ENABLING INFORMATION GATHERING PATTERNS FOR EMERGENCY RESPONSE WITH THE OPENKNOWLEDGE SYSTEM

Transcription

1 Computing and Infomatics, Vol. 29, 2010, ENABLING INFORMATION GATHERING PATTERNS FOR EMERGENCY RESPONSE WITH THE OPENKNOWLEDGE SYSTEM Gaia Tecaichi, Veonica Rizzi, Mauizio Machese Depatment of Infomation Engineeing and Compute Science Univesity of Tento Via Sommaive 14, I POVO (TN), Italy {gtecai, vizzi, Loenzino Vaccai Spatial Data Infastuctue Unit Euopean Commission Joint Reseach Cente via Enico Femi 2749, Ispa (VA), Italy Paolo Besana Laboatoie d infomatique médicale Univesité de Rennes I 2 Avenue du P. Leon Benad, Rennes Cedex, Fance paolo.besana@univ-ennes1.f Revised manuscipt eceived 24 Mach 2010 Abstact. Today s infomation systems must opeate effectively within open and dynamic envionments. This challenge becomes a necessity fo cisis management systems. In emegency contexts, in fact, a lage numbe of actos need to collaboate and coodinate in the disaste scenes by exchanging and epoting infomation with each othe and with the people in the contol oom. In such open settings, coodination technologies play a cucial ole in suppoting mobile agents located in aeas pone to sudden changes with adaptive and flexible inteaction pattens.

2 538 G. Tecaichi, V. Rizzi, M. Machese, L. Vaccai, P. Besana Reseach effots in diffeent aeas ae conveging to devise suitable mechanisms fo pocess coodination: specifically, cuent esults on sevice-oiented computing and multi-agent systems ae being integated to enable dynamic inteaction among autonomous components in lage, open systems. This wok focuses on the exploitation and evaluation of the OpenKnowledge famewok to suppot diffeent infomationgatheing pattens in emegency contexts. The OpenKnowledge (OK) system has been adopted to model and simulate possible emegency plans. The Lightweight Coodination Calculus (LCC) is used to specify inteaction models, which ae published, discoveed and executed by the OK distibuted infastuctue in ode to simulate pee inteactions. A simulation envionment fully integated with the OK system has been developed to: (1) evaluate whethe such infastuctue is able to suppot diffeent models of infomation-shaing, e.g., centalized and decentalized pattens of inteaction; (2) investigate unde which conditions the OK paadigm, exploited in its decentalized natue, can impove the pefomance of moe conventional centalized appoaches. Peliminay esults show the capability of the OK system in suppoting the two afoe-mentioned pattens and, unde ideal assumptions, a compaable pefomance in both cases. Keywods: Inteaction modeling, P2P coodination, cisis management, agentbased simulation Mathematics Subject Classification 2000: 68T35, 68T27, 68N17, 68M14 1 INTRODUCTION In cisismanagement,itisimpotanttocoodinateemegencyesponse 1 activitiesin an effective way. At pesent, most of the infomation management infastuctues equied fo dealing with emegencies ae based on centalized achitectues that (i) ae specifically designed pio to the emegency, (ii) gathe centally the available infomation, (iii) distibute it upon equest to the appopiate agents (e.g., emegency pesonnel, doctos, citizens). While such infastuctues povide a numbe of significant advantages (e.g., quality contol, eliability, tustwothiness, sustainability, etc.), they also pesent some well-known intinsic poblems (e.g., physical and conceptual bottlenecks, communication channel oveloads, single point of failue). Altenative solutions ae cuently being exploed, studied and analyzed to suppot data shaing also in the absence of a centalized infastuctue[6, 5]. In this study, we exploe the flexibility and adaptability of the famewok developed within the OpenKnowledge poject 2. This famewokpovides a distibuted infastuctue, that enables pees to find and coodinate with each othe by publishing, discoveing and executing multi paty convesational potocols. 1 In the est of this pape, we will efe to emegency esponse as e-response. 2

3 Infomation Gatheing Pattens fo Emegency Response with OpenKnowledge 539 In this pape, the poposed OpenKnowledge infastuctue is used to exploe its capability to suppot both centalized and decentalized infomation-gatheing pattens in open envionments. Fo this pupose, we built a simulation-based testbed fully integated with the OK platfom. The final goal of such vitual envionment is to evaluate this famewok in the e-response domain. In paticula, we implemented an e-response simulation envionment though which existing emegency plans based on eal-data ae modelled and simulated. Moeove, a suite of expeiments has been designed and un to evaluate the pefomance of the OK e-response system unde specific assumptions. Peliminay esults show the system s capability of suppoting the two afoe-mentioned achitectues and a compaable pefomance in both cases. The idea to test with simulations the effectiveness of diffeent data management achitectues within e-response settings is not new, as shown by the agent-based simulations developed in [7, 8, 9]. The est of the pape is oganized as follows: in Section 2, the fundamentals of the OK system ae pesented. Section 3 pesents the e-response case study, based on ealistic data and emegency plans, which is used to evaluate the OK system. In Section 4, the p2p simulation envionment achitectue is analysed and, in Section 5, the expeimental testbed designed fo the evaluation is pesented; hee the peliminay esults of centalized vs. decentalized infomation management achitectues ae discussed. Conclusion and futue wok ae given in Section 6. 2 THE OPENKNOWLEDGE SYSTEM The OpenKnowledge (OK) system povides the undelying pee-to-pee infastuctue needed to un ou expeiments. The coe concepts in OK ae: (1) the inteactions between agents, defined by inteaction models; and (2) a distibuted infastuctue, denoted as OK kenel, that suppots the publishing, discovey, execution, monitoing and management of inteaction models. Inteaction models 3 ae witten in the Lightweight Coodination Calculus (LCC) [2], an executable choeogaphy language based on pocess calculus and specifically designed to expess P2P style inteactions within multi-agent systems. Inteactions in LCC ae expessed as the message passing behavious associated with oles. The most basic behavious ae to send o eceive messages, whee sending a message may be conditional on satisfying a constaint(pecondition) and eceiving a message may imply constaints (postcondition) on the agent accepting it. LCC makes no commitment to the method used to solve constaints, so diffeent paticipants might opeate diffeent constaint solves (including human intevention). LCC clauses of some inteactions elevant to ou expeiments ae shown late in this pape (Figue 4, Section 4.1). The OK kenel [1] povides the laye that assoted sevices and applications can use to inteact using a choeogaphy-based achitectue able to deal both with the semantic heteogeneity of the actos and with thei discovey. The IMs ae 3 Hencefoth, we use the shothand tem IM in place of inteaction model.

4 540 G. Tecaichi, V. Rizzi, M. Machese, L. Vaccai, P. Besana published by the authos on a distibuted discovey sevice (DDS) with a keywodbased desciption. A pee willing to pefom a task (e.g., veifying the flood state in some aea), seaches fo published IMs by sending a keywod-based quey to the DDS which in tun collects them by matching the quey and sends back the list to the pee; it then selects an inteaction by compaing the constaints with its own capabilities; finally, it subscibes to one of the oles on the DDS. When, in a given inteaction, all the oles ae subscibed by at least one pee, a compatible team is fomed and the inteaction is executed. The pee s capabilities ae povided by plug-in components, called OpenKnowledge Components (OKCs) and consist of a set of Java methods. Figue 1 shows a snapshot of a netwok, when the oles in inteaction IM1 ae all subscibed by at least one pee. The pees have installed thei OKCs locally: some of them can be found online (e.g., OKC1, OKC2 and OKC3), othes might be pivate to a pee (e.g., OKC4). Subsciptions Published Inteaction Models OKC1 OKC2 P1 Pees DDS IM IM2 IM3 OKC1 OKC3 OKC1 P2 P3 OKC3 Nodes of the DDS: IMs and OKCs can be stoed in multiple locations OKC2 OKC1 Shaed OKCs P4 OKC1 OKC4 Locally installed OKCs Fig. 1. OpenKnowledge achitectue 3 EMERGENCY RESPONSE: A CASE STUDY This section pesents the case study used to evaluate the OK system: an e-response scenaio. In paticula, we consideed a flooding disaste in Tento (Italy). The wok stated fom a peliminay analysis on this kind of disaste, esulted fom documents elated to the cuent flood emegency plan foeseen by the Tentino egion and fom inteviews with expets. We selected emegency pees(e.g., fiemen,

5 Infomation Gatheing Pattens fo Emegency Response with OpenKnowledge 541 police, bus/ambulance agents, etc.), the main oganization involved(e.g., Emegency Coodination Cente, Fie Agency, Civil Potection 4, etc.), a hieachy between the actos (e.g., emegency chief, subodinate pees, etc.), sevice pees (e.g., wate level sensos, oute, weathe foecast and GIS sevices) and a numbe of possible scenaios, i.e., possible inteactions among the agents and thei assigned tasks. The pees can be distinguished into two main categoies: sevice pees and emegency pees. While the fome ae basically pees poviding sevices unde equest, the latte ae pees often acting on behalf of human agents that ae in chage of ealizing the emegency plan. Ou analysis esulted in the modeling of the pe-alam and the evacuation phases of the emegency plan. In the pe-alam phase, an Emegency Monitoing System (EMS) continuously gathes data fom wate level sensos placed in stategic points (beak points) along the ive. It also checks weathe infomation in ode to enich the data needed to pedict the evolution of a potential flood. When a citical situation is egisteed, the automatic system notifies the emegency chief, who can then decide whethe to enact the evacuation plan o not. The evacuation phase egads all the activities needed to move people to safe places. Hee, the key pees ae emegency pees, i.e., all the pees in chage of helping in the evacuation of citizens: emegency coodinatos, fiemen, govenment agencies (e.g., civilian potection depatment), eal-time epotes (e.g., people, sensos). Of couse, the emegency pees ae suppoted by sevice pees such as oute sevices and sensos scatteed acoss the emegency aea. The evacuation plan consideed consists of agents (e.g., emegency subodinates such fie-fightes) moving to specific locations assigned by the chief. In ode to move, they need to pefom some activities: choosing a path to follow by asking a oute sevice; checking if the path is pacticable by inteacting with the CP o with available epotes distibuted in the aea; poceeding along the path. The CP is able to seve equests on the blockage state of a given path, since it continuously gathes infomation fom epotes (e.g., sensos) scatteed aound the emegency aea and epoting the wate level egisteed at thei locations. Figue2sketchesthetwophasesinvolvedinoucasestudy. Itshowstheinvolved actos (denoted by ound cicles), thei inteactions and the kind of infomation exchanged. The smooth ectangle denotes the simulato, i.e., the vitual envionment whee all the pees act; obviously, it does not coespond to any entity in the eality, theefoe, we do not descibe it in this context. Howeve, the simulato is essential fo the simulation-based testbed and will be illustated in detail in Section 4.2. It also shows two diffeent evacuation sub-scenaios: in both of them, an emegency subodinate (ES) needs to get infomation on oute s pacticability but while in one case (aea above the ed line) such pee gets oute infomation by asking the CP, in the othe one (aea below the ed line) it inteacts diectly with epotes (1, 2, 5) physically pesent at the locations of inteest. These two infomationgatheing pattens ae efeed to as centalized and decentalized stategies. 4 Hencefoth, we use the shothand tem CP in place of Civil Potection.

6 542 G. Tecaichi, V. Rizzi, M. Machese, L. Vaccai, P. Besana WFS weathe conditions wate level at beak points s1 EMS s4 s2 alam s3 EC diective oute RS Simulato action ES ES ES oute status wate level at city locations CP wate level at city locations centalized stategy decentalized stategy Pealam Evacuation Fig. 2. e-response case study: pe-alam and evacuation phases 4 THE PEER-TO-PEER SIMULATION ENVIRONMENT To fully use and test the OK system in the peviously descibed e-response scenaio, we built a p2p simulation envionment. The cuent e-response simulation envionment is based on the system pesented in [4] and extends it both in a complete integation with the OK kenel and in the inclusion of a ealistic flood-simulato. The testbed is used to evaluate IMs, coodination tasks and the divese emegency infomation-gatheing models; though simulations, it is possible to estimate how the platfom could pefom in a eal-wold emegency. In paticula, the developed e-response system is used to: 1. model and execute inteactions among pees (e.g., institutional agents, individuals, sensos, web sevices) involved in emegency esponse activities; 2. povide feedbacks about the envionment at appopiate moments, in a way that mios the eal wold (fo example, an agent attempting to take a oad will be infomed at that moment if that oad is blocked, and it can then shae this infomation with othe pees though the netwok); 3. visualise and analyze a simulated coodination task though a Gaphical Use Inteface (GUI). The e-response system is composed of two main components: the pee netwok and the e-response simulato. Figue 3 sketches its oveall achitectue. All pees ae equipped with thei own OKCs; black aows epesent LCC inteactions eithe among simulato pees o between simulato and netwok pees; the gey aows indicate inteactions among netwok pees only. 4.1 The Pee Netwok The pee netwok epesents the goup of agents involved in a simulated coodination task. An agent in the pee netwok can inteact with othe agents, pefom some

7 Infomation Gatheing Pattens fo Emegency Response with OpenKnowledge 543 Flood Sub-Simulato Flood Contolle Visualise Visualise simulato simulato pee LCC inteaction btw netwok pees Connect/Sensoy-Info OK plug-in netwok pee Emegency Monitoing System Wate Senso Pefom Action Repote pee netwok Gazettee Sevice Emegency Coodinato Emegency Subodinate Queie Repote WMS Weathe Sevice Check Route State Civil Potection Find Route Route Sevice Fig. 3. The e-response system s achitectue actions (e.g., move along a oad) and gathe infomation (e.g., sense the wate level in its vicinity). In ode to pefom an action o eceive sensoy infomation nea its location, a pee must connect to the simulato by enacting the Connect IM. Once added to the simulation, the connected pee peiodically eceives sensoy infomation fom the simulato via the Sensoy-Info IM; finally, to pefom an action, a connected pee enacts the Pefom-Action IM which models the action coodination with the simulato. The connected netwok pees ae called physical pees (shaded ellipses in Figue 3). Not all pees must connect to the simulato: non-physical pees, such as a oute sevice that povides existing outes, do not need to communicate with the contolle but only with othe pees in the pee netwok. In the eal wold such pees would not actuallybe in the disasteaea and could not affect it diectly, but could povide sevices to pees that ae thee. Non-physical pees ae epesented as not shaded ellipses in Figue 3. The inteactions modeled as LCC specifications among the netwok pees which take place duing the evacuation phase (see Figue 2) can be ecaped as follows: 1. Stat evacuation: the emegency coodinato EC alets its subodinates to go to a specific location. The team-membes pepae to satisfy the diective;

8 544 G. Tecaichi, V. Rizzi, M. Machese, L. Vaccai, P. Besana 2. Find a oute: an emegency subodinate ES equests a path connecting its cuent location to the destination fom a oute sevice RS; 3. Check path conditions: a subodinate ES elies eithe on the CP (centalized stategy) o on epotes dislocated in the inteested aea (decentalized stategy) to get infomation on the oute s pacticability; 4. Gathe info fom epotes: an agent (e.g., CP, ES) equests eal-time wate level infomation fom a goup of epotes. The Stat evacuation IM is the main one in the selected use case. It simulates the evacuation phase and can be used in all those situations whee an emegency chief sends the diective of eaching specific locations to its subodinates. In shot, an emegency subodinate ES eceives an alet message fom the chief and esolves someconstaintsinodetosetthegoaltobeachieved(eachthegoaldestinationg) and get the cuent position. The activities of ES thus evolve though thee key oles: the goal achieve ole which abstactly models the activity of seaching fo a path and moving towads the goal; the fee path finde ole which defines the opeations needed to find a fee path; the goal move ole which models the actions needed to move towads the goal destination. Figue 4 shows an LCC code snippet fo two of the key ES oles. The constaints specified in bold indicate that they ae solved by enacting sepaate IMs. This is a key functionality of the OK platfom, since it allows to wite simple, modula and eusable LCC specifications. In paticula, the constaint equest path state enacts the Check-Route-State ( Queie-Repote ) IM when the centalized(decentalized) infomation-gatheing stategy is adopted. The execution of both IMs is needed to get oute condition infomation and then decide whethe to go ahead o to find anothe path. Howeve, while in the centalized scenaio the CP acts as the only povide of such infomation, in the decentalized setting thee is a diect inteaction between an emegency subodinate ES and a set of epotes. In this last case, afte having found a oute, the pee subscibes to the Queie-Repote IM, selects an appopiate goup of epotes and stat inteacting with them. The selection of a suitable goup of epotes is done by looking at the epote s subsciptions etuned by the DDS and that indicate thei cuent locations. 4.2 The e-response Simulato The simulato is designed to epesent the envionment whee all the involved agents act. It is composed of thee modules which ae themselves pees: the contolle, the flood sub-simulato, and the visualise (Figue 3). The contolle egulates the simulation cycles and the management of the simulated agent activities; the flood sub-simulato epoduces the actual evolution of the 1966 flood in Tento; the visualise stoes simulation infomation used by the GUI to view a simulation un in a step-by-step way. The simulato does not intefee o help the coodination among netwok pees: it just simulates the eal wold.

9 Infomation Gatheing Pattens fo Emegency Response with OpenKnowledge 545 a(emegency_subodinate,ff):: alet(g) <= a(emegency_chief,ffc) then null <- set_goal(g) and get_cuent_position(cupos) then a(goal_achieve(cupos,g),ff) a(goal_achieve(fom,to),ga):: ( //moving pee aleady at destination null <- equal(to,fom) and setgoalachieved(to) o ( //ty to find a fee path a(fee_path_finde(fom,to,feepath), GA) then //no fee paths between Fom and To null <- FeePath=[] and setgoaluneachable(to) a) a(fee_path_finde(fom,to,feepath), FRF) :: null <- find_path(fom,to,path) then ( //no paths ae found null <- Path=[] and makeemptylist(feepath) o ( //check if the path is fee null <- equest_path_state(path,pathstate) and path_fee(pathstate) then null <- assign(path,feepath) ) o //seach fo an altenative path which is fee a(fee_path_finde(fom,to,feepath), FRF) ) b) Fig. 4. LCC fagments; a) goal-achieve ole, b) fee-path-finde ole Contolle dives the simulation cycles and keeps tack of the cuent state of the wold. In ode to achieve that, it needs to know what changes ae happening to the wold and updates its state accodingly. Afte updating its state, it also infoms the elevant pees of these changes. The simulation thus evolves though cycles (o time-steps). A simulation cycle foesees two main opeations: Gatheing changes: the contolle eceives infomation about the changes that happened to the wold:

10 546 G. Tecaichi, V. Rizzi, M. Machese, L. Vaccai, P. Besana 1. it eceives the disaste (e.g., flood) changes fom the disaste sub-simulato via the Flood IM and 2. it seves equests of pefoming(move) actions with the Pefom-Action IM(see Figue 3). In this latte inteaction, the contolle veifies whethe cetainactions ae legalo not befoe they ae pefomed, and if a cetain action is illegal, the pee is infomed of the eason of failue; Infoming pees: the contolle sends infomation about the changes that happened in the wold: 1. it sends, at each time-step, local changes to each connected pee via the Sensoy-Info IM and 2. it sends, to the visualise, infomation on (a) the locations of all connected pees; (b) the status of the epote pees (e.g., available, esponding to equests) and (c) the wate level egisteed; hee, the Visualise IM is used. Befoe a simulation cycle initiates, some peliminay activities ae pefomed: establish key paametes (e.g., numbe of simulation cycles, timeouts, wate level thesholds), connect with the flood sub-simulato, shae with it the initial topology of the wold, and add connecting pees. Once a simulation cycle teminates, the contolle updates the time-step and stats the next cycle. Note that, due to the modulaity of the above achitectue, it is easonably easy to add as many disaste sub-simulatos (e.g., landslides, eathquake, etc.) as needed. Flood sub-simulato simulates a flood in Tento town (Italy). The equation defined in its coe OKC is based on flooding levels and flooding timings deduced fom existing flood models. The flood sub-simulato has been developed in Java and it is fully integated into the OK platfom. The main component is an OK pee that subscibes to two IMs: the fist is enacted at the beginning of the simulation to shae the topology (e.g., point of inteests and oads) of the wold between the contolle and the flood sub-simulato pees and to stoe, in the contolle local knowledge, the connection state of the sub-simulato; the second one, ( Flood, in Figue 3) is used by the contolle at evey time-step, to get fom the flood sub-simulato the wate level changes egisteed at the topology nodes. Visualise enables the GUI used to visualise the simulation. In paticula, the GUI shows the infomation povided by the contolle though the Visualise IM. At evey time-step, the visualise eceives the changes and updates its histoy accoding to the new infomation. The update esults in a change on the GUI. Figue 5 shows the appeaance of the GUI in the simulated centalized and decentalized scenaios. A geen dot epesents a epote pee available fo giving infomation on the wate level egisteed at its location; a gey dot epesents

11 Infomation Gatheing Pattens fo Emegency Response with OpenKnowledge 547 this pee actually giving this infomation; the wate level at a location is depicted as a blue cicle whose size depends on how high the wate level is; finally, the hat epesents the emegency subodinate. The lack of space pevents us to descibe all the developed LCC IMs. Fo moe details, we diect the inteested eade to the technical epot [3]. 5 THE EXPERIMENTAL TESTBED This section descibes the evaluation of the OK famewok in the e-response domain. A seies of expeiments simulating both centalized and decentalized infomation gatheing stategies wee conducted with a thee-fold aim: 1. Show the OK system in action, illustating that all pats of the system ae capable of woking cohesively in the desied manne. 2. Veify that the technology povided by OK suppots diffeent infomation-gatheing pattens. 3. Establish whethe the OK paadigm can make positive diffeences in pefomance between such disaste scenaios. In paticula, what is expected (and desiable) is to have the OK P2P famewok compaable o even impoving taditional centalized systems when specific fault conditions aise. In espect to the last point, the hypotheses to be tested ae that: 1. unde ideal conditions, the OK system exploited in its decentalized natue is compaable in pefomance to taditional centalized systems and 2. it impoves on conventional centalized systems when specific fault conditions aise. In this pape, we only test the fist hypothesis, leaving the exploation of the second one to futue wok. 5.1 Expeimental Design To design ou expeiments we established adequate pefomance measues, analyzed the vaiables involved, and set some assumptions. Pefomance measues fo the pesented expeiments: 1. the pecentage of times an emegency subodinate aives at destination; 2. the tavelling time, i.e., the numbe of time-steps needed to each the destination. These indicatos ae used to compute and compae the expeimental esults.

12 548 G. Tecaichi, V. Rizzi, M. Machese, L. Vaccai, P. Besana a) a) Fig. 5. e-response GUI; a) Centalized and b) Decentalized infomation-gatheing

13 Infomation Gatheing Pattens fo Emegency Response with OpenKnowledge 549 Expeimental vaiables a list of the vaiables consideed follows: A. Numbe of moving pees: the numbe of pees moving to a specific destination. Since the main aim is to compae two diffeent stategies (centalized vs decentalized) athe than to make a ealistic simulation, this vaiable is fixed to 1 in all expeiments. By unning an expeiment a cetain numbe of times, we compute the pefomance 1. of the simulated scenaio. B. Distance: set of paths in the topology connecting two locations. To get significant esults it is cucial to conside, fo each expeiment type, the outes coveing both safe and flood-pone aeas. C. Flooding law: how the flood evolves ove time. The flooding law, which is fixed in ou expeiments, stongly affects the outcome of an expeiment un: a pee may eithe aive at destination o be blocked depending on how apidly the flood popagates along the oute taken. D. Numbe of nodes: locations included in the topology and those whose status can be epoted by some pee. Incementing this numbe is useful to test the capacity of the OK kenel to suppot many pees. In ou testbed, this vaiable is the numbe of nodes composing only those outes involved in a given expeiment. E. Numbe of (epote) pees pe node: the numbe of epotes located in one node. As befoe, this vaiable is useful to test the obustness of the OK kenel and, moeove, the effectiveness of some of its modules. Assumptions in ode to intepet the esults in a easonable way, the following assumptions wee set: 1. the CP pee has infinite esouces (unde ideal conditions). This means that thepeeisabletoseveanynumbeofsimultaneousequestsandthecommunication channel neve beaks; theefoe, unde this assumption, bottleneck poblems due to ovewhelming equests neve occu; 2. a queie, asking a cetain numbe of epotes fo an info, will eceive all the answes within a time-step. This is due to how the time-step inteval is set: the value is such that the time elapsing between one time-step and the next one is sufficiently high to guaantee the eplies fom all the epotes. With such assumptions, we simulate a scenaio whee advantages and disadvantages of both centalized and decentalized achitectues ae kind of balanced. The configuation of the expeiment is sketched in Table 1: each expeiment is un 10 times; at each un, the only vaiables that change ae the destination assigned and the locations whee epotes ae pesent. Such locations ae detemined accoding to the set of outes associated with the destination assigned. The flooding law, the numbe of emegency subodinates and epotes emain unchanged duing all uns. Each expeiment consists in the simulation of the evacuation scenaio descibed in the pevious section. Independently on the kind of stategy adopted, the final

14 550 G. Tecaichi, V. Rizzi, M. Machese, L. Vaccai, P. Besana Vaiable Settings Exp N o Infomation Gatheing Runs A B C D E 1 centalized distance/un fixed 70 x un 1 2 decentalized distance/un fixed 70 x un 1 Table 1. Expeiments configuation (no fault conditions) goal of an emegency subodinate is to safely each the assigned destination. Thee ae thee possible expeimental outcomes: 1. the agent eaches the destination by following the fist oute found; 2. the agent finds blocked outes but finally eaches the destination afte a numbe of altenative paths and 3. the agent does not each the destination at all. 5.2 Expeimental Results Afte having un an expeiment, the elative simulation was visualized on the GUI in ode to analyze the movements of the emegency pees and veify the coect mechanism in the coodination among the agents. Figues 5,a) and b) show a simulation un fo the centalized and decentalized scenaio, espectively. Figue 5 a) shows the agent out fom the flooded aea. Hee, all the dots ae gey, meaning that all epotes ae being queied by the CP in ode to obtain the wate level of thei location. Some of them egiste high levels of wate. Figue 5b) shows the agent moving along a oute which can be deduced by the gey dots ahead of the agent; in fact, these dots epesent those epotes located along the oute followed and theefoe queied by the moving agent; all the othe epotes emain available (geen dots). Hee, the OK paadigm is exploited in its decentalized natue, since the infomation-gatheing is based on the use of distibuted infomation epote agents and not on a unique povide, as in the fist case. Figue 6 a) shows the outcome distibution obtained by unning 10 times the fist expeiment. As can be seen, 70 pecent of the time the expeiment has outcome 1) (the pee eaches the destination without poblems) while 30 pecent of the time the outcome is 3) (the pee does not each the destination). The outcome 2) is neve obtained. Although we setup the outes in ode to cove diffeent kind of aeas (eithe safe o flood-pone aeas), the case whee an agent finds fee outes afte a e-outing neve happens. This could be explained by consideing how the design of the flooding law and its elated flood speed affect the evolution of the scenaio. The outcome distibution elated to the second expeiment, which simulates the decentalized scenaio, is identical to the one found fo the fist expeiment and hence is not epoted hee. This esult can be explained with the assumptions peviously made: asking infomation on the oute s pacticability to eithe the CP o epotes scatteed aound the city does not make the diffeence.

15 Infomation Gatheing Pattens fo Emegency Response with OpenKnowledge 551 Figue 6b) shows the time taken (measued as the numbe of simulation timesteps) by an agent to each the goal location accoding to the shotest distance (in tems of intemediate locations) between the initial position and the final destination. The tend is shown fo both expeiments. It can be obseved that, in both cases, the time needed to achieve the goal is nealy equal to the shotest distance. This can be explained by how the simulation is designed an agent moves fom a location to the next one exactly in a time-step and by the missing outcome 2). Finally, Figue 6 b) eveals vey simila tends fo both centalized and decentalized scenaios. Again, this is mainly due to the assumptions made and the vaiable settings. In view of the esults descibed above, we can conclude that ou fist expectation is met: the use of the OK famewok suppots both achitectues (centalized and decentalized) and povides compaable pefomances unde the selected ideal assumptions. 6 CONCLUSIONS AND FUTURE WORK This wok focuses on testing whethe the OK famewok is capable to suppot the coodination of emegency activities and how, in absence of fault conditions, the OK p2p famewok is compaable in pefomance to taditional centalized gatheing appoaches. An agent-based e-response simulation system fully integated with the OK infastuctue has been developed. It is used to model specific emegency scenaios and agents in tems of both LCC specifications and OKC components. A suite of expeiments has been designed and un to evaluate the pefomance of the OK e-response system in diffeent scenaios and unde specific assumptions. The peliminay esults thus obtained show how the OK infastuctue is equally effective in both centalized and decentalized infomation-gatheing. We ae cuently woking on futhe expeiments. In paticula, we want to epeat the descibed expeiments by inceasing the numbe of uns and by tuning paametes like the flood speed and the outes to follow, so that diffeent outcomes can be obtained. This way, we could econfim ou hypothesis in a moe obust setting. Also, we want to un expeiments whee two types of fault conditions ae injected: failues in the communication channels and inaccuate signaling. Fo this, the following vaiables will be consideed: Distibution of tustwothy (epote) pees: numbe of tustwothy epotes, i.e., pees always epoting accuate wate level values. By setting this vaiable, the fault due to inaccuate signaling, its location and its seveity can be simulated. Degadation of the CP communication channel: measued as the likelihood of a fault in the communication channel of the CP agent. Fo example, a degadation of the 80% means to have this agent seving incoming equests only 20% of the times.

16 552 G. Tecaichi, V. Rizzi, M. Machese, L. Vaccai, P. Besana OUTCOME DISTRIBUTION expeiment=centalised wl_th=0.8 Destination not eached, 30% Destination eached without e-outing, 70% Destination eached with e-outing, 0% Destination not eached Destination eached with e-outing Destination eached without e-outing a) 40 Timesteps vs. Path Lenght Timesteps Path Lenght Centalized b) Decentalized Fig. 6. a) Outcome Distibution, b) Time-steps vs. Path Length Distibution of degaded epote s communication channels: defines, fo each epote communication channel, the pobability of its disuption. With these new expeiments, we can investigate if and eventually unde which conditions a complete p2p achitectue impoves the oveall pefomance and obustness ove taditional centalized achitectues. Finally, in espect to the simulated scenaios and the involved agents, it is woth to conside the epote agents as mobile agents athe than fixed sensos, and thus to exploe how

17 Infomation Gatheing Pattens fo Emegency Response with OpenKnowledge 553 the OK platfom suppots the coodination of team-membes in an emegency site. Acknowledgements This wok was suppoted by the OpenKnowledge poject (FP ). REFERENCES [1] Siebes, R. Dupplaw, D. Kotoulas, S. Peeau de Pinninck, A. van Hamelen, F. Robetson, D.: The OpenKnowledge System: An Inteaction-Centeed Appoach to Knowledge Shaing. In: CoopIS [2] Robetson, D.: A Lightweight Coodination Calculus fo Agent Systems. In: Lectue Notes in Compute Science DALT, Vol. 3476, 2005, pp [3] Tecaichi, G. Rizzi, V. Vaccai, L. Pane, J. Machese, M.: Openknowledge Deliveable 6.8: Summative Repot on Use of OK Appoach in eresponse: Integation and Evaluation Results. Technical epot, Openknowledge poject, [4] Machese, M. Vaccai, L. Tecaichi, G. Osman, N. McNeill, F. Besana, P.: An Inteaction-Centic Appoach to Suppot Pee Coodination in Distibuted Emegency Response Management. In: IDT, Special Issue on Incident Management, Vol. 3, No. 1, 2009, pp [5] D Apano, F. de Leoni, M. Mecella, M.: Emulating Mobile Ad-Hoc Netwoks of Hand-Held Devices. The OCTOPUS Vitual Envionment. In: Poc. of the ACM Wokshop on System Evaluation fo Mobile Platfom: Metics, Methods, Tools and Platfoms (MobiEval) at Mobisys, [6] Mecella, M. Cataci, T. Angelaccio, M. Buttazzi, B. Kek, A. Dustda, S. Vetee, G.: Wokpad: An Adaptive Pee-To-Pee Softwae Infastuctue fo Suppoting Collaboative Wok of Human Opeatos in Emegency/Disaste Scenaios. In: CTS [7] Bellamine-Ben, Saoud N. Ben Mena, T. Dugdale, J. Pavad, B. Ben Ahmed, M.: Assessing Lage Scale Emegency Rescue Plans: An Agent Based Appoach. Special Issue on Emegency Management Systems. In: IJICS, Vol. 11, 2006, No. 4, pp [8] Kanno, T. Moimoto, Y. Fuuta, K.: A Distibuted Multi-Agent Simulation System fo the Assessment of Disaste Management Systems. In: IJRAM, Vol. 6, 2006, No. 4 5, pp [9] Massague, D. Balasubamanian, V. Mehota, S. Venkatasubamanian, N.: Multi-Agent Simulation of Disaste Response. In: ATDM Wokshop in AAMAS 2006.

18 554 G. Tecaichi, V. Rizzi, M. Machese, L. Vaccai, P. Besana GaiaÌÖ Ö is a Ph.D. student at the Univesity of Tento. She is cuently woking on the LiveMemoies poject fo the development of an advanced Web 2.0 platfom enabling communities in the constuction of pesonal and collective memoies. Sheisalsoinvolvedinthe Glocal poject, whoseaimistobuild an event-based multimedia etieval system. She woked on the OpenKnowledge poject and, in paticula, on the evaluation of the OK famewok in the e-response domain. She obtained a Maste Degee in compute engineeing fom the Univesity of Palemo. VeonicaÊ ÞÞ is a eseachtechnician at Univesity of Tento. She cuently woks on the LiveMemoies and the EU-funded Glocal pojects. She holds a postgaduate degee in compute science fom the Univesity of Tento. MauizioÅ Ö is Associate Pofesso of compute science at the Depatment of Infomation Engineeing and Compute Science, Univesity of Tento. He is autho of ove 80 publications and has been pogam coodinato of a numbe Euopean Reseach Pojects. His main eseach inteest ae: the design and development of sevice achitectues in distibuted systems; the integation of sevices in Geogaphical Infomation Systems (GIS) envionments; the analysis, development and integation of sevices to suppot scientific knowledge ceation and dissemination pocesses.

19 Infomation Gatheing Pattens fo Emegency Response with OpenKnowledge 555 LoenzinoÎ Ö has eceived his Ph.D. examining the semantic inteopeability between geogaphic web sevices fom the Univesity of Tento, Italy; his M.Sc. fom the same univesity, and his B.Eng. fomthe TuinPolytechnic, Italy. He is now woking at the Euopean Commission (DG JRC) as a post-doc eseache. Woking in the ENABLE action of the SDI Unit, he undetakes eseach to suppot the development of the Euopean Spatial Data Infastuctue foeseen by the INSPIRE diective, focusing on the inteopeability of spatial data and sevices. He peviously woked in the FP6 EU-funded Open- Knowledge poject that investigated the dynamic and semantic integation of components and sevices in open, pee-to-pee (P2P) systems. Pio to joining the JRC, he woked fo thiteen yeas at the Autonomous Povince of Tento (PAT), as a GIS/SDI specialist. Duing his pemanence at PAT, he also joined the Italian geogaphic national committees of CPSG and SINA. His pevious wok has also included softwae design in the field of eal time embedded systems, closed loop systems and PID contolles in distibuted and centalized envionments. His eseach inteests include semantic inteopeability and spatial data infastuctues, GIS management, P2P achitectues fo emegency esponse and semantic web issues. Paolo Ò is a post doctoal eseache at the Univesité de Rennes I. He is cuently woking on ASTEC poject fo automating the pesceening of patients fo clinical tials. Peviously he woked in the UK-funded Safe and Sound poject, aiming at ceating a distibuted appoach to medical decision suppot systems and in the EU-funded OpenKnowledge poject, whose taget was the dynamic integation of the components and sevices in open, pee-to-pee systems. He holds a Ph.D. in Infomatics fom the Univesity of Edinbugh and a postgaduate degee in telecommunication engineeing fom the Politecnico of Milan.