28,089 research outputs found
On a Low-Rate TLDPC Code Ensemble and the Necessary Condition on the Linear Minimum Distance for Sparse-Graph Codes
This paper addresses the issue of design of low-rate sparse-graph codes with
linear minimum distance in the blocklength. First, we define a necessary
condition which needs to be satisfied when the linear minimum distance is to be
ensured. The condition is formulated in terms of degree-1 and degree-2 variable
nodes and of low-weight codewords of the underlying code, and it generalizies
results known for turbo codes [8] and LDPC codes. Then, we present a new
ensemble of low-rate codes, which itself is a subclass of TLDPC codes [4], [5],
and which is designed under this necessary condition. The asymptotic analysis
of the ensemble shows that its iterative threshold is situated close to the
Shannon limit. In addition to the linear minimum distance property, it has a
simple structure and enjoys a low decoding complexity and a fast convergence.Comment: submitted to IEEE Trans. on Communication
Neural Machine Translation Inspired Binary Code Similarity Comparison beyond Function Pairs
Binary code analysis allows analyzing binary code without having access to
the corresponding source code. A binary, after disassembly, is expressed in an
assembly language. This inspires us to approach binary analysis by leveraging
ideas and techniques from Natural Language Processing (NLP), a rich area
focused on processing text of various natural languages. We notice that binary
code analysis and NLP share a lot of analogical topics, such as semantics
extraction, summarization, and classification. This work utilizes these ideas
to address two important code similarity comparison problems. (I) Given a pair
of basic blocks for different instruction set architectures (ISAs), determining
whether their semantics is similar or not; and (II) given a piece of code of
interest, determining if it is contained in another piece of assembly code for
a different ISA. The solutions to these two problems have many applications,
such as cross-architecture vulnerability discovery and code plagiarism
detection. We implement a prototype system INNEREYE and perform a comprehensive
evaluation. A comparison between our approach and existing approaches to
Problem I shows that our system outperforms them in terms of accuracy,
efficiency and scalability. And the case studies utilizing the system
demonstrate that our solution to Problem II is effective. Moreover, this
research showcases how to apply ideas and techniques from NLP to large-scale
binary code analysis.Comment: Accepted by Network and Distributed Systems Security (NDSS) Symposium
201
SWATI: Synthesizing Wordlengths Automatically Using Testing and Induction
In this paper, we present an automated technique SWATI: Synthesizing
Wordlengths Automatically Using Testing and Induction, which uses a combination
of Nelder-Mead optimization based testing, and induction from examples to
automatically synthesize optimal fixedpoint implementation of numerical
routines. The design of numerical software is commonly done using
floating-point arithmetic in design-environments such as Matlab. However, these
designs are often implemented using fixed-point arithmetic for speed and
efficiency reasons especially in embedded systems. The fixed-point
implementation reduces implementation cost, provides better performance, and
reduces power consumption. The conversion from floating-point designs to
fixed-point code is subject to two opposing constraints: (i) the word-width of
fixed-point types must be minimized, and (ii) the outputs of the fixed-point
program must be accurate. In this paper, we propose a new solution to this
problem. Our technique takes the floating-point program, specified accuracy and
an implementation cost model and provides the fixed-point program with
specified accuracy and optimal implementation cost. We demonstrate the
effectiveness of our approach on a set of examples from the domain of automated
control, robotics and digital signal processing
NASTRAN as a resource in code development
A case history is presented in which the NASTRAN system provided both guidelines and working software for use in the development of a discrete element program, PATCHES-111. To avoid duplication and to take advantage of the wide spread user familiarity with NASTRAN, the PATCHES-111 system uses NASTRAN bulk data syntax, NASTRAN matrix utilities, and the NASTRAN linkage editor. Problems in developing the program are discussed along with details on the architecture of the PATCHES-111 parametric cubic modeling system. The system includes model construction procedures, checkpoint/restart strategies, and other features
Energy-Delay Tradeoff and Dynamic Sleep Switching for Bluetooth-Like Body-Area Sensor Networks
Wireless technology enables novel approaches to healthcare, in particular the
remote monitoring of vital signs and other parameters indicative of people's
health. This paper considers a system scenario relevant to such applications,
where a smart-phone acts as a data-collecting hub, gathering data from a number
of wireless-capable body sensors, and relaying them to a healthcare provider
host through standard existing cellular networks. Delay of critical data and
sensors' energy efficiency are both relevant and conflicting issues. Therefore,
it is important to operate the wireless body-area sensor network at some
desired point close to the optimal energy-delay tradeoff curve. This tradeoff
curve is a function of the employed physical-layer protocol: in particular, it
depends on the multiple-access scheme and on the coding and modulation schemes
available. In this work, we consider a protocol closely inspired by the
widely-used Bluetooth standard. First, we consider the calculation of the
minimum energy function, i.e., the minimum sum energy per symbol that
guarantees the stability of all transmission queues in the network. Then, we
apply the general theory developed by Neely to develop a dynamic scheduling
policy that approaches the optimal energy-delay tradeoff for the network at
hand. Finally, we examine the queue dynamics and propose a novel policy that
adaptively switches between connected and disconnected (sleeping) modes. We
demonstrate that the proposed policy can achieve significant gains in the
realistic case where the control "NULL" packets necessary to maintain the
connection alive, have a non-zero energy cost, and the data arrival statistics
corresponding to the sensed physical process are bursty.Comment: Extended version (with proofs details in the Appendix) of a paper
accepted for publication on the IEEE Transactions on Communication
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