Providing End-to-End Delay Guarantees for Multi-hop Wireless Sensor Networks I-Hong Hou.

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Presentation transcript:

Providing End-to-End Delay Guarantees for Multi-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) = r

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 1Flow 2Deadline

Channel and QoS Model When a sensor n transmits to its parent, the transmission is successful with probability p n A flow f requires its throughput to be at least q f 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 q f = α, others require q f = β Compare two policies –Random policy –Static priority r

Results for Orthogonal Relay Systems

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

Results for Half Duplex Systems

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