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An increasing number of streaming applications need packets to be strictly in-order at the receiver. This paper provides a framework for analyzing in-order packet delivery in such applications. We consider the problem of multicasting an ordered stream of packets to two users over independent erasure channels with instantaneous feedback to the source. Depending upon the channel erasures, a packet which is in-order for one user, may be redundant for the other. Thus there is an inter-dependence between throughput and the smoothness of in-order packet delivery to the two users. We use a Markov chain model of packet decoding to analyze these throughput-smoothness trade-offs of the users, and propose coding schemes that can span different points on each trade-off.
Unlike traditional file transfer where only total delay matters, streaming applications impose delay constraints on each packet and require them to be in order. To achieve fast in-order packet decoding, we have to compromise on the throughput. We stu
We study privacy-utility trade-offs where users share privacy-correlated useful information with a service provider to obtain some utility. The service provider is adversarial in the sense that it can infer the users private information based on the
This paper investigates delay-distortion-power trade offs in transmission of quasi-stationary sources over block fading channels by studying encoder and decoder buffering techniques to smooth out the source and channel variations. Four source and cha
Multicasting is the general method of conveying the same information to multiple users over a broadcast channel. In this work, the Gaussian MIMO broadcast channel is considered, with multiple users and any number of antennas at each node. A closed lo
Dealing with the shear size and complexity of todays massive data sets requires computational platforms that can analyze data in a parallelized and distributed fashion. A major bottleneck that arises in such modern distributed computing environments