On the Delay Distribution of Random Linear Network Coding

Nistor, Maricica; Lucani, Daniel E.; Vinhoza, Tiago T. V.; Costa, Rui; Barros, João

doi:10.1109/jsac.2011.110518

Cited by 63 publications

(41 citation statements)

References 22 publications

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“…Figure 6 shows the mathematical expectation of transmitting nodes ( ) versus . For OR, the theoretical values are calculated by (15). It shows that OR is close to NCCC when is near 0, which indicates that these two algorithms supply similar redundancy for original data when the link is in good state.…”

Section: Simulation Resultsmentioning

confidence: 87%

A Novel Energy-Efficient Reception Method Based on Random Network Coding in Cooperative Wireless Sensor Networks

Cheng

Yang

2015

International Journal of Distributed Sensor Networks

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This paper presents an opportunistic reception (OR) algorithm for energy-efficient transmission in cooperative wireless sensor networks (WSNs), where the characteristics of random linear network coding and the energy consumption property of WSNs are jointly considered. In OR, the sensor nodes in intermediate cluster generate the independent coding vector through simple forwarding or decoding-recoding manners opportunistically, so that the number of received packets can be reduced. To evaluate the algorithm, we derive the average number of received packets, the transmitting nodes, and decoding failure probability under specific assumption. The obtained theoretical and simulation results verify the effectiveness offered by the proposed approach.

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Section: Simulation Resultsmentioning

confidence: 87%

A Novel Energy-Efficient Reception Method Based on Random Network Coding in Cooperative Wireless Sensor Networks

Cheng

Yang

2015

International Journal of Distributed Sensor Networks

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“…State Definition: We adopt the state definition in [10] and say that a node has k degrees of freedom (dof) if the number of independent linear combinations at that node is k. Each state s is defined as s = (i 1 , i 2 , c), where i k is the number of dof at receiver R k , and c represents the dimension of the common knowledge between R 1 and R 2 . The state s(M, M, M ) is defined as absorbing state which shows that the packet transmission was completed.…”

Section: A An Mdp Model Of the Data Exchangementioning

confidence: 99%

Network coding for wireless cooperative networks: Simple rules, near-optimal delay

Khamfroush

Lucani

Barros

2014

2014 IEEE International Conference on Communications Workshops (ICC)

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We consider the problem of finding an optimal packet transmission policy that minimizes the total cost of transmitting M data packets from a source S to two receivers R1, R2 over half-duplex, erasure channels. The source can either broadcast random linear network coding (RLNC) packets to the receivers or transmit using unicast sessions at each time slot. We assume that the receivers can share their knowledge with each other by sending RLNC packets using unicast transmissions. We model this problem by using a Markov Decision Process (MDP), where the actions include the source of and type of transmission to be used in a given time slot given perfect knowledge of the system state. We study the distribution of actions selected by the MDP in terms of the knowledge at the receivers, the channel erasure probabilities, and the ratio between the cost of broadcast and unicast. This allowed us to learn from the optimal policy and devise two simple, yet powerful heuristics that are useful in practice. Our heuristics rely on different levels of feedback, namely, sending 1 or 2 feedback packets per receiver per M data packets by choosing the right moment to send this feedback. Our numerical results show that our heuristics are able to achieve the same performance of the MDP solution.

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“…In this case, the GS provides us with the minimum expected completion time. State Definition: We adopt the state definition in [8]. Each state is defined by three elements: s(i 1 , i 2 , c) where i 1 is the degree of freedom 1 of the received packets at receiver R 1 , i 2 is the degree of freedom of the received packets at receiver R 2 and c is the dimension of the common knowledge between receivers R 1 and R 2 .…”

Section: A Nc Scenariomentioning

confidence: 99%

Minimizing the completion time of a wireless cooperative network using network coding

Khamfroush

Lucani

Barros

2013

2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

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We consider the performance of network coding for a wireless cooperative network in which a source wants to transmit M data packets to two receivers. We assume that receivers can share their received packets with each other or simply wait to receive the packets from the source. The problem of finding an optimum packet transmission policy that minimizes the completion time in such a network is solved by modeling the problem as a Markov Decision Process (MDP). Our analysis is useful for a series of network coding and forwarding schemes with or without feedback. Our results show that the optimal network coding solution in terms of completion time, outperforms broadcasting with network coding by a factor of 2.13 and outperforms forwarding mechanisms by a factor of 6.1. Beyond computing the optimal completion time, we identify the critical decision policies derived from the MDP solution.

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On the Delay Distribution of Random Linear Network Coding

Cited by 63 publications

References 22 publications

A Novel Energy-Efficient Reception Method Based on Random Network Coding in Cooperative Wireless Sensor Networks

A Novel Energy-Efficient Reception Method Based on Random Network Coding in Cooperative Wireless Sensor Networks

Network coding for wireless cooperative networks: Simple rules, near-optimal delay

Minimizing the completion time of a wireless cooperative network using network coding

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