Providing End-to-End Delay Guarantees for Multi-hop Wireless Sensor Networks

1. Providing End-to-End Delay Guarantees forMulti-hop Wireless Sensor Networks I-Hong Hou

2. Motivation • Wireless sensor networks are being deployed for real-time surveillance

3. Challenges • Wireless sensor networks can be deployed over a large area • Multi-hop transmissions are required to deliver sensed data • Need to provide end-to-end delay guarantees • Sensors are limited in transmission capacityand may suffer from low transmission reliability

4. Contributions of this Work • Study the problem of providing end-to-end delay guarantee and throughput guarantee for multi-hop wireless sensor networks • Develop scheduling policies for two kinds of networks • Provide simulation results to justify the performance

5. Network Model 3 6 • A number of sensors transmitting data to a base station through multi-hop transmissions • A routing tree is formed by the routing protocol, with the base station being the root • h(n) = parent of n • h(6) = 4 • h(5) = 2 1 7 4 r 2 8 5 9

6. Traffic Model • Time is slotted and grouped into intervals of length T time slots • Each sensor may generate several flows • Packets generated in an interval need to be delivered before the end of the interval, or they are dropped Flow 1 Flow 2 Deadline T

7. Channel and QoS Model • When a sensor n transmits to its parent, the transmission is successful with probability pn • A flow f requires its throughput to be at least qf • A scheduling policy is feasibility optimal if it satisfies requirements of all flows whenever feasible

8. Communication Model • Consider two types of sensor networks • Orthogonal relay system: Sensors can transmit and receive simultaneously • Sensors are equipped with full-duplex radio, or they use OFDMA • Half-duplex system: Sensors can either transmit or receive. They can receive one transmission at a time

9. Solution Overview • Debt of flow f at interval k: • Theorem: A policy that maximizes in every interval is feasibility optimal Indicator function of packet delivery

10. Orthogonal Relay System • Greedy Forwarder: Each sensor transmits the packet with the largest debt among the available ones in each time slot • Theorem: Greedy Forwarder is feasibility optimal for orthogonal relay system

11. Half Duplex System • Closest Sensor First: Order packets by the number of hops between their current sensor and the base station, break ties by their debts • Use this ordering to greedily select a maximal set of packets that can be transmitted simultaneously • Theorem: Closest Sensor First is feasibility optimal for line topologies • Line topology: all flows are originated at the same sensor

12. Simulation Setup 3 6 • 12 flows generated by sensors 3, 5, 6, 7, 8, 9 • Channel reliability is randomly selected from [0.4, 0.9] • Half of the flows require qf = α, others require qf = β • Compare two policies • Random policy • Static priority 1 7 4 r 2 8 5 9

13. Results for Orthogonal Relay Systems

14. Impact of Delayed Information • Sensors notify their children information about debts periodically • Sensors far away from the base station has stale information

15. Results for Half Duplex Systems

16. Conclusion • Study the problem of providing end-to-end delay guarantees for wireless sensor networks with unreliable transmissions • Develop scheduling policies for both orthogonal relay system and half duplex system • They offer provable performance guarantees • Simulation results show that they are superior than other policies