Delay Minimization for Instantly Decodable Network Coding in Persistent Channels with Feedback Intermittence

In this paper, we consider the problem of minimizing the multicast decoding delay of generalized instantly decodable network coding (G-IDNC) over persistent forward and feedback erasure channels with feedback intermittence. In such an environment, the sender does not always receive acknowledgement from the receivers after each transmission. Moreover, both the forward and feedback channels are subject to persistent erasures, which can be modelled by a two state (good and bad states) Markov chain known as Gilbert-Elliott channel (GEC). Due to such feedback imperfections, the sender is unable to determine subsequent instantly decodable packets combination for all receivers. Given this harsh channel and feedback model, we first derive expressions for the probability distributions of decoding delay increments and then employ these expressions in formulating the minimum decoding problem in such environment as a maximum weight clique problem in the G-IDNC graph. We also show that the problem formulations in simpler channel and feedback models are special cases of our generalized formulation. Since this problem is NP-hard, we design a greedy algorithm to solve it and compare it to blind approaches proposed in literature. Through extensive simulations, our adaptive algorithm is shown to outperform the blind approaches in all situations and to achieve significant improvement in the decoding delay, especially when the channel is highly persisten

On Minimizing the Maximum Broadcast Decoding Delay for Instantly Decodable Network Coding

In this paper, we consider the problem of minimizing the maximum broadcast decoding delay experienced by all the receivers of generalized instantly decodable network coding (IDNC). Unlike the sum decoding delay, the maximum decoding delay as a definition of delay for IDNC allows a more equitable distribution of the delays between the different receivers and thus a better Quality of Service (QoS). In order to solve this problem, we first derive the expressions for the probability distributions of maximum decoding delay increments. Given these expressions, we formulate the problem as a maximum weight clique problem in the IDNC graph. Although this problem is known to be NP-hard, we design a greedy algorithm to perform effective packet selection. Through extensive simulations, we compare the sum decoding delay and the max decoding delay experienced when applying the policies to minimize the sum decoding delay [1] and our policy to reduce the max decoding delay. Simulations results show that our policy gives a good agreement among all the delay aspects in all situations and outperforms the sum decoding delay policy to effectively minimize the sum decoding delay when the channel conditions become harsher. They also show that our definition of delay significantly improve the number of served receivers when they are subject to strict delay constraints

Delay Reduction in Multi-Hop Device-to-Device Communication using Network Coding

This paper considers the problem of reducing the broadcast decoding delay of wireless networks using instantly decodable network coding (IDNC) based device-to-device (D2D) communications. In a D2D configuration, devices in the network can help hasten the recovery of the lost packets of other devices in their transmission range by sending network coded packets. Unlike previous works that assumed fully connected network, this paper proposes a partially connected configuration in which the decision should be made not only on the packet combinations but also on the set of transmitting devices. First, the different events occurring at each device are identified so as to derive an expression for the probability distribution of the decoding delay. The joint optimization problem over the set of transmitting devices and the packet combinations of each is, then, formulated. The optimal solution of the joint optimization problem is derived using a graph theory approach by introducing the cooperation graph and reformulating the problem as a maximum weight clique problem in which the weight of each vertex is the contribution of the device identified by the vertex. Through extensive simulations, the decoding delay experienced by all devices in the Point to Multi-Point (PMP) configuration, the fully connected D2D (FC-D2D) configuration and the more practical partially connected D2D (PC-D2D) configuration are compared. Numerical results suggest that the PC-D2D outperforms the FC-D2D and provides appreciable gain especially for poorly connected networks

A protocol design paradigm for rateless fulcrum code

Establecer servicios Multicast eficientes en una red con dispositivos heterogéneos y bajo los efectos de un canal con efecto de borradura es una de las prioridades actuales en la teoría de la codificación, en particular en Network Coding (NC). Además, el creciente número de clientes con dispositivos móviles de gran capacidad de procesamiento y la prevalencia de tráfico no tolerante al retardo han provocado una demanda de esquemas Multicast sin realimentación en lo que respecta a la gestión de recursos distribuidos. Las plataformas de comunicación actuales carecen de un control de codificación gradual y dinámico basado en el tipo de datos que se transmiten a nivel de la capa de aplicación. Este trabajo propone un esquema de transmisión fiable y eficiente basado en una codificación hibrida compuesta por una codificación sistemática y codificación de red lineal aleatoria (RLNC) denominada codificación Fulcrum. Este esquema híbrido de codificación distribuida tipo Rateless permite implementar un sistema adaptativo de gestión de recursos para aumentar la probabilidad de descodificación durante la recepción de datos en cada nodo receptor de la información. En última instancia, el esquema propuesto se traduce en un mayor rendimiento de la red y en tiempos de transmisión (RTT) mucho más cortos mediante la implementación eficiente de una corrección de errores hacia delante (FEC).DoctoradoDoctor en Ingeniería de Sistemas y Computació