The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

We review a model of computation used in industrial practice in signal processing software environments and experimentally and other contexts. We give this model the name "dataflow process networks," and study its formal properties as well as its utility as a basis for programming language design. Variants of this model are used in commercial visual programming systems such as SPW from the Alta Group of Cadence (formerly Comdisco Systems), COSSAP from Synopsys (formerly Cadis), the DSP Station from Mentor Graphics, and Hypersignal from Hyperception. They are also used in research software such as Khoros from the University of New Mexico and Ptolemy from the University of California at Berkeley, among many others. Dataflow process networks are shown to be a special case of Kahn process networks, a model of computation where a number of concurrent processes communicate through unidirectional FIFO channels, where writes to the channel are nonblocking, and reads are blocking. In dataflow process networks, each process consists of repeated "firings" of a dataflow "actor." An actor defines a (often functional) quantum of computation. By dividing processes into actor firings, the considerable overhead of context switching incurred in most implementations of Kahn process networks is avoided. We relate dataflow process networks to other dataflow models, including those used in dataflow machines, such as static dataflow and the tagged-token model. We also relate dataflow process networks to functional languages such as Haskell, and show that modern language concepts such as higher-order functions and polymorphism can be used effectively in dataflow process networks. A number of programming examples using a visual syntax are given. >

/pdf/dataflow-process-networks-3mdwy0uhx2.pdf

Dataflow process networks

The rapid uptake of mobile devices and the rising popularity of mobile applications and services pose unprecedented demands on mobile and wireless networking infrastructure. Upcoming 5G systems are evolving to support exploding mobile traffic volumes, real-time extraction of fine-grained analytics, and agile management of network resources, so as to maximize user experience. Fulfilling these tasks is challenging, as mobile environments are increasingly complex, heterogeneous, and evolving. One potential solution is to resort to advanced machine learning techniques, in order to help manage the rise in data volumes and algorithm-driven applications. The recent success of deep learning underpins new and powerful tools that tackle problems in this space. In this paper, we bridge the gap between deep learning and mobile and wireless networking research, by presenting a comprehensive survey of the crossovers between the two areas. We first briefly introduce essential background and state-of-the-art in deep learning techniques with potential applications to networking. We then discuss several techniques and platforms that facilitate the efficient deployment of deep learning onto mobile systems. Subsequently, we provide an encyclopedic review of mobile and wireless networking research based on deep learning, which we categorize by different domains. Drawing from our experience, we discuss how to tailor deep learning to mobile environments. We complete this survey by pinpointing current challenges and open future directions for research.

/pdf/deep-learning-in-mobile-and-wireless-networking-a-survey-ct8cy2kuqi.pdf

Deep Learning in Mobile and Wireless Networking: A Survey

Objects. The ~ b s t rac t ~ b j ect forms the fundamental base class for the entire design and all other classes are derived from this base class. The Abstract Object class defines and characterizes all the essential properties every class in this 404 OBJECT-ORIENTED SIMULATION

Handbook of Simulation

Network lifetime has become the key characteristic for evaluating sensor networks in an application-specific way. Especially the availability of nodes, the sensor coverage, and the connectivity have been included in discussions on network lifetime. Even quality of service measures can be reduced to lifetime considerations. A great number of algorithms and methods were proposed to increase the lifetime of a sensor network—while their evaluations were always based on a particular definition of network lifetime. Motivated by the great differences in existing definitions of sensor network lifetime that are used in relevant publications, we reviewed the state of the art in lifetime definitions, their differences, advantages, and limitations. This survey was the starting point for our work towards a generic definition of sensor network lifetime for use in analytic evaluations as well as in simulation models—focusing on a formal and concise definition of accumulated network lifetime and total network lifetime. Our definition incorporates the components of existing lifetime definitions, and introduces some additional measures. One new concept is the ability to express the service disruption tolerance of a network. Another new concept is the notion of time-integration: in many cases, it is sufficient if a requirement is fulfilled over a certain period of time, instead of at every point in time. In addition, we combine coverage and connectivity to form a single requirement called connected coverage. We show that connected coverage is different from requiring noncombined coverage and connectivity. Finally, our definition also supports the concept of graceful degradation by providing means of estimating the degree of compliance with the application requirements. We demonstrate the applicability of our definition based on the surveyed lifetime definitions as well as using some example scenarios to explain the various aspects influencing sensor network lifetime.

/pdf/on-the-lifetime-of-wireless-sensor-networks-59hdyqoqi3.pdf

On the lifetime of wireless sensor networks

Tailoring cloud support for each autonomous-driving application would require maintaining multiple infrastructures, potentially resulting in low resource utilization, low performance, and high management overhead. To address this problem, the authors present a unified cloud infrastructure with Spark for distributed computing, Alluxio for distributed storage, and OpenCL to exploit heterogeneous computing resources for enhanced performance and energy efficiency.

A Unified Cloud Platform for Autonomous Driving

Data-flow languages have been hailed as the solution to the programmability of general-purpose multiprocessors. However, data-flow semantics introduce constructs that lead to much overhead at compilation, allocation, and execution time. Indeed, due to its functionality, the data-flow model of computation does not handle repetitive program constructs very efficiently. This is due to the fact that the cornerstone of data flow, namely the concept of single assignment, is opposed to the idea of reexecution of a portion of program as in a loop. A corollary of this problem is the effective representation, storage, and processing of data structures, as these will most often be used in loops. In this paper, various aspects of this issue are explailned in detail. Several solutions that have been put forward in the current literature are then surveyed and analyzed. In order to offset some of the disadvantages presented by these, we introduce new methods for handling arrays. In the first one, we raise the level of computation to that of arrays for more efficient operation. In the two others, the opposite approach is taken, and the notion of array is done away with entirely at the execution level in order to take advantage of the data-flow semantics at their best logical level of performance.

Sructure Handling in Data-Flow Systems

From the Publisher:
Examines recent advances in design, modeling, and implementation of dataflow and multithreaded computers. The text contains reports concerning many of the world's leading projects engaged in the continuing evolution and application of dataflow concepts. It covers the broad range of dataflow principles in program representation - from language design to processor architecture - and compiler optimization techniques. The book includes papers on massively parallel distributed memory and multithreaded architecture design, synchronization and pipelined design, and superpipelined data-driven VLSI processors. Other sections discuss stream data types, the development of well-structured software, and parallelization of dataflow programs. It also details an analytical model for the behavior of dataflow graphs, compares a centralized work distribution scheme with a distributed scheme, and presents a comprehensive approach to understanding workload management schemes. Altogether, the text introduces the reader to dataflow concepts that show how functional programming ideas can be harnessed to exploit the power of parallel computing.

Advanced Topics in Dataflow Computing and Multithreading

This paper describes an abstract multithreaded architecture for distributed memory multicomputers that significantly reduces the number of message transfers when compared to conventional "remote memory access" approaches instead of statically executing on its assigned processor and fetching data from remote storage, a Nomadic Thread transfers itself to the processor which contains the data it needs. This enables Nomadic Threads to take advantage of spatial locality found in the usage of many data structures, because the migration of a thread to a node makes access to surrounding data local. By reducing the number of messages and laking advantage of locality the Nomadic Threads approach allows programs to use fewer data transfers than conventional approaches while providing a simple runtime interface to compilers. The Nomadic Threads runtime system is currently implemented for the Thinking Machines Corp. Connection Machine 5 (CM5), but is portable to other distributed memory systems, including networks of workstations.

Nomadic Threads: a migrating multithreaded approach to remote memory accesses in multiprocessors

Multicore processors have emerged to be the popular and powerful computing engines to address the increasing performance demands and energy efficiency requirements of modern real-time applications. Voltage and frequency island (VFI) was recently adopted as an effective energy management technique for multicore processors. For a set of periodic real-time tasks that access shared resources running on a VFI-based multicore system with dynamic voltage and frequency scaling (DVFS) capability, we study both static and dynamic synchronization-aware energy management schemes. First, based on the enhanced MSRP resource access protocol with a suspension mechanism, we devise a synchronization-aware task mapping heuristic for partitioned- EDF scheduling. The heuristic assigns tasks that access similar set of resources to the same core to reduce the synchronization overhead and thus improve schedulability. Based on the result task-to-core mapping, static energy management schemes with both a uniform and different scaled frequencies for VFIs are studied. To further exploit dynamic slack for more energy savings, we propose an integrated synchronization-aware slack management framework to appropriately reclaim, preserve, release and steal slack at runtime to slow down the execution of tasks subject to the common voltage/frequency limitation of VFIs and timing/synchronization constraints of tasks. Taking the additional delay due to task synchronization into consideration, the new scheme allocates slack in a fair manner and scales down the execution of both non-critical and critical sections of tasks for more energy savings. Simulation results show that, the synchronization-aware task mapping scheme can significantly improve the schedulability of tasks. The energy savings obtained by the static scheme with different frequencies for VFIs is close to that of an optimal INLP (integer non-linear programming) solution. Moreover, compared to the simple extension of existing solutions for uniprocessor systems, our dynamic scheme can obtain much better energy savings (up to 40%) with comparable DVFS overhead.

/pdf/synchronization-aware-energy-management-for-vfi-based-1f3jqlo23s.pdf

Jean-Luc Gaudiot

Papers

A Unified Cloud Platform for Autonomous Driving

Sructure Handling in Data-Flow Systems

Advanced Topics in Dataflow Computing and Multithreading

Nomadic Threads: a migrating multithreaded approach to remote memory accesses in multiprocessors

Synchronization-Aware Energy Management for VFI-based Multicore Real-Time Systems (Extended Version)