Energy and Latency Control in Low Duty Cycle MAC Protocols Yuan Li, Wei Ye, John Heidemann Information Sciences Institute, University of Southern California.

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Presentation transcript:

Energy and Latency Control in Low Duty Cycle MAC Protocols Yuan Li, Wei Ye, John Heidemann Information Sciences Institute, University of Southern California WCNC 2005 Speaker : Shih-Yun Hsu

Outline Introduction Motivation Global Schedule Algorithm (GSA) Fast Path Algorithm (FPA) Experimental Results Conclusion

Introduction A B C Wake up Sleep

Introduction Sensor networks Changing batteries is difficult Energy efficiency is important Using sleep/wakeup MAC protocol S-MAC T-MAC ZigBee Schedule-based MAC can increase latency in a multi-hop network

Introduction Sleep/wakeup MAC protocol Multiple schedules can occur in large networks Nodes that share the same schedule are in the same virtual cluster Border nodes spend more time listening or sending data and therefore consume more energy Although some optimizations schedule such as S- MAC and T-MAC reduce latency, the sleep/wakeup cycle still incurs additional delay

Motivation Allows all nodes to converge on a single global schedule to saving energy Reduce the additional delay with schedule- based MAC

Global Schedule Algorithm (GSA) To converge on a single schedule Uniquely identify Propagate new schedules to other nodes Discover new schedules Assume it handle by the basic of sleep/wakeup MAC

GSA Uniquely identify A node may start a new schedule with the same ID when it reboots Assigned a random identifier each time when it reboots Combination of the schedule originator’s ID and the age of the schedule

GSA Propagate schedules A node discover a new schedule, it compare the age of the new schedule to its own schedule Change schedule to the older one If has the same age Compare the schedule ID Change schedule to the lower one When change to the new schedule, it will update its neighbor The new schedule will propagate through its virtual cluster

GSA ACBA Schedule ID : 1 Schedule Age : 0 Adopt AC Schedule ID :1 Schedule Age : 0 + t

GSA ACBA Schedule ID : 1 Schedule Age : 0 Adopt A Schedule ID : 2 Schedule Age : 50 B’s Schedule Age : 50 > A’s Schedule Age : 0 C Schedule ID : 2 Schedule Age : 50 Schedule ID : 1 Schedule Age : 50 + t C’s Schedule Age : 0 < A’s Schedule Age : 50

Fast Path Algorithm (FPA) When a packet travels over multiple hops it can be delayed when its next-hop node is sleeping FPA adds additional wakeup periods called fast path schedules along the path of source to sink

FPA Node 1 Node 2 Node 3 Node 4 Regular listen Fast path schedule Data transmission S-MAC

FPA Node 1 Node 2 Node 3 Node 4 Regular listen Fast path schedule Data transmission S-MAC

FPA Node 1 Node 2 Node 3 Node 4 Regular listen Fast path schedule Data transmission S-MAC T tx T cs d = T cs + T tx d 2d

FPA The request of FPA is piggybacked on the routing packet AODV DSR The time needed to transfer each following data packet in a n hop network over a fast path is approximately nd

FPA Node 1 Node 2 Node 3 Node 4 Regular listen Fast path schedule Data transmission Node 5

FPA When the fast path schedule overlaps with the regular listen time, data is transferred during regular listen time instead No explicit mechanism to remove fast path schedules When the routing path changes, another fast path is established along with the new path The old fast path will expire

FPA Many fast paths may exist at the same time Assume each node can support a small number of active paths each node maintained fast path independently If fast path slots from different paths overlap in time at a node This slot could be lengthened

Experimental Results - GSA Multiple schedules with GSA Using S-MAC without global scheduling in an outdoor network of 50 sensor node Schedule are identified by the initializing nodes IDs Schedule 1 is initialized by node 1

Experimental Results - GSA With linear topology 50 Mica2Dot motes with TinyOS S-MAC based 10% duty cycle Each nodes are placed about 90cm apart, making a line about 45m long. Set transmission power to the lowest level RF output power, -20dBm; PA POW, 01 Transmission range : 2m

Experimental Results - GSA Schedule adoption is based on which nodes hear each other, the order in which nodes are activated is important Randomly activate each mote at the start Each nodes turned on manually, in pre-experiment state, and listens continuously Broadcast a message from a central node to make all nodes to begin Collect sleep schedule information in the network Repeat the test for 4 times

Experimental Results - GSA Trigger packet was not always received by the nodes and in most experiments, 18 ~ 36% failed to participate

Experimental Results - GSA

- : failed to active * : initial the schedule X : use the primary schedule o : use the secondary schedule

Experimental Results - GSA FailWake1234Change %84%37.5% %49%29%67.6% 94129%37%27%7%100% %48%24%8%91.2%

Experimental Results - GSA Expected that schedule boundaries would be relatively distinct Only a few nodes on the border knowing multiple schedules Short-range radio reception is quite good to some distance

Experimental Results - FPA With linear topology 10 Mica2 motes with TinyOS S-MAC based 5% duty cycle Each motes are placed about 2m apart Transmission range : 3m

Experimental Results - FPA Source sent 10 unicast messages, each 100B long Each message is sent 25s after the previous Measure the arrival time of the message at each node Repeat the experiment 5 times each with and without fast paths enabled.

Experimental Results - FPA In the 100 packets transmitted in all the experiments, 2 packets are lost and not successfully retransmitted after 7 retries These packets will be ignored 6 packets were lost and then successfully retransmitted by the MAC layer The effect of these packets will be discussed

Experimental Results - FPA

Conclusion Global Schedule Algorithm (GSA) allows all nodes to converge on a single global schedule to conserve energy Fast Path Algorithm (FPA) allocate additional slots to avoid schedule misses and reduce latency GSA and FPA both are experiment with actual networks