84 research outputs found
Optimal Active Social Network De-anonymization Using Information Thresholds
In this paper, de-anonymizing internet users by actively querying their group
memberships in social networks is considered. In this problem, an anonymous
victim visits the attacker's website, and the attacker uses the victim's
browser history to query her social media activity for the purpose of
de-anonymization using the minimum number of queries. A stochastic model of the
problem is considered where the attacker has partial prior knowledge of the
group membership graph and receives noisy responses to its real-time queries.
The victim's identity is assumed to be chosen randomly based on a given
distribution which models the users' risk of visiting the malicious website. A
de-anonymization algorithm is proposed which operates based on information
thresholds and its performance both in the finite and asymptotically large
social network regimes is analyzed. Furthermore, a converse result is provided
which proves the optimality of the proposed attack strategy
Seeded Graph Matching: Efficient Algorithms and Theoretical Guarantees
In this paper, a new information theoretic framework for graph matching is
introduced. Using this framework, the graph isomorphism and seeded graph
matching problems are studied. The maximum degree algorithm for graph
isomorphism is analyzed and sufficient conditions for successful matching are
rederived using type analysis. Furthermore, a new seeded matching algorithm
with polynomial time complexity is introduced. The algorithm uses `typicality
matching' and techniques from point-to-point communications for reliable
matching. Assuming an Erdos-Renyi model on the correlated graph pair, it is
shown that successful matching is guaranteed when the number of seeds grows
logarithmically with the number of vertices in the graphs. The logarithmic
coefficient is shown to be inversely proportional to the mutual information
between the edge variables in the two graphs
Distortion-Memory Tradeoffs in Cache-Aided Wireless Video Delivery
Mobile network operators are considering caching as one of the strategies to
keep up with the increasing demand for high-definition wireless video
streaming. By prefetching popular content into memory at wireless access points
or end user devices, requests can be served locally, relieving strain on
expensive backhaul. In addition, using network coding allows the simultaneous
serving of distinct cache misses via common coded multicast transmissions,
resulting in significantly larger load reductions compared to those achieved
with conventional delivery schemes. However, prior work does not exploit the
properties of video and simply treats content as fixed-size files that users
would like to fully download. Our work is motivated by the fact that video can
be coded in a scalable fashion and that the decoded video quality depends on
the number of layers a user is able to receive. Using a Gaussian source model,
caching and coded delivery methods are designed to minimize the squared error
distortion at end user devices. Our work is general enough to consider
heterogeneous cache sizes and video popularity distributions.Comment: To appear in Allerton 2015 Proceedings of the 53rd annual Allerton
conference on Communication, control, and computin
Analysis of simple inventory control systems with execution errors: Economic impact under correction opportunities
Cataloged from PDF version of article.Motivated by recent empirical evidence, we study the economic impact of inventory record inaccuracies that arise due to execution errors. We model a set of probable events regarding the erroneous registering of sales at each demand arrival. We define correction opportunities that can be used to (at least partially) correct inventory records. We analyze a simple inventory control model with execution errors and correction opportunities, and demonstrate that decisions that consider the existence of recording errors and the mechanisms with which they are corrected can be quite complicated and exhibit complex tradeoffs. To evaluate the economic impact of inventory record inaccuracies, we use a simulation model of a (Q,r) inventory control system and evaluate suboptimalities in cost and customer service that arise as a result of untimely triggering of orders due to inventory record inaccuracies. We show that the economic impact of inventory record inaccuracies can be significant, particularly in systems with small order sizes and low reorder levels. (C) 2010 Elsevier BM. All rights reserved
The Cauchy problem for a class of two-dimensional nonlocal nonlinear wave equations governing anti-plane shear motions in elastic materials
This paper is concerned with the analysis of the Cauchy problem of a general
class of two-dimensional nonlinear nonlocal wave equations governing anti-plane
shear motions in nonlocal elasticity. The nonlocal nature of the problem is
reflected by a convolution integral in the space variables. The Fourier
transform of the convolution kernel is nonnegative and satisfies a certain
growth condition at infinity. For initial data in Sobolev spaces,
conditions for global existence or finite time blow-up of the solutions of the
Cauchy problem are established.Comment: 15 pages. "Section 6 The Anisotropic Case" added and minor changes.
Accepted for publication in Nonlinearit
Approximation Algorithms for Stochastic Inventory Control Models
Approximation Algorithms for Stochastic Inventory Control Model
Near-optimal modified base stock policies for the capacitated inventory problem with stochastic demand and fixed cost
In this study, we investigate a single-item, periodic-review inventory problem where the production capacity is limited and unmet demand is backordered. We assume that customer demand in each period is a stationary, discrete random variable. Linear holding and backorder cost are charged per unit at the end of a period. In addition to the variable cost charged per unit ordered, a positive fixed ordering cost is incurred with each order given. The optimization criterion is the minimization of the expected cost per period over a planning horizon. We investigate the infinite horizon problem by modeling the problem as a discrete-time Markov chain. We propose a heuristic for the problem based on a particular solution of this stationary model, and conduct a computational study on a set of instances, providing insight on the performance of the heuristic. © 2014 World Scientific Publishing Co
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