Foreword to the special issue on parallel and distributed computing with its applications

Abstract

Parallel and distributed computing has been under many years of development, and paved the way that what information and communication technology looks like nowadays. With the advance of new techniques, such as 5G, cloud computing, and big data, the theory, design, analysis, evaluation, and application of parallel and distributed computing have encountered great challenges to meet the increasing requirements on high performance, energy efficiency, as well as reliability and security. To achieve these goals, interdisciplinary knowledge and some specialized technical skills are required. This special issue is a collection of many examples of how researchers, scholars, vendors, and practitioners are collaborating to address these challenges.The scope of this special issue is broad on parallel and distributed computing and networking. Especially, it presents the research work that addressing heterogeneous computing with the use of accelerators, cloud computing, tools, and methodologies to improve the quality of parallel programming, and applying generic computing approaches to wireless networks. In addition, the work on trusted and security computing is also included. In total, 8 outstanding papers are selected from a number of high quality submissions after rigorous review process.High performance and energy efficiency of parallel and distributed systems and applications are the key topics in this special issue. As a core component of many network infrastructures, packet classification that involves rule matching is required to provide high throughput in order to avoid affecting the network performance. G. Li, D. Zhang, Y. Li, J. Zheng, and K. Li 1 proposed a fuzzy control-based optimizing model for GPU-accelerated packet classification, where energy consumption is saved with a reasonable throughput. Many important parallel algorithms, including matrix computing, sorting, dynamic programming, encryption, and decryption, can be performed by oblivious sequential algorithms. D. Takafuji, K. Nakano, Y.Ito, and J. L. Bordim 2 demonstrated a time-optimal implementation for bulk execution of an oblivious sequential algorithm and developed a tool named C2CU to automatically generate a CUDA C program for this bulk execution. End-to-end delay and energy consumption are the key concerns in designing wireless sensor networks (WSNs); B. Niu, H. Qi, K. Li, X. Liu, and W. Xue addressed this problem in previous study, 3 where a dynamic duty cycle scheme is proposed to reduce the energy consumption while guaranteeing the expected end-to-end delay demand in the opportunistic routing network.Several interesting applications of parallel and distributed computing can also be found in this issue. In typical Internet of Things application scenarios, numerous sensors are deployed to monitor a phenomenon, which in many cases, can be modeled by an underlying stochastic process. H. Jafari, X. Li, L. Qian, A. Aved, and T. Kroecker 4 investigated how to detect change in this process with tolerable false alarm rate. In Shape analysis and part-b...