Smart Plankton: a nature inspired underwater wireless sensor network

Davide Anguita, Davide Brizzolara, Alessandro Ghio, Giancarlo ParodiDIBE - Department of Biophysical and Electronic Engineering

University of GenoaVia Opera Pia 11A, 16045 Genoa (Italy)

{Davide.Anguita,Davide.Brizzolara,Alessandro.Ghio, Giancarlo.Parodi }@unige.it

Abstract

In the last years with the flourishing of the WSN (wire-less sensor network) paradigm, ignited by DARPA fundedUC Berkeley ”Smart Dust” project, the monitoring and ex-ploration of the terrestrial enviroment has greatly improved.The acquatic world, which covers more than the 70% of theearth, instead, has been largely unaffected by the WSN revo-lution due to the difficulty of transferring most of the know-how developed for terrestrial and aerial systems and de-vices to their underwater counterparts. The aim of this ar-ticle is to propose a new generation of UWSN(UnderwaterWireless Sensor Network), called Smart Plankton, by get-ting inspiration from marine biology and acquatic micro-organisms.

1. Introduction

The progress and new developments in Wireless Sen-sor Networks paradigm was clearly addressed by the SmartDust project [25], which explored whether an autonomoussensing, computing, and communication system can bepacked into a cubic-millimeter mote (a small particle orspeck) to form the basis of integrated, massively distributedsensor networks. This research led to new opportunities toobserve and act on the world by using a large number ofsmall sensing self-powered nodes, which gather informa-tion or detect special events and communicate in a wirelessfashion.

Transferring this paradigm to Underwater Wireless Sen-sor Networks (UWSN), largely unaffected by WSN revolu-tion, is a challenge that can open great opportunities [2][18].As in many cases, where ICT got inspiration from nature,interesting solutions can be found by getting inspirationfrom marine biology and acquatic micro-organism. In par-ticular, the most common organism of the acquatic world[9] includes zooplankton and phytoplankton.

The potential applications of this new generation of de-vices are related both to long-term acquatic monitoring andshort-term acquatic monitoring [27]. They include: marinebiology, deep-sea archaeology, pollution detection (chem-ical, biological and nuclear), ocean circulation modelingfor improved understanding of climate systems, improvedweather forecast, fish stock dynamics and spread of contam-inants, monitoring of ocean currents and winds, detectingclimate change, understanding and predicting the effect ofhuman activities on marine ecosystems, disaster preventiondistributed tactical surveillance [7], reconnaissance, target-ing and intrusion detection systems, underwater natural re-source discovery, distributed tactical surveillance, assistednavigation and mine reconnaissance, etc. [2] [1].

One of the traditional approaches for underwater moni-toring is to deploy and then to recover underwater sensorsthat record data during the monitoring mission, but this pro-cedure does not allow to perform a real-time monitoring,with on-line system reconfiguration and failure detectionand it is limited as concern the storage capacity [1].

A more recent technique for aquatic applications is theuse of static underwater sensor nodes, placed on the seafloor or attached to pillars or surface buoys, in conjunctionwith an underwater unmanned vehicle for data muling andand network maintenance [12], with a good computationalpower and of large size.

In general, terrestrial networks emphasize low cost nodes(around US$ 100), dense deployments, multihop commu-nication, short-range communication [19]; by comparison,typical underwater wireless networks today are typically ex-pensive, (US$ 10k or more) sparsely deployed (a few nodes,placed kilometers apart), typically communicating directlyto a base-station and sometimes are based on the use of un-derwater manned or unmanned vehicles [11].

The nature inspired approach proposed in this article,in comparison with the common strategy, discusses pos-sible solutions for an underwater self-organizing networkcomposed by a relatively large number of innovative nodes

(Smart Plankton), equipped with sensors for monitoring,surveillance and underwater control.

This article is organized in Sections which focus themost important challenges and possible solutions for a na-ture inspired UWSN:

• implementation of the single node and its characteris-tics in order to operate in a very harsh enviroment;

• communication between the nodes and the problem ofnetworking because, in comparison with ground-basedsensor networks, mobile UWSNs cannot employ radiowaves since they do not propagate well in underwaterenvironments.

• energy scavenging in order to allow a long life to thenetwork;

• shoal intelligence for computational cooperation be-tween the individuals.

Figure 1. Examples of plankton structure(pictures from PlanktonNet)

2. Network node (Smart plankton) individualbody

In order to develop an UWSN it is necessary to built anartefact that can survive, communicate, sense and cooperatein the underwater harsh and demanding environment wherehigh pressure, corrosion, fouling and bioerosion from colo-nizing organisms are threats to structure integrity and func-tionality.

The inspiration to the rich inventory of plankton adapta-tions [10][9] can help in the construction of underwater de-vices and lead to a new approach for building the individualnode (Smart Plankton) of an UWSN addressed to solve theproblems caused by the underwater environment. Planktonconsists of drifting organisms inhabiting the water columnin oceans and lakes. which rely on large-scale circulationfor horizontal transport, although many of them are motile(Figure 1). Plankton range in body size from sub-micron(bacteria and viruses) to meters (some jelly-fish) but typi-cally most plankton are within 1 to 1000 µm. The range insize and taxonomic affinity have led to evolution of a greatdiversity of adaptations to ensure survival and reproductionin the water-column. In particular, as concern the UWSNindividual body, it is necessary to focus attention on motil-ity and computational capability.

2.1 Motility

In order to perform the movement of each individualbodies innovative solutions can be proposed like, for ex-ample, thermal expansion of solids and liquids and com-pression under pressure, such as in sperm whale (Figure 2)which uses spermaceti, a semiliquid, waxy substance formovements and stability. The use of pumping of water, infact, used in many underwater vehicles, is not feasible,

because it is energy consuming and requires complicatedmechanical solutions. The method selected is, obviously,influenced by the requirements regarding operation of thedevice (e.g. depth) and by knowledge of daily/seasonalchanges of environmental conditions. The movement ofSmart Plankton is influenced also by the body surfaceequipped with the required sensors, transducers and devicesimplementing the interface between the Smart Plankton in-dividual and the external world.

2.2 Computation capability

The Smart Plankton brain and nervous system can be de-signed as a reconfigurable digital system, allowing the in-dividuals adaptation to the changing environmental stimuliand objectives and, at the same time, containing the a-prioriknowledge and behaviour rules, coded by design. The ner-vous system has to target the interfacing, collection, fusion

Figure 2. Internal structure of a sperm whale(pictures from Wikipedia)

and control of the external environment through the sens-ing and communicating devices. The use of a reconfig-urable architecture, through the use of HW/SW co-designtechniques, is proposed to satisfy peak computational orcognitive demands with a limited energy consumption, sobalancing the need of computation (sense, communicate,etc.) with the survivability constraints (energy foraging andstorage). Algorithms recently developed for computationalembedded intelligence (e.g. kernel methods for embeddedand pervasive systems [4][3]) can be a good choice, rang-ing from supervised to unsupervised methods up to rein-forcement learning technologies for acquiring or improvingintelligent behaviour during the entire life span of individu-als.

3. Communication link among underwater de-vices

One of the challenging aspect in order to built an ef-ficient UWSN is the underwater wireless communication[23]. High frequency radio waves are strongly attenuated inwater, especially in electrically more conductive salt water,and the available radio modules such as Bluetooth or Wire-less LAN (802.11) operate in the gigahertz range, around2.4 GHz.

The alternative is suggested by living organisms which

use both acoustical and optical communication [9] .Acoustic underwater communication is a classical ap-

proach but it can be considered still an open problem dueto the particular environment condition: the signal prop-agation speed in an underwater acoustic channel is about1.5× 103 m/s, which is five orders of magnitude lower thanthe radio propagation speed in open air, almost the speed oflight in vacuum (3× 108 m/s). The available bandwidth ofunderwater acoustic channels is limited due to absorptionand dramatically depends on both transmission range andfrequency. According to [16], no research nor commercialsystem can exceed 40 km kb/s as the maximum attainablerange x rate product.

In addition to the physical layer, nowadays there are alot of studies for adapting and extending the existing link-layer, routing and transport layer protocols to the physi-cal properties of the underwater scenarios in order to per-form a good acoustical communication. The use of soft-ware modem, that rely on software for implementing themodulation, demodulation, filtering, and synchronizationfunctionality among a network devices can be an adapt-able and flexible solution. Moreover artefacts intelligencecan be exploited, as in Cognitive Radio [13], to select thebest communication strategy and channel. The softwaremodems should operate in conjunction with acoustic hard-ware, namely a microphone and a speaker and elastic latexmembranes will be used to waterproof each device. Newalgorithm can be developed such as the hardware-friendlySVM described in [4] addressed problem of equalizing anonlinear communication channel.

Figure 3. Light absorption in water (picturefrom M.Chaplin, Water Structure and Sci-ence)

The alternative and more innovative method of opticalcommunication is suggested by the natural world (e.g. quo-

rum sensing through bioluminescence in plankton shoals[10]) and can allow the development of a high rate and lowcost communication link among devices.

Light is strongly scattered [8] and absorbed by water[22], so a possible solution is to replace the traditional in-frared communication [21], influenced by water turbidity,with LEDs and phototransistors considering the minimumabsorption wavelength window of the water where SmartPlankton is operating [15].

Experimental tests (Figure 3) have shown that the betterwavelenght lies around 420 nm (blue-violet wavelengths)and that the value changes in presence of turbidity [22]. Anexperimental testbench, such the one depicted Figure 4 atour Department can be used in order to test underwater op-tical communication between devices.

Figure 4. Experimental set-upfor testing opti-cal communication underwater

The development of an optical communication systembased on LEDs [17] can be effective because of low powerconsumption, low operating voltage, long lifetime, low costand it can establish high rate communication (up to 320Kb/s), as showed in [12] [23] [24], between fixed nodes andan autonomous underwater vehicle.

New and customized signal processing mechanisms canbe developed with a new physical layer implementationwhich can be inspired, for instance, to the 802.11a physicallayer implementation [20] but replacing infrared with bluelight, targeting a careful balance between communicationquality, bit rates and processing complexity.

4. Energy scavenging and production

Energy is a vital aspect in the development of underwa-ter devices [14] and it is possible to consider to followingsolutions:

• mechanical energy can be scavenged and each devidecan supply power indefinitely from a self containedmechanism. Mechanical energy occurs in the form ofdisplacements and movements of the Smart Planktonand there is also the potential to exploit pressure differ-entials that occur with varying depth. The amount ofmovement and expected pressure differentials will bedetermined in order to calculate how much energy canbe scavenged given the size constraints of the plank-ton. The inertial system will be designed to maxi-mize the energy coupled from these displacements tothe transduction mechanism that converts the mechan-ical energy into electrical. Typically, this transduc-tion is achieved using electromagnetics, electrostaticsor smart materials such as piezoelectrics [26].

• the extraction of energy can be based on pressure dif-ferentials by using the cyclical contraction/expansionof a pressurized bladder. The amount of energy avail-able with this approach will depend upon the size ofthe bladder and the magnitude and frequency of thepressure variations.

• energy can be generated by using electrochemicallyactive bacteria which have been recently discoveredand have the property to oxidize organic matter andrelease the electron to an electrode. This has some def-inite advantages over the use of a chemical catalyst, asbacteria can sustain themselves and recover after inad-vertent poisoning [5].

5. Shoal intelligence

Smart Plankton can be based on collective behaviour, thewireless network should be able to perform complex tasksonly by cooperation of the individuals; this approach can beconsidered as an application of Swarm Intelligence model[6] for dealing with the peculiarities of the harsh underwaterenvironment and develop a new model (Shoal Intelligence).The focus is on:

• the possibility of support and even increase the embod-ied intelligent properties of individuals by the shoaldistributed sensing, computation, cognition and com-munication collective capabilities

• the implementation of the cooperative foraging: thestudy and simulation of mechanisms for cooperativeforaging and energy consumption behaviour with theaim of survivability optimization

The shoal configuration should take into account differ-ent solutions based on specific application such as the dif-ferent number of nodes, a specific geographical deploymentscheme and the on-board sensors.

6. Conclusions

In this article are shown new challenges and possibilitiesin the development of a new generation of nature inspiredUWSN. The described problems look for innovative ideasand new solutions in different areas of investigation: sin-gle node hardware and software implementation, communi-cation, networking and computational cooperation betweendevices, etc.

7. Acknoledgements

Many of the ideas in this paper stem out from discussionswith: H.P.Schwefel (Dept.of Electronics Systems), Aal-borg University, DK; S.P.Beeby, (Dept. of Electronics andComputer Science), Southampton Univ., UK; L.Rowinsky,(Dept. of Underwater Technology), GdanskUniv. of Tech.,PL; P.Jonsson, (Marine Biological Laboratory), GoteborgUniv., SE.

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