Wireless Sensors Networks as Black-Box Recorder for Fast Flight Data Recovery during Aircraft Crash Investigation

Proceedings of the 20th World Congress Proceedings of the 20th World The International Federation of Congress Automatic Control Proceedings of the 20th World Proceedings of the 20th World Congress The International Federation of Congress Automatic Control Available online at www.sciencedirect.com Toulouse, France,Federation July 9-14, 2017 The International of The International of Automatic Automatic Control Control Toulouse, France,Federation July 9-14, 2017 Toulouse, Toulouse, France, France, July July 9-14, 9-14, 2017 2017

ScienceDirect

IFAC PapersOnLine 50-1 (2017) 814–819

Wireless Sensors Networks as Black-Box Recorder for Fast Flight Data Recovery Wireless Sensors Networks as Black-Box Recorder for Fast Flight Data Recovery Wireless Sensors Networks as Black-Box Recorder for Fast Flight Data Recovery Wireless Sensors Networks as Black-Box Recorder for Fast Flight Data Recovery during Aircraft Crash Investigation during Aircraft Crash Investigation during Aircraft Crash Investigation during Aircraft Crash Investigation Kais Mekki, William Derigent, Eric Rondeau, André Thomas Kais Mekki, William Derigent, Eric Rondeau, André Thomas Kais Mekki, Derigent, Eric Rondeau, André Thomas Mekki, William William Rondeau, André Thomas Research CentreKais for Automatic ControlDerigent, of Nancy, Eric CNRS UMR 7039, Campus Sciences, BP 70239, Research Centre for Automatic Control of Nancy, CNRS UMR 7039, Campus Sciences, BP 70239, Vandoeuvre-lès-Nancy Cedex, 54506, France. Research Centre for Automatic Control of Nancy, CNRS UMR 7039, Campus Research Centre for Automatic Control of Nancy,Cedex, CNRS UMR Campus Sciences, Sciences, BP BP 70239, 70239, Vandoeuvre-lès-Nancy 54506,7039, France. {kais.mekki,william.derigent,eric.rondeau,andre.thomas}@univ-lorraine.fr Vandoeuvre-lès-Nancy Cedex, 54506, France. Vandoeuvre-lès-Nancy Cedex, 54506, France. {kais.mekki,william.derigent,eric.rondeau,andre.thomas}@univ-lorraine.fr {kais.mekki,william.derigent,eric.rondeau,andre.thomas}@univ-lorraine.fr {kais.mekki,william.derigent,eric.rondeau,andre.thomas}@univ-lorraine.fr

Abstract: Commercial aircrafts use black box comprising a Flight Data Recorder (FDR) required for Abstract: Commercial aircrafts use black box comprising a Flight Data Recorder (FDR) required for crash investigation purposes. While becomprising easily recovered in crash on land, same does Abstract: Commercial aircrafts use black box aa Flight Data Recorder (FDR) required for Abstract: Commercial aircrafts useFDR blackcan box Flight Data events Recorder (FDR)the for crash investigation purposes. While FDR can becomprising easily recovered in crash events on land, therequired same does not apply to crash events in great deep ocean water. This paper presents a new solution towards solving crash investigation purposes. While FDR can be easily recovered in crash events on land, the same does crash investigation purposes. While FDR can be easily recovered in crash events on land, the same does not apply to crash events in great deep ocean water. This paper presents a new solution towards solving FDR datato recovery usingin agreat paradigm calledwater. "communicating materials". Thesolution solution is developed not crash deep This aa new towards solving not apply apply crash events events deep ocean ocean This paper paper presents presents new towards solving FDR datatorecovery usinginagreat paradigm calledwater. "communicating materials". Thesolution solution is developed through uniformly integrating hundreds of tiny sensor nodes in the aircraft structure. The nodes could FDR data recovery using a paradigm called "communicating materials". The solution is developed FDR data recovery using a paradigm called "communicating materials". The solution is developed through uniformly integrating hundreds of tiny sensor nodes in the aircraft structure. The nodes could then construct a Wireless Sensor Network (WSN) inside the aircraft. Thus, the latest FDR data could be through uniformly integrating hundreds of tiny sensor nodes in the aircraft structure. The nodes could through uniformly integrating hundreds tiny sensor in the aircraft structure. Thedata nodes could then construct a Wireless Sensor Networkof(WSN) insidenodes the aircraft. Thus, the latest FDR could be stored in the nodes using data storage protocol for WSN. The proposed storage protocol uses the then construct a Wireless Sensor Network (WSN) inside the aircraft. Thus, the latest FDR data could be then construct a Wireless (WSN) inside the aircraft. Thus, thestorage latest FDR data could be stored in the nodes usingSensor data Network storage protocol for WSN. The proposed protocol uses the probabilistic-based flooding scheme to forward data to all nodes inside the aircraft structure within the stored in the nodes using data storage protocol for WSN. The proposed storage protocol uses stored in the nodesflooding using data storage protocol Theinside proposed storagestructure protocolwithin uses the the probabilistic-based scheme to forward dataforto WSN. all nodes the aircraft lowest delay. To improve reliability collision-avoidance flooding, different complementing probabilistic-based flooding scheme scheme to and forward data to to all all nodes nodes of inside the aircraft aircraft structure within the the probabilistic-based flooding to forward data inside the structure within lowest delay. To improve reliability and collision-avoidance of flooding, different complementing corrective measures are used based on neighborhood information. The protocol is evaluated using lowest delay. To improve reliability and collision-avoidance of flooding, different complementing lowest delay. To improve reliability and collision-avoidance of flooding, different complementing corrective measures are used based on neighborhood information. The protocol is evaluated using Castalia/OMNeT++ corrective measures are corrective measures simulator. are used used based based on on neighborhood neighborhood information. information. The The protocol protocol is is evaluated evaluated using using Castalia/OMNeT++ simulator. Castalia/OMNeT++ simulator. Castalia/OMNeT++ simulator. © 2017, IFAC (International Federation of Sensor Automatic Control)Data Hosting by Elsevier Ltd. All rightsFlooding. reserved. Keywords: Aircraft Black Box, Wireless Networks, storage, Probabilistic-based Keywords: Aircraft Black Box, Wireless Sensor Networks, Data storage, Probabilistic-based Flooding. Keywords: Aircraft Black Box, Wireless Sensor Networks, Data storage, Probabilistic-based Flooding. Keywords: Aircraft Black Box, Wireless Sensor Networks, Data storage, Probabilistic-based Flooding.   was published that the battery of the black box of this  1. INTRODUCTION was published that the battery of the black box of this airplane expired that in December 2012of out was published published the battery battery ofand thepossibly black has boxbeen of 1. INTRODUCTION was the the black box of this this airplane expired that in December 2012 and possibly has been out 1. INTRODUCTION 1. INTRODUCTION of order (ABC, 2015). The flight black box itself not been Per international rules, commercial aircrafts are provided airplane expired in December 2012 and possibly has been out airplane expired2015). in December 2012 andbox possibly out of order (ABC, The flight black itself has has been not been Per international rules, commercial aircrafts are provided found, so the cause of the incident remains undetermined. with a unit generally known as a "black box" having means of order (ABC, 2015). The flight black box itself has not been Per international rules, commercial aircrafts are provided of order (ABC, 2015). The flight black box itself has not been Per international rules, commercial aircrafts are provided with a unit generally known as a "black box" having means found, so the cause of the incident remains undetermined. for data known regarding the aircraft for means crash found, so the with arecording unit as box" Considering the of advances of remains modernundetermined. communication so the the cause cause of the incident incident remains undetermined. with unit generally generally as aa "black "black box" having having for arecording data known regarding the aircraft for means crash found, Considering the advances of modern communication investigation purposes. Black boxes record, on one side, for recording data regarding the aircraft for crash technology, the investigators and airframe manufacturers Considering the advances of modern communication for recording data regarding the aircraft for crash investigation purposes. Black boxes record, on one side, technology, Considering the the investigators advances of and modern airframe communication manufacturers aircraft flight parameters and, onboxes the other side, conversations investigation purposes. record, on recommended thus for flights black boxes to be extended or the investigators and airframe manufacturers investigation purposes. Black Black record, on one one side, side, technology, aircraft flight parameters and, onboxes the other side, conversations technology, the investigators and airframe manufacturers recommended thus for flights black boxes to be extended or between the pilot, ground control, andconversations other flight replaced aircraft parameters and, on other by live data system from theextended aircraft or to recommended thus forstreaming flights black black boxes to be be extended or aircraft flight flight parameters and, on the the co-pilot other side, side, between the pilot, ground control, co-pilot andconversations other flight replaced recommended thus for flights boxes to by live data streaming system from the aircraft to crew. between the pilot, ground control, co-pilot and other flight the ground (The guardian, 2014), by triggered transmission of replaced by live data streaming system from the aircraft to between the pilot, ground control, co-pilot and other flight replaced crew. liveguardian, data streaming fromtransmission the aircraft of to the groundby(The 2014), system by triggered crew. flight data (French BEA, 2011), or by enabling data While black box can be easily recovered in crash events on the ground (The guardian, 2014), by triggered transmission of crew. the ground (The guardian, 2014), by triggered transmission of flight data (French BEA, 2011), or by enabling data While black box can be easily recovered in crash events on transmission from the black to a Cloud satellite land, the samebox does crash events the sea where flight BEA, 2011), or enabling data While black can beapply easily recovered in crash events on flight data data (French (French BEA, box 2011), or by bythrough enabling data While black cannot easilyto in in crash events on transmission from the black box to a Cloud through satellite land, the samebox does notbeapply to recovered crash events in the sea where communication (Wiseman, 2016). The investigators the problem is to find the black box in great deep waters. As transmission from the black box to a Cloud through satellite land, the same does not apply to crash events in the sea where transmission from the black box to a Cloud through satellite land, the same does not apply to crash events in the sea where (Wiseman, 2016). The investigators the problem is to find the black box in great deep waters. As communication recommended for the ULB battery to be example, the is AirFrance flight 447 was in the Atlantic (Wiseman, 2016). The investigators the problem to black box in great waters. As communication also (Wiseman, 2016). The lifetime investigators the problem to find find the the black box incrashed great deep deep waters. As communication recommended also for the ULB battery lifetime to be example, the isAirFrance flight 447 was crashed in the Atlantic extended from 30 to 90 days and the beacons range to be Ocean on 1 June 2009, while flying from Rio de Janeiro in recommended also for the ULB battery lifetime to example, the AirFrance flight 447 was crashed in the Atlantic recommended the ULB battery lifetime be example, AirFrance wasfrom crashed Atlantic from also 30 tofor 90 days and the beacons range to to be Ocean onthe 1 June 2009, flight while447 flying Rioindethe Janeiro in extended increased. Moreover, the patent in (Santolalla et al., 2013) Brazil to Paris in France. In fact, the black box is fitted with extended from 30 to 90 days and the beacons range to Ocean on 1 June 2009, while flying from Rio de Janeiro in extended from 30 to 90 beacons etrange to be be Ocean to onParis 1 June 2009, while flying from Rio Janeiro in increased. Moreover, the days patentand in the (Santolalla al., 2013) Brazil in France. In fact, the black box de is fitted with toMoreover, eject the black box prior to the aircraft such an Underwater Locator that box begins to radiate increased. the in et al., Brazil to France. In the is with increased. the patent patent in (Santolalla (Santolalla et crash al., 2013) 2013) Brazil to Paris Paris in in France.Beacon In fact, fact,(ULB) the black black is fitted fitted with proposes proposes toMoreover, eject the black box prior to the aircraft crash such an Underwater Locator Beacon (ULB) that box begins to radiate as the military airplane, and to provide the black box with an acoustic signal at 37.5 kHz if its sensor touches water. proposes to eject the black box prior to the aircraft crash such Locator Beacon (ULB) that to to ejectairplane, the blackand boxtoprior to thethe aircraft an Underwater Underwater Locator Beacon that begins begins to radiate radiate as the military provide blackcrash box such with an acoustic signal at 37.5 kHz (ULB) if its sensor touches water. proposes specific water floating tools. However, this proposal has not They work to a depth of just over four kilometers (4.270 as the military airplane, and to provide the black box with an acoustic signal at 37.5 kHz if its sensor touches water. the military airplane,tools. and However, to providethis theproposal black box an acoustic signal at 37.5 kHz over if itsfour sensor touches (4.270 water. as specific water floating haswith not They work to a depth of just kilometers been implemented nowadays in commercial aircraft because meters), and can ping once a second for 30 days before the specific water floating tools. However, this proposal has They work to a depth of just over four kilometers (4.270 water floating tools. However, this proposal has not not They work a ping depthonce of just over four kilometers (4.270 been implemented nowadays in commercial aircraft because meters), andtocan a second for 30 days before the specific the ejection mechanisms uses explosive which may raise battery runs out. During 30aadays after the AirFrance flight been implemented nowadays in commercial aircraft because meters), and can ping once second for 30 days before the been implemented nowadays in commercial aircraft because meters), and can ping once second for 30 days before the the ejection mechanisms uses explosive which may raise battery runs out. During 30 days after the AirFrance flight security concerns (Marzuoliuses et al.,explosive 2016). which 447 crash, used after to listen for the acoustic the mechanisms may raise battery runs out. 30 the flight the ejection ejection mechanisms battery runssubmarines out. During Duringwere 30 days days the AirFrance AirFrance flight security concerns (Marzuoliuses et al.,explosive 2016). which may raise 447 crash, submarines were used after to listen for the acoustic signal emitted by the ULB in a search area with a radius of 80 security concerns (Marzuoli et al., 2016). 447 crash, submarines were used to listen for the acoustic This paper is oriented towards solving the enounced security concerns (Marzuoli et al., 2016). 447 crash, submarines were to area listenwith fora the acoustic signal emitted by the ULB in aused search radius of 80 This paper is oriented towards solving the enounced kilometres, centred on the aircraft's last known position, but signal emitted by the ULB in a search area with a radius of 80 drawbacks using a new paradigm called Communicating This paper is oriented towards solving the signal emitted by theon ULB a searchlast areaknown with aposition, radius ofbut 80 This kilometres, centred the in aircraft's paper using is oriented towards solving the enounced enounced drawbacks a new paradigm called Communicating without any success. However, it took search teams two years kilometres, centred on the aircraft's last known position, but Materials (CM) (Thomas, 2009). The CM enhances a classic drawbacks using a new paradigm called Communicating kilometres, the aircraft's known position, but Materials without any centred success.on However, it tooklast search teams two years drawbacks using a new paradigm called Communicating (CM) (Thomas, 2009). The CM enhances a classic (i.e. untilany 2 success. May 2011) to findit theteams blacktwo boxyears at a Materials without any success. However, itand tookraise search teams two years product material with the following capabilities: it can store (CM) (Thomas, 2009). The CM enhances aa classic without However, took search (i.e. until 2 May 2011) to find and raise the black box at a Materials (CM) (Thomas, 2009). Thecapabilities: CM enhances classic material with the following it can store cost of $40 million. Another case is the disappearing ofaa product (i.e. until 2 May 2011) to find and raise the black box at data, communicate information at any point of its surface, product material with the following capabilities: it can store (i.e. until 2 May 2011) to find and raise the black box at cost of $40 million. Another case is the disappearing of product material with the following capabilities: store data, communicate information at any point of ititscan surface, Antonov An-72 flight in 22 December 1997, while flying cost of $40 million. Another case is the disappearing of and keep these previous properties after physical data, communicate information at any point of its surface, cost of $40 million. Another case is the disappearing of Antonov An-72 flight in 22 December 1997, while flying and data, communicate information at any point of its surface, keep these previous properties after physical from Abidjan Côte in Ivoire to Rundu1997, in Namibia. The modifications. Antonov An-72 flight 22 while Indeed,previous the product does notafter communicate and properties physical Antonov An-72in 22 December December while flying flying from Abidjan inflight Côte inIvoire to Rundu1997, in Namibia. The modifications. and keep keep these these properties physical Indeed,previous the product does notafter communicate airplane vanished over the South Atlantic Ocean, but since from Abidjan in Côte Ivoire to Rundu in Namibia. The using some electronic devices in specific points, but becomes Indeed, the product does not communicate from Abidjan in over Côte the Ivoire to Atlantic Rundu in Namibia. The modifications. airplane vanished South Ocean, but since modifications. Indeed, the product does not communicate using some electronic devices in specific points, but becomes the flightvanished black box hasthe notSouth been Atlantic found, the reason the intrinsically airplane over Ocean, but since and continuously this some devices specific but becomes airplane over Ocean, butof the flightvanished black box hasthenotSouth been Atlantic found, the reason ofsince the using using some electronic electronic devices in incommunicating. specific points, points, To butmeet becomes intrinsically and continuously communicating. To meet this disappearance remains unknown. One more notable the flight black box has not been found, the reason of the vision, thousands micro/nano electronic devices are inserted intrinsically and continuously communicating. To meet this the flight black remains box has not been found, reasonnotable of the intrinsically disappearance unknown. Onethemore and continuously communicating. To meet this vision, thousands micro/nano electronic devices are inserted is the Malaysia Airlines flight 370 that disappearance remains unknown. One more notable into the material of the product during its industrial vision, thousands micro/nano electronic devices are inserted disappearance isremains unknown. One flight more 370 notable disappearance the Malaysia Airlines that into vision, thousands micro/nano electronic devices are inserted the material of the product during its industrial disappeared the the Indian Ocean Airlines on 8 March disappearance is Malaysia flight 370 that manufacturing. In (Kubler al., 2014),during a CM its application is the of product industrial disappearancein Malaysia flight2014, 370while that into disappeared in is the the Indian Ocean Airlines on 8 March 2014, while into the material material of the theet industrial manufacturing. In (Kubler et product al., 2014),during a CM its application is flying from Kuala Lumpur in Malaysia to Beijing in China. It disappeared in the Indian Ocean on 8 March 2014, while manufacturing. In (Kubler et al., 2014), a CM application disappeared in the Indian Ocean on 8 March 2014, while flying from Kuala Lumpur in Malaysia to Beijing in China. It manufacturing. In (Kubler et al., 2014), a CM application is is flying from Kuala Lumpur in Malaysia to Beijing in China. It flying from Kuala Lumpur in Malaysia to Beijing in China. It

2405-8963 © IFAC (International Federation of Automatic Control) Copyright © 2017, 2017 IFAC 837Hosting by Elsevier Ltd. All rights reserved. Copyright 2017 responsibility IFAC 837Control. Peer review©under of International Federation of Automatic Copyright © 2017 IFAC 837 Copyright © 2017 IFAC 837 10.1016/j.ifacol.2017.08.145

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introduced by scattering a huge amount of μtags RFID in a manufactured textile. In (Peña et al., 2011), authors use nanosensor nodes integrated in the product and a localization technique to automatically determine the product dimensions. In (Mekki et al. 2016a), a new service was developed for smart building using CM paradigm: a communicating precast concrete is developed which could store and read information directly into the building through thousands of micro-sensor nodes uniformly integrated in the concrete. The information is stored and retrieved in the micro-nodes during the building lifecycle, using specifics protocols (Mekki et al., 2016b) (Mekki et al., 2016c). In this paper, we define a new application of CM paradigm for aircraft which could store the black box data into its structure. This service is developed through uniformly integrating hundreds/thousands of tiny sensor nodes in the aircraft structure as shown in figure 1. Each node could communicate wirelessly with others. Thus, the nodes could construct a Wireless Sensor Network (WSN) inside the aircraft. In crash detection, the latest recorded black box data could be replicated throughout all nodes inside the aircraft structure using storage protocol for WSN. Thus in this paper, a WSN storage protocol is proposed for this issue. It empowers nodes with the ability to make storing decisions that only rely on neighbourhood information. The protocol guarantees that the latest recorded black box data is present in each node inside the aircraft structure. Hence, information could be read in all pieces of the aircraft, and investigators could gather preliminary crash causes information from the nodes inside any floated aircraft wreckage on the ocean. However, finding the black box stills unavoidable to get all the recorded flight data. The proposed protocol is evaluated with Castalia/OMNeT++ by studying the reliability (i.e. the data have to be efficiently stored by all nodes inside the simulated aircraft structure) and the storage capacity. The rest of paper is organized as follows. Section 2 details the background and the problem statement. Section 3 presents the design of the data storage protocol. Section 4 is dedicated to the performance evaluation of the proposed protocol through simulation. Finally, Section 5 discusses and concludes the paper.

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2. BACKGROUND AND PROBLEM STATEMENT 2.1 Background Currently, commercial aircrafts are equipped with two black boxes that record information about the flight. Both recorders are installed to help reconstruct the events leading to an aircraft accident. One of these, the Cockpit Voice Recorder (CVR), records last 2 hours of radio transmissions and sounds in the cockpit (American FAA, 2005), such as the pilot's voices and engine noises. The other, the Flight Data Recorder (FDR), retains 25 hours of mandatory flight control parameters (American FAA, 2005) such as time, airspeed, altitude, heading, acceleration, trajectory, attitude, outside air temperature, engine and motor parameters, cockpit controls data, etc. Commercial aircraft models use FDR systems, which store 64 words per second of 12 bits each (wps) over a 25 hours period in electronic memory (French BEA, 2005). At the end of the 25 hours, the FDR begins recording the most recent data over the oldest data. No tape removal is required with these systems. Actually, a honeycomb panel is used in modern aircraft structure (Soutis, 2005). It is a sandwich structure with a cellular core sandwiched between two facing sheets by bonding as shown in figure 2. The honeycomb sandwich construction in aircraft design came as a major breakthrough in the search for a more efficient structure. It is used for such area as bulkheads, control surfaces, fuselage panels, wing panels, empennage skins, radomes, and shear webs (Soutis, 2005).

Fig. 2. Fabricated sandwich honeycomb panel in modern aircraft.

2.2 Problem statement The CVR allows 2 hours of audio recording which leads to big data size, and it would be difficult to store it in WSN memory. Thus, the study of this paper is limited to FDR data storage which brings, to investigators, preliminary idea of the cause of the aircraft crash. Sandwich honeycomb panel of modern aircraft structure allows easier integration of micro-nodes for communicating material paradigm application. Thousands of micro-nodes could be embedded in the honeycomb cells. As example, the honeycomb panels could be instrumented using the density of 1 node in each 1 m2. Indeed, each node could communicate wirelessly with others inside the panels. The nodes could then construct a uniformly deployed WSN inside all the aircraft structure. Indeed, the nodes inside the aircraft are in deep sleep until an aircraft crash is detected by FDR recorder as shown in figure 3. In that moment, all nodes must wake-up to begin successive storage of the latest FDR data (see figure 3). Different Wake-up mechanisms could be used such as

Fig. 1. Uniform deployment of tiny sensor nodes inside the aircraft structure.

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discussed in (Magno et al., 2014). The work of this paper focus only on FDR data storage, thus the wake-up mechanism solution is not treated in this paper. The key focus of our study is to ensure the existence of the latest FDR data in each piece of the aircraft floated wreckage following ocean crash. Therefore, the data should be efficiently stored in all the nodes of the aircraft structure. The nodes must ensure also a high storage capacity. As example, if each node stores 38400 words of 12 bits each (memory size=57,6 Kbyte) of the FDR, investigators could have information of the last 10 minutes of the recorded FDR data (i.e. FDR records 64 words per second of 12 bits each as discussed in the previous section). Figure 3 presents also the warning times which is the time elapsed from the instant of the crash detection, to the impact of the aircraft with the ground/ocean. In (French BEA, 2011), the statistic results indicate that the warning times is greater than 15 seconds in 75% of the crash cases, greater than 30 seconds in 59% of the cases, greater than 60 seconds in 34% of the cases and greater than 120 seconds in 23% of the cases. Thus, the protocol should ensure a very low delay, as much as possible, for storing the last recorded FDR data during the warning times. The rest of the paper details the proposed protocol. Finally, the performance evaluation through Castalia/OMNeT++ simulation is presented.

limitations. The main challenges are (Yu et al., 2014): duplication (i.e. a node is forced to receive messages twice from two different nodes), collision (i.e. the broadcast increases contention), and resource blindness (i.e. nodes do not adopt energy-saving mechanisms). Therefore, various schemes for controlled flooding have been proposed. These schemes are commonly divided into two categories: deterministic and probabilistic. Deterministic schemes use network topology information to build a virtual backbone (e.g. clusters, tree, etc.) that covers all the nodes in WSN (i.e. messages are sent throughout the virtual backbone). To build a virtual backbone, nodes exchange information, typically about their immediate or two hop neighbours. However, it demands a large overhead in terms of delay and message complexity for building and maintaining the backbone (Aminu et al., 2009). In the probabilistic approach, a node rebroadcasts the message per a fixed probability value P (Sekkas et al., 2010). Probabilistic techniques are appealing since they are very simple, and are inherently robust to failures and mobility in WSN. To obtain a very high reliability with pure probabilistic broadcasting, the retransmission probability P must be set to relatively high values. Consequently, such schemes generate many redundant messages. Other approaches combine probabilistic approach with some additional locally computable mechanism, such as counter-based (Miranda et al., 2006), distance-based, location-based (Sanchez et al., 2011), or any combination of those, to determine whether it should rebroadcast the message or not. Location-based and distance-based mechanisms exploit position and distance information between nodes to reduce the number of redundant retransmissions. However, nodes need to be equipped with a Global Positioning System (i.e. GPS could not be applied in our work as the nodes are embedded in the aircraft panels) or a Received Signal Strength Indicator which incur more cost and latency (Heurtefeux and Valois, 2012). On the other hand, in counterbased, the node fixes a Random Assessment Delay (RAD) before making the forwarding decision. During this delay, the node counts the number of retransmissions of the same message by neighbour nodes. After the waiting delay has elapsed, the message is only forwarded if the number of retransmissions is smaller than a predetermined threshold Cth. It is clear that the RAD delay incurs more latency for message broadcasting in each node, as discussed in (Mekki et al., 2016d), which increase the FDR data dissemination delay. Hence, the original fixed probabilistic-based strategy is adopted as the broadcast mechanism in our FDR data storage protocol. In literature, various works studied the fixed probabilistic mechanism. Authors in (Drabkin et al., 2007) have proposed an adaptive probabilistic scheme, called RAPID. The probability P for a node to rebroadcast a message is determined by the local nodes density to achieve high reliability level. In (Miranda et al., 2006) an efficient counter-based scheme has been described which combines the merits of fixed probabilistic and counter-based algorithms using a rebroadcast probability value of around 0.65. P=0.65 is a value recommended in (Sekkas et al., 2010). This yield

Fig. 3. Nodes modes before and after aircraft crash detection.

3. FDR DATA STORAGE PROTOCOL IN WSN The aim of this paper is to fully broadcast the latest FDR data for storage in all nodes, to make data present in each piece of the aircraft panels. Thus, this section focuses on the broadcasting techniques in WSN. In the following, the existing broadcast mechanisms for WSN are firstly presented. Then, the proposed protocol is detailed. 3.1 Existing broadcast mechanisms for WSN Broadcast is a basic service in WSN, it enables any node to disseminate messages to all other nodes in the network. A useful broadcast service should be both efficient and provide a high reliability (i.e. meaning that most nodes in WSN receive almost every broadcasted message). A simple implementation of broadcast in WSN is by employing Flooding: “the sender transmits the message to all nodes in its transmission range. Each node that receives a message for the first time forwards it to all other nodes in its range. Thus, the message traverses the entire network and reaches all the nodes”. Although flooding is an extremely simple and efficient mechanism for data dissemination, it has certain 839

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good performance levels in terms of saved-retransmissions, delay, and reliability trade-off. Furthermore, in (Aminu et al., 2007), the authors have shown that a better rebroadcast probability value was around 0.5, that can achieve better performance than their earlier scheme. Our solution proposes to benefit from the best features employed by these works. The proposed probabilistic-based protocol is detailed in the following.

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message to very few additional nodes. Hence, if a node n has heard two transmissions of the same message m (the first and the second reception), there is little point for it to also retransmit. Yet, the optimization of deciding to rebroadcast m even if initially a node n probabilistically chose not to, but later did not hear any of its neighbours rebroadcast m (lines 12-16 in figure 4) helps boosting the reliability of the protocol, by ensuring that a message will be propagated to almost every neighbourhood of the network.

3.2 Proposed protocol for FDR data storage in WSN In the proposed probabilistic-based protocol shown in figure 4, the data is stored if the message is received for the first time. A fixed broadcasting probability P=0.65 is adopted as recommended in (Miranda et al., 2006) (Aminu et al., 2007) (Sekkas et al., 2010). As discussed in (Aminu et al., 2009), a relatively high probability value improves reliability, but it increases redundancy and collisions in WSN. Hence, to reduce the chance of collision, and thereby be able to obtain high reliability levels, the protocol employs a jitter (Jacobsson et al., 2011): when a node decides to rebroadcast a message, it waits for a short random time RT before doing so. Thus, nodes wait for a certain amount of time before they rebroadcast a message such as the counter-based broadcasting scheme. Yet, the average waiting time is much shorter in our protocol (proposed jitter ≤ 50ms) than in counter-based protocols (counter-based timer ≥ 200ms). The idea described above has two important drawbacks. First, two nodes can choose to broadcast the same message even if they are very close to each other. Obviously, retransmissions by nodes that are located close to each other cover very little additional area. The second drawback is even more severe: if all nodes in a given neighbourhood decide not to broadcast a message, the dissemination of this message will not reach some WSN regions (i.e. some aircraft panels are left empty of FDR data). Thus, the idea is to slightly change the protocol by adding two complementary corrective measures that are based on each node monitoring its neighbours. That is, instead of immediately rebroadcasting a message m with the probability P, a node n adds m to its casting queue during RT and in parallel monitors its neighbours (lines 6 and 7 in figure 4). If n overhears a transmission of the same message m by one of its neighbours, n removes m from its casting queue without broadcasting m (lines 8 and 9 in figure 4). Otherwise, after RT elapses, n broadcasts m with the probability P as discussed above (line 11 in figure 4). The second corrective measure is that whenever n probabilistically decides not to rebroadcast m, but later n does not hear any other rebroadcasting of m, then n adds m to its casting queue. Either n will hear a retransmission of m by one of its neighbours until the end of the next message processing, or n will retransmit m (lines 12-16 in figure 4). Now, explanation is given on how these two corrective measures complement each other. The optimization of cancelling a retransmission (lines 8 and 9 in figure 4) might seem, at first, to hurt the probabilistic behaviour of the original fixed protocol. The reason for this optimization is that, on average, beyond the first two transmissions of a message m in a given one-hop neighbourhood, any additional transmission in the same neighbourhood will only deliver the

1: procedure FDR_DATA_STORAGE(DATA_MESSAGE) by node n 2: if DATA-MESSAGE is known, Sequence_Number already received 3: - Drop DATA_MESSAGE 4: else 5: - Store DATA 6: - Add DATA_MESSAGE to casting queue 7: - Set RT and wait for it to expire 8: if DATA_MESSAGE is received with same Sequence_Number 9: - Remove DATA_MESSAGE from casting queue 10: else 11: - Broadcast DATA_MESSAGE with probability P 12: if DATA_MESSAGE is not broadcasted 13: if DATA_MESSAGE with same Sequence_Number is not received until the end of the next message processing 14: - Broadcast DATA_MESSAGE 15: else 16: - Remove DATA_MESSAGE from casting queue 17: end if 18: end if 19: end if 20: end if 21: end procedure

Fig. 4. The proposed protocol for FDR data storage in WSN.

4. EVALUATION OF THE PROPOSED PROTOCOL In this section, the simulation settings are firstly described, and then, the performance results of the proposed protocol are presented and discussed. 4.1 Simulation setup The proposed protocol was implemented using Castalia/OMNeT++ tools. In this simulation study, the SensorCube node (Diall et al., 2007) is modelled which is a tiny micro-node (size=1 cm3). SensorCube has 120 Kbyte memory size, and uses the 2.4 GHz frequency band with 1 Mbps as bit rate. All nodes in the simulated scenarios are deployed uniformly in a 10m-large square aircraft panel. The FDR recorder is located in the bottom of the area. Various nodes density is simulated: 1 node each 1 m2, 4 nodes each 1 m2, 8 nodes each 1 m2, and 12 nodes each 1 m2. The jitter is fixed to 30 ms (i.e. the RT parameter is a random value between 0 and 30 ms). Each message contains 32 words of the FDR data. The FDR data are transmitted using successively messages. To avoid congestion in WSN, a waiting delay of 30 ms is used before transmitting each message by FDR recorder (i.e. FDR recorder is the source of messages). The proposed storage protocol is evaluated in terms of reception rate (reliability), number of transmissions, and number of stored FDR words. The protocol is compared with the performance of a fixed probabilistic protocol (F-probabilistic) to show the impact of the proposed corrective measures.

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Proceedings of the 20th IFAC World Congress 818 Kais Mekki et al. / IFAC PapersOnLine 50-1 (2017) 814–819 Toulouse, France, July 9-14, 2017

highest neighbourhood density around each node which increases the number of transmissions and the message duplication rate (increasing the message dissemination delay in the WSN). Thus, the total number of messages that could be disseminated during the warning times cuts down. Finally as presented before in this paper, the FDR recorder stores 64 words per second of 12 bits each. So, as shown in table 2, the maximum of storage capacity for the proposed protocol is obtained for the density of 1 node each m2 in the aircraft panels. The proposed protocol stores the last 1.73 minutes of FDR data during 15 seconds, the last 3.46 minutes during 30 seconds, the last 6.8 minutes during 60 seconds, and the last 13.6 minutes during 120 seconds. However, for F-probabilistic protocol, the reliability is very low for 1 node each m2 (40% as shown in table 1). Thus, the best storage performance for F-probabilistic protocol is obtained for the density of 4 nodes each m2 in the aircraft panels. In that case, F-probabilistic protocol stores the last 2.5 minutes during 15 seconds, the last 5.06 minutes during 30 seconds, the last 9.94 minutes during 60 seconds, and the last 19.75 minutes during 120 seconds.

4.2 Reception rate and number of transmissions Table 1 shows the performances of the reception rate and the number of transmissions for different node density. The table shows that the proposed protocol ensures the message reception by all nodes (99% for 1/m2 and 100% for the rest) due to the following used corrective measures: i) the jitter avoids collisions between neighbor nodes ii) if the node decides to not rebroadcast the message but after it does not hear any broadcasting of the same message, thus the node rebroadcasts it. These mechanisms are not developed in F-probabilistic. This is why only 40% of nodes receive the message for 1/m2, due to collisions in each neighborhood which avoid the transmission of the message to many regions in WSN. However, the reception rate increases for highest nodes density (95% for 4/m2, 99% for 8/m2, and 98% for 12/m2) due to the increasing of number of retransmissions in each neighborhood (i.e. the chance of message forwarding in each neighborhood increase). As shown in table 1, the proposed protocol is better also in terms of number of retransmissions due to the following corrective measure: if the node overhears a transmission of the same message by one of its neighbors, the node removes it from its casting queue without broadcasting. However in Fprobabilistic, the message is immediately rebroadcasted with the given probability P=0.65 which increases the total number of transmissions in WSN. Compared to F-probabilistic, the proposed protocol avoids 40% of number of message transmissions for 1/m2, and more than 60% for 4/m2, 8/m2, and 12/m2. Therefore, the proposed protocol consumes less energy than F-probabilistic as the communication is the main activity responsible for the energy consumption in WSN.

Table 2. Number of stored words in each node for the proposed protocol vs. F-probabilistic during 15, 30, 60, and 120 seconds.

Proposal

1/m2

2

1/m2 2

1/m

4/m

8/m

12/m

Proposal (%)

99

100

100

100

F-probabilistic (%)

40

95

99

98

F-probabilistic

2

Reception rate

Number of transmissions

8/m2

12/m2

Table 1. Reception rate and number of transmissions of the proposed protocol vs. F-probabilistic. 2

4/m2

Proposal

17

65

333

572

F-probabilistic

27

236

1038

1594

4.3 Number of stored FDR words Table 2 presents the total number of stored FDR words for the proposed protocol and F-probabilistic for the different nodes density, during the warning times 15, 30, 60 and 120 seconds. First, the table shows that F-probabilistic allows the storage of more words than the proposed protocol. This is due to the delay: F-probabilistic disseminates the message faster than the proposed protocol. In fact, the jitter used by our solution increases the delay of the message dissemination. In contrast, F-probabilistic does not use jitter. However, the absence of a jitter in F-probabilistic increases the chance of collision and reduces the reliability especially for very low node density 1/m2 as discussed in the previous section. Second, the number of stored words decreases when the nodes density grows for both protocols, this is due to the

4/m2

8/m2

12/m2

15 s

30 s

60 s

120 s

Number of words

6656

13312

26112

52224

Last FDR period (min)

1,73

3,46

6,8

13,6

Number of words

6348

12706

25602

50688

Last FDR period (min)

1,65

3,3

6,66

13,2

Number of words

5324

10444

20889

41779

Last FDR period (min)

1,38

2,71

5,43

10,87

Number of words

4352

8725

17613

34816

Last FDR period (min)

1,13

2,27

4,58

9,06

Number of words

9881

19968

39424

79360

Last FDR period (min)

2,57

5,2

10,26

20,66

Number of words

9625

19456

38195

75878

Last FDR period (min)

2,5

5,06

9,94

19,75

Number of words

6862

13721

27648

54681

Last FDR period (min)

1,78

3,57

7,2

14,23

Number of words

6758

13516

27033

54272

Last FDR period (min)

1,75

3,51

7,03

14,13

5. CONCLUSION This paper is oriented towards solving the problem of black box recovery in deep ocean water during aircraft crash investigation, using "communicating materials" paradigm. The solution consists in uniformly integrating hundreds/thousands of tiny sensor nodes in the aircraft structure. After crash detection, the latest recorded FDR data are replicated throughout all the nodes using storage protocol for WSN. The proposed storage protocol guarantees that FDR data is present in each node inside the aircraft structure. Thus, investigators could gather information related to preliminary crash causes from the nodes inside any floated aircraft wreckage. The proposed protocol uses the probabilistic-based 841

Proceedings of the 20th IFAC World Congress Toulouse, France, July 9-14, 2017 Kais Mekki et al. / IFAC PapersOnLine 50-1 (2017) 814–819

flooding scheme to forward data to all nodes with the lowest delay. The simulation results show that the protocol ensures high reliability, reduces the number of transmissions (reduces the energy consumption). Using SensorCube node, the protocol stores the last 1.73 minutes of FDR data during 15 seconds, the last 3.46 minutes during 30 seconds, the last 6.8 minutes during 60 seconds, and the last 13.6 minutes during 120 seconds.

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of the Asiana Crash. IEEE Transactions on Intelligent Transportation Systems, 17(2), 587-604. Mekki, K., Derigent, W., Zouinkhi, A., Rondeau, E., Thomas, A., and Abdelkrim, M.N. (2016a). New Communicating Concrete for Data Storage and Retrieval through Integrated Micro Sensor Nodes. 4th IEEE International Conference on Future Internet of Things and Cloud, Vienna, Austria. Mekki, K., Zouinkhi, A., Derigent, W., Rondeau, E., Thomas, A., and Abdelkrim, M.N. (2016b). USEE: A Uniform Data Dissemination and Energy Efficient Protocol for Communicating Materials. Journal of Future Generation Computer Systems, 56, 651-663. Mekki, K., Derigent, W., Zouinkhi, A., Rondeau, E., Thomas, A., and Abdelkrim, M.N. (2016c). RaWPG: A data retrieval protocol in micro-sensor networks based on random walk and pull gossip for communicating materials. IEEE Internet of Things Journal, doi: 10.1109/JIOT.2016.2584620. Mekki, K., Derigent, W., Zouinkhi, A., Rondeau, E., Thomas, A., and Abdelkrim, M.N. (2016d). Nonlocalized and localized data storage in large-scale communicating materials: Probabilistic and hop-counter approaches. Journal of Computer Standards & Interfaces, 44, 243-257. Miranda, H., Leggio, S., Rodrigues, L., and Raatikainen, K. (2006). A power-aware broadcasting algorithm. 17th IEEE Symposium on Personal, Indoor and Mobile Radio Communications, Helsinki, Finland. Peña, R., Krommenacker, N., and Charpentier, P. (2011). A New Strategy for Dimensional Metrology using Smart Dust Networks. International Conference on Indoor Positioning and Indoor Navigation, Guimarães, Portugal. Sanchez, E.R., Rebaudengo, M., and Zhang, L. (2011). Performance evaluation of reliable and unreliable opportunistic flooding in wireless sensor network. 17th IEEE International Conference on Networks, Singapore. Santolalla, E., Cortes, D., Gonzalez, E., Fernandez, E., and Abaurrea, P. (2013). Aircraft black box. US Patent No. US8489259B2, 16 July 2013. Sekkas, O., Piguet, D., and Alyfantis, G. (2010). Probabilistic information dissemination for MANETs: the IPAC approach. 20th Tyrrhenian Workshop on Digital Communication, Pula, Italy. Soutis, C. (2005). Fibre reinforced composites in aircraft construction. Progress in Aerospace Sciences, 41(2), 143-151. The guardian (2014). Malaysia Airlines flight MH370 makes it clear: we need to rethink black boxes. 31 March 2014. Thomas, A. (2009). RFID et nouvelles technologies de communication : enjeux économiques incontournables et problèmes d’éthique. 6th Conference on Integrated Design and Production, Fès, Marocco. Wiseman, Y. (2016). Unlimited and Protected Memory for Flight Data Recorders. Aircraft Engineering and Aerospace Technology, 88(6), 866-872. Yu, S., Zhang, B., Li, C., and Mouftah, H. (2014). Routing protocols for wireless sensor networks with mobile sinks: a survey. IEEE Communications Magazine, 52(7), 150-157.

REFERENCES ABC (2015). Malaysia Airlines MH370: Report finds battery powering locator beacon on black box expired in 2012, no red flags raised over crew or aircraft. 9 Mar 2015. American FAA (2005). Revisions to Cockpit Voice Recorder and Digital Flight Data Recorder Regulations. Technical report, 28 February 2005. Aminu, M., Ould-Khaoua, M., Mackenzie, L., and Abdulai, J. (2007). Improving the Performance of Counter-Based broadcast Scheme for Mobile Ad Hoc Networks. IEEE International Conference on Signal Processing and Communications, Dubaï, UAE. Aminu, M., Khaoua, M., Mackenzie, L., and Abdulai, J. (2009). Performance Analysis of an Adaptive Probabilistic Counter-Based Broadcast Scheme for Mobile Ad Hoc Networks. International Journal of Simulation: Systems, Science & Technology, 10(1), 2431. Diall, H., Raja, I., Hailes, G., Torfs, T., Hoof, C.V. (2007). Sensor Cube: A Modular, Ultra-Compact, Power-Aware Platform for Sensor Networks. Information and Media Technologies, 2(3), 914-924. Drabkin, V., Friedman, R., Kliot, G., and Segal, M. (2007). RAPID: Reliable Probabilistic Dissemination in Wireless Ad-Hoc Networks. 26th IEEE International Symposium on Reliable Distributed Systems, Beijing, China. French BEA (2011). Triggered Transmission of Flight Data Working Group. Technical Report, 8 March 2011. French BEA (2005). Flight Data Recorder Read-Out: Technical and Regulatory Aspects. Study Report, May 2005. Heurtefeux, K. and Valois, F. (2012). Is RSSI a Good Choice for Localization in Wireless Sensor Network?. 26th IEEE International Conference on Advanced Information Networking and Applications, Fukuoka, Japon. Jacobsson, M., Guo, C., and Faculty, I. (2011). An experimental investigation of optimized flooding protocols using a wireless sensor network testbed. Computer Networks Journal, 55, 2899-2913. Kubler, S., Derigent, W., Thomas, A., and Rondeau, E. (2014). Embedding data on communicating materials from context-sensitive information analysis. Journal of Intelligent Manufacturing, 25(5), 1053-1064. Magno, M., Marinkovic, S., and Popovici, E. (2014). Wakeup radio receiver based power minimization techniques for wireless sensor networks: A review. Microelectronics Journal, 45(12), 1627-1633. Marzuoli, A., Boidot, E., Feron, E., Van-Erp, P., Ucko, A., Bayen, A., and Hansen, M. (2016). Multimodal Impact Analysis of an Airside Catastrophic Event: A Case Study 842