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Explore a novel approach using stationary battery-powered relays, known as Throwboxes, maximizing network performance while addressing individual energy constraints in Disruption Tolerant Networks (DTNs). The design goals, mobility prediction engine, lifetime scheduler, prototype, and experimental results are discussed. Enjoy substantial power savings and routing performance boosts with this innovative architecture!
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An Energy-Efficient Architecture for DTN Throwboxes Presenter: Zhe Chen Author: Nilanjan Banerjee, Mark Corner, Brian N. Levine
What are Disruption Tolerant Networks ? • DTNs are sparse networks with low node density • Nodes are largely disconnected • Transfer data through intermittent contacts • 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
Examples of DTN UMass DieselNet [Burgess et al. Infocom 06]
Limitations of Mobile DTNs • Do you have enough capacity in your DTN? • Most influential factor in DTN performance? • the frequency and number of contact opportunities • How can we increase contacts? • more mobile nodes=$$$$ • or change the mobility pattern of nodes • (mobility patterns inherent to a particular network)
Observation Place a relay and create a virtual contact Route A Route B
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
Solution : Throwboxes • Throwboxes: stationary battery powered relays • has radios and storage • cheap, small, easy to deploy • Challenges • Previous paper: where to place these boxes thus maximize network performance: ? [Wenrui et al. : Mass 06] • Power management: trade of between nodes’ lifetime and connection opportunities • Aim: maximize performance and simultaneously meet individual energy constraints
Outline • Design Goals • Throwbox Architecture • Mobility Prediction Engine • Lifetime Scheduler • Throwbox Prototype and Deployment • Experimental Results • Power Savings • Routing Performance • Conclusions
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
Primary source of overhead • Energy cost of neighbor discovery • Idle, on and off, searching contacts • DTN networks • Sparse, is it worth the cost of waking the node
Mobility Measurement and Prediction • 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(is it worth?) • 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
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. • C1 ... Cnevents, each has • total energy cost ei(weight), bytes transferred di (value) • Energy constraint P ∙t (capacity) • Solution is subset of events s.t. (∑ei ≤ P∙t) and maximizes ∑di
Token Bucket Approach new tokens ? Events Battery capacity Takenevents Ignored or skipped events • 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
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)
Throwbox Placement Throwbox deployed on bikes in UMassDieselNet
Power Savings (equivalent transfers) • 20x less power than periodic wakeup • 5x less power than just mobility prediction
Routing performance • Throwbox at 80mW equivalent to best case.
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
Energy performance • Need larger cell, but perpetual operation possible • Unanswered questions about solar variation