Instantly Decodable Network Coding for Real-Time Scalable Video Broadcast over Wireless Networks

In this paper, we study a real-time scalable video broadcast over wireless networks in instantly decodable network coded (IDNC) systems. Such real-time scalable video has a hard deadline and imposes a decoding order on the video layers.We first derive the upper bound on the probability that the individual completion times of all receivers meet the deadline. Using this probability, we design two prioritized IDNC algorithms, namely the expanding window IDNC (EW-IDNC) algorithm and the non-overlapping window IDNC (NOW-IDNC) algorithm. These algorithms provide a high level of protection to the most important video layer before considering additional video layers in coding decisions. Moreover, in these algorithms, we select an appropriate packet combination over a given number of video layers so that these video layers are decoded by the maximum number of receivers before the deadline. We formulate this packet selection problem as a two-stage maximal clique selection problem over an IDNC graph. Simulation results over a real scalable video stream show that our proposed EW-IDNC and NOW-IDNC algorithms improve the received video quality compared to the existing IDNC algorithms

On the Minimum Number of Transmissions in Single-Hop Wireless Coding Networks

The advent of network coding presents promising opportunities in many areas of communication and networking. It has been recently shown that network coding technique can significantly increase the overall throughput of wireless networks by taking advantage of their broadcast nature. In wireless networks, each transmitted packet is broadcasted within a certain area and can be overheard by the neighboring nodes. When a node needs to transmit packets, it employs the opportunistic coding approach that uses the knowledge of what the node's neighbors have heard in order to reduce the number of transmissions. With this approach, each transmitted packet is a linear combination of the original packets over a certain finite field. In this paper, we focus on the fundamental problem of finding the optimal encoding for the broadcasted packets that minimizes the overall number of transmissions. We show that this problem is NP-complete over GF(2) and establish several fundamental properties of the optimal solution. We also propose a simple heuristic solution for the problem based on graph coloring and present some empirical results for random settings.Comment: 6 page

Nearly Optimal Scheduling of Wireless Ad Hoc Networks in Polynomial Time

In this paper, we address the scheduling problem in wireless ad hoc networks by exploiting the computational advantage that comes when such scheduling problems can be represented by claw-free conflict graphs where we consider a wireless broadcast medium. It is possible to formulate a scheduling problem of network coded flows as finding maximum weighted independent set (MWIS) in the conflict graph of the network. Finding MWIS of a general graph is NP-hard leading to an NP-hard complexity of scheduling. In a claw-free conflict graph, MWIS can be found in polynomial time leading to a throughput-optimal scheduling. We show that the conflict graph of certain wireless ad hoc networks are claw-free. In order to obtain claw-free conflict graphs in general networks, we suggest introducing additional conflicts (edges) while keeping the decrease in MWIS size minimal. To this end, we introduce an iterative optimization problem to decide where to introduce edges and investigate its efficient implementation. Besides, we exemplify some physical modifications to manipulate the conflict graph of a network and also propose a mixed scheduling strategy for specific networks. We conclude that claw breaking method by adding extra edges can perform nearly optimal under the necessary assumptions.Comment: This work is to be submitted to the IEEE for possible publicatio

Network Codes for Real-Time Applications

We consider the scenario of broadcasting for real-time applications and loss recovery via instantly decodable network coding. Past work focused on minimizing the completion delay, which is not the right objective for real-time applications that have strict deadlines. In this work, we are interested in finding a code that is instantly decodable by the maximum number of users. First, we prove that this problem is NP-Hard in the general case. Then we consider the practical probabilistic scenario, where users have i.i.d. loss probability and the number of packets is linear or polynomial in the number of users. In this scenario, we provide a polynomial-time (in the number of users) algorithm that finds the optimal coded packet. The proposed algorithm is evaluated using both simulation and real network traces of a real-time Android application. Both results show that the proposed coding scheme significantly outperforms the state-of-the-art baselines: an optimal repetition code and a COPE-like greedy scheme.Comment: ToN 2013 Submission Versio

Network-Coded Macrocell Offloading in Femtocaching-Assisted Cellular Networks

The femtocaching idea was proposed as a solution to compensate for the weak backhaul capacity, by deploying coverage-limited nodes with high storage capacity called femtocaches (FCs). In this paper, the macrocell offloading problem in femtocaching-assisted cellular networks is investigated. The objective is to minimize the number of transmissions by the macrocell base station (MBS) given that all requests should be served simultaneously to satisfy quality-of-experience (QoE) of the clients. We first formulate this MBS offloading problem as an optimization problem over a network coding graph, and show that it is NP-hard. Therefore, we propose an ONC-broadcast offloading scheme that exploits both broadcasting and opportunistic network coding (ONC) to minimize the number of required MBS transmissions. We utilize a random graph model to approximate the performance of the proposed ONC-broadcast scheme in terms of the resultant average number of transmissions by the MBS. Moreover, despite the complexity of finding the optimal solution for each and every case, we prove that this ONC-broadcast scheme is asymptotically optimal, i.e., for large number of requests, the ONC-broadcast scheme achieves a similar macrocell offloading performance to that of the optimal solution. To implement the ONC-broadcast scheme, we devise a heuristic that employs a dual conflict graph or broadcasting at the FCs such that the remaining requests can be served using the minimum number of transmissions at the MBS. Simulations show that the dual graph scheme improves MBS offloading as compared to the traditional separate graph scheme. Furthermore, the simple heuristic proposed to implement the ONC-broadcast scheme achieves a very close performance to the optimal ONC-broadcast scheme

Dynamic Edge Caching with Popularity Drifting

Caching at the network edge devices such as wireless caching stations (WCS) is a key technology in the 5G network. The spatial-temporal diversity of content popularity requires different content to be cached in different WCSs and periodically updated to adapt to temporal changes. In this paper, we study how the popularity drifting speed affects the number of required broadcast transmissions by the MBS and then design coded transmission schemes by leveraging the broadcast advantage under the index coding framework. The key idea is that files already cached in WCSs, which although may be currently unpopular, can serve as side information to facilitate coded broadcast transmission for cache updating. Our algorithm extends existing index coding-based schemes from a single-request scenario to a multiple-request scenario via a "dynamic coloring" approach. Simulation results indicate that a significant bandwidth saving can be achieved by adopting our scheme

On the Packet Decoding Delay of Linear Network Coded Wireless Broadcast

We apply linear network coding (LNC) to broadcast a block of data packets from one sender to a set of receivers via lossy wireless channels, assuming each receiver already possesses a subset of these packets and wants the rest. We aim to characterize the average packet decoding delay (APDD), which reflects how soon each individual data packet can be decoded by each receiver on average, and to minimize it while achieving optimal throughput. To this end, we first derive closed-form lower bounds on the expected APDD of all LNC techniques under random packet erasures. We then prove that these bounds are NP-hard to achieve and, thus, that APDD minimization is an NP-hard problem. We then study the performance of some existing LNC techniques, including random linear network coding (RLNC) and instantly decodable network coding (IDNC). We proved that all throughput-optimal LNC techniques can approximate the minimum expected APDD with a ratio between 4/3 and 2. In particular, the ratio of RLNC is exactly 2. We then prove that all IDNC techniques are only heuristics in terms of throughput optimization and {cannot guarantee an APDD approximation ratio for at least a subset of the receivers}. Finally, we propose hyper-graphic linear network coding (HLNC), a novel throughput-optimal and APDD-approximating LNC technique based on a hypergraph model of receivers' packet reception state. We implement it under different availability of receiver feedback, and numerically compare its performance with RLNC and a heuristic general IDNC technique. The results show that the APDD performance of HLNC is better under all tested system settings, even if receiver feedback is only collected intermittently

Content-Aware Network Coding over Device-to-Device Networks

Consider a scenario of broadcasting a common content to a group of cooperating mobile devices that are within proximity of each other. Devices in this group may receive partial content from the source due to packet losses over wireless broadcast links. We further consider that packet losses are different for different devices. The remaining missing content at each device can then be recovered, thanks to cooperation among the devices by exploiting device-to-device (D2D) connections. In this context, the minimum amount of time that can guarantee a complete acquisition of the common content at every device is referred to as the "completion time". It has been shown that instantly decodable network coding (IDNC) reduces the completion time as compared to no network coding in this scenario. Yet, for applications such as video streaming, not all packets have the same importance and not all devices are interested in the same quality of content. This problem is even more interesting when additional, but realistic constraints, such as strict deadline, bandwidth, or limited energy are added in the problem formulation. We assert that direct application of IDNC in such a scenario yields poor performance in terms of content quality and completion time. In this paper, we propose a novel Content and Loss-Aware IDNC scheme that improves content quality and network coding opportunities jointly by taking into account importance of each packet towards the desired quality of service (QoS) as well as the channel losses over D2D links. Our proposed Content and Loss-Aware IDNC (i) maximizes the quality under the completion time constraint, and (ii) minimizes the completion time under the quality constraint. We demonstrate the benefits of Content and Loss-Aware IDNC through simulations.Comment: 7 page

Networked Computing in Wireless Sensor Networks for Structural Health Monitoring

This paper studies the problem of distributed computation over a network of wireless sensors. While this problem applies to many emerging applications, to keep our discussion concrete we will focus on sensor networks used for structural health monitoring. Within this context, the heaviest computation is to determine the singular value decomposition (SVD) to extract mode shapes (eigenvectors) of a structure. Compared to collecting raw vibration data and performing SVD at a central location, computing SVD within the network can result in significantly lower energy consumption and delay. Using recent results on decomposing SVD, a well-known centralized operation, into components, we seek to determine a near-optimal communication structure that enables the distribution of this computation and the reassembly of the final results, with the objective of minimizing energy consumption subject to a computational delay constraint. We show that this reduces to a generalized clustering problem; a cluster forms a unit on which a component of the overall computation is performed. We establish that this problem is NP-hard. By relaxing the delay constraint, we derive a lower bound to this problem. We then propose an integer linear program (ILP) to solve the constrained problem exactly as well as an approximate algorithm with a proven approximation ratio. We further present a distributed version of the approximate algorithm. We present both simulation and experimentation results to demonstrate the effectiveness of these algorithms

Energy efficient D2D communications in dynamic TDD systems

Network-assisted device-to-device communication is a promising technology for improving the performance of proximity-based services. This paper demonstrates how the integration of device-to-device communications and dynamic time-division duplex can improve the energy efficiency of future cellular networks, leading to a greener system operation and a prolonged battery lifetime of mobile devices. We jointly optimize the mode selection, transmission period and power allocation to minimize the energy consumption (from both a system and a device perspective) while satisfying a certain rate requirement. The radio resource management problems are formulated as mixed-integer nonlinear programming problems. Although they are known to be NP-hard in general, we exploit the problem structure to design efficient algorithms that optimally solve several problem cases. For the remaining cases, a heuristic algorithm that computes near-optimal solutions while respecting practical constraints on execution times and signaling overhead is also proposed. Simulation results confirm that the combination of device-to-device and flexible time-division-duplex technologies can significantly enhance spectrum and energy-efficiency of next generation cellular systems.Comment: Submitted to IEEE Journal of Selected Areas in Communication