Locally Decodable Codes and Private Information Retrieval Schemes

Locally Decodable Codes and Private Information Retrieval Schemes
Author: Sergey Yekhanin
Publisher: Springer Science & Business Media
Total Pages: 88
Release: 2010-11-02
Genre: Computers
ISBN: 364214358X

Locally decodable codes (LDCs) are codes that simultaneously provide efficient random access retrieval and high noise resilience by allowing reliable reconstruction of an arbitrary bit of a message by looking at only a small number of randomly chosen codeword bits. Local decodability comes with a certain loss in terms of efficiency – specifically, locally decodable codes require longer codeword lengths than their classical counterparts. Private information retrieval (PIR) schemes are cryptographic protocols designed to safeguard the privacy of database users. They allow clients to retrieve records from public databases while completely hiding the identity of the retrieved records from database owners. In this book the author provides a fresh algebraic look at the theory of locally decodable codes and private information retrieval schemes, obtaining new families of each which have much better parameters than those of previously known constructions, and he also proves limitations of two server PIRs in a restricted setting that covers all currently known schemes. The author's related thesis won the ACM Dissertation Award in 2007, and this book includes some expanded sections and proofs, and notes on recent developments.

Decodable Network Coding in Wireless Network

Decodable Network Coding in Wireless Network
Author: Junwei Su
Publisher:
Total Pages: 33
Release: 2017
Genre:
ISBN:

"Network coding is a network layer technique to improve transmission efficiency. Coding packets is especially beneficial in a wireless environment where the demand for radio spectrum is high. However, to fully realize the benefits of network coding two challenging issues that must be addressed are: (1) Guaranteeing separation of coded packets at the destination, and (2) Mitigating the extra coding/decoding delay. If the destination has all the needed packets to decode a coded packet, then separation failure can be averted. If the scheduling algorithm considers the arrival time of coding pairs, then the extra delay can be mitigated. In this paper, we develop a network coding method to address these (decoding and latency) issues for multi-source multi-destination unicast and multicast sessions. We use linear programming to find the most efficient coding design solution with guaranteed decodability. To reduce network delay, we develop a scheduling algorithm to minimize the extra coding/decoding delay. Our coding design method and scheduling algorithm are validated through experiments. Simulation results show improved transmission efficiency and reduced network delay"--Abstract, page iii.

Instantly Decodable Network Coding

Instantly Decodable Network Coding
Author: Mohammad Shahedul Karim
Publisher:
Total Pages: 0
Release: 2017
Genre:
ISBN:

The network coding paradigm enhances transmission efficiency by combining information flows and has drawn significant attention in information theory, networking, communications and data storage. Instantly decodable network coding (IDNC), a subclass of network coding, has demonstrated its ability to improve the quality of service of time critical applications thanks to its attractive properties, namely the throughput enhancement, delay reduction, simple XOR-based encoding and decoding, and small coefficient overhead. Nonetheless, for point to multi-point (PMP) networks, IDNC cannot guarantee the decoding of a specific new packet at individual devices in each transmission. Furthermore, for device-to-device (D2D) networks, the transmitting devices may possess only a subset of packets, which can be used to form coded packets. These challenges require the optimization of IDNC algorithms to be suitable for different application requirements and network configurations. In this thesis, we first study a scalable live video broadcast over a wireless PMP network, where the devices receive video packets from a base station. Such layered live video has a hard deadline and imposes a decoding order on the video layers. We design two prioritized IDNC algorithms that provide a high level of priority to the most important video layer before considering additional video layers in coding decisions. These prioritized algorithms are shown to increase the number of decoded video layers at the devices compared to the existing network coding schemes. We then study video distribution over a partially connected D2D network, where a group of devices cooperate with each other to recover their missing video content. We introduce a cooperation aware IDNC graph that defines all feasible coding and transmission conflictfree decisions. Using this graph, we propose an IDNC solution that avoids coding and transmission conflicts, and meets the hard deadline for high importance video packets. It is demonstrated that the proposed solution delivers an improved video quality to the devices compared to the video and cooperation oblivious coding schemes. We also consider a heterogeneous network wherein devices use two wireless interfaces to receive packets from the base station and another device concurrently. For such network, we are interested in applications with reliable in-order packet delivery requirements. We represent all feasible coding opportunities and conflict-free transmissions using a dual interface IDNC graph. We select a maximal independent set over the graph by considering dual interfaces of individual devices, in-order delivery requirements of packets and lossy channel conditions. This graph based solution is shown to reduce the in-order delivery delay compared to the existing network coding schemes. Finally, we consider a D2D network with a group of devices experiencing heterogeneous channel capacities. For such cooperative scenarios, we address the problem of minimizing the completion time required for recovering all missing packets at the devices using IDNC and physical layer rate adaptation. Our proposed IDNC algorithm balances between the adopted transmission rate and the number of targeted devices that can successfully receive the transmitted packet. We show that the proposed rate aware IDNC algorithm reduces the completion time compared to the rate oblivious coding schemes.

Neural Codes and Distributed Representations

Neural Codes and Distributed Representations
Author: L. F. Abbott
Publisher: MIT Press
Total Pages: 378
Release: 1999
Genre: Coding theory
ISBN: 9780262511001

Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by topic, the most significant papers that have appeared in the journal over the past nine years. The present volume focuses on neural codes and representations, topics of broad interest to neuroscientists and modelers. The topics addressed are: how neurons encode information through action potential firing patterns, how populations of neurons represent information, and how individual neurons use dendritic processing and biophysical properties of synapses to decode spike trains. The papers encompass a wide range of levels of investigation, from dendrites and neurons to networks and systems.

Completion Delay Minimization for Instantly Decodable Network Coding

Completion Delay Minimization for Instantly Decodable Network Coding
Author: Sameh Sorour
Publisher:
Total Pages: 422
Release: 2011
Genre:
ISBN: 9780494776438

Instantly Decodable Network Coding (IDNC) is a subclass of opportunistic network coding that has numerous desirable properties for a wide spectrum of applications, namely its faster decoding delay, simpler coding and decoding processes, and no decoding buffer requirements. Nonetheless, IDNC suffers from two main problems that may limit its attractiveness, as an implementable solution in future wireless networks, against full network coding (FNC), widely studied in the literature. First, it cannot guarantee the decoding of a new packet at each receiver in each transmission, which may severely affect its completion delay. Second, it requires full feedback in order to operate properly, which may be prohibitive for several practical network settings.To study the effect of feedback reduction, we formulate the completion delay minimization problem, for the cases of intermittent and lossy feedback, as extended SSP and partially observable SSP problems, respectively. We show that these new formulations have the same structure of the original SSP. We thus extend the designed algorithms to operate in intermittent and lossy feedback scenarios, after taking update decisions on the attempted and un-acknowledged packets. These redesigned algorithms are shown to achieve tolerable degradation for relatively low feedback frequencies and high feedback loss rates. iiiIn this thesis, we aim to reduce the effect of these drawbacks by studying the problems of minimizing the IDNC completion delay in full and limited feedback scenarios. Since completion delay cannot be optimized only through local decisions in each of the transmissions, we first study the evolution of the IDNC coding opportunities and determine the strategies maximizing them, not only for one transmission, but for all future transmissions. We then formulate the completion delay problem as a stochastic shortest path (SSP) problem, which turns out to be of extremely large dimensions that makes its optimal solution intractable. Nonetheless, we exploit the structure of this SSP and the evolution of the coding opportunities to design efficient algorithms, which outperform FNC in most multicast scenarios and achieve a near-optimal performance in broadcast scenarios. However, since FNC still outperforms IDNC in some network scenarios, we design an adaptive selection algorithm that efficiently selects, between these two schemes, the one that achieves the smaller completion delay.

1997 IEEE International Conference on Communications

1997 IEEE International Conference on Communications
Author: IEEE Communications Society
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
Total Pages: 600
Release: 1997
Genre: Electrical engineering
ISBN:

These two volumes offer an international perspective on communication systems, presenting advances in telecommunications systems and networks. The topics the books discuss include: ATM; PCS; broadband; optical switching; and signal processing."

Neuro-informatics and Neural Modelling

Neuro-informatics and Neural Modelling
Author: F. Moss
Publisher: Gulf Professional Publishing
Total Pages: 1081
Release: 2001-06-26
Genre: Medical
ISBN: 0080537421

How do sensory neurons transmit information about environmental stimuli to the central nervous system? How do networks of neurons in the CNS decode that information, thus leading to perception and consciousness? These questions are among the oldest in neuroscience. Quite recently, new approaches to exploration of these questions have arisen, often from interdisciplinary approaches combining traditional computational neuroscience with dynamical systems theory, including nonlinear dynamics and stochastic processes. In this volume in two sections a selection of contributions about these topics from a collection of well-known authors is presented. One section focuses on computational aspects from single neurons to networks with a major emphasis on the latter. The second section highlights some insights that have recently developed out of the nonlinear systems approach.