16 research outputs found
Informed Network Coding for Minimum Decoding Delay
Network coding is a highly efficient data dissemination mechanism for
wireless networks. Since network coded information can only be recovered after
delivering a sufficient number of coded packets, the resulting decoding delay
can become problematic for delay-sensitive applications such as real-time media
streaming. Motivated by this observation, we consider several algorithms that
minimize the decoding delay and analyze their performance by means of
simulation. The algorithms differ both in the required information about the
state of the neighbors' buffers and in the way this knowledge is used to decide
which packets to combine through coding operations. Our results show that a
greedy algorithm, whose encodings maximize the number of nodes at which a coded
packet is immediately decodable significantly outperforms existing network
coding protocols.Comment: Proc. of the IEEE International Conference on Mobile Ad-hoc and
Sensor Systems (IEEE MASS 2008), Atlanta, USA, September 200
Estudo de mercado de redes AD-HOC como plataforma colaborativa para jogos de telemóveis.
Tese de mestrado. Mestrado em Inovação e Empreendedorismo Tecnológico. Faculdade de Engenharia. Universidade do Porto. 201
Effective Delay Control in Online Network Coding
Motivated by streaming applications with stringent delay constraints, we
consider the design of online network coding algorithms with timely delivery
guarantees. Assuming that the sender is providing the same data to multiple
receivers over independent packet erasure channels, we focus on the case of
perfect feedback and heterogeneous erasure probabilities. Based on a general
analytical framework for evaluating the decoding delay, we show that existing
ARQ schemes fail to ensure that receivers with weak channels are able to
recover from packet losses within reasonable time. To overcome this problem, we
re-define the encoding rules in order to break the chains of linear
combinations that cannot be decoded after one of the packets is lost. Our
results show that sending uncoded packets at key times ensures that all the
receivers are able to meet specific delay requirements with very high
probability.Comment: 9 pages, IEEE Infocom 200
From Instantly Decodable to Random Linear Network Coding
Our primary goal in this paper is to traverse the performance gap between two
linear network coding schemes: random linear network coding (RLNC) and
instantly decodable network coding (IDNC) in terms of throughput and decoding
delay. We first redefine the concept of packet generation and use it to
partition a block of partially-received data packets in a novel way, based on
the coding sets in an IDNC solution. By varying the generation size, we obtain
a general coding framework which consists of a series of coding schemes, with
RLNC and IDNC identified as two extreme cases. We then prove that the
throughput and decoding delay performance of all coding schemes in this coding
framework are bounded between the performance of RLNC and IDNC and hence
throughput-delay tradeoff becomes possible. We also propose implementations of
this coding framework to further improve its throughput and decoding delay
performance, to manage feedback frequency and coding complexity, or to achieve
in-block performance adaption. Extensive simulations are then provided to
verify the performance of the proposed coding schemes and their
implementations.Comment: 30 pages with double space, 14 color figure
Coding Opportunity Densification Strategies for Instantly Decodable Network Coding
In this paper, we aim to identify the strategies that can maximize and
monotonically increase the density of the coding opportunities in instantly
decodable network coding (IDNC).Using the well-known graph representation of
IDNC, first derive an expression for the exact evolution of the edge set size
after the transmission of any arbitrary coded packet. From the derived
expressions, we show that sending commonly wanted packets for all the receivers
can maximize the number of coding opportunities. Since guaranteeing such
property in IDNC is usually impossible, this strategy does not guarantee the
achievement of our target. Consequently, we further investigate the problem by
deriving the expectation of the edge set size evolution after ignoring the
identities of the packets requested by the different receivers and considering
only their numbers. We then employ this expected expression to show that
serving the maximum number of receivers having the largest numbers of missing
packets and erasure probabilities tends to both maximize and monotonically
increase the expected density of coding opportunities. Simulation results
justify our theoretical findings. Finally, we validate the importance of our
work through two case studies showing that our identified strategy outperforms
the step-by-step service maximization solution in optimizing both the IDNC
completion delay and receiver goodput
On Throughput and Decoding Delay Performance of Instantly Decodable Network Coding
In this paper, a comprehensive study of packet-based instantly decodable
network coding (IDNC) for single-hop wireless broadcast is presented. The
optimal IDNC solution in terms of throughput is proposed and its packet
decoding delay performance is investigated. Lower and upper bounds on the
achievable throughput and decoding delay performance of IDNC are derived and
assessed through extensive simulations. Furthermore, the impact of receivers'
feedback frequency on the performance of IDNC is studied and optimal IDNC
solutions are proposed for scenarios where receivers' feedback is only
available after and IDNC round, composed of several coded transmissions.
However, since finding these IDNC optimal solutions is computational complex,
we further propose simple yet efficient heuristic IDNC algorithms. The impact
of system settings and parameters such as channel erasure probability, feedback
frequency, and the number of receivers is also investigated and simple
guidelines for practical implementations of IDNC are proposed.Comment: This is a 14-page paper submitted to IEEE/ACM Transaction on
Networking. arXiv admin note: text overlap with arXiv:1208.238