Current Research in Sensor Networks

1. Boleslaw K. Szymanski Thomas Babbitt, EyuphanBulut, Chris Morrell,ZijianWang Center for Pervasive Computing and Networking & Department of Computer Science Rensselaer Polytechnic Institute Troy, New York Current Research inSensor Networks

2. Lecture Hall Algorithm and Local Leader Election Lecture Hall Algorithm Voice in a lecture hall behaves similarly as wireless communication medium in sensor networks Implicit Synchronization Point (receiving a data packet) • Based on a commonly observable event/signal • Synchronization for free (byproduct of observing the event/signal) Prioritized Backoff Delay • Converting a metric or a combination of several metrics into time • Equivalent to assigning different priority values to nodes Optional Reinforce Acknowledgement (receiving an acknowledgement packet) • To suppress multiple announcements Local Leader Election The problem of finding a node with the desired property among a local group of nodes • A leader is a node that possesses the desired property, such as largest/smallest value of a variable, a distance, a load, etc. Possible applications: • Routing • Clustering • Building blocks for other, more complicated algorithms The traditional approach requires at least log(n) messages and log(n) time There is a better way!

3. The larger the better The smaller the better Sender Target Routeless Routing The closer to the target node is, the higher priority it should have How to estimate the distance to the target node? • Listening to packets coming from the target • The number of hops these packets have traveled is an estimate of the distance • Bidirectional links required Path Preference (PP) – give the previous winner preference Packets always carry a field called desired hop count A receiving node retrieves the desired hop count from the packet, compares it with the known hop count to the target node, and then derive the backoff delay using the following formula: 0 if the node was a previous winner and PP is used U(0,1) is a random number function that returns uniformly distributed numbers from interval (0,1). Routing is based on a distance gradient: a packet sent to a destination is forwarded by the node among those that received it that has the lowest cost of forwarding.

4. Routing Illustration 4 1 3 2 S D Best student approach: the delay for the previous winner is zero! This creates a Preferred Path (PP), e.g. thick path below S D 5 1 4 2 3 A failure breaks the Preferred Path and establishes The new Preferred Path shown below X X 6 6 1 2 S D 5 1 4 2 3

5. A:2 F:1 A:1 F:2 D B A F A:3 F:3 C E A:1 F:3 A:3 F:1 Properties: (1) Fault Tolerance, and (2) Path Optimality When a node fails, other nodes take over immediately and seamlessly A:2 F:1 A:1 F:2 D B A F A:3 F:3 C E A:1 F:3 A:2 F:1 Every node learns something from any packet and randomness helps C F C F B E H B H A D G I A D G I C F C F B E H B E H A D G I A D G I

6. Routless Routing with Self-Healing: Failure Response Route repair via correcting hop distances • DATA packets update distance of upstream node to destination • HELLO packets sent when node reactivates • If HELLO packet improves route, it is forwarded • Example shows effect of node C going down Parameter tuning: • l in a back-off formula: speed versus probability of interference • Number of failed broadcast (with no response from a node one hope closer to the sender) needed for starting route repair algorithm: speed of recovery from permanent failures versus unnecessary overhead of adjusting the network to transient failures • Path preference setting: speed versus agility All three parameters must be tuned according to the mission goals, there is no single value best for different missions. Effect of node C going down

7. Data PKT node is > dist to Dest • Data PKT • Create/Send Ack PKT • Ack PKT New • Data PKT node is the Destination • Create/Send Ack PKT • Start Timer SendAck • Data PKT node ≤ dist to Dest • Start Timer (Four lengths) • 1. PP – λ/625 (min val TT) • 2. One Hop closer Rand(λ/4) • 3. Closer than one hop Rand(λ/4) + λ/4 • 4. Equal HC Rand(λ/2) + λ/2 AckPKT Timer Expires SSR(v3) : SHR-PP • AckPKT • Previous winner = 0 (no longer preferred path) • Data PKT from a node closer to the Dest. • Cancel the timer • Cancel sending the PKT if in the process of transmitting • Previous winner = 0 (no longer preferred path) Possible Ignore • Data PKT from a node closer to the Dest • Cancel the timer • Send Ack • Ack PKT • - Cancel the timer; • Timer Expires • Data PKT from a node closer to the Dest • Cancel the timer • Ack PKT • - Cancel the timer; • Timer Expires • Increase the hop count by 2 for the packet • - Send Data Packet • Timer Expires • Send Data Packet • Previous Winner++ (preferred path) • Start Timer • Data PKT from a node closer to the Dest and timer expired • Ack PKT • Cancel the timer; Father • Data PKT from a node closer to the Dest and timer active Owner Resend • Timer Expires • Send Data Packet • - Set timer

8. Self-healing Routing Performance: Sink Network SSR-PP outperforms AODV in all metrics

9. Conclusions and Future Work • The delivery ratio of SHR can be increased by replicating packets. Experiments show that the drops are largely independent of each other. The number of packets sent by SHR is much lower than by AODV or MintRout in unreliable environments. • Keeping radio on listening is nearly as expensive as transmitting For the cost of a delay, all node can sleep most of the time and awake periodically to listen for wake up call Nodes on the path may know from the source the time of the next packet, so can sleep the rest of the time The route repair involves waking nodes on alternative paths. The simulation and experimental measurements of this version of SHR are being conducted with initial results encouraging in terms of energy savings. 4. Data-driven routing Finding the node with the largest (smallest) value (measurements) in the field by following the gradient of the values (measurements) (scent, flavor following in bio systems: e.g., field based coordination), establishing priority based on data content.

10. Quality-Cost Tradeoff in Cooperative Networking Collaboration Motivation: • Sensor nodes have limited sensing range to sense the environment. • Collaboration of nodes can increase the knowledge of each sensor about the environment. • It also brings an extracommunication cost to the sensor network and the application. • We look at this tradeoff in four different applications: • Coverage Redundancy Based Sleep Scheduling • Traffic Light Adjustment Problem • Random Sleeping Schedule Routing • Mobile Sink Routing

11. Simulation Results for Sensing Coverage Problem • 500mx500m region • Rs=100m, Rt=30m • Average of 10 runs