Let X = I1, " '" , a}, Y = {1, ' " , b} be finite sets. A stochastic matrix w with a rows and b columns will be called a channel. X, Y are the input and output alphabets (respectively) of the channel. We denote the set of all channels with input alphabet X and output alphabet Y by e (X, Y). A channel w E C (X, Y) can be used for communication from one person, the sender, to another person, the ...

We establish the deterministic-code capacity region of a network with one transmitter and two receivers: an “ordinary receiver” and a “robust receiver.” The channel to the ordinary receiver is a given (known) discrete memoryless channel (DMC), whereas the channel to the robust receiver is an arbitrarily varying channel (AVC). Both receivers are required to decode the “common message,” whereas o...

HTTP-based video streaming technologies allow for flexible rate selection strategies that account for time-varying network conditions. Such rate changes may adversely affect the user’s Quality of Experience; hence online prediction of the timevarying subjective quality can lead to perceptually optimized bitrate allocation policies. Recent studies have proposed to use dynamic network approaches ...

Finite blocklength and second-order (dispersion) results are presented for the arbitrarily-varying channel (AVC), a classical model wherein an adversary can transmit arbitrary signals into the channel. A novel finite blocklength achievability bound is presented, roughly analogous to the random coding union bound for non-adversarial channels. This finite blocklength bound, along with a known con...

The formation of network structure is mainly influenced by an individual node’s activity and its memory, where activity can usually be interpreted as the individual inherent property and memory can be represented by the interaction strength between nodes. In our study, we define the activity through the appearance pattern in the time-aggregated network representation, and quantify the memory th...

In this work, we study two models of arbitrarily varying channels, when causal side information is available at the encoder in a causal manner. First, we study the arbitrarily varying channel (AVC) with input and state constraints, when the encoder has state information in a causal manner. Lower and upper bounds on the random code capacity are developed. A lower bound on the deterministic code ...

The Temporal Network Visualizer is an experimental system to perform real-time visualization of time varying network oriented data. It builds upon the concept of stripcharts to augment a user's memory of past events, enhancing the user's ability to recognize patterns that occur across time as well as space, patterns that we associate with causality. Examples are given for visualizing transactio...

We study the problem of computing minimum-cost paths through a time-varying network, in which the travel time and travel cost of each arc are known functions of one’s departure time along the arc. For some problem instances, the ability to wait at nodes may allow for less costly paths through the network. When waiting is allowed, it is constrained by a (potentially time-varying) waiting policy ...

1. Theory of graph-theoretical data analysis: a series of possible projects on the conceptual and mathematical extensions of techniques for the representation of data as graphs, and the coarsegraining of such representations. These include topics such as: * time-varying networks and their partitions: detecting break points using multidimensional algorithms * development of notions of robustness...

Travel times in congested transportation networks are time-varying quantities that can at best be known a priori probabilistically. In such networks, the arc weights (travel times) are represented by random variables whose probability distribution functions vary with time. These networks are referred to herein as stochastic, time-varying, or STV, networks. The determination of ‘‘least time’’ ro...