2,651 research outputs found
Private Function Retrieval
The widespread use of cloud computing services raises the question of how one
can delegate the processing tasks to the untrusted distributed parties without
breeching the privacy of its data and algorithms. Motivated by the algorithm
privacy concerns in a distributed computing system, in this paper, we introduce
the private function retrieval (PFR) problem, where a user wishes to
efficiently retrieve a linear function of messages from
non-communicating replicated servers while keeping the function hidden from
each individual server. The goal is to find a scheme with minimum communication
cost. To characterize the fundamental limits of the communication cost, we
define the capacity of PFR problem as the size of the message that can be
privately retrieved (which is the size of one file) normalized to the required
downloaded information bits. We first show that for the PFR problem with
messages, servers and a linear function with binary coefficients the
capacity is . Interestingly, this
is the capacity of retrieving one of messages from servers while
keeping the index of the requested message hidden from each individual server,
the problem known as private information retrieval (PIR). Then, we extend the
proposed achievable scheme to the case of arbitrary number of servers and
coefficients in the field with arbitrary and obtain
State-Dependent Relay Channel with Private Messages with Partial Causal and Non-Causal Channel State Information
In this paper, we introduce a discrete memoryless State-Dependent Relay
Channel with Private Messages (SD-RCPM) as a generalization of the
state-dependent relay channel. We investigate two main cases: SD-RCPM with
non-causal Channel State Information (CSI), and SD-RCPM with causal CSI. In
each case, it is assumed that partial CSI is available at the source and relay.
For non-causal case, we establish an achievable rate region using
Gel'fand-Pinsker type coding scheme at the nodes informed of CSI, and
Compress-and-Forward (CF) scheme at the relay. Using Shannon's strategy and CF
scheme, an achievable rate region for causal case is obtained. As an example,
the Gaussian version of SD-RCPM is considered, and an achievable rate region
for Gaussian SD-RCPM with non-causal perfect CSI only at the source, is
derived. Providing numerical examples, we illustrate the comparison between
achievable rate regions derived using CF and Decode-and-Forward (DF) schemes.Comment: 5 pages, 2 figures, to be presented at the IEEE International
Symposium on Information Theory (ISIT 2010), Austin, Texas, June 201
Effects of a Dielectric Barrier Discharge (DBD) treatment on chitosan/polyethylene oxide nanofibers and their cellular interactions
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