Robin Kravets Tarek Abdelzaher Department of Computer Science University of Illinois The Phoenix Project.

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Presentation transcript:

Robin Kravets Tarek Abdelzaher Department of Computer Science University of Illinois The Phoenix Project

Consider the aftermath of a natural disaster No power Damaged communication infrastructure Goal Survivable communication and networking in post disaster scenarios Research Challenges Heterogeneous devices Diverse resource availability Diverse mobility patterns Robin Kravets, UIUC - January 2007 The-Day-After Networks

Project Goals Protocol Stack to support Disconnected operation Service oriented communication Resource limited environments Approach Exploit topology and mobility characteristics Adapt protocol behavior to changing conditions Robin Kravets, UIUC - January 2007 The-Day-After Networks Police

Robin Kravets, UIUC - January 2007 The-Day-After Networks Designing Protocols for DTNs Challenge Lack of models to describe network topology and mobility Question What high-level principles guide the design of efficient routing protocols for post-disaster DTNs?

Design Principles Conservation of popularity A node that has been popular in the recent past will continue to be popular in the near future Ties into the role of the node in the network Police-officer, rescue worker, etc Recurrence Many network nodes tend to perform recurrent activities Police patrols, supply shuttles, ambulances Clustering Nodes tend to cluster Due to mobility At aggregation points (supply centers, distress scenes, etc) Robin Kravets, UIUC - January 2007 The-Day-After Networks

Leveraging Popularity: Encouter-Based Routing Routing Quota-based protocols reduce resource usage Blindly distribute quota Approach Push quota to more popular nodes Protocol Every node maintains an encounter value (EV) Exchange EVs on contact Quota transmitted is in proportion to EV ratio Robin Kravets, UIUC - January 2007 The-Day-After Networks

Leveraging Popularity: Encouter-Based Routing Routing Quota-based protocols reduce resource usage Blindly distribute quota Approach Push quota to more popular nodes Protocol Every node maintains an encounter value (EV) Exchange EVs on contact Quota transmitted is in proportion to EV ratio Robin Kravets, UIUC - January 2007 The-Day-After Networks EBR 1.Resource efficient 2.Low overhead / state 3.Low complexity 4.High message delivery ratio

Leveraging Recurrence: Inter-Contact Routing Dynamic, yet predictable behavior Nodes may frequently meet a few other nodes at predictable times New routing Metric: Inter-contact delay Track recurrent contact times Construct paths with high delivery probability Robin Kravets, UIUC - January 2007 The-Day-After Networks B C A 20 ACAC ABAB 5 15 BC A 20 min loop 5 20 Encounter graphIC-Routing

Leveraging Recurrence: Inter-Contact Routing Dynamic, yet predictable behavior Nodes may frequently meet a few other nodes at predictable times New routing Metric: Inter-contact delay Track recurrent contact times Construct paths with high delivery probability The-Day-After Networks Inter-Contact Routing 1.Reduce end-to-end delay 2.Save resources by reducing the number of replicas

Leveraging Clustering: Mercury Observation Clustering occurs even in partitioned networks Augment store-carry- forward routing with path- based routing Base routing mechanism: Hop-by-hop opportunistic forwarding Use end-to-end routing when available Light-weight clustering Route discovery throughout lifetime of message Inter-cluster communication when nodes move in groups Robin Kravets, UIUC - January 2007 The-Day-After Networks Single hop connection opportunity Multi hop connection opportunity

Leveraging Clustering: Mercury Observation Clustering occurs even in partitioned networks Augment store-carry- forward routing with path- based routing Base routing mechanism: Hop-by-hop opportunistic forwarding Use end-to-end routing when available Light-weight clustering Route discovery throughout lifetime of message Inter-cluster communication when nodes move in groups Robin Kravets, UIUC - January 2007 The-Day-After Networks Mercury: 1.Improved delivery ratio 2.Low control overhead

Putting It All Together Target network is dynamic Valid principles change over time Approach: Adaptive Routing Dynamically use principles that are valid Routing layer is composed of several routing experts Routing expert focus on a specific principle Convert expert routing information to a common metric Routing decisions consult all experts Experts with valid assumptions provide high-confidence paths Robin Kravets, UIUC - January 2007 The-Day-After Networks

Resource Management: Congestion Control Observation Congestion is a global condition Nodes only have local (neighborhood) information Dynamically adjust replication rate Based on current network conditions Collect drop, duplicate delivery and message hop statistics Compare ratio of good (dups) over bad (drops) against congestion threshold Robin Kravets, UIUC - January 2007 The-Day-After Networks Congestion Decrease

Environment: Mobility Modeling Current models All nodes to follow the same behavior Persistent behavior Observations Object movement is heavily dependent on events Object reactions are completely dependent on the current role of the object High-level framework Event-driven Events directly change movement patterns Role-based Nodes assume roles, which react to events by changing their movement patterns Robin Kravets, UIUC – April 2009 The Phoenix Project

Additional Research Directions Context-awareness Survivor-activity recognition and distress situation detection Application automatically identifies likely distress Device sends an SOS signal for help Energy saving strategies Content batching to reduce total energy consumption Use of heterogeneous radios to improve communication energy efficiency Robin Kravets, UIUC – April 2009 The Phoenix Project

Robin Kravets Tarek Abdelzaher Department of Computer Science University of Illinois