Subspace Properties of Network Coding and their Applications

Systems that employ network coding for content distribution convey to the receivers linear combinations of the source packets. If we assume randomized network coding, during this process the network nodes collect random subspaces of the space spanned by the source packets. We establish several fundamental properties of the random subspaces induced in such a system, and show that these subspaces implicitly carry topological information about the network and its state that can be passively collected and inferred. We leverage this information towards a number of applications that are interesting in their own right, such as topology inference, bottleneck discovery in peer-to-peer systems and locating Byzantine attackers. We thus argue that, randomized network coding, apart from its better known properties for improving information delivery rate, can additionally facilitate network management and control.Comment: Submitted to IEEE transactions on information theory. The paper has 21 page

Efficient packet delivery in modern communication networks

Modern communication networks are often designed for diverse applications, such as voice, data and video. Packet-switching is often adapted in today’s networks to transmit multiple types of traffic. In packet-switching networks, network performance is directly affected by how the networks handle their packets. This work addresses the packet-handling issues from the following two aspects: Quality of Service (QoS) and network coding. QoS has been a well-addressed issue in the study of IP-based networks. Generally, nodes in a network need to be informed of the state of each communication link in order to make intelligent decisions to route packets according to their QoS demands. The link state can, however, change rapidly in a network; therefore, nodes would have to receive frequent link state updates in order to maintain the latest link state information at all times. Frequent link state updating is resource-consuming and hence impractical in network design. Therefore, there is a trade-off between the link state updating frequency and the QoS routing performance. It is necessary to design a link state update algorithm that utilizes less frequent link state updates to achieve a high degree of satisfaction in QoS performance. The first part of this work addresses this link state update problem and provides two solutions: ROSE and Smart Packet Marking. ROSE is a class-based link state update algorithm, in which the class boundaries are designed based on the statistical data of users’ QoS requests. By doing so, link state update is triggered only when certain necessary conditions are met. For example, if the available bandwidth of a link is fluctuating within a range that is higher than the highest possible bandwidth request, there is no need to update the state of this link. Smart Packet Marking utilizes a similar concept like ROSE, except that the link state information is carried in the probing packet sent in conjunction with each connection request instead of through link state updates. The second part of this work addresses the packet-handling issue by means of network coding. Instead of the traditional store-and-forward approach, network coding allows intermediate nodes in a multi-hop path to code multiple packets into one in order to reduce bandwidth consumption. The coded packet can later be decoded by its recipients to retrieve the original plain packet. Network coding is found to be beneficial in many network applications. This dissertation makes contributions in network coding in two areas: peer-to-peer file sharing and wireless ad-hoc networks. The benefit of network coding in peer-to-peer file sharing networks is analyzed, and a network coding algorithm – Downloader-Initiated Random Linear Network Coding (DRLNC) – is proposed. DLRNC shifts the coding decision from the seeders to the leechers; by doing so it solves the “collision” problem without increasing the field size. In wireless network coding, this work addresses the implementation difficulty pertaining to MAC layer scheduling. To achieve the ideal network coding gain in wireless networks, it requires perfect MAC layer scheduling. This dissertation first provides an algorithm to solve the ideal-case MAC layer scheduling problem. Since the ideal MAC layer schedule is often difficult to realize, a practical approach is then proposed to increase the network coding performance by modifying the ACK packets in the 802.11 MAC

Practical Random Linear Network Coding on GPUs

Abstract. Recently, random linear network coding has been widely applied in peer-to-peer network applications. Instead of sharing the raw data with each other, peers in the network produce and send encoded data to each other. As a result, the communication protocols have been greatly simplified, and the appli-cations experience higher end-to-end throughput and better robustness to net-work churns. Since it is difficult to verify the integrity of the encoded data, such systems can suffer from the famous pollution attack, in which a malicious node can send bad encoded blocks that consist of bogus data. Consequently, the bogus data will be propagated into the whole network at an exponential rate. Homomorphic hash functions (HHFs) have been designed to defend systems from such pollution attacks, but with a new challenge: HHFs require that network coding must be performed in GF(q), where q is a very large prime number. This greatly increases the computational cost of network coding, in ad-dition to the already computational expensive HHFs. This paper exploits the po-tential of the huge computing power of Graphic Processing Units (GPUs) to reduce the computational cost of network coding and homomorphic hashing. With our network coding and HHF implementation on GPU, we observed significant computational speedup in comparison with the best CPU implemen-tation. This implementation can lead to a practical solution for defending the pollution attacks in distributed systems

Band Codes for Energy-Efficient Network Coding with Application to P2P Mobile Streaming

A key problem in random network coding (NC) lies in the complexity and energy consumption associated with the packet decoding processes, which hinder its application in mobile environments. Controlling and hence limiting such factors has always been an important but elusive research goal, since the packet degree distribution, which is the main factor driving the complexity, is altered in a non-deterministic way by the random recombinations at the network nodes. In this paper we tackle this problem proposing Band Codes (BC), a novel class of network codes specifically designed to preserve the packet degree distribution during packet encoding, ecombination and decoding. BC are random codes over GF(2) that exhibit low decoding complexity, feature limited and controlled degree distribution by construction, and hence allow to effectively apply NC even in energy-constrained scenarios. In particular, in this paper we motivate and describe our new design and provide a thorough analysis of its performance. We provide numerical simulations of the performance of BC in order to validate the analysis and assess the overhead of BC with respect to a onventional NC scheme. Moreover, peer-to-peer media streaming experiments with a random-push protocol show that BC reduce the decoding complexity by a factor of two, to a point where NC-based mobile streaming to mobile devices becomes practically feasible.Comment: To be published in IEEE Transacions on Multimedi

Avoiding Interruptions - QoE Trade-offs in Block-coded Streaming Media Applications

We take an analytical approach to study Quality of user Experience (QoE) for video streaming applications. First, we show that random linear network coding applied to blocks of video frames can significantly simplify the packet requests at the network layer and save resources by avoiding duplicate packet reception. Network coding allows us to model the receiver's buffer as a queue with Poisson arrivals and deterministic departures. We consider the probability of interruption in video playback as well as the number of initially buffered packets (initial waiting time) as the QoE metrics. We characterize the optimal trade-off between these metrics by providing upper and lower bounds on the minimum initial buffer size, required to achieve certain level of interruption probability for different regimes of the system parameters. Our bounds are asymptotically tight as the file size goes to infinity.Comment: Submitted to ISIT 2010 - Full versio

On the Limit of Fountain MDC Codes for Video Peer-To-Peer Networks

Video streaming for heterogeneous types of devices, where nodes have different devices characteristics in terms of computational capacity and display, is usually handled by encoding the video with different qualities. This is not well suited for Peer-To-Peer (P2P) systems, as a single peer group can only share content of the same quality, thus limiting the peer group size and efficiency. To address this problem, several existing works propose the use of Multiple Descriptions Coding (MDC). The concept of this type of video codec is to split a video in a number of descriptions which can be used on their own, or aggregated to improve the global quality of the video. Unfortunately existing MDC codes are not flexible, as the video is split in a defined number of descriptions. In this paper, we focus on the practical feasibility of using a Fountain MDC code with properties similar to existing Fountain erasure codes, including the ability to create any number of descriptions when needed (on the fly). We perform simulations using selected pictures to assess the feasibility of using these codes, knowing that they should improve the availability of the video pieces in a P2P system and hence the video streaming quality. We observe that, although this idea seems promising, the evaluated benefits, demonstrated by the PSNR values, are limited when used in a real P2P video streaming system