8 research outputs found
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
Centralized and Cooperative Transmission of Secure Multiple Unicasts using Network Coding
We introduce a method for securely delivering a set of messages to a group of
clients over a broadcast erasure channel where each client is interested in a
distinct message. Each client is able to obtain its own message but not the
others'. In the proposed method the messages are combined together using a
special variant of random linear network coding. Each client is provided with a
private set of decoding coefficients to decode its own message. Our method
provides security for the transmission sessions against computational
brute-force attacks and also weakly security in information theoretic sense. As
the broadcast channel is assumed to be erroneous, the missing coded packets
should be recovered in some way. We consider two different scenarios. In the
first scenario the missing packets are retransmitted by the base station
(centralized). In the second scenario the clients cooperate with each other by
exchanging packets (decentralized). In both scenarios, network coding
techniques are exploited to increase the total throughput. For the case of
centralized retransmissions we provide an analytical approximation for the
throughput performance of instantly decodable network coded (IDNC)
retransmissions as well as numerical experiments. For the decentralized
scenario, we propose a new IDNC based retransmission method where its
performance is evaluated via simulations and analytical approximation.
Application of this method is not limited to our special problem and can be
generalized to a new class of problems introduced in this paper as the
cooperative index coding problem
Performance characterization and transmission schemes for instantly decodable network coding in wireless broadcast
We consider broadcasting a block of packets to multiple wireless receivers under random packet erasures using
instantly decodable network coding (IDNC). The sender first broadcasts each packet uncoded once, then generates
coded packets according to receivers’ feedback about their missing packets. We focus on strict IDNC (S-IDNC), where
each coded packet includes at most one missing packet of every receiver. But, we will also study its relation with
generalized IDNC (G-IDNC), where this condition is relaxed. We characterize two fundamental performance limits of
S-IDNC: (1) the number of transmissions to complete the broadcast, which measures throughput and (2) average
packet decoding delay, which measures how fast each packet is decoded at each receiver on average. We derive a
closed-form expression for the expected minimum number of transmissions in terms of the number of packets and
receivers and the erasure probability. We prove that it is NP-hard to minimize the average packet decoding delay of
S-IDNC. We also prove that the graph models of S- and G-IDNC share the same chromatic number. Next, we design
efficient S-IDNC transmission schemes and coding algorithms with full/intermittent receiver feedback. We present
simulation results to corroborate the developed theory and compare our schemes with existing ones
Instantly Decodable Network Coding: From Centralized to Device-to-Device Communications
From its introduction to its quindecennial, network coding has built a strong reputation for enhancing packet recovery and achieving maximum information flow in both wired and wireless networks. Traditional studies focused on optimizing the throughput of the system by proposing elaborate schemes able to reach the network capacity. With the shift toward distributed computing on mobile devices, performance and complexity become both critical factors that affect the efficiency of a coding strategy. Instantly decodable network coding presents itself as a new paradigm in network coding that trades off these two aspects. This paper review instantly decodable network coding schemes by identifying, categorizing, and evaluating various algorithms proposed in the literature. The first part of the manuscript investigates the conventional centralized systems, in which all decisions are carried out by a central unit, e.g., a base-station. In particular, two successful approaches known as the strict and generalized instantly decodable network are compared in terms of reliability, performance, complexity, and packet selection methodology. The second part considers the use of instantly decodable codes in a device-to-device communication network, in which devices speed up the recovery of the missing packets by exchanging network coded packets. Although the performance improvements are directly proportional to the computational complexity increases, numerous successful schemes from both the performance and complexity viewpoints are identified
Throughput and Delay Optimization of Linear Network Coding in Wireless Broadcast
Linear network coding (LNC) is able to achieve the optimal
throughput of packet-level wireless broadcast, where a sender
wishes to broadcast a set of data packets to a set of receivers
within its transmission range through lossy wireless links. But
the price is a large delay in the recovery of individual data
packets due to network decoding, which may undermine all the
benefits of LNC. However, packet decoding delay minimization and
its relation to throughput maximization have not been well
understood in the network coding literature.
Motivated by this fact, in this thesis we present a comprehensive
study on the joint optimization of throughput and average packet
decoding delay (APDD) for LNC in wireless broadcast. To this end,
we reveal the fundamental performance limits of LNC and study the
performance of three major classes of LNC techniques, including
instantly decodable network coding (IDNC), generation-based LNC,
and throughput-optimal LNC (including random linear network
coding (RLNC)).
Various approaches are taken to accomplish the study, including
1) deriving performance bounds, 2) establishing and modelling
optimization problems, 3) studying the hardness of the
optimization problems and their approximation, 4) developing new
optimal and heuristic techniques that take into account practical
concerns such as receiver feedback frequency and computational
complexity.
Key contributions of this thesis include:
- a necessary and sufficient condition for LNC to achieve the
optimal throughput of wireless broadcast;
- the NP-hardness of APDD minimization;
- lower bounds of the expected APDD of LNC under random packet
erasures;
- the APDD-approximation ratio of throughput-optimal LNC, which
has a value of between 4/3 and 2. In particular, the ratio of
RLNC is exactly 2;
- a novel throughput-optimal, APDD-approximation, and
implementation-friendly LNC technique;
- an optimal implementation of strict IDNC that is robust to
packet erasures;
- a novel generation-based LNC technique that generalizes some of
the existing LNC techniques and enables tunable throughput-delay
tradeoffs