Journal Information
Journal of Parallel and Distributed Computing (JPDC)
Impact Factor:

Call For Papers
The Journal of Parallel and Distributed Computing (JPDC) is directed to researchers, scientists, engineers, educators, managers, programmers, and users of computers who have particular interests in parallel processing and/or distributed computing. The goal of the journal is to publish in a timely manner original research, critical review articles, and relevant survey papers on the theory, design, implementation, evaluation, programming, and applications of parallel and/or distributed computing systems. The journal provides an effective forum for communication among researchers and practitioners from various scientific areas working in a wide variety of problem areas, sharing a fundamental common interest in improving the ability of parallel and distributed computer systems to solve increasing numbers of difficult and complex problems as quickly and as efficiently as possible.

The scope of the journal includes (but is not restricted to) the following topics as they relate to parallel and/or distributed computing:

• Theory of parallel and distributed computing
• Parallel algorithms and their implementation
• Innovative computer architectures
• Shared-memory multiprocessors
• Peer-to-peer systems
• Distributed sensor networks
• Pervasive computing
• Optical computing
• Software tools and environments
• Languages, compilers, and operating systems
• Fault-tolerant computing
• Applications and performance analysis
• Bioinformatics
• Cyber trust and security
• Parallel programming
• Grid computing
Last updated by Dou Sun in 2019-11-24
Special Issues
Special Issue on Smart Mobility Management and 5G/Beyond 5G (B5G) Wireless Access
Submission Date: 2020-11-10

The world’s population growth and increased urbanization are significant trends in the formation of tomorrow’s society. Estimates show that more than 85% of the developed world’s population will be living in a relatively small number of big cities by 2025, and the world’s population will reach 11.2 billion people by 2100, even with the slower population growth. The ever-growing population and expected agglomeration in big cities will increase vehicles on the roads and deteriorate urban mobility and traffic-related situations, such as congestion and safety. With the ever-increasing demand for more efficient and safer mobility in large urban centers, reliable and distributed wireless services will be required to support intelligent transportation systems, smart mobility, and infotainment services for high mobile users in public and private transportation networks towards efficient, green, safe and enjoyable urban mobility. This vision requires a more pervasive and ubiquitous wireless access and networking core technologies for the provisioning of highly reliable and ultra-low latency services for interoperable communication and multimedia content distribution in smart mobility applications. With huge improvements over the past generations, upcoming 5G networks have tremendous potential to satisfy highly dynamic traffic and stringent delay requirements of rich and heterogeneous mobile services and intelligent transportation systems. However, it will require the high-density deployment of a large number of small base stations, which will bring many open issues to be addressed, including the design of mobility-enabled resource management for small cells, multimedia content cache and delivery on the 5G network edge, efficient D2D communication, and architectures for interoperable communication among heterogeneous mobile entities. Thus, the aim of this JPDC special issue is to provide state-of-the-art solutions for smart mobility and mobility management in 5G/B5G networks. This special issue seeks high-quality and original technical contributions in the field of mobility management and 5G/Beyond 5G (B5G) wireless access to efficiently support the vision of smart mobility and mobile services for urban computing. Submissions will be judged on their originality, significance, clarity, relevance, and technical correctness. Submitted papers must not be under consideration in any other venue(s). Potential topics include, but are not limited to: Modeling, analysis and characterization of urban mobility Data analytics for smart mobility services Data analytics for 5G-enabled intelligent transportation systems 5G/B5G-enabled mobile cloud and edge computing for mobile applications Architectures, techniques and applications of 5G/B5G-enabled mobile intelligent edge cloud Machine learning algorithms and systems for 5G-enabled edge computing Radio technologies for high mobility transportation systems Information-centric networking architectures for 5G mobile services Mobility-assisted content caching on 5G small cells Mobility-assisted protocols for efficient D2D communication Architectures, protocols and algorithms for efficient interconnection of smart mobile objects Mobility-enabled resource management on 5G networks AI-based modeling and analysis for 5G mobile communications 5G-enabled multimedia-based smart mobility applications Mobility management and crowdsourcing for smart cities and ITS Mobility management for connected cars Hand-over management and predictive models
Last updated by Dou Sun in 2020-05-27
Special Issue on Connected Vehicles meet Big Data technologies: Recent Advances and Future Trends
Submission Date: 2020-12-15

Nowadays, connected vehicles are able to collect up to 170 measurements (speed, temperature, fuel consumption, etc.) from on board built-in sensors and transmit them to an infrastructure, usually by 4G/5G wireless communications. This raises many opportunities to develop new and innovative telematics services including, among others, driver safety, customer experience, location-based services, dealer services, infotainment, etc. It is expected that there will be roughly 2 billion connected cars by the end of 2025 on the world’s roadways, where each of which can produce up to 30 terabytes of data each day. This huge amount of data, whereas it offers interesting commercial opportunities, it emphasizes however the development of sophisticated computation frameworks, in particular parallel and distributed ones, for collecting, gathering and analyzing the generated data. Most notable, among the challenges facing connected vehicles applications, is the infrastructure’s ability of real-time or near real time processing in order to enable new and innovative services. In fact, a broad range of applications, more precisely safety application (e.g., early alert on the presence of freezing rain on roads), is based on a new emerging communication paradigm, known as “car-to-car communication via infrastructure”. The performance, and even the existence, of this paradigm is highly dependent on the infrastructure’s ability to collect information, process and gather it and finally deliver it (i.e., sending back) to cars within acceptable delays. Even the latter depend on the target applications, they are mostly required to be very short to meet real-time or near real-time delays. This is true specifically for safety applications. The objective of this special issue is to explore recent advances and future trends in developing, as well as deploying innovative applications related to connected vehicles. It aims to provide a forum for researchers and practitioners to foster exchange of research ideas, approaches, theories, practices and industrial experiences to resolve challenging issues associated with managing big data generated from connected vehicles, whilst considering their intrinsic requirements. This special issue seeks high-quality and original technical contributions as well as industrial experiences. Submissions will be judged on their originality, significance, clarity, relevance, and technical correctness. High-quality survey papers are also welcome. Submitted papers must not be under consideration in any other venue(s). Topics of interest are (but not limited to): Stream computing for connected vehicle’s big data Parallel and distributed Big Data architectures for connected vehicles VANET Big Data for Predicting Traffic Congestion IoT connected vehicles data analytics Cloud computing systems for connected vehicles Massive parallel-processing systems for connected vehicle’s big data Architectures (software and hardware) for managing connected vehicle data Dynamic resource, service and context management for connected vehicle applications Quality of Service/Experience (QoS/QoE) provisioning for connected vehicle’s applications Formal verification techniques for protocols and applications of connected vehicles. 5G communication architecture and protocols for V2I and I2V Performance evaluation of connected vehicles big data platforms Big Data Analysis for Vehicular Social Networks (VSN) Transportation visualization based on VSN big data Mobility modeling and big data mining in Connected and Autonomous Vehicles Human mobility prediction and visualization leveraging big data AI based techniques for connected and autonomous vehicles Data privacy and security for connected vehicular networks
Last updated by Dou Sun in 2020-07-04
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