1,120 research outputs found
Estimating Minimum Sum-rate for Cooperative Data Exchange
This paper considers how to accurately estimate the minimum sum-rate so as to
reduce the complexity of solving cooperative data exchange (CDE) problems. The
CDE system contains a number of geographically close clients who send packets
to help the others recover an entire packet set. The minimum sum-rate is the
minimum value of total number of transmissions that achieves universal recovery
(the situation when all the clients recover the whole packet set). Based on a
necessary and sufficient condition for a supermodular base polyhedron to be
nonempty, we show that the minimum sum-rate for a CDE system can be determined
by a maximization over all possible partitions of the client set. Due to the
high complexity of solving this maximization problem, we propose a
deterministic algorithm to approximate a lower bound on the minimum sum-rate.
We show by experiments that this lower bound is much tighter than those lower
bounds derived in the existing literature. We also show that the deterministic
algorithm prevents from repetitively running the existing algorithms for
solving CDE problems so that the overall complexity can be reduced accordingly.Comment: 6 pages, 6 figure
e-SAFE: Secure, Efficient and Forensics-Enabled Access to Implantable Medical Devices
To facilitate monitoring and management, modern Implantable Medical Devices
(IMDs) are often equipped with wireless capabilities, which raise the risk of
malicious access to IMDs. Although schemes are proposed to secure the IMD
access, some issues are still open. First, pre-sharing a long-term key between
a patient's IMD and a doctor's programmer is vulnerable since once the doctor's
programmer is compromised, all of her patients suffer; establishing a temporary
key by leveraging proximity gets rid of pre-shared keys, but as the approach
lacks real authentication, it can be exploited by nearby adversaries or through
man-in-the-middle attacks. Second, while prolonging the lifetime of IMDs is one
of the most important design goals, few schemes explore to lower the
communication and computation overhead all at once. Finally, how to safely
record the commands issued by doctors for the purpose of forensics, which can
be the last measure to protect the patients' rights, is commonly omitted in the
existing literature. Motivated by these important yet open problems, we propose
an innovative scheme e-SAFE, which significantly improves security and safety,
reduces the communication overhead and enables IMD-access forensics. We present
a novel lightweight compressive sensing based encryption algorithm to encrypt
and compress the IMD data simultaneously, reducing the data transmission
overhead by over 50% while ensuring high data confidentiality and usability.
Furthermore, we provide a suite of protocols regarding device pairing,
dual-factor authentication, and accountability-enabled access. The security
analysis and performance evaluation show the validity and efficiency of the
proposed scheme
Cooperative Data Exchange with Unreliable Clients
Consider a set of clients in a broadcast network, each of which holds a
subset of packets in the ground set X. In the (coded) cooperative data exchange
problem, the clients need to recover all packets in X by exchanging coded
packets over a lossless broadcast channel. Several previous works analyzed this
problem under the assumption that each client initially holds a random subset
of packets in X. In this paper we consider a generalization of this problem for
settings in which an unknown (but of a certain size) subset of clients are
unreliable and their packet transmissions are subject to arbitrary erasures.
For the special case of one unreliable client, we derive a closed-form
expression for the minimum number of transmissions required for each reliable
client to obtain all packets held by other reliable clients (with probability
approaching 1 as the number of packets tends to infinity). Furthermore, for the
cases with more than one unreliable client, we provide an approximation
solution in which the number of transmissions per packet is within an
arbitrarily small additive factor from the value of the optimal solution.Comment: 8 pages; in Proc. 53rd Annual Allerton Conference on Communication,
Control, and Computing (Allerton 2015
A Practical Approach for Successive Omniscience
The system that we study in this paper contains a set of users that observe a
discrete memoryless multiple source and communicate via noise-free channels
with the aim of attaining omniscience, the state that all users recover the
entire multiple source. We adopt the concept of successive omniscience (SO),
i.e., letting the local omniscience in some user subset be attained before the
global omniscience in the entire system, and consider the problem of how to
efficiently attain omniscience in a successive manner. Based on the existing
results on SO, we propose a CompSetSO algorithm for determining a complimentary
set, a user subset in which the local omniscience can be attained first without
increasing the sum-rate, the total number of communications, for the global
omniscience. We also derive a sufficient condition for a user subset to be
complimentary so that running the CompSetSO algorithm only requires a lower
bound, instead of the exact value, of the minimum sum-rate for attaining global
omniscience. The CompSetSO algorithm returns a complimentary user subset in
polynomial time. We show by example how to recursively apply the CompSetSO
algorithm so that the global omniscience can be attained by multi-stages of SO
Coded Cooperative Data Exchange for a Secret Key
We consider a coded cooperative data exchange problem with the goal of
generating a secret key. Specifically, we investigate the number of public
transmissions required for a set of clients to agree on a secret key with
probability one, subject to the constraint that it remains private from an
eavesdropper.
Although the problems are closely related, we prove that secret key
generation with fewest number of linear transmissions is NP-hard, while it is
known that the analogous problem in traditional cooperative data exchange can
be solved in polynomial time. In doing this, we completely characterize the
best possible performance of linear coding schemes, and also prove that linear
codes can be strictly suboptimal. Finally, we extend the single-key results to
characterize the minimum number of public transmissions required to generate a
desired integer number of statistically independent secret keys.Comment: Full version of a paper that appeared at ISIT 2014. 19 pages, 2
figure
Efficient Algorithms for the Data Exchange Problem
In this paper we study the data exchange problem where a set of users is
interested in gaining access to a common file, but where each has only partial
knowledge about it as side-information. Assuming that the file is broken into
packets, the side-information considered is in the form of linear combinations
of the file packets. Given that the collective information of all the users is
sufficient to allow recovery of the entire file, the goal is for each user to
gain access to the file while minimizing some communication cost. We assume
that users can communicate over a noiseless broadcast channel, and that the
communication cost is a sum of each user's cost function over the number of
bits it transmits. For instance, the communication cost could simply be the
total number of bits that needs to be transmitted. In the most general case
studied in this paper, each user can have any arbitrary convex cost function.
We provide deterministic, polynomial-time algorithms (in the number of users
and packets) which find an optimal communication scheme that minimizes the
communication cost. To further lower the complexity, we also propose a simple
randomized algorithm inspired by our deterministic algorithm which is based on
a random linear network coding scheme.Comment: submitted to Transactions on Information Theor
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