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Combining LT codes and XOR network coding for reliable and energy efficient transmissions in wireless sensor networks. Anya Apavatjrut , Katia Jaffres-Runser , Claire Goursaud and Jean-Marie Gorce. Sarnoff Symposium (SARNOFF), 2012 35th IEEE. Outline . Introduction
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Combining LT codes and XOR network coding for reliable and energy efficient transmissions in wireless sensor networks Anya Apavatjrut , KatiaJaffres-Runser, Claire Goursaud and Jean-Marie Gorce Sarnoff Symposium (SARNOFF), 2012 35th IEEE
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
Introduction • In large scale wireless sensor network • A nodeadvertises its data to one orseveral sink nodes. • Thetransmission 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
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.
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.
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.
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. • Cost field setup • The nodes distributivelybuild the gradient cost field • 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 304–309, 2001.
Cost field setup : ADV packet containing its own cost Q • If Qp+L < QA then update QA=Qp+L L=the link cost • A new ADV packet is sent with a new packet cost Qp = QA Sink All the other nodes have an initial cost Q = +∞ Q=0 flooding node A : ADV packet with packet cost Qp QA
Cost field setup • The node with the lowest value of QAsends 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.
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 Qi 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.
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 pf . • If the sensor is allowed to forward a packet based on its cost, it will do it with probability pf . [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.
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.
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 500m×500m. • 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.
Combining LT codes and gradient broadcasting • The following simulation results are obtained using WSNet event-driven simulator [24]. [24] WSNet. Worldsens simulator. http://wsnet.gforge.inria.fr/.
Combining LT codes and gradient broadcasting • In the simulations, a message is decomposed into K fragments.
Combining LT codes and gradient broadcasting • 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.
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
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
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.
XLT-GRAB • A relay node forwards a packet based on a probability pfif it is located closer to the sink than the previous hop relay. • A relay decides with a given XORing probability pxor to apply network coding using to forward a network coded packet instead of the received one.
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 pf and pxor on the number of duplicated packets . • pf < 0.4 : the network is not reliable at all for whichever XORing probability • pf > 0.6 : the network is reliable for whichever XORing probability • 0.4 < pf < 0.6 : transitory area
Performance results • The end-to-end message transmission delay in seconds
Performance results • The total energy consumed by all nodes of the network for emission and reception actions.