Optimization Modeling andDecision Support forWireless InfrastructureDeployment in DisasterPlanning and ManagementMichael R...
Natural and Manmade DisastersCreate Problems for WirelessNetworks Damaged wireless mobile network basestations (towers an...
Impact from 2011 TohokuEarthquake and Tsunami
Impact from 2011 TohokuEarthquake and TsunamiRed areas are NTT DoCoMo service areas disrupted by the disasterand gray area...
Impact of 2011 TohokuEarthquake and Tsunami
Wireless Infrastructure Planningand Management During Disasters The Impacted Organizations◦ Local, state, federal governm...
Wireless Infrastructure and itsFacilitation of Social Media arePlaying Increasing Roles inEmergency Management For identi...
Dominant Uses of Social Media Duringthe 2011 Tohoku Earthquake andTsunami (as per a World Bank Report)Social media require...
In the Context of Last Year’sISCRAM Presentation and Beyond Ozceylan and Bartolacci looked at the impact of the availabil...
The Reality of Replacing WirelessInfrastructure Talk given at Wireless TelecommunicationsSymposium 2011 (WTS 2011) in New...
The Reality of Replacing WirelessInfrastructure Currently NTT DoCoMo has only about 50 truck-operated portable base stati...
The Reality of Replacing WirelessInfrastructure Softbank, Japan’s third largest mobilenetwork operator, lost 3,786 base s...
Mobile Base Stations andMicro, Femto, Pico Cells May BeDeployed
Mobile Base Stations andMicro, Femto, Pico Cells May BeDeployed
An Innovative Way to ProvideTemporary Wireless Connectivity Use of small helium-filled blimps for providingtemporary wire...
An Innovative Way to ProvideTemporary Wireless Connectivity Conversion of voice transmissions (shortmessages) to text and...
Emerging Network StandardsThat Can Be Applicable SON (Self Organizing Networks) – grew outof the 3GPP (Third Generation P...
Why Do Wireless TechnologiesInvolved Matter ? Conference reviewer questioned why thewireless network technologies should ...
Why Do Wireless TechnologiesInvolved Matter ? Conference reviewer questioned why the wirelessnetwork technologies should ...
We Examined the Literature forModels Addressing This Area Two Types of Wireless Infrastructure Modeling– Deterministic an...
We Examined the Literature forModels Addressing This Area Two Phases to the deployment of wirelessequipment in a disaster...
We Examined the Literature forModels Addressing This Area Planning Models◦ The only models in the literature examine thee...
Planning Problem in a DisasterContextRoot PLANNING problem is similar to the traditional FixedBase Station Location Proble...
Generalized CombinedOptimization Problem for Planningand Management Given an area affected by natural or manmade disaster...
Planning Problem in a DisasterContextAdditional Factors in the Context of Disaster PLANNINGthat May Be Incorporated The p...
Management Problem in a DisasterContextAdditional Factors in the Context of Disaster MANAGEMENTThat May Be Incorporated S...
Management Problem in a DisasterContextAdditional Factors in the Context of Disaster MANAGEMENTThat May Be Incorporated D...
Approaches In The Literature Fixed Base Station Location PLANNING Problem withAssignment of BS’s to Mobile Switching Cent...
Approaches In The Literature “Multiperiod Cellular Network Design via Price-Influenced Simulated Annealing (PISA)” – Meno...
Approaches In The Literature More Base Station Placement OptimizationProblems in the Literature◦ “Radio planning and cove...
Factors to Consider that areMissing in the Literature Capacity/Coverage for a given area can belimited by the network ope...
Factors to Consider that areMissing in the Literature Optimal linking of ad hoc infrastructures toportable base stations ...
Factors to Consider that areMissing in the Literature Notion of what is “connectivity”◦ Coverage for a proposed base stat...
Possible Optimization SolutionApproaches Quasi-Static◦ Assumes that demand is relatively static in all givenregions over ...
Next Steps Formulate a model with both Planning andManagement variables Choose a solution approach Attempt to solve to ...
 QUESTIONS ?◦ Michael Bartolacci – mrb24@psu.edu◦ Albena Mihovska – albena@es.aau.dk◦ Dilek Ozceylan – ozceylan@sakarya.e...
Optimization Modeling and Decision Support for Wireless Infrastructure Deployment in Disaster Planning and Management
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Optimization Modeling and Decision Support for Wireless Infrastructure Deployment in Disaster Planning and Management

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Michael R. Bartolacci, Albena Mihovska, and Dilek Ozceylan on "Optimization Modeling and Decision Support for Wireless Infrastructure Deployment in Disaster Planning and Management" at ISCRAM 2013 in Baden-Baden.

10th International Conference on Information Systems for Crisis Response and Management
12-15 May 2013, Baden-Baden, Germany

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Optimization Modeling and Decision Support for Wireless Infrastructure Deployment in Disaster Planning and Management

  1. 1. Optimization Modeling andDecision Support forWireless InfrastructureDeployment in DisasterPlanning and ManagementMichael R. BartolacciPenn State University – Berks, U.S.Albena MihovskaAalborg University, DenmarkDilek OzceylanSakarya University, Turkey
  2. 2. Natural and Manmade DisastersCreate Problems for WirelessNetworks Damaged wireless mobile network basestations (towers and associated equipment)(e.g. – 29,000 base stations were affected bythe 2011 Tohoku Earthquake and Tsunami) Damaged mobile switching centers Damaged “landline” connectivity (coaxial andfiber optic cable networks) that interface withthe wireless networks (e.g. - 1.9 millionfixed-line service subscribers were affectedby the 2011 Tohoku Earthquake andTsunami)
  3. 3. Impact from 2011 TohokuEarthquake and Tsunami
  4. 4. Impact from 2011 TohokuEarthquake and TsunamiRed areas are NTT DoCoMo service areas disrupted by the disasterand gray areas are fixed-line NTT East service areas disrupted bythe disaster in three Japanese prefectures (Iwate, Myagi, andFukushima with the earthquake location shown)
  5. 5. Impact of 2011 TohokuEarthquake and Tsunami
  6. 6. Wireless Infrastructure Planningand Management During Disasters The Impacted Organizations◦ Local, state, federal governmental agencies thatown/lease portable wireless network devices andmobile infrastructures and provide disaster relief◦ Mobile network providers with existing subscribersor connectivity in an affected region◦ Fixed line telecommunications providers in anaffected region◦ NGO’s that utilize wireless networks to providedisaster relief◦ Public utility companies and general commerce
  7. 7. Wireless Infrastructure and itsFacilitation of Social Media arePlaying Increasing Roles inEmergency Management For identifying/locating family, friends, etc. For coordinating emergency response For identifying/locating “persons of interest”(such as in Boston recently) For adding to the resilience of an affectedpopulace by allowing people to helpthemselves and their neighbors in real time(such as informing them where emergencysupplies will be distributed)
  8. 8. Dominant Uses of Social Media Duringthe 2011 Tohoku Earthquake andTsunami (as per a World Bank Report)Social media requires the network infrastructure to beoperable
  9. 9. In the Context of Last Year’sISCRAM Presentation and Beyond Ozceylan and Bartolacci looked at the impact of the availability ofwireless mobile connectivity on the resilience of a populaceaffected by a disaster (specifically looking at China and otherdeveloping countries) World Bank Report on telecommunications related to the 2011Tohoku Earthquake recommended improving the reliability ofcommunication networks in developing countries in the context ofnatural disasters by:◦ Reducing damage by developing backup systems, such asbatteries, generators, and backup trunk lines◦ Mitigating congestion by increasing the capacity of facilities such asswitching equipment◦ Restoring service by deploying emergency facilities, such as portableswitching equipment and portable satellite stations◦ All three have implications for modeling both the planning andmanagement of a portable wireless infrastructure
  10. 10. The Reality of Replacing WirelessInfrastructure Talk given at Wireless TelecommunicationsSymposium 2011 (WTS 2011) in New York City inApril 2011 by an official from NTT DoCoMo (Japan’sleading wireless mobile network operator)regardingthe aftermath of the 2011 Tohoku Earthquake andTsunami in March 11, 2011◦ The general tone of the talk spoke to the need to reactquickly and repair or replace several thousand non-functioning or destroyed base stations in the impactedareas, some with portable ones◦ He did not put forth any preplanning for such a deploymentand the assignment of mobile base stations in the affectedareas appeared to be conducted in an ad hoc fashion
  11. 11. The Reality of Replacing WirelessInfrastructure Currently NTT DoCoMo has only about 50 truck-operated portable base stations with 3G capabilitiesand is currently expanding its inventory of 4G ones The ability of a wireless network operator to comeback online quickly or be “robust” in the face of adisaster may even lead to greater customer loyalty orincrease subscriber base http://japandailypress.com/ntt-docomo-to-deploy-truck-based-lte-base-stations-0126160 During Superstorm Sandy, I went without power for 5days and without mobile network service for 3.5; Ihave mobile devices with two different carriers andAT&T stayed functional longer and came back onlinebefore Verizon, but I am unsure as to why
  12. 12. The Reality of Replacing WirelessInfrastructure Softbank, Japan’s third largest mobilenetwork operator, lost 3,786 base stations tothe 2011 Tohoku Earthquake and Tsunami http://www.softbank.co.jp/en/initiatives/csr/reconstruction/instance_01/contents_01/ The are installing new base stations withextended life batteries (but they only last for24 hours)
  13. 13. Mobile Base Stations andMicro, Femto, Pico Cells May BeDeployed
  14. 14. Mobile Base Stations andMicro, Femto, Pico Cells May BeDeployed
  15. 15. An Innovative Way to ProvideTemporary Wireless Connectivity Use of small helium-filled blimps for providingtemporary wireless mobile networkconnectivity Such balloon-based base stations would havea 3 km radius of coverage Softbank, Japan’s third largest wirelessmobile network operator is already testingthis platform for emergency use http://japandailypress.com/softbank-develops-blimps-for-floating-emergency-cell-towers-112047
  16. 16. An Innovative Way to ProvideTemporary Wireless Connectivity Conversion of voice transmissions (shortmessages) to text and sent over thenetwork as data packets (was done duringthe Japanese disaster in 2011) Use of VSAT technology (Very SmallAperture Terminal) which uses a smallsatellite dish and a LAN to connect smallmobile terminals to the Internet and forvoice communications
  17. 17. Emerging Network StandardsThat Can Be Applicable SON (Self Organizing Networks) – grew outof the 3GPP (Third Generation PartnershipProject) and created standards for networksthat self organize and self “heal” (deal withlink and node failures) LTE (Long Term Evolution) heterogeneousnetworks (HetNet) allows for the deploymentof picocells with little planning in terms oftheir integration into the network
  18. 18. Why Do Wireless TechnologiesInvolved Matter ? Conference reviewer questioned why thewireless network technologies should beincluded in the modeling discussion◦ Limited resource for any model developed isthe number of portable base stations available;and due to the variety of technologies that maybe employed, it imposes limits on the model◦ There are also opportunities for the inclusion ofinnovative technologies (such as the blimp-based base stations) into the modeling effort
  19. 19. Why Do Wireless TechnologiesInvolved Matter ? Conference reviewer questioned why the wirelessnetwork technologies should be included in themodeling discussion◦ Deployment of emerging technologies, such as hydrogenfuel cell powered base stations that could still operatewhen their power grid sources fail, may be factored intosuch a model (total cost to deploy a portable basestation and lost service until it is deployed against thecost of the fuel cell powered one)◦ Cost to retrofit existing base stations with generatorsand seismic reinforcement versus the cost to deployportable ones and the loss of service
  20. 20. We Examined the Literature forModels Addressing This Area Two Types of Wireless Infrastructure Modeling– Deterministic and Stochastic◦ Deterministic assumes stable (in otherwords, known) demand for capacity for each areaserved in the network over time and usuallyassumes fixed base station locations; the bulk ofthe literature for wireless infrastructure modelingassumes fixed base stations and known demand◦ Stochastic allows for variations in capacity demandand also variations in the topological design of theinfrastructure (such as the lack of any fixedstructure with an Ad Hoc Mobile network)
  21. 21. We Examined the Literature forModels Addressing This Area Two Phases to the deployment of wirelessequipment in a disaster context◦ Planning◦ Management There is a plethora of wireless infrastructurePlanning models in the literature; thoughnone of them specifically address their useduring or after a disaster
  22. 22. We Examined the Literature forModels Addressing This Area Planning Models◦ The only models in the literature examine theexpansion of capacity to new areas, addingcapacity to existing areas, or the assignment ofbase stations to switching centers (whichconnect to several base stations at once)◦ Essentially, they all examine the Planningphase in the context of normal day-to-dayoperations
  23. 23. Planning Problem in a DisasterContextRoot PLANNING problem is similar to the traditional FixedBase Station Location Problem (deterministic in nature)› Given a set of candidate sites for mobile base station locations and theassociated costs to use and connect each base station to form thewireless network architecture› Given a set of demand constraints (users in areas that must be served bythe architecture)› Choose the optimal design (locations for mobile basestations, microcells, picocells, etc.) for the network that minimizesoverall cost while satisfying demand (which may include minimumacceptable quality of service constraints or reflect a maximization oflevels of connectivity to serve)› Can be solved before a disaster for areas that may be impacted(essentially deciding where to place mobile base stations to cover a givenarea as if no previous infrastructure existed)
  24. 24. Generalized CombinedOptimization Problem for Planningand Management Given an area affected by natural or manmade disaster:› Provide wireless connectivity for the duration of the relief effortin the form of portable base stations, microcells, picocells, etc.(and possibly related ad hoc equipment) to support relief andrecovery efforts while maximizing connectivity (being able to geta usable signal to communicate across the affectedarea), minimizing the cost of deployment (or other similar goal)› Subject to: Budgetary costs constraints Availability of base station constraints over time (stochastic) Area connectivity coverage constraints over time (stochastic) Mobile base station location restriction constraints Portable Base station type match constraints Demand (capacity) constraints over time (stochastic) Fixed line connection point constraints Ad hoc architectural component constraints (could be stochastic)
  25. 25. Planning Problem in a DisasterContextAdditional Factors in the Context of Disaster PLANNINGthat May Be Incorporated The provisioning process for mobile base stations and relatedportable wireless infrastructure by networkproviders, governmental agencies, etc. may play a big role inthe practical application of any optimization model’s results andcould be included Provisioning directly relates to the availability of the mobilebase stations and related equipment from both a spatial and atemporal point of view; it forms the foundation for any costconstraints on their deployment and use (the more money youuse to acquire an inventory of mobile base stations andtransport them to staging or storage areas, the less you haveavailable for the actual setup and use when and where theyare needed)
  26. 26. Management Problem in a DisasterContextAdditional Factors in the Context of Disaster MANAGEMENTThat May Be Incorporated Some remnants of a pre-existing functioning cellularnetwork may exist to incorporate into a overall design forthe deployment of mobile base stations (for a networkoperator attempting to restore service), would requireincorporation into the planning model while managing itsimplementation There may be little functioning fixed line infrastructureremaining to connect to for data backhaul or PSTN(Public Switched Telephone Network) connectivity(forrural and “hard hit” areas)
  27. 27. Management Problem in a DisasterContextAdditional Factors in the Context of Disaster MANAGEMENTThat May Be Incorporated Due to terrain, land ownership, and similarfactors, during implementation, desired connectivitycoverage may require the integration of an ad hocnetwork architecture with the mobile base station cellulararchitecture, creating what is termed a “multi-hopcellular network” – not addressed in typical base stationoptimization models in the literature Only seen in a few traffic engineering models dealingwith protocol design for interoperability - “MediaHandling for Multimedia Conferencing in Multihop CellularNetworks” – Khedher, Glitho, and Dssouli (2009)
  28. 28. Approaches In The Literature Fixed Base Station Location PLANNING Problem withAssignment of BS’s to Mobile Switching Centers/Controllersincluded either as decision variables or incorporated intolocation constraints – most of these use a two stepoptimization approach where towers are first placed in anoptimal fashion and then assigned to switching centers◦ “Location Area Planning in Cellular Networks Using SimulatedAnnealing” – Demirkol, Ersoy, Caglayan, and Delic (2001)◦ “Location Area Planning and Cell-to-Switch Assignment in CellularNetworks” – Demirkol, Caglayan, and Delic (2004)◦ “UMTS base station location planning: a mathematical model andheuristic optimisation algorithms” – Yang, Aydin, Zhang, and Maple(2007) modeled as a p-median problem and used three meta-heuristics forsolving: genetic algorithm, simulated annealing and evolutionary-simulated annealing
  29. 29. Approaches In The Literature “Multiperiod Cellular Network Design via Price-Influenced Simulated Annealing (PISA)” – Menonand Amiri (2006) Takes a broader temporal view of the PLANNINGproblem and utilizes a hybrid heuristic with ideasfrom simulated annealing and linear programming
  30. 30. Approaches In The Literature More Base Station Placement OptimizationProblems in the Literature◦ “Radio planning and coverage optimization of 3Gcellular networks’ – Amaldi, Capone, and Malucelli(2008) Includes more technical aspects of the base station’scoverage characteristics in the optimization model◦ “Robust Tower Location for Code Division MultipleAccess Networks” – Rosenberger and Olinick (2006) Used a stochastic integer programming approach tooptimize locations under uncertainty of demand
  31. 31. Factors to Consider that areMissing in the Literature Capacity/Coverage for a given area can belimited by the network operator for a given typeof service◦ In other words, certain kinds of voice and data traffic can begiven priority therefore reducing the capacity needed tocover a given area (emergency traffic can be given prioritysuch as in the Japanese disaster where regular traffic on themobile networks available was reduced by 70% and fixed-line regular traffic was reduced by 90%) Cost/ability to implement substitutiontechnologies such as satellite communications
  32. 32. Factors to Consider that areMissing in the Literature Optimal linking of ad hoc infrastructures toportable base stations (ala a VSATarrangement, but with a terrestrial connectioninstead of satellite) Optimal preplanning of portable base stationplacement based on topography and otherphysical factors (it is possible to locate candidatesites ahead of time in areas prone to disasters)
  33. 33. Factors to Consider that areMissing in the Literature Notion of what is “connectivity”◦ Coverage for a proposed base station location is usuallyassumed based on signal strength with little thoughtgiven to the technology involved or related factors Time – very little exists in the literature withrespect to planning for changes in demand(usage) over time◦ Creates the need to deal with the mobility of portablebase stations
  34. 34. Possible Optimization SolutionApproaches Quasi-Static◦ Assumes that demand is relatively static in all givenregions over a short time window and optimize a modelfor the time window (probably using a suboptimalheuristic due to computing time necessities), thisapproach is a good compromise in order to reducecomplexity and time to solve, but requires re-optimization periodically as conditions change Stochastic◦ A dynamic programming approach gives a more cogentapproach to solving the problem, but can involve makingmany assumptions about future states in order to derivethe model adequately enough
  35. 35. Next Steps Formulate a model with both Planning andManagement variables Choose a solution approach Attempt to solve to optimality ifpossible, otherwise heuristically◦ Possibly a decomposition is required for solution Test the model with actual data andsimulation if possible
  36. 36.  QUESTIONS ?◦ Michael Bartolacci – mrb24@psu.edu◦ Albena Mihovska – albena@es.aau.dk◦ Dilek Ozceylan – ozceylan@sakarya.edu.tr

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