirementseasily.

V. TESTBED CAPABILITIES

Aqua-TUNE provides various capabilities to the testbedusers. These capabilities, including networking modules, syn-chronization, localization, link control and power control, areessential to our research. With all these capabilities, Aqua-TUNE becomes an ideal platform for conducting experimentsof underwater networks.

Radio

Frequency

Antenna

Wi-Fi

Router

RF Link

(900 MHZ)

RF Modem

(Subscriber)

RF Modem

(Access Point)

Acoustic

Modem

Micro-

Controller

Wi-Fi Link

(2.4 GHZ)

Fig. 3. Monitoring and Remote Control Subsystem

A. Monitoring and Remote Control

Via monitoring and remote control, users can monitor theoutput of the running protocols in real time, change settingssuch as protocol parameters, upload new versions of protocolsonto the micro-controllers and download log files with theprocedures and results of all the tests reported in details.

As shown in Fig. 3, the monitoring and remote controlsubsystem is composed of two wireless networks, namely a 2.4GHz direct sequence spread spectrum (DSSS) Wi-Fi wirelessnetwork and a 900 MHz FHSS network. The former one isused by experiment operators, while the latter one is used bythe network nodes. The Wi-Fi network consists of multiplelaptops serving as monitoring and remote control terminalsas well as a Wi-Fi wireless router. An RF modem with anattached antenna, serves as an Access Point that is connectedto a Wi-Fi router via an ethernet port. All the other RF modemsfunction as subscribers, which are connected to the micro-controllers via ethernet ports. Similar to the Access Point, aRF antenna is attached to each subscriber. All the RF modemsincluding the Access Point and the subscribers form a RFwireless network. In this system, the Wi-Fi router and theAccess Point work as the corresponding gateway for each ofthese two wireless networks and therefore all the nodes inthese two networks can talk to each other. In this way, theterminal laptops can freely interact with the micro-controllers.

Compared to other systems, the biggest advantages ofour monitoring and remote control system is that multiplelaptops can talk to one micro-controllers at the same timeand that a single laptop can simultaneously communicate withmultiple micro-controllers. This feature is perfectly suitable forreal time program monitoring, control and even debugging.Additionally, since the Wi-Fi network is already mature androbust, as long as we can guarantee a stable and fast RF link,the communication between laptops and micro-controllers canbe reliable and efficient.

The monitoring and remote control subsystem has beenproven to be working reliably and efficiently in our field testand has provided great support for our program monitoring,online debugging and data analysis.

B. Network Modules

The unique characteristics of underwater sensor networkssuch as long propagation delay, limited bandwidth and higherror probability have posed significant challenges in designinga reliable and efficient network structure. First, how to allowmultiple devices to effectively and fairly share a commonchannel is a big issue. Schedule based methods may not workwell due to the high uncertainty in the underwater environ-ment. Carrier sensing based approaches also lack efficiencysince propagation delay can be close to or even larger thanthe packet duration in underwater networks. Second, routingmethods must adapt swiftly to the dynamic topology changesin the network and cannot incur too much communicationoverhead. Finally, the error prone underwater acoustic channelmakes reliable data transfer a desirable feature in a lot ofapplication scenarios.

To address the above challenges, we have implementedsome compelling protocols at each layer of the underwatersensor networks. For the Medium Access Control (MAC)layer, we implemented handshake based Slotted-FAMA [13]and random access based UW-Aloha [3], which is an Aloha-like approach. Both of these two approaches are specificallydesigned for the underwater environment and have takenunderwater communication characteristics into consideration.On the routing layer, we implemented static routing and adistance vector based dynamic routing method, which canquickly respond to the topology changes in the network.We have also implemented a reliable data transfer schemeUW-RDT using sliding window and selective repeat on thetransport layer, upon which we further built a reliable filetransfer program for the application layer.

All the protocols mentioned above are implemented usingAqua-Net [3], a layered underwater network protocol stackincluding physical layer, MAC layer, routing layer, transportlayer and application layer. Aqua-Net provides a set of socketsbased user-friendly APIs serving as programming interfaces.Using Aqua-Net, a protocol developer can easily and seam-lessly plug in one protocol running as a single layer ormultiple protocols running on different layers. In this way, onecan efficiently test the performance of an individual protocolor a combination of multiple protocols. Besides, Aqua-Netprovides APIs or configuration interfaces which allows usersto dynamically configure network topology and transmissionpower on the fly. Furthermore, Aqua-Net has implementeddrivers for a couple of popular acoustic modems and provideswell formatted APIs, which saves developers from the troubleof digging into hardware details on the physical layer.

C. Localization

Our experience shows that knowing where our networknodes are is important. In some extreme weather, whendeployed in the sea, a buoy could drift miles away fromthe original location. If the buoy can provide its geographiclocation, it would be much easier to recover the buoy. Locationinformation is also requested by a range of applications, suchas estuary monitoring and pollutant tracking. For underwater

networks, geographic routing protocols, such as VBVA [14],require location information to efficiently route the networktraffic to the destination for multi-hop networks.

Our testbed provides geographic information using theGlobal Positioning System (GPS). Each of the network nodesconnects to a GPS receiver via a USB connection. The GPSreceiver is small, cheap, USB powered and easily replace-able. We have made a customized USB driver for the GPSreceiver for our testbed system. By using the GPS receiver,an open source software GPSd [15] and a software modulewe developed, the geographic information can be shared byall applications. With a more advanced GPS receiver, such asa Garmin 18x LVC [16], not only location information canbe obtained, but also the system time of our network nodes,which can also be synchronized to the satellites to obtain betteraccuracy.

D. Synchronization

Time synchronization is another important service whichmany applications benefit from or require. For example, inorder to calculate the end to end delay of a particular protocolfor underwater networks, the system time on both the sourceand the destination should be synchronized. Moreover, manylocalization and MAC protocols , such as [17], [13] assumethe availability of the time synchronization service.

In our testbed, we provide different methods of synchroniza-tion services. Since we have constructed an 802.11 wirelessnetwork for our testbed, the most straight forward and ac-curate way is to use the Network Time Protocol (NTP) [18].Nowadays, most of our computers are synchronized to Internettime servers. We can arbitrarily elect any computer that isconnected to the testbed wireless network to be the time server.All network nodes in our testbed can then adjust their timeperiodically according to the time server via NTP.

The second method is to utilize the GPS. Most GPSreceivers use NMEA (National Marine Electronics Associ-ation) sentences which also report time information. Manysimplified commercial GPS receivers can only reach secondlevel accuracy. However, with some GPS models described inlater part of Section V-C, millisecond level accuracy can alsobe achieved.

When the previous two methods fail, it does not meanour testbed loses time synchronization. We have developeda software module to provide synchronization service in thissituation. A random network node will be selected as the timeserver and all other nodes will adjust their time accordingto the server time. However, if the time on the server is notaccurate, the time of the whole testbed will suffer from thesame error. Fortunately, with the current electrical system,the time offset and skew is small. In our experiments, wealso find the time to be accurate enough for our performancemeasurements, e.g. calculating end to end delay.

E. Link Control

In field experiments, it is usually desirable to test a protocolin multiple topologies with a single deployment. Otherwise,

one has to redeploy the network nodes which is often costlyand involves a lot of labor work. According to our experience,redeploying a network of 6 nodes in open sea may take half aday to complete because of the time spent on lifting the nodesoff the water, navigating to the new positions and putting themback to the water. In other words, this choice should only beconsider when there are sufficient resources (i.e. time, manand money).

To better understand how the link control works, oneneeds to differentiate the physical topology and the networktopology. The physical topology is determined by the actualdeployment, which is not easy to chance due to the reasonsjust mentioned. Once the deployment is finished and the trans-mitting power of the acoustic modem is decided, the actualnetwork topology is fixed. However, with limited resources,it is often desirable to have multiple network topology forprotocol tests. We then come up with the idea of emulatingnetwork topologies by a link control module.

Taking this issue into account, an essential part of Aqua-TUNE is the capability of configuring various topologieswithout redeployment. Different network topologies can beemulated by our link control module. In our testbed, thismodule is implemented by having a component in the physicallayer, which takes in a given topology according to con-figurations and filters packets based on that topology. Thiscomponent also provides APIs such that users can change thetopology on the fly, which makes it possible to emulating linkfailure.

An important point to make regarding the link controlmodule is that it is different from a static routing protocol. Itworks more like a firewall by placing a packet filter betweenthe acoustic modem and Aqua-Net. The packet filter on a nodeis given the list of direct neighbors that it is configured tocommunicate with by the people who design the experiments.It then checks every incoming packets and only pass the onesthat are from a neighbor in the list; otherwise, it will drop thepackets. This means that the packet filter is not part of Aqua-Net and only serves experiments because it knows about thetopology beforehand.

F. Power Control

Along with the above feature, the testbed also includes amodule which can choose the optimal transmitting power foreach node based on a given topology. This module is neededto minimize power consumption and collisions in the network.For example, if a node is configured to talk with its two nearestneighbors, it may not need to use the highest power level.In this way, it can prevent the acoustic signal from reachingundesired nodes and causing collisions.

An important issue relating to this module is to preventcollisions introduced by this module because probing packetsneed to travel among network nodes to determine the appro-priate power level. In the power control module, this issue isdealt with by a classical term: spanning tree. First, each nodeconstructs a spanning tree of the given topology whose root isalways the node with the smallest ID. This node then selects

its power level and triggers its neighbor in the spanning treeone after another. When a node has finished this process, ittriggered its parent node to continue with another neighbor.

A node chooses its power level in a binary search principle.The available power levels are divided into halves, with themiddle power level as the pivot. The node first uses the middlepower level and sends probing packets to neighbor nodes. Ifall these nodes can be reached, this node will try finding alower power level in the lower half. Otherwise, it tries withthe upper half of power levels. In this way, a node needs atmost dlog2ne tries to determine the appropriate power level,where n is the number of power levels.

VI. PRELIMINARY EXPERIMENTS AND RESULTS

In a recent field experiment, we deployed four nodes in theMansfield Hollow Lake, Connecticut, USA. Fig. 4 illustratesthe actual location of the network nodes based on the GPSinformation collected during the experiment. The distancesfrom node 5 to node 2, 3, 6 are 198, 169 and 356 metersrespectively. As a case study, we will present the results ofUW-Aloha, Slotted FAMA and a dynamic routing protocolwe have implemented.

In all these tests, a Poisson traffic generator ran at the appli-cation layer which sent out data packets in such a way that theinter-departure time between two consecutive packets followsthe Poisson distribution. The parameter of the distribution (λ)is called the sending rate of the data generator.

Fig. 4. Field Test Deployment

A. UW-Aloha and Slotted FAMA

UW-Aloha was tested with both static routing and dynamicrouting in the network layer. Two tests were conducted withstatic routing, in which the Poisson traffic generator sent outdata at 0.1 and 0.2 packets/s, respectively. Three nodes, 3, 5

and 6, were involved in these tests, in which the latter twonodes were configured as traffic sources sending data to theremaining one. In the test with dynamic routing, four nodes 2,3, 5 and 6 were involved, in which data was sent from node2 to node 3 at 0.05 packets/s and node 5 and 6 served as therelays.

It is clear from Fig. 5 that the throughput of UW-Aloha withdynamic routing is, in general, lower than with static routing.This is because part of the bandwidth must be allocated torouting packets. When the sending rate is high, it is likelythat data packets collide with routing packets or with oneanother, as a result, negatively affecting the performance ofUW-Aloha. However, also from Fig. 5, we can observe thata higher sending rate can improve the performance of UW-Aloha. Nevertheless, since acoustic modems cannot send dataarbitrarily fast and higher sending rate causes more collisions,the throughput of UW-Aloha is actually bounded.

Slotted FAMA was tested with static routing in a similarsetting. Two 40-minute long tests were carried out with thesending rate of 0.1 and 0.2 packets/s, respectively. The resultsare also shown in Fig. 5.

0

100

200

300

400

500

600

0 200 400 600 800 1000 1200 1400 1600

Throughput (bps)

Experiment time (seconds)

UW-Aloha+dynamic routing (λ=0.05pkt/s)Slotted FAMA+static routing (λ=0.10pkt/s)Slotted FAMA+static routing (λ=0.20pkt/s)

UW-Aloha+static routing (λ=0.10pkt/s)UW-Aloha+static routing (λ=0.20pkt/s)

Fig. 5. Throughput of Different Protocols

From Fig. 5, one can obverve that the throughputs yieldedby two different sending rates are very close. Indeed, thesesending rates far exceeds the capacity of the acoustic modem,and therefore many packets are queued in the MAC layer. Inother words, the MAC layer is always working with a non-empty packet queue.

In addition, Fig. 5 showed that the throughput in the first fewminutes was very high. This fact is rooted from our selectionof time point 0 as the time that the first packets was received.As more data was received, the effect of this choice becomesfaded, the throughput converges to a constant value.

B. Dynamic Routing

A dynamic routing protocol was also implemented andtested on the testbed. As shown in Fig. 4, four nodes are

deployed in the lake. They are configured to form a diamond-shaped topology. In this two-hop network, node 2 is electedto be the data source and node 3 is the destination node. Weassume that the obstacles between node 2 and node 3 block thesignals such that they can not reach each other directly. In thiscase, intermediate nodes 5 and 6 served as relays forwardingpackets to their final destination. Two possible routes from thesender to the receiver are 2 - 6 - 3 and 2 - 5 - 3. When thenetwork faces unpredictable failures, e.g. either node 5 or 6stops working, the dynamic routing protocol will automaticallyadapt to this change by delivering data packets through thealternative route.

A node using dynamic routing periodically broadcasts itsrouting table to neighbors to inform that it is still alive. In ourexperiment, this period, called update period, was 10 minuteslong.

The test for dynamic routing ran for 30 minutes and thesending rate was 0.05 packets/s. The result showed that ittook 134 seconds for all the routing tables to get stable.Additionally, at this sending rate, totally 62 routing packetswas transmitted to maintain the routing tables of all networknodes. There are 65 packets can be transferred successfullyfrom node 2 to node 3. On average, each node needs 16routing packets to detect the routes through the network. Ourexperience shows that this sending rate is not high especiallyfor a two-hop network; in fact, appropriate higher sending ratewill reduce the number of routing packets needed per each datapacket.

In the middle of the test, we turned off one of the relaynodes to test if the other route can be detected. Since in ourdeployment node 2 is slightly closer to node 6 than node 5, itselected node 6 as the next hop to node 3, the destination node.We deliberately disabled node 6 to break this route. Node 2then has to find out another way to reach node 6. In thisexperiment, it took 98 seconds for node 2 to find the alternativeroute. Only a few packets are lost due to the “failure” of node6 and therefore the overall performance of the network is notaffected much, as shown in Fig. 5. The length of the routingre-establish time depends on the update rate of the dynamicrouting protocol. When the update rate is too high, routingpackets dominate network traffic, although it provides moretimely updates of the network dynamics. This fact poses aquestion on choosing the appropriate update period. Generally,a more dynamic environment needs a shorter update period.

VII. FUTURE WORK AND CONCLUSIONS

In this paper, Aqua-TUNE, a field testbed for underwatersensor networks, is presented. The testbed has a network ofacoustically connected nodes. Each node contains a floatingplatform for electronic devices, an acoustic modem, a RFbased monitor and remote control system and the softwareplatform that accommodates the protocols building an un-derwater network. Aqua-TUNE offers a variety of servicesthat open many potentials to the researchers and applicationdevelopers. The testbed is designed to be affordable, accessibleand easy to handle. Aqua-TUNE can be used to experimentally

evaluate algorithms and protocols designed for underwaternetworks in real world scenarios. It will be a valuable toolfor future advances of underwater network research.

While working with the University of Connecticut’s MarineScience Department, we will plan to set up a testbed in LongIsland Sound, an estuary of the Atlantic Ocean between thestate of Connecticut and Long Island. This will present achallenge as there is much more maritime activity in thisarea and the underwater acoustic channel could change dras-tically. The goal will be to bring Aqua-TUNE into a tougherenvironment and observe if the current system is robustenough to handle the new challenges. We want to test ouralgorithms and protocols for underwater networks and evaluatetheir performance in the sea. During this process, it is alsopossible to identify new problems that are worth studying. Thebasic design of Aqua-TUNE will not be changed. Therefore,testbed users do not have to change their protocols from thelake testbed environment. In other words, the same softwaredeveloped by the researchers can be used in the new platformwithout any modification. We will focus on replacing thecurrent kayaks with bigger and more robust buoys, load thesystem with more batteries for longer system life time andconsider waterproofing alternatives for the electronic devicecompartment. The enhanced Aqua-TUNE will not only benefitthe research of underwater networks but also help marinescientists in various applications.

ACKNOWLEDGMENT

This work is supported in part by the US National ScienceFoundation under CAREER Grant No. 0644190, Grant No.0709005, Grant No. 0721834, Grant No. 0821597, Grant No.1018422 and the US Office of Navy Research under YIP GrantNo. N000140810864.

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