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Remote Deployment of Sensor Networks Case Study: Monitoring the mountains of Afghanistan.

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Presentation on theme: "Remote Deployment of Sensor Networks Case Study: Monitoring the mountains of Afghanistan."— Presentation transcript:

1 Remote Deployment of Sensor Networks Case Study: Monitoring the mountains of Afghanistan

2 Context Military monitoring of Oppositional Forces in remote, inaccessible areas like the mountains of Afghanistan and Pakistan using wireless sensor networks. The deployment and uplink methods in this application are largely unexplored

3 Kyber Pass – One of the more accessible roadways in this part of the world, rarely used by guerilla fighters

4 Main Problems Wireless sensor networks still require (in most applications): Manual (even if random) placement of nodes Infrastructure at head end These obstacles must be overcome to deploy a monitoring network readily in the target environment

5 Issues outlined today Distribution method (hands-off) Data aggregation, sensor configuration Uplink strategy (no infrastructure) Network management Energy optimization Security Final Goals

6 Distribution: Methods Air-scatter, Air-drop Likely conducted at night to avoid detection Multiple Launch Rocket System GOOD: Takes ground personnel out of dangerous or hostile-controlled terrain BAD: Result in very poorly-behaved, random distributions: wind currents or terrain features may cause many sensors to channel into a ravine, or river Ballistics and delivery will not be a main focus of this research

7 Distribution: Package Smart Dust or bigger motes could be dropped at altitude as a bundle with parachute… then scattered at low altitude to control distribution area Smart dust is great for military applications because it is small (appx 1mm), difficult to detect, can be dropped at high altitude Motes could be disguised as rocks…

8 Data, Sensors: The Target Seismic, audio, heat, visual, chemical, electromagnetic signatures Trucks, horses, pedestrians

9 Data, Sensors: Sensor Devices Heterogeneous approach: multiple types of sensors, nodes Since life of network is dependent on functionality of many types of nodes, lifetime and failure calculations become more complex

10 Data, Sensors: Sensor Devices Use passive or low power sensors as first- responders (piezoelectrics like audio, seismic) The first-responder sensors will wake up neighboring nodes with other sensors (thermal, visual, electromagnetic, chemical, radiological, etc) Power-hungry sensors should sleep as much as possible

11 Uplink: Heterogeneous Nodes Connect to military satellite constellation Uplink nodes will be different from sensor nodes: larger, more battery, more power Uplink nodes form some small % of all nodes

12 Uplink: Initialization How to initialize the network when the head is seen as being in multiple places? How to avoid partitioning? This will be researched and protocol developed. ?

13 Network: Expendable Uplinks Active

14 Network: Expendable Uplinks Active POWER LOW TAKE OVER

15 Network: Expendable Uplinks Active One can see this rerouting may be computation intensive, and is in fact similar to MANET routing when nodes fail. The main difference here: the network can still be operational if it is partitioned.

16 Network: Protocols A significant undertaking of the project is to develop and simulate the protocol which reassigns the network head in an energy efficient manner for various configurations Important to optimize whole network power consumption

17 Network: Protocols Routing must transition to avoid periods of downtime or routing confusion Current head node must select its successor to eliminate routing confusion

18 Energy: Lifetime Network needs to be operational for at least a few months at a time: otherwise satellite monitoring becomes preferable in some circumstances The heterogeneous nodes will have to adapt to over-stimulus to keep network alive. i.e. if animals constantly pass by the network and trip seismic sensors, they should be able to be ignored in favor of reliable detectors like electromagnetic

19 Security Primary risk is detection of presence not data decoding Spread spectrum, noise-like signals should be used “Chatter” must be kept to minimum Alert uplinks are okay

20 Security The network may be compromised by several means: Stimulate for false positives, perhaps rapidly depleting the network of energy Compromise the uplink signal/device Jamming

21 Security: Countermeasures Detect, isolate, ignore false-positive flood input Encode uplink transmission Spread spectrum jam resistant communications links

22 Goals Develop basic application proposal for DARPA SBIR Identify one narrow topic within the system which needs research and development, write a paper on that topic Current candidate for narrow research: protocol to identify, shift network head- ends

23 Conclusions Next lecture will involve the analysis of key challenges, quantitative approaches, and outline of the draft proposal for DARPA


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