1,942 research outputs found

    Oblivious channels

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    Let C = {x_1,...,x_N} \subset {0,1}^n be an [n,N] binary error correcting code (not necessarily linear). Let e \in {0,1}^n be an error vector. A codeword x in C is said to be "disturbed" by the error e if the closest codeword to x + e is no longer x. Let A_e be the subset of codewords in C that are disturbed by e. In this work we study the size of A_e in random codes C (i.e. codes in which each codeword x_i is chosen uniformly and independently at random from {0,1}^n). Using recent results of Vu [Random Structures and Algorithms 20(3)] on the concentration of non-Lipschitz functions, we show that |A_e| is strongly concentrated for a wide range of values of N and ||e||. We apply this result in the study of communication channels we refer to as "oblivious". Roughly speaking, a channel W(y|x) is said to be oblivious if the error distribution imposed by the channel is independent of the transmitted codeword x. For example, the well studied Binary Symmetric Channel is an oblivious channel. In this work, we define oblivious and partially oblivious channels and present lower bounds on their capacity. The oblivious channels we define have connections to Arbitrarily Varying Channels with state constraints.Comment: Submitted to the IEEE International Symposium on Information Theory (ISIT) 200

    Distributed Broadcasting and Mapping Protocols in Directed Anonymous Networks

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    We initiate the study of distributed protocols over directed anonymous networks that are not necessarily strongly connected. In such networks, nodes are aware only of their incoming and outgoing edges, have no unique identity, and have no knowledge of the network topology or even bounds on its parameters, like the number of nodes or the network diameter. Anonymous networks are of interest in various settings such as wireless ad-hoc networks and peer to peer networks. Our goal is to create distributed protocols that reduce the uncertainty by distributing the knowledge of the network topology to all the nodes. We consider two basic protocols: broadcasting and unique label assignment. These two protocols enable a complete mapping of the network and can serve as key building blocks in more advanced protocols. We develop distributed asynchronous protocols as well as derive lower bounds on their communication complexity, total bandwidth complexity, and node label complexity. The resulting lower bounds are sometimes surprisingly high, exhibiting the complexity of topology extraction in directed anonymous networks

    Graphs with tiny vector chromatic numbers and huge chromatic numbers

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    Karger, Motwani, and Sudan [J. ACM, 45 (1998), pp. 246-265] introduced the notion of a vector coloring of a graph. In particular, they showed that every k-colorable graph is also vector k-colorable, and that for constant k, graphs that are vector k-colorable can be colored by roughly Δ^(1 - 2/k) colors. Here Δ is the maximum degree in the graph and is assumed to be of the order of n^5 for some 0 < δ < 1. Their results play a major role in the best approximation algorithms used for coloring and for maximum independent sets. We show that for every positive integer k there are graphs that are vector k-colorable but do not have independent sets significantly larger than n/Δ^(1- 2/k) (and hence cannot be colored with significantly fewer than Δ^(1-2/k) colors). For k = O(log n/log log n) we show vector k-colorable graphs that do not have independent sets of size (log n)^c, for some constant c. This shows that the vector chromatic number does not approximate the chromatic number within factors better than n/polylogn. As part of our proof, we analyze "property testing" algorithms that distinguish between graphs that have an independent set of size n/k, and graphs that are "far" from having such an independent set. Our bounds on the sample size improve previous bounds of Goldreich, Goldwasser, and Ron [J. ACM, 45 (1998), pp. 653-750] for this problem

    The Capacity of Online (Causal) qq-ary Error-Erasure Channels

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    In the qq-ary online (or "causal") channel coding model, a sender wishes to communicate a message to a receiver by transmitting a codeword x=(x1,,xn){0,1,,q1}n\mathbf{x} =(x_1,\ldots,x_n) \in \{0,1,\ldots,q-1\}^n symbol by symbol via a channel limited to at most pnpn errors and/or pnp^{*} n erasures. The channel is "online" in the sense that at the iith step of communication the channel decides whether to corrupt the iith symbol or not based on its view so far, i.e., its decision depends only on the transmitted symbols (x1,,xi)(x_1,\ldots,x_i). This is in contrast to the classical adversarial channel in which the corruption is chosen by a channel that has a full knowledge on the sent codeword x\mathbf{x}. In this work we study the capacity of qq-ary online channels for a combined corruption model, in which the channel may impose at most pnpn {\em errors} and at most pnp^{*} n {\em erasures} on the transmitted codeword. The online channel (in both the error and erasure case) has seen a number of recent studies which present both upper and lower bounds on its capacity. In this work, we give a full characterization of the capacity as a function of q,pq,p, and pp^{*}.Comment: This is a new version of the binary case, which can be found at arXiv:1412.637

    Optimal Unviersal Schedules for Discrete Broadcast

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    In this paper we study the scenario in which a server sends dynamic data over a single broadcast channel to a number of passive clients. We consider the data to consist of discrete packets, where each update is sent in a separate packet. On demand, each client listens to the channel in order to obtain the most recent data packet. Such scenarios arise in many practical applications such as the distribution of weather and traffic updates to wireless mobile devices and broadcasting stock price information over the Internet. To satisfy a request, a client must listen to at least one packet from beginning to end. We thus consider the design of a broadcast schedule which minimizes the time that passes between a clients request and the time that it hears a new data packet, i.e., the waiting time of the client. Previous studies have addressed this objective, assuming that client requests are distributed uniformly over time. However, in the general setting, the clients behavior is difficult to predict and might not be known to the server. In this work we consider the design of universal schedules that guarantee a short waiting time for any possible client behavior. We define the model of dynamic broadcasting in the universal setting, and prove various results regarding the waiting time achievable in this framework
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