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4. References [1] LabVir. Virtual Distributed Laboratory forOceanographic Research. [2] R. Boza. “Sistema de adquisición de datosoceanográficos (SADO)” hubo-CSIC. March2000. [3] E. Trullols, J. Sorribas, J. del Río, C. Samitier.,A. Manuel., R. Palomera, “A Virtual DistributedMeasurement System”, IMTC03, Vail, Colorado,USA, 2003. [4] E. Trullols, J. del Río, J. Sorribas, C. Samitier,A. Manuel. “A Virtual Real Time DistributedLaboratory” SCI03, Orlando, Florida, USA. 2003. [5] Several authors. MarTech, Vilanova i laGeltrú, Spain, 2005

Figure 2. A GPS-GSM prototype

Network Management for Marine Sensor NetworksJ. Sorribas (1), NE. ApellidosTrullols (2), NJ. Del Rio (3), A. Manuel

(1) Unidad de Tecnología Marina. Paseo Marítimo 37-49. 08003 Barcelona932309500 sorribas@cmima.csic.es

(2) Universitat Politècnica de Catalunya, Av Victor Balaguer s/n, 08800 Vilanova i la Geltrú

1. IntroductionCommunication networks for connectingheterogeneous systems are going to play a keyrole in the development of future large dataacquisition systems projects in marine science(some of them have already become a reality),particularly in Oceanographic ObservationSystems.

In these scenarios, many technological challengesarise that can be approached either improvingeach of the individual network elements separately(data, sensors, communication protocols, physicallayer, etc..) or managing the system as a whole.The purpose of this paper is to make a firsttheoretical approach to the use of networkmanagement techniques in “Marine SensorNetworks”. These are already being applied inother fields in which the management of resourcesis a key element and in which it is necessary toprovide services under QoS agreements, suchas mobile telephone providers or Internet serviceproviders.

1.1. Marine Sensor NetworksA Marine Sensor Network (MSN) is a group ofInstruments and Data Acquisition Systems that,by means of a communications link, work in acooperative way in order to obtain data from themarine environment.For instance, cabled MSNs are an ideal way ofobserving the ocean in a continuous way. Theyare reliable for many years, offer high band widthtelemetry and are inexpensive to operate onceinstalled [1].

When deployed over large sea floor areas withthe purpose of obtaining long term datasets,MSNs will be a basic tool in OperationalOceanography[1]. The development of MSNs has

been widely promoted by the most relevantinternational organisms for marine science andtechnology management [2][3].Some large MSN projects have started recently,such as NEPTUNE [4], that is now in the firstsea tests phase. Other projects at their firstdefinition stage, like ESONET [5], are drawingtogether several marine science centers andtechnological enterprises from differentcountries.One of the most important key items related tothe development of these networks is themanagement of the heterogeneity: differentsystems and technologies are concurrent in thesame network, forced to share hardwareresources and exchange data.

Another important aspect of these networks isthe maximum extension of the operational timerange of the deployed instrumentation, in orderto elongate the time data series and also tomake the high costs of the network installationmore profitable.

Some other projects related to NEPTUNE, suchas SENSORS [6], have started recently withthe objective of solving these two importantaspects.

1.2. Network ManagementThe Network Management is defined as thegroup of tasks and techniques related to theplanning, organization and supervision of allelements within a network, independently oftheir nature and location.

The main goal of the Network Management isto reach the maximum levels of availability,efficiency and effectiveness, through the global

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management and control of the elements in anetwork.The Network Management is based on a cyclethat comprises:

·Obtaining information about the networkelements status·Global analysis of this information·Decisions and actions over the network.

In a MSN scenario, obtaining information is notrestricted to the physical elements of the network(instruments and the communication networkitself) but is also centered in the knowledge ofthe marine environment (Fig. 1). The knowledgeof the ocean in a MSN is a fundamental part ofthe information that will determine the decisionsdevoted to the improvement of the global efficiencyof the network.

2. Applicability of Network Managementtechniques to MSNs

2.1. Operational Time RangeIn a MSN, if we don´t consider the wearing ofsensors subject to the aggressive marineconditions (fouling, etc.), the instruments'operational time range is determined by the energyavailability and by the data storage capacity.Because Network Management allows a deepknowledge of the state of each network elementand also a global knowledge of the environment,the acquisition rate of each instrument can beadapted to the predicted variability of the measuredparameters, thus extending the operational timerange.

Some network technologies can provideinteresting solutions, such as Mobile Agents,which have already been proposed for networkmanagement tasks [7] [8].

Mobile Agents have the ability to take decisionsover their own mobility. This is an advantagewhen an adaptive behavior is needed or in lowbandwidth networks, because their use reducesthe network traffic.

An Agent visiting periodically each network nodecan collect information about the energy statusand free storage capacity of each instrument. Itcan also get a general image of the environment,and thus tell each instrument its appropriate

working rate.As an example, an Agent could detect thepropagation velocity of the seawatertemperature in the observed area. With thisknowledge, the Agent can decide to adjust datastorage and transmission rates in eachinstrument, accordingly. This is a decentralizedway to adjust the MSN performance to theenvironment variability, hence increasing theoperational time range.

2.2. HeterogeneityBecause of deployment costs, the MSNs willbe shared infrastructures. For the same reasonthey will be operative during several years.It is necessary to provide MSNs with easy rulesin order to integrate different instruments fromdifferent manufacturers and operators, most ofthem not planned to be attached at the initialdesign phase. Instruments will not use the MSNas a mere way of obtaining energy ortransmitting their data, but they will cooperatewith each other. Therefore, there is a need tointegrate instruments in a logical way (datastructures, and communication protocols).This integration can be reached using very welldefined interfaces that provide accuratespecifications on how instruments can sharedata, and also using the permanent knowledgeof where the needed data is placed (nodes andcommunication ports).

Network services in a MSN are defined as thecollection of the data provided by any instrument,and the storage and to land transmissioncapabilities offered by any network node. Theseservices and the network topology will changewith the integration of new instruments.A more flexible and scalable way of integratinginstruments is to use mechanisms for a dynamicdetection of the communication rules imposedby each instrument, and to find out on-line thenetwork services.

Network management is a perfect tool for theintegration procedures above mentioned. Oncemore, advanced network technologies canprovide interesting solutions to this issue.An Agent can be launched by a new instrumentincorporated to the network. Then the Agentwill visit every node and will collect informationon where the services needed for the correctintegration of the instrument are located, andhow to access them. At the same time, theAgent will announce the characteristics of thenewcomer to the rest of the nodes.Other plug and play and service discoverytechnologies, like JiniTM or WebServices [9]service description language (WSDL), can besuccessfully implemented in a MSN, butprobably lack the flexibility provided by Agents.

2.3. Fault ToleranceAlthough MSN are remotely operated, theymust have a low maintenance. This is because

Figure 1. Management cycle for a Marine SensorNetwork

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it is quite difficult to have a physical access to thenodes in order to fix problems.Fault tolerance and automatic recovery must bedesirable features. A MSN must provide faultnotification and procedures to reconstruct thedata acquisition and transmission scheme whenone or more components fail.Fault tolerance can be implemented with enoughredundancy at different levels (sensors andnetwork), but network management can also bea good tool to enhance the reliability of the MSN.

It is possible to predict some faulty conditions -detecting worsening of data and sensinginstrument and network performances- by asystematic analysis of both MSN nodes andacquired data. This analysis will also provide thedata quality log, which is an important parameterfor a correct interpretation of the data.

The global network knowledge can be used againas a parameter for taking decisions. It can beused for searching alternative data sources orcommunication routes, in order to maintain dataconsistency and avoid losses of information.

Performance checking can be included as astandard service of each instrument, and thetechnologies aforementioned can be used tomaintain a global view of the MSN performanceand react automatically against a faulty condition.Once again, the most important aspect is theability of the management system to detectservices and to obtain a global perspective.

2.4. Quality of ServiceQuality of Service (QoS) in a MSN must beunderstood as the level of data quality.It is mandatory to know the measurementsaccuracy and the error rate related to anyinstrument, the accuracy of the references (mainlytime and position also in the case of mobileinstruments), and the knowledge of all theacquisition conditions that can induce errors(energy source levels, data transmission quality,environment conditions like temperature orpressure, etc.). It is also important to know howthe MSN is working as a whole, if there is anyfaulty condition in any node that provide data tothe other nodes or if the environment is changingmore quickly than the storage and transmissionrates.Network management provides a good way forobtaining this QoS knowledge, and technologiesthat collect information from nodes in adecentralized way can be a good choice.

3.ConclusionsNetwork management technologies offer goodsolutions for dealing with the complexity, reliability,data quality and maintenance of a MSN.New network management technologies, suchas Mobile Agents and WebServices, are optionsthat must be taken into consideration. Particularlythe way to implement them, considering the MSNconditions and the necessary infrastructure to

allow them to work.Network Management policies must be includedas a part of the present and future MSN projects,investigating the application of new networktechnologies.

4. References[1] G. Griffiths, et. al., “Towards New PlatformTechnology for Sustained Observations”, inObserving the Oceans in the 21st Century, C.J.Koblinsky and N.R. Smith (Eds), GODAE ProjectOffice and Bureau of Meteorology, Melbourne:pp 324-338.

[2] European Science Foundation Marine Board,“5Th Position Paper”, 2002.

[3] National Science Foundation,“05-526Program Solicitation”, 2005.

[4] D.H. Rodgers et. al., “NEPTUNE RegionalObservatory System Design”, in Proceedingsof Oceans 2001 Conference, Honolulu, HI.,Nov. 2001.

[5] European SeaFloor Observatory Network,“ESONET Final Report (Version 3.0)”, ProfessorI.G (Monty) Priede & Dr Martin Solan. Universityof Aberdeen. Scotland UK. 2005

[6] SENSORS. National Science FoundationPro ject Nº 2003-0330428; 2004-07

[7] M. Günter and T Braun, “Internet ServiceMonitoring with Mobile Agents”. IEEE Network,2002.

[8] P.H. Nghia and V. Limpoka, ”A FlexibleMobile Agent Framework for Distributed NetworkManagement.” Networks and CommunicationSystems. 2005

[9] A. Pras, “WEB Services For NetworkManagement”. Presentation at the 17th IRTF-NMRG Meeting, November 14, 2004, Davis,USA