Providing End-to-End Delay Guarantees forMulti-hop Wireless Sensor Networks

I-Hong Hou

Motivation

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

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 capacity

and may suffer from low transmission reliability

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

Network Model

• 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

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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

T Flow 1 Flow 2 Deadline

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

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

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

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

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

Simulation Setup

• 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

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Results for Orthogonal Relay Systems

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1Greedy Forwarder

Static Priority

Random

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Impact of Delayed Information

• Sensors notify their children information about debts periodically

• Sensors far away from the base station has stale information

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1 Instant knowledgeUpdate period = 100Update period = 200

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Results for Half Duplex Systems

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0.8Closest Sensor FirstStatic PriorityRandom

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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