Anya Apavatjrut, Katia Jaffres-Runser, Claire Goursaud and Jean-Marie Gorce Combining LT codes and XOR network coding for reliable and energy efficient.
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Slide 1
Anya Apavatjrut, Katia Jaffres-Runser, Claire Goursaud and
Jean-Marie Gorce Combining LT codes and XOR network coding for
reliable and energy efcient transmissions in wireless sensor
networks Sarnoff Symposium (SARNOFF), 2012 35th IEEE
Slide 2
Outline Introduction Reaching reliability Gradient broadcast
routing Through coding: LT codes Combining LT codes and gradient
broadcasting Improving energy with network coding XOR network
coding heuristic XLT-GRAB Performance results
Slide 3
Introduction In large scale wireless sensor network A node
advertises its data to one or several sink nodes. The transmission
is multi-hop between the data source node and the sink. High
reliability is important. To increase reliability Introducing
redundancy through path diversity Adding a coding layer on top of
the routing algorithm
Slide 4
Multi-path routing Several copies of a same packet travel on
multiple paths in parallel Increasing transmission reliability Also
increasing in energy expenditure for redundant transmission
Gradient broadcast algorithms Allow several nodes at a time to
forward a same packet in broadcast based on pre-defined set of
forwarding rules A cost field is set in an initialization stage
Nodes are able to adjust locally to instantaneous changes in the
network node failure or link failure. More flexible Increasing the
number of copies traveling in the network.
Slide 5
Adding coding layer Each message m Encoded using a specific
coding algorithm Adds redundancy to m to compensate for the losses
Still retrieve m at the sink HARQ Fountain codes A source S can
potentially generate a limitless number of encoded packets until it
receives an acknowledgement from D. D only acknowledges end to end
a successful decoding to S This acknowledgement can be merged with
the gradient cost field maintenance packets of the protocol.
Slide 6
In this paper Adding fountain codes to a gradient broadcast
algorithm Perfect reliability To reduce the number of redundant
packets travel in the network. Using network coding, relays
re-combine the received packet along the multi-hop diffusion We
show in a simulation study how our implementation of a XOR network
coding solution over an LT code [2] performs over a simple gradient
broadcast algorithm: Reliability is maintained at a reduced energy
and delay cost.
Slide 7
Gradient broadcast routing Broadcast mode Any relay hearing a
packet has to decide whether it can forward it or not. Only relays
located closer to the sink than the previous hop relay are allowed
to forward packets. 1. Cost field setup The nodes distributively
build the gradient cost field 2. Forwarding stage [26] F. Ye, A.
Chen, S. Liu, and L. Zhang. A scalable solution to minimum cost
forwarding in large sensor networks. In International Conference on
Computer Communications and Networks: Proceedings, pages 304309,
2001.
Slide 8
Cost field setup If Q p +L < Q A then update Q A= Q p +L
L=the link cost A new ADV packet is sent with a new packet cost Q p
= Q A Sink : ADV packet containing its own cost Q Q=0 flooding All
the other nodes have an initial cost Q = + node A QAQA : ADV packet
with packet cost Q p
Slide 9
Cost field setup The node with the lowest value of Q A sends
its packet first Prevents other nodes with higher costs from
forwarding their ADV packet. With this algorithm, only one ADV
packet per node is sent in the cost field setup stage. The link
cost value can be expressed in various metrics (in hops, in meters,
etc..). We consider a simple euclidian distance metric.
Slide 10
Forwarding stage Once a sensor S has a packet to send to the
sink, it appends its own cost Qs to the packet and broadcasts it.
All nodes receiving it decide to forward it if and only if their
own cost Q i is lower than Qs. This algorithm is particularly
reliable compared to single path routing Having very low control
overhead but at the price of a very high packet redundancy.
Slide 11
Gradient broadcast routing Following works Creating additional
forwarding rules to improve the tradeoff between reliability and
energy consumption We control the amount of redundancy by
introducing a forwarding probability p f. If the sensor is allowed
to forward a packet based on its cost, it will do it with
probability p f. [12], [13]. [12] K. Jaffr`es-Runser and C.
Comaniciu. A probabilistic interference and energy aware gradient
broadcasting algorithm for wireless sensornetworks. In Proceedings
of IEEE ISWPC 2008, Santorini, Greece,2008. [13] K.
Jaffr`es-Runser, C. Comaniciu, J.-M. Gorce, and R. Zhang. U-GRAB:A
Utility- Based Gradient Broadcasting Algorithm for Wireless Sensor
Networks. In IEEE Conference on Military Communications (MILCOM
2009), Boston, MA, USA, October 2009.
Slide 12
Through coding: LT codes Fountain codes provide both rate-less
and universal property Transmission reliability can be assured
without requiring channel state information LT code Having lower
decoding complexity But at the price of a very high packet
redundancy [17] M. Luby. LT Codes. In Foundations of Computer
Science - FOCS 2002, pages 271, Vancouver, BC, Canada, November
2002. IEEE Computer Society.
Slide 13
Combining LT codes and gradient broadcasting We have considered
a wireless sensor network 50 nodes spatially distributed following
a Poisson distribution in a 2 dimensional space of 500m500m.
Average node degree is of about three. The source first encodes the
information with LT codes before broadcasting the encoded message.
The message propagates in a relaying mesh from S to D following the
gradient broadcast routing defined earlier.
Slide 14
The following simulation results are obtained using WSNet
event- driven simulator [24]. Combining LT codes and gradient
broadcasting [24] WSNet. Worldsens simulator.
http://wsnet.gforge.inria.fr/.
Slide 15
Combining LT codes and gradient broadcasting In the
simulations, a message is decomposed into K fragments.
Slide 16
LT codes show a higher success rate on average for the same
forwarding probabilities compared to the no coding case. Even if LT
codes should ensure perfectly reliable transmissions, we do not
always obtain a success rate equal to 1. Because of bad
transmission conditions, nodes can keep trying (unsuccessfully) to
relay the new packets of the source. Combining LT codes and
gradient broadcasting
Slide 17
XOR network coding heuristic Transmission with network coding
More scalable and can lead to the optimization of complexity,
throughput, transmission delay and security. In this paper,we
applying intra-flow network coding to fountain encoded packets
Network coding can play an efficient role to optimize the
redundancy The degree d of the packet to be created at the relay
node is chosen with respect to the Robust Soliton distribution
Buffered packets are then randomly selected and XOR-ed together
until degree d is obtained or a MAXROUND value is reached if d {1,
2} then a combination is only performed with probability p=0.2
Slide 18
XOR network coding heuristic [2] A. Apavatjrut, C. Goursaud, K.
Jaffres-Runser, C. Comaniciu, and J.-M.Gorce. Toward increasing
packet diversity for relaying lt fountain codes in wireless sensor
networks. Communications Letters, IEEE, 15(1):52-54, January
2011
Slide 19
XLT-GRAB The source sends each message m using an LT-code K=100
This ADV message serves two purposes Namely acknowledging m
Updating the costs to account for topology changes in the network.
The source keeps transmitting coded packets until an
acknowledgement is received.
Slide 20
A relay node forwards a packet based on a probability p f if it
is located closer to the sink than the previous hop relay. A relay
decides with a given XORing probability p xor to apply network
coding using to forward a network coded packet instead of the
received one. XLT-GRAB
Slide 21
Performance results Performance results are averaged over 50
consecutive message transmissions, each message encoded with an LT
code. We have first evaluated the impact of p f and p xor on the
number of duplicated packets. p f < 0.4 : the network is not
reliable at all for whichever XORing probability p f > 0.6 : the
network is reliable for whichever XORing probability 0.4 < p f
< 0.6 : transitory area
Slide 22
Performance results
Slide 23
Slide 24
The end-to-end message transmission delay in seconds
Performance results
Slide 25
The total energy consumed by all nodes of the network for
emission and reception actions. Performance results