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University of Massachusetts, Amherst An Energy-Efficient Architecture for DTN Throwboxes Nilanjan Banerjee, Mark Corner, Brian N. Levine

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Presentation on theme: "University of Massachusetts, Amherst An Energy-Efficient Architecture for DTN Throwboxes Nilanjan Banerjee, Mark Corner, Brian N. Levine"— Presentation transcript:

1 University of Massachusetts, Amherst An Energy-Efficient Architecture for DTN Throwboxes Nilanjan Banerjee, Mark Corner, Brian N. Levine http://prisms.cs.umass.edu/dome

2 2 What are Disruption Tolerant Networks ? DTNs are sparse networks with low node density Transfer data through intermittent contacts Nodes are largely disconnected Come naturally from the applications they support Wildlife tracking Underwater exploration and monitoring Or from fragility and failures in the network itself Major natural disasters Jamming and Noise Power Failure

3 3 Examples of DTN UMass DieselNet [Burgess et al. Infocom 06]

4 4 Limitations of Mobile DTNs Do you have enough capacity in your DTN? what can you do about it? Most influential factor in DTN performance? the frequency and number of contact opportunities How can we increase contacts? more mobile nodes=$$$$ change the mobility pattern of nodes mobility patterns inherent to a particular network

5 5 Observation Place a relay and create a virtual contact Route B Route A

6 6 Solution : Throwboxes Throwboxes: stationary battery powered relays has radios and storage cheap, small, easy to deploy solar power=perpetual operation Challenges where do we place these boxes ? [Wenrui et al. : Mass 06] make them ultra low power for perpetual operation

7 7 Solution : Throwboxes Throwboxes: stationary battery powered relays has radios and storage cheap, small, easy to deploy solar power=perpetual operation Challenges where do we place these boxes ? [Wenrui et al. : Mass 06] make them ultra low power for perpetual operation

8 8 Outline Design Goals Throwbox Architecture Mobility Prediction Engine Lifetime Scheduler Throwbox Prototype and Deployment Experimental Results Power Savings Routing Performance Conclusions

9 9 Throwbox Design Goals Small form factor, portable and cheap Can be placed practically anywhere in the network Design should be general Applicable to wide variety of DTNs Should not use prior information about mobility patterns Run perpetually on solar panels of the size of the box Translates to a small average power constraint Optimization goal: maximize the number of packets forwarded for now, purely a local metric, not end-to-end delivery

10 10 Present Approches Use PSM on the 802.11 card [Anand et. al : MobiCom 2005] Neighbor Discovery Cost is huge (> 95% of total energy cost) Huge idle cost of the platform hosting the card Wasted Energy due to wakeups on brief contacts Use Dual Radio platforms [Jun et. al : Chants 2006] Huge idle cost of the platform hosting the radios Short range radio cannot detect a large number of contacts Energy consumption too high for perpetual operation !

11 11 Our Approach : Tiered Architecture Neighbor Discovery DTNs are sparse: discovery is extremely expensive Energy is wasted when waking the platform Data Transfer Requires a powerful WiFi Radio High power platform Tier-0 (low power): search peers, decide tier-1 wakeups Tier-1 (high power) : data transfers and routing

12 12 Overview

13 13 Buses transmit: pos, dir, and speed. Throwbox predicts: if bus will reach data-range before tier-1 can be woken? length of time in range Mobility Measurement and Prediction Track the probability the node enters data-range given series of cells it must traverse Statistics kept on each cell Markovian assumption allows simple calculation

14 14 Scheduling Each contact incurs fixed cost to wake tier-1 platform. Most efficient strategy: wake for largest contacts saves energy, but mostly designed to limit power 0-1 Knapsack problem reduces to this scheduling problem choose items to carry s.t. ( ∑weight ≤ capacity ) and maximizes ∑value. C 1... C n events, each has total energy cost e i (weight), bytes transferred d i (value) Energy constraint P ∙ t (capacity) Solution is subset of events s.t. (∑e i ≤ P ∙ t) and maximizes ∑d i

15 15 Token Bucket Approach Take this event, next event, or both? Token rate = average power constraint Estimate the size & energy cost ignore if insufficient tokens Compute tokens generated till next event based on tracking inter-arrival times If sufficient tokens for both events take current event If current event larger than next connection take it otherwise wait for next one new tokens Battery capacity ? Events Taken events Ignored or skipped events

16 16 Prototyping: Throwbox TelosB Mote (sensor) 900 MHz XTend radio 8 MHz microcontroller Stargate 802.11b CF card 400MHz PXA255 Xscale All DieselNet code Rechargeable cells, solar power, energy monitoring some custom hardware

17 17 Experimental Setup How effective is our energy management design? compare with single platform periodic wake up (PSM*) Two-platform with mobility prediction (WoW*) Can we really run it on solar-power? At reduced consumption does it still help? use the successful delivery metric Use trace-based simulation and deployment equipped 40 busses with XTend radios placed three Throwboxes for several weeks record contact opportunities with buses (both radios)

18 18 Throwbox Placement Throwbox deployed on bikes in UMassDieselNet

19 19 Power Savings (equivalent transfers) 20x less power than periodic wakeup 5x less power than just mobility prediction

20 20 Routing performance Throwbox at 80mW equivalent to best case.

21 21 Conclusions Placing relays in DTNs can produce huge performance boost Motivates studies on adding Meshes or Infostations to DTN Tiered Architecture can produce substantial energy savings Can lead to 31 times less energy consumption Need for systems to adapt to variable solar power Multi-radio systems are energy efficient in sparse networks Need for more efficient use of the XTend channel Low bitrate radio can be used to gather packet info Need to integrate power management into routing

22 University of Massachusetts, Amherst An Energy-Efficient Architecture for DTN Throwboxes Nilanjan Banerjee, Mark Corner, Brian N. Levine http://prisms.cs.umass.edu/dome

23 23 Throwbox Vs Infostations Infostations are hotspots connected to the Internet. Throwboxes are untethered routers in a DTN. Infostations build to provide mobile users with data of interest. Throwboxes act as routers to improve capacity of DTNs. Infostations designed with the motivation of providing always available service for urgent messages in cellular networks. Throwboxes designed with the motivation to engineer large number of contacts in disruption tolerant networks.

24 24 Energy performance Need larger cell, but perpetual operation possible Unanswered questions about solar variation


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