On Multi-Sensor Task Allocation
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This document summarizes Diego Pizzocaro's seminar on multi-sensor task allocation held at the University of Padova in April 2009. The seminar covered multi-sensor task allocation problems in both homogeneous and heterogeneous sensor networks. It discussed motivations and applications of sensor networks, presented examples of task allocation problems, and outlined algorithms for allocating sensors to tasks in different network types.
On Multi-Sensor Task Allocation
- 1. Seminar @ DEI Cardiff School of Computer Science University of Padova (Italy) April, 2009 On Multi-Sensor Task Allocation Diego Pizzocaro PhD candidate Supervisors: Prof. Alun Preece - Dr. Roger Whitaker http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 2. Brief Bio • 2007 - Computer Engineering, University of Padova (Italy), supervised by Prof. Luca Schenato • 2008 - Start PhD in Computer Science at Cardiff University (UK), supervised by Prof. Alun Preece and Dr. Roger Whitaker • International Technology Alliance (ITA) project: multi-national teams supported by complex information networks U.K. Ministry of Defence U.S. Army Research Lab • Our research focus: intelligent resource allocation in sensor networks. http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 3. Outline 1. Motivations & MSTA problem 2. MSTA in Homogeneous Sensor Network 3. MSTA in Heterogeneous Sensor Network 4. Taxonomy of MSTA problems 5. Conclusion http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 4. Motivation & MSTA problem http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 5. Sensors Simple sensors Platforms http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 6. Sensors Simple sensors Platforms http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 7. Sensors Tasks Simple sensors e.g. Search-&-Rescue mission Platforms http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 8. Sensors Tasks Simple sensors e.g. Search-&-Rescue mission TASK 3 TASK 4 Area Surveillance Area (possible threats) TASK 1 Platforms Surveillance (possible threats) Injured people to TASK 2 identify Injured people to identify http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 9. Scenario http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 10. Scenario • An already deployed network of sensors http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 11. Scenario TASK 3 TASK 7 Monitor Area weather Surveillance TASK 4 TASK 6 Identify Identify evacuation route evacuation route TASK 2 TASK 5 TASK 8 TASK 1 Area Monitor Surveillance Detect weather Injured vehicles people to identify • An already deployed network of sensors - Support multiple tasks to be accomplished simultaneously http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 12. Scenario TASK 3 TASK 7 Monitor Area weather Surveillance TASK 4 TASK 6 Identify Identify evacuation route evacuation route TASK 2 TASK 5 TASK 8 TASK 1 Area Monitor Surveillance Detect weather Injured vehicles people to identify • An already deployed network of sensors - Support multiple tasks to be accomplished simultaneously - Sensors are scarce and in high demand. http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 13. Scenario TASK 3 TASK 7 Monitor Area weather Surveillance TASK 4 TASK 6 Identify Identify evacuation route evacuation route TASK 2 TASK 5 TASK 8 TASK 1 Area Monitor Surveillance Detect weather Injured vehicles people to identify • An already deployed network of sensors - Support multiple tasks to be accomplished simultaneously - Sensors are scarce and in high demand. - Highly dynamic (sensor failures, change of plan) http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 14. Scenario “Where is it better to send that particular UAV?” TASK 2 TASK 1 Area Surveillance Injured people to identify • An already deployed network of sensors - Support multiple tasks to be accomplished simultaneously - Sensors are scarce and in high demand. - Highly dynamic (sensor failures, change of plan) http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 15. MSTA problem • We need schemes to allocate sensors to the task they best serve, considering all the relevant parameters. • In general we can have • static or mobile sensing devices • tasks requiring multiple sensors or one sensor • sensors shared or not shared between multiple tasks • etc... http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 16. MSTA problem • We need schemes to allocate sensors to the task they best serve, considering all the relevant parameters. • In general we can have • static or mobile sensing devices • tasks requiring multiple sensors or one sensor • sensors shared or not shared between multiple tasks • etc... • The fundamental question remains: Which sensor should be allocated to which task? http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 17. MSTA problem • We need schemes to allocate sensors to the task they best serve, considering all the relevant parameters. • In general we can have • static or mobile sensing devices • tasks requiring multiple sensors or one sensor • sensors shared or not shared between multiple tasks • etc... • The fundamental question remains: Which sensor should Multi-Sensor Task Allocation be allocated to which task? (MSTA) http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 18. MSTA applications • MSTA arises in a variety of domains: • environmental monitoring • natural disaster (e.g. earthquakes), .... http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 19. MSTA applications • MSTA arises in a variety of domains: • environmental monitoring • natural disaster (e.g. earthquakes), .... • We focus on military/humanitarian scenarios ‣ our allocation mechanisms can be applied to other domains! http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 20. MSTA applications • MSTA arises in a variety of domains: • environmental monitoring • natural disaster (e.g. earthquakes), .... • We focus on military/humanitarian scenarios ‣ our allocation mechanisms can be applied to other domains! • The task allocation process differs a lot when ‣ in a homogeneous sensor network (e.g. only seismic sensors) ‣ in a heterogeneous sensor network (e.g. seismic+UAVs+UGVs) http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 21. MSTA applications • MSTA arises in a variety of domains: • environmental monitoring • natural disaster (e.g. earthquakes), .... • We focus on military/humanitarian scenarios ‣ our allocation mechanisms can be applied to other domains! • The task allocation process differs a lot when ‣ in a homogeneous sensor network (e.g. only seismic sensors) ‣ in a heterogeneous sensor network (e.g. seismic+UAVs+UGVs) • We discuss two examples of MSTA instances in both networks http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 22. MSTA in Homogeneous Sensor Network http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 23. Why Homogeneous SN ? • Governmental institutions (ARL, MoD), and researchers suggest Wireless Sensor Networks (WSNs) as “the future” for military operations. http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 24. Why Homogeneous SN ? • Governmental institutions (ARL, MoD), and researchers suggest Wireless Sensor Networks (WSNs) as “the future” for military operations. • WSNs are often composed exclusively by hundreds of cheap miniaturized wireless sensors (called motes) with the same sensing capabilities. http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 25. Why Homogeneous SN ? • Governmental institutions (ARL, MoD), and researchers suggest Wireless Sensor Networks (WSNs) as “the future” for military operations. • WSNs are often composed exclusively by hundreds of cheap miniaturized wireless sensors (called motes) with the same sensing capabilities. • In general every network composed exclusively sensors with the same sensing capabilities is called “Homogeneous Sensor Network”. http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 26. Problem settings • We considered a particular instance of the MSTA problem in a Homogeneous Sensor Network (see DCOSS 08). • Assumptions: ‣ Sensors can serve only one task per time: Single-Task sensors - Therefore tasks are competing for the exclusive usage of a sensor x T2 T1 ‣ A task might require more than one sensor: Multi-Sensor tasks T1 ‣ Available info does not permit planning for future: Instantaneous allocation http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 27. Formal model • Tasks: Sensors ‣ vary in priority S1 (e11, c11 Tasks ) ‣ have a different demand for sensing resource (e 12 ,c (p1, d1, b1) capabilities T1 12 ) ‣ have to respect a budget (e.g. monetary). S2 • Each sensor: T2 (p2, d2, b2) ‣ S3 has a different utility for each task (e.g. geography & distance) ‣ has a different cost for each task. S4 e = utility of sensor to a task • Goal: c = cost of a sensor to a task maximizes the utility p = task priority while not exceeding the budgets of each task. d = task utility demand b = task budget http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 28. Allocation algorithms • At least as hard as the Knapsack problem which is NP-Complete ➡ we developed heuristic algs and compared them with state of the art pre-existent approaches. • Simulation environment implemented in Java (with Penn State University) http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 29. Allocation algorithms • At least as hard as the Knapsack problem which is NP-Complete ➡ we developed heuristic algs and compared them with state of the art pre-existent approaches. • Simulation environment implemented in Java (with Penn State University) • The algorithm which offers the best trade-off optimality Vs computational cost: MRGAP algorithm: ‣ a centralized algorithm: i.e. we collect all the info about the network in a single node ‣ it can be easily implemented as a distributed algorithm: less communication overhead. http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 30. MSTA in Heterogeneous Sensor Network http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 31. Why Heterogeneous SN ? • Sensor network deployment during military/humanitarian missions: ‣ UAV will fly on the battlefield and drop hundreds of motes ‣ Some motes might also be mobile. http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 32. Why Heterogeneous SN ? • Sensor network deployment during military/humanitarian missions: ‣ UAV will fly on the battlefield and drop hundreds of motes ‣ Some motes might also be mobile. • Therefore we have a sensor network composed by sensors with different sensing capabilities and mobility capabilities: “Heterogeneous sensor network” http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 33. Why Heterogeneous SN ? • Sensor network deployment during military/humanitarian missions: ‣ UAV will fly on the battlefield and drop hundreds of motes ‣ Some motes might also be mobile. • Therefore we have a sensor network composed by sensors with different sensing capabilities and mobility capabilities: “Heterogeneous sensor network” • Another example: Sensor Web by Open Geospatial Consortium (OGC) with environmental monitoring applications. http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 34. Problem settings • We considered a particular instance of the MSTA problem in a Heterogeneous Sensor Network. x • Same assumptions: T2 T1 ‣ Single-Task sensors ‣ Multi-Sensor tasks ‣ Instantaneous allocation T1 • Difference with homogeneous case: ‣ Combined utilities of groups of sensors (bundles) are in general much complex to compute than the homogeneous SN. TASK 1 Area video Surveillance (possible threats) http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 35. Problem settings • We considered a particular instance of the MSTA problem in a Heterogeneous Sensor Network. x • Same assumptions: T2 T1 ‣ Single-Task sensors ‣ Multi-Sensor tasks ‣ Instantaneous allocation T1 • Difference with homogeneous case: ‣ Combined utilities of groups of sensors (bundles) are in general much complex to compute than the homogeneous SN. Sensor bundles TASK 1 Area video Surveillance (possible threats) http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 36. Formal model • We first want to group sensors into bundles, and then we want to find the best assignment of bundles to tasks. Sensors Bundles Tasks S1 e11 B1 T1 (p1) S2 e1 2 S3 B2 T2 (p2) S4 e = joint utility of a bundle to a task p = task priority http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 37. Allocation mechanisms (1) • Problem well studied in Multi-agent Systems: Coalition formation • Typical approach: combinatorial auction ‣ bidders: tasks ‣ items: sensors ‣ tasks bids for bundles of sensors http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 38. Allocation mechanisms (1) • Problem well studied in Multi-agent Systems: Coalition formation • Typical approach: combinatorial auction ‣ bidders: tasks ‣ items: sensors ‣ tasks bids for bundles of sensors • Need to enumerate all possible bundles for each task. • Large number of sensors and tasks: the computational cost is too large. • Our contribution: Prune the set of bids placed by tasks (i.e. reduce the number of possible bundles). http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 39. Allocation mechanisms (2) • We define a system architecture in which we gradually reduce the search space of the allocation algorithms (see EKAW08). http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 40. Allocation mechanisms (2) • We define a system architecture in which we gradually reduce the search space of the allocation algorithms (see EKAW08). • Three main components: Reasoner < Package Config > Sensor types compatible with the task. Bundle Generator { < Bundle1, e1 >, < Bundle2, e2 >, ... } Sensor Bundles generated based on the package configuration. Allocation Algorithms http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 41. Allocation mechanisms (2) • We define a system architecture in which we gradually reduce the search space of the allocation algorithms (see EKAW08). • Three main components: Reasoner < Package Config > Sensor types compatible with the task. Bundle Generator { < Bundle1, e1 >, < Bundle2, e2 >, ... } Sensor Bundles generated based on the package configuration. Allocation Algorithms • Current work: Implementing/Testing this approach using the simulation environment “Player/Stage”. http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 42. Taxonomy of MSTA problems http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 43. Related work - MRTA • MSTA is closely related to Multi-Robot Task Allocation (MRTA): “Which robot should execute which task?" in a Multi-Robot System (MRS). http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 44. Related work - MRTA • MSTA is closely related to Multi-Robot Task Allocation (MRTA): “Which robot should execute which task?" in a Multi-Robot System (MRS). • Gerkey et al (2004) proposed an MRTA taxonomy: ➡ MRTA problems can be viewed as instances of other well-studied, optimization problems. ➡ therefore allowing comparison of different solutions. http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 45. Preliminary MSTA taxonomy • We propose a preliminary MSTA taxonomy as an extension of MRTA to cover important features of sensor networks (INFOCOM 09). http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 46. Preliminary MSTA taxonomy • We propose a preliminary MSTA taxonomy as an extension of MRTA to cover important features of sensor networks (INFOCOM 09). • MSTA taxonomy organized on four main axes: 1. Sensors: Single-task (ST) vs. multi-task (MT). 2. Tasks: Single-sensor (SS) vs. multi-sensor (MS). 3. Assignment: Instantaneous (IA) vs. time-extended (TA). 4. Sensor Network: Homogeneous (HO) vs. heterogeneous (HE). • Example: previously we have considered ST-MS-IA-HO and ST-MS-IA-HE http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 47. Conclusion • We have presented the general MSTA problem, • Discussed two MSTA instances with applications in military/humanitarian missions, • Outlined the need for a MSTA taxonomy and presented a preliminary version of it. http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 48. Conclusion • We have presented the general MSTA problem, • Discussed two MSTA instances with applications in military/humanitarian missions, • Outlined the need for a MSTA taxonomy and presented a preliminary version of it. • Future research: ‣ Refine MSTA taxonomy ‣ What are the most important SN features to include? ‣ Explore different MSTA instances: ‣ Heterogeneous SN with Multi-Task sensors (sensors can be shared) http://users.cs.cf.ac.uk/D.Pizzocaro [email protected]
- 49. Thanks for listening ! Cardiff School of Computer Science [email protected] http://users.cs.cf.ac.uk/D.Pizzocaro