Journal Information
Future Generation Computer Systems
Impact Factor:

Call For Papers
The Grid is a rapidly developing computing structure that allows components of our information technology infrastructure, computational capabilities, databases, sensors, and people to be shared flexibly as true collaborative tools. Over the last 3 years there has been a real explosion of new theory and technological progress supporting a better understanding of these wide-area, fully distributed computing systems. After the advances made in distributed system design, collaborative environments, high performance computing and high throughput computing, the Grid is the logical next step.

The new Aims and Scope of FGCS will cover new developments in:

[1] Grid Applications and application support:

    Novel applications
    eScience and eBusiness applications
    Problem solving environments and virtual laboratories
    Grid economy
    Semantic and knowledge based grids
    Collaborative Grids and virtual organizations
    High Performance and high throughput computing on grids
    Complex application workflows
    Scientific, industrial and social implications
    Grids in education

[2] Grid methods and middleware:

    Tools for grid development: monitoring and scheduling
    Distributed dynamic resource management
    Grid- and web-services
    Information management
    Protocols and emerging standards
    Peer to peer and internet computing
    Pervasive computing
    Grid Security

[3] Grid Theory:

    Process specification; program and algorithm design
    Theoretical aspects of wide area communication and computation
    Scaling and performance theory
    Protocol verification

Last updated by Xin Yao in 2017-11-12
Special Issues
Special Issue on Emerging Edge-of-Things Computing: Opportunities and Challenges
Submission Date: 2017-11-30

Recently, the Internet of Things (IoT) has emerged as a revolutionary technology that promises to offer a fully connected “smart” world. It enables billions of everyday objects such as consumer goods, enduring products, vehicles, utility components, sensors, and other physical devices to be connected with the global Internet that aims to transform the way we live, work, and play. However, a wide-scale realization of IoT is hindered due to the significant constraints of IoT devices in terms of memory, processing resources, energy, or communication bandwidth. The rise of Cloud-assisted Internet of Things or Cloud-of-Things (CoT) paradigm has been seen as an enabler to solve many of these issues as it offers networked and remote computing resources to process, manage, store and share huge volume of IoT data. It has stimulated the development of various innovative and novel applications in areas such as smart cities, smart homes, smart grids, smart agriculture, smart transportation, smart healthcare, etc. to improve all aspects of people’s life. However, currently the CoT paradigm is facing increasing difficulty to handle the Big data that IoT generates from these application use cases. As billions of previously unconnected devices are now generating more than two exabytes of data each day, it is challenging to ensure low latency and network bandwidth consumption, optimal utilization of computational recourses, scalability and energy efficiency of IoT devices while moving all data to the Cloud. To cope with these challenges, a recent trend is to deploy anEdge Computinginfrastructure between IoT systems and Cloud computing. This new paradigm termed asEdge-of-Things(EoT) computing, allows data computing, storage and service supply to be moved from Cloud to the local Edge devices such as smart phones, smart gateways or routers and local PCs that can offer computing and storage capabilities on a smaller scale in real-time. EoT pushes data storage, computing and controls closer to the IoT data source(s); therefore, enables each Edge device to play its own role of determining what information should be stored or processed locally and what needs to be sent to the Cloud for further use. Thus, EoT complements CoT paradigm in terms of high scalability, low delay, location awareness, and allowing of using local client computing capabilities in real time. While researchers and practitioners have been making progress within the area of Edge-of Things computing, still there exists several issues that need to be addressed for its large-scale adoption. Some of these issues are: novel network architecture and middleware platform for EoT paradigm considering emerging technologies such as 5G wireless networks, software defined network and semantic computing; Edge analytics for IoT Big data; novel security and privacy methods for EoT; social intelligence into the Edge node to host IoT applications; and context-aware service management on the EoT with effective quality of service (QoS) support and other issues. This special issue targets a mixed audience of researchers, academics and investigators from different communities to share and exchange new ideas, approaches, theories and practice to resolve the challenging issues associated with the leveraging of Edge computing for Edge-of-Things paradigm. Therefore, the suggested topics of interest for this special issue include, but are not limited to: - Novel middleware architecture design for EoT paradigm - Semantic Edge computing for IoT - Edge analytics for Big data in IoT - Edge-enabled 5G network architecture and protocols for IoT - Software Defined Networking for EoT paradigm - Social intelligence in EoT system - EoT operating system design and validation - Interoperability and mobility for Edge to IoT connectivity - Trust, security and privacy issues in EoT system - Resource, service and context management on Edge computing for IoT applications - Software and simulation platform for EoT paradigm - Energy-aware resource scheduling in Edge computing for IoT applications - Emerging Edge commuting services and applications for IoT - Industrial Edge computing in IoT paradigm
Last updated by Dou Sun in 2017-08-05
Special Issue on Intelligent Security and Optimization in Edge/Fog Computing
Submission Date: 2017-12-15

Edge/fog computing is considered a potential characteristic novel technique that powers up the implementation of cloud computing in industry 4.0. The edge server layer is expected to be a medium that intelligently optimize the use of the computing resources. This technology innovation has begun to drive new levels of performance and productivity in multiple domains. Meanwhile, cloud computing also is becoming a major enabler of various industrial innovations. Within the transformations, edge/fog computing is a quick powered component that combines cloud computing with other network-based techniques, such as Internet-of-Things (IoT) and web services. Even though edge/fog computing has a great potential to speed up the next generation of the networking implementations, security and privacy concerns still are restricting its applications. The threats exist at different layers due to more parties are involved in the service processes. Both detecting threats and finding out solutions are significant. Building up an intelligent security mechanism in edge/fog computing is an urgent mission in an advanced network setting. This special issue aims to gather recent research work in security and privacy topics and discuss, evaluate, and improve the novel approaches of data protections in edge/fog computing. Our primary focus will address novel security mechanisms in edge/fog computing, advanced secure deployments for large scaled edge/fog computing, intelligent secure solutions, and new efficient data encryption strategy of edge/fog computing. Scope: Topics of particular interest include, but are not limited to: - Trust in social networks in edge/fog computing in edge/fog computing - Security policy, model and architecture in edge/fog computing - Security in social networks in edge/fog computing - Security in parallel and distributed systems in edge/fog computing - Security in mobile and wireless communications in edge/fog computing - Security in cloud/pervasive computing in edge/fog computing - Privacy in parallel and distributed systems in edge/fog computing - Privacy in cloud/pervasive computing in edge/fog computing - Privacy in mobile and wireless communications in edge/fog computing - Privacy in e-commerce and e-government in edge/fog computing - Privacy in network deployment and management in edge/fog computing - Computational forensics in edge/fog computing - Cyber-physical system forensics in edge/fog computing - Data mining for forensics in edge/fog computing
Last updated by Dou Sun in 2017-10-29
Special Issue on Big Data for Context-Aware Applications and Intelligent Environments
Submission Date: 2017-12-15

This special issue addresses core topics on the design, the use and the evaluation of Big Data enabling technologies to build next-generation context-aware applications and computing systems for future intelligent environments. Disruptive paradigm shifts such as the Internet of Things (IoT) and Cyber-Physical Systems (CPS) will create a wealth of streaming context information. Large-scale context-awareness combining IoT and Big Data will drive to creation of smarter application ecosystems in diverse vertical domains, including smart health, finance, smart grids and cities, transportation, Industry 4.0, etc. However, effectively tapping into growing amounts of disparate contextual information streams remains a challenge, especially for large-scale application and service providers that need timely and relevant information to support adequate decision-making. A deeper understanding is necessary on the strengths and weaknesses of state-of-the-art big data processing and analytics systems (Hadoop, Spark, Storm, Samza, Flume, Kafka, Kudu, etc.) to realize large-scale context-awareness and build Big Context architectures. In particular, the key question is how one can help identify relevant context information, ascertain the quality of the context information, extract semantic meaning from heterogeneous distributed information sources, and do this data processing effectively for many concurrent context-aware applications with different requirements for adequate decision-making. At the same time, fundamental research is necessary to understand how context information about these large-scale distributed data processing infrastructures itself can offer the intelligence to self-adapt the configuration of these systems to optimize resource usage, such as the networking, data storage, and computation required to process context data. The particular focus of this special issue is on Big Context solutions covering the modeling, designing, implementation, assessment and systematic evaluation of large-scale context-aware applications and intelligent Big Data systems. We are soliciting high-quality, original research papers and encourage submissions that cover the broad range of research topics combining Big Data and context-aware applications or intelligent environments, including practical applications and case studies, application design methodologies, empirical evaluation of systems and metrics, underpinning theories, and more technical/scientific research topics. The possible topics include but are not limited to: - Big Data architectures for large-scale context-aware applications - Context models and query languages for heterogeneous data streams - Distributed context reasoning with Big Data technologies - Machine learning and prediction of situational awareness with Big Data - Effective data collection and processing for concurrent context-aware applications - Modeling of Quality of Service constraints and enforcing of Service Level Agreements - Context-aware dynamic decision making on streaming Big Data - Context-driven monitoring, adaptation and optimization of Big Data systems - Large-scale Quality of Context management - Systematic comparison of Big Data technologies for context-aware applications - Big Context solutions for finance, health, smart cities, industry 4.0, etc. - Security, privacy, scalability, and sustainability concerns Big Context systems
Last updated by Dou Sun in 2017-08-05
Special Issue on Edge of the Cloud
Submission Date: 2017-12-31

This special issue aims to draw together a number of papers which address challenges in the area of Edge or Fog computing. The inter-networking of physical devices, vehicles and buildings has led to the Internet of Things (IoT). But such cyber-physical systems need to respond in real-time and traditional Cloud computing does not support systems with such time dependency well. Time-sensitive applications are therefore moving from the centre to the edge of the cloud to avoid latency in communication. But when should a service sit on the edge of the cloud and when in the centre? How can applications be partitioned such that a time-critical part can be at the edge and time independent part in the Cloud? The decision might depend on the particular use at a particular time creating the desirability of migration and leading to a Fog of Things. Artificial intelligence or data-driven methods can be used to ascertain whether a service should sit on the edge or in the centre of the cloud and indeed whether, when and how migration should take place. Platforms and systems need to be developed to support such dynamics. This special issue calls for papers from researchers working making inroads in this fascinating area so that we can gather together a state-of-the-art account. Research or review papers are sought. The following themes are of particular interest: - Implementing time-critical applications in a Cloud environment - Models of implementation for cyber-physical systems - Conditions and systems that support dynamic migration of applications - Trade-off between performance and energy efficiency among cloud and fog computing in complex and large applications - New network systems or architectures for dynamic environments in fog and cloud computing - New economic models for the configuration of cloud and fog environments - New standards for heterogeneous communication and network - New task and storage allocation models for cloud and fog computing - Interesting application stories and lessons - Service models for composing or integrating heterogeneous resources in cloud and fog - Security models for fog computing and the Internet of Things
Last updated by Dou Sun in 2017-09-16
Special Issue on Accountability and Privacy Issues in Blockchain and Cryptocurrency
Submission Date: 2017-12-31

Cryptocurrency is a digital version of currency that uses cryptographic technologies to guarantee the security of transactions. In recent years, cryptocurrencies such as Bitcoin and Ether are increasingly popular, including among cybercriminals (e.g. in ransomware cases). Blockchain underpins many of the existing cryptocurrencies, and plays an extremely important role due to its many desirable properties (e.g. transaction distribution and decentralized consensus). Applications of blockchain include identity management, smart contract, e-health, and many others are emerging. Currently, the daily cryptocurrency trading volume reportedly exceeds USD 1 billion. Similar to other technologies, ensuring privacy and accountability is important. For example, how to balance privacy, accountability, and security in blockchain and cryptocurrency is a challenging problem, and one that we focus on in this special issue. This special issue aims to publish state-of-the-art research advances in accountability, security and privacy topics relating to blockchain and cryptocurrency, with emphasis on the following aspects: - Accountability in Blockchain and Cryptocurrency - Anonymity in Blockchain and Cryptocurrency - Application of Blockchain - Auditing in Blockchain and Cryptocurrency - Blockchain Application - Bitcoin & Altcoins - Distributed Ledger Technology - Integrity in Blockchain and Cryptocurrency - Proof-of-Work - Proof-of-State - Privacy-Preserving Authentication - Smart Contract - Scalability of Blockchain and Cryptocurrency - Legal and Regulation Issues in Blockchain and Cryptocurrency
Last updated by Dou Sun in 2017-09-23
Special Issue on High Performance Services Computing and Internet Technologies
Submission Date: 2017-12-31

Since its establishment as a software design style, Service Oriented Architectures have taken the ICT world by storm. The Lego pieces logic thrived through Cloud Computing and it is now considered the standard approach in practically every application framework. The keyword for this success is adaptivity: Service Oriented Architectures are implemented through a wide range of technologies and tools leading to numerous combinations that meet the application requirements in the desired way. But there is a specific combination of application characteristics and requirements that seemingly put SOAs to the test: data-intensive tasks coupled with performance and temporal requirements. The challenge is justified because SOAs are simply not meant to deal with shifting large data volumes between nodes. And unfortunately this is a common problem nowadays: IoT and big data applications are simply two general application categories that come with exactly those characteristics and -more often than not- with the said temporal requirements. To a certain extent the problem is mitigated through the increase of the SOA infrastructures’ computing and storage node density while “stretching” them at the same time. Edge and fog computing as well as lambda services are emerging trends that validate the concept. This special issue invites research communities from a diverse set of scientific areas such as cloud, distributed, parallel and high-performance computing to publish their work and share opinions about applications, challenges and viable solutions to the potential new systems emerging from the need to deal with data intensive application tasks within a SOA framework. The issue will focus on technologies and solutions related (but not limited) to: - Foundational aspects of SOA, Services Computing and HPC - Service oriented computing architectures for Big data and data-intensive tasks - Internet of Things Technologies - Edge and Fog Computing - HPC Cloud and Services oriented computing - Service-oriented Computing for Smart Systems and Cyber Physical Systems - System Virtualization and Container infrastructures for Service Computing - Microservice-based systems and architectures - Lambda and nano services - Service migration and other approaches to Elastic Computing - Operations and Management for Service-Based Systems - Software Engineering and Programming models for Service Oriented Computing - Service-oriented Business Models and Business Process Integration - Standards and Specifications of Services - Service Security, Privacy and Trust - Use cases for Service-oriented Computing
Last updated by Dou Sun in 2017-09-30
Special Issue on Autonomous Cloud
Submission Date: 2017-12-31

Autonomous Cloud is an exciting area of development and research that utilizes artificial intelligence, machine learning and data analytics to aid in intelligent cloud management and decision making. Such techniques can support automation of operations such as services mapping, scaling, network design, data organization and security management. However the drawback with machine learning is that the learning period can be long. Furthermore the priority of particular performance indicators can vary with changing stakeholder requirements adding more complexity and learning time. . To what extent can the Cloud be self-organising? This special issue brings together high-standard research and review papers that reveal the edge of the art in this important, challenging area. Areas of interest include but are not limited to: - New models for the distributed cloud infrastructure - Autonomous and distributed cloud management systems - Novel methods for predictive load modelling possibly using application semantics and considering time zones and location - Distributed analytics – considering data and usage patterns across the network and federated Cloud - Load balancing, data balancing and task scheduling in dynamic environments - Services and application mapping considering both Cloud and Cloud edge locations - Intelligent Cloud responses to application and usage behaviours - Application agents that determine best placement for applications - Machine learning for autonomous Cloud - Vertical and horizontal tuning for application areas and application examples - Dynamic network design to meet changing requirements and loading - Cloud security and dynamic security management
Last updated by Dou Sun in 2017-10-29
Special Issue on Cyber Threat Intelligence and Analytics
Submission Date: 2017-12-31

In today’s Internet-connected world where technologies underpin almost every facet of our society, cyber security and forensics specialists are increasingly dealing with wide ranging cyber threats in almost real-time conditions. The capability to detect, analyze and defend against such threats in near real-time conditions is not possible without employment of threat intelligence, big data and machine learning techniques. For example, when a significant amount of data is collected from or generated by different security monitoring solutions, intelligent and next generation big-data analytical techniques are necessary to mine, interpret and extract knowledge of these unstructured/structured (big) data. Thus, this gives rise to cyber threat intelligence and analytics solutions, such as big data, artificial intelligence and machine learning, to perceive, reason, learn and act against cyber adversaries tactics, techniques and procedures. Cyber threat intelligence and analytics is among one of the fastest growing interdisciplinary fields of research bringing together researchers from different fields such as digital forensics, political and security studies, criminology, cyber security, big data analytics, machine learning, etc. to detect, contain and mitigate advanced persistent threats and fight against malicious cyber activities (e.g. organized cyber crimes and state-sponsored cyber threats). This special issue is focused on cutting-edge research from both academia and industry, with a particular emphasis on novel techniques, combination of tools and so forth to perceive, reason, learn and act on a wide range of cyber threat data collected from different intrusion attempts, malware campaigns and indications of compromise. Only technical papers describing previously unpublished, original, state-of-the-art research, and not currently under review by a conference or a journal will be considered. Extended work must have a significant number of "new and original" contributions along with more than 60% brand "new" material. Specifically, this issue welcomes two categories of papers: (1) invited articles from qualified experts; and (2) contributed papers from open call with list of addressed topics. Topics of interest include but not limited to: - Detection and analysis of advanced threat actors tactics, techniques and procedures - Analytics techniques for detection and analysis of cyber threats - Application of machine learning tools and techniques in cyber threat intelligence - Theories and models for detection and analysis of advanced persistent threats - Automated and smart tools for collection, preservation and analysis of digital evidences - Threat intelligence techniques for constructing, detecting, and reacting to advanced intrusion campaigns - Applying machines learning tools and techniques for malware analysis and fighting against cyber crimes - Intelligent forensics tools, techniques and procedures for cloud, mobile and data-centre forensics - Intelligent analysis of different types of data collected from different layers of network security solutions - Threat intelligence in cyber security domain utilising big data solutions such as Hadoop - Intelligent methods to manage, share, and receive logs and data relevant to variety of adversary groups - Interpretation of cyber threat and forensic data utilising intelligent data analysis techniques - Infer intelligence of existing cyber security data generated by different monitoring and defense solutions - Automated and intelligent methods for adversary profiling - Automated integration of analysed data within incident response and cyber forensics capabilities
Last updated by Dou Sun in 2017-08-05
Special Issue on Security and Privacy in Cyber Physical Systems
Submission Date: 2017-12-31

A cyber-physical system (CPS) is a complex blend of physical and computer components in which physical systems are usually monitored or controlled by computer-based algorithms with possibly humans in the loop. In cyber physical systems, physical and software components are deeply intertwined, each operating on different spatial and temporal scales, exhibiting multiple and distinct behavioral modalities, and interacting with each other in a myriad of ways that change with context. Examples of CPS include smart grid, autonomous transportation systems, medical monitoring, process control systems, robotics systems, and automatic pilot avionics. New smart CPSs will drive innovation and competition in sectors such as food and agriculture, energy, different modes of transportation including air and automobiles, building design and automation, healthcare and medical implants, and advanced manufacturing. Advances in CPS will enable capability, adaptability, scalability, and usability that will far exceed the simple embedded systems of today. CPSs are subject to security and privacy issues stemming from the increasing reliance on computer and communication technologies. The more complex a system gets, the more vulnerabilities it will have. Cybersecurity and privacy threats exploit the increased complexity and connectivity of critical infrastructure systems, placing the Nation’s security, economy, public safety, and health at risk. Historically, reliance on subtle assumptions at interface boundaries between hardware components, between hardware and software components, and between software components, as well as between a system and its operators and maintainers, has been a source of vulnerability and can be especially troublesome in these critical systems. The goal of this special issue is to foster novel, transformative and multidisciplinary approaches that ensure the security of current and emerging cyber-physical systems by taking into consideration the unique challenges present in this environment. This special issue also aims to foster a research community committed to advancing research and education at the confluence of cybersecurity, privacy, and cyber-physical systems, and to transitioning its findings into engineering practice. The proposed Special Issue of FGCS will promote research and reflect the most recent advances of security and privacy in cyber physical systems, with emphasis on the following aspects, but certainly not limited to: - Adaptive attack mitigation for CPS - Authentication and access control for CPS - Availability, recovery and auditing for CPS - Data security and privacy for CPS - Embedded systems security and privacy - EV charging system security - Intrusion detection for CPS - Key management in CPS - Legacy CPS system protection - Lightweight crypto and security - Security and privacy in industrial control systems - Smart grid security - Threat modeling for CPS - Urban transportation system security - Vulnerability analysis for CPS - Wireless sensor network security and privacy
Last updated by Dou Sun in 2017-08-05
Special Issue on Blockchain and Decentralization for Internet of Things
Submission Date: 2018-02-01

The Internet of things (IoT) has been connecting extraordinarily large number of devices to the Internet. Handling the massive amount of data generated by these devices in efficient, secure and economic ways is an essential research question. Current solutions are mostly based on cloud computing infrastructures, which necessitate high-end servers and high-speed networks to provide services related to storage and computation. However, a cloud-enabled IoT framework manifests a number of significant disadvantages, such as high cloud server maintenance costs, weakness for supporting time-critical IoT applications, security and trust issues, etc., which impede its wide adoption. Therefore, it is essential for research communities to solve these problems associated with the cloud-enabled IoT frameworks and to develop new methods for IoT decentralization. Recently, blockchain is perceived as a promising technique to solve the aforementioned problems and to design new decentralization frameworks for IoT. Nevertheless, there is no consensus towards any schemes or best practices that specify how blockchain should be used in IoT. Employing blockchain mechanisms in IoT is still particularly challenging. This special issue invites original research that investigates blockchain technologies and decentralization mechanisms for IoT, for examples, key theories, innovative schemes, and significant applications of these techniques. Potential topics include but not limited to the following: - Theories of blockchain and distributed systems - Smart contract and distributed ledger for IoT devices and data - Distributed consensus on resource-limited IoT devices - Blockchain schemes for decentralization in IoT - Byzantine fault tolerance - Security of blockchain and decentralized schemes for IoT - Performance evaluation of blockchain and decentralized schemes for IoT - IoT applications with blockchain technique - Lightweight protocols and algorithms for IoT devices - Lightweight data structures for IoT data - Blockchain based IoT security solutions - Applications of blockchain in IoT scenarios - Blockchain and Bitcoin Security - Blockchain in social networking - Bolckchain in crowdsourcing and crowdsensing
Last updated by Dou Sun in 2017-09-30
Special Issue on Novel edge computing-inspired approaches and paradigms for mobile IoT applications
Submission Date: 2018-02-01

Mobile-oriented cloud architectures and technologies play an important and increasing role in practice due to the widespread adoption of mobile devices. From the industry perspective, the synergy between mobile and cloud technologies has resulted in new cloud provisioning models for supporting mobile application development and deployment, such as Mobile Backend as a Service (MBaaS). MBaaS supports cloud services which are commonly needed by web and mobile systems (e.g., data storage, identity and access management, synchronization and push notifications). From an academic perspective, mobile cloud computing (MCC) is a way of augmenting mobile devices and dealing with the inherent limitations related to remote resources located in the cloud. Specifically, MCC combines advances from mobile computing, cloud computing and wireless/fixed networks so that rich applications, such as speech recognition and augmented reality, can be seamlessly and efficiently “executed” on mobile devices via the actual execution of computations and data processing on remote cloud resources. Techniques materializing this idea include offloading and cyber-foraging. Fog computing paradigm was introduced around 2012 to provide highly-scalable infrastructures for latency and location-aware MCC applications, where geographical distribution, mobility and SW/HW heterogeneity prevail. While fog computing can be viewed as a special case of MCC, it represents also an evolution of the latter since it includes the ability of augmenting mobile (e.g., laptops, smartphones, tablets and wearables) and wireless devices (e.g., sensors and actuators) with processing/storage resources in their proximity, in terms of network topology. Indeed, several flavors of this idea, including micro-data centers, cloudlets and fog computing itself, follow the edge computing model, by which data/computations are processed using computing resources located at the edge of the network –accessible through wireless protocols– and optionally using remote resources in the cloud. Motivated not only by the increasing number of mobile devices, but also their ever-growing computing and sensing capabilities, there have been efforts to leverage these devices as destination for offloading computations/data in the context of edge/fog applications. Such a trend has also been referred to as dew computing in the literature. However, current research in the area is still focused on augmenting mobile clients via fixed computing resources (e.g., local servers and computer clusters), so huge unexploited computing and sensing capabilities remain “at the edge”. Therefore, many research opportunities to exploit mobile devices in the context of edge/fog computing arise. Topics This special issue aims at collecting novel ideas to materialize this new evolutionary step of Edge Computing, i.e. those moving the edge even closer to the application/data source and conceiving mobile devices as having a dual role by which they both exploit nearby and remote fixed resources, and also offer their own resources (e.g., CPU cycles, storage and even sensors) to nearby/external applications and services. Potential topics include, but are not limited to, the ones shown below: - Architectures, frameworks, standards and platforms for dew/fog/edge computing - Programming models, APIs and toolkits for dew/fog/edge computing and IoT - Offloading techniques for compute-intensive and data-intensive IoT applications - Middleware for distributed computations and data management in edge computing - Resource scheduling and management in edge computing - Energy efficiency and energy consumption aspects (middleware-level and application-level) - Fault-tolerance and scalability mechanisms - Service-orientation and QoS concepts applied to edge computing - Context-awareness for IoT applications at the edge - Technical solutions to address security and privacy in edge computing environments - Novel applications and experiences with edge computing
Last updated by Dou Sun in 2017-10-29
Special Issue on Cloud and Fog Computing for Smart Cities Data Analytics and Visualisation
Submission Date: 2018-03-01

Information and Communication Technologies are becoming the prime enabler for smart and sustainable cities in recent years. This is mainly due to realising and making effective use of the ever-increasing data generated in urban environments. Sensors, smart phones, geo-tagged devices, RFIDs, smart gadgets and Internet of Things are major source of collecting ever increasing temporal and geo-coded land-use, built-environment, transport, energy, health, socio-economic and environmental Big Data. Often data is kept in different repositories and managed by different departments, which raise data access, harmonisation, processing and information visualisation challenges for generating new insights and knowledge. Cloud and Fog/Edge are becoming enablers for managing cross-departmental temporal and geocoded Big Data, developing cross-thematic applications and providing necessary computation power to perform data analytics and present new knowledge to city stakeholders for awareness raising, city planning, policy development and decision making. High-performance visual processing techniques provide opportunity to intuitively present temporal and geo-coded information from neighbourhood scale to city or city-region scale and fosters innovation, co-creation and co-designing sustainable future cities. In the above context, the real value of smart city big data is gained by applying data mining, machine learning or new statistical methods for data analytics, visualisation and decision making. This becomes challenging when applied to large scale or real time data and hence requires appropriate tools and techniques to be applied using Cloud and Fog/Edge computing. These applications also require dealing with privacy and data security issues to avoid sharing intrusive details of citizens or other stakeholders. Topics of interest include use of cloud and fog computing in smart cities but are not limited to: - Smart city data analytics - Geo-processing and innovative visualisation techniques - Spatial data techniques and tools for analytics - City data quality, harmonisation, integration and processing - Real-time city data processing and visualisation - Predictive analytics, visualisation and simulation for future city models - Visual computing and analytics for city applications - Interactive data analysis and visualisation - Smart city services and applications platforms - Security and privacy solutions for smart city applications - Crowd sourcing and establishing trust on data sources - Internet of Things for cross-thematic city applications - Methods and techniques for city data collection and curation - Automated and intelligent city data processing methods - Design patterns and computing models for smart city applications - Open government data for automated processing and knowledge generation - Decision support systems for smart cities - Data provenance techniques for city applications, decision making and policy making - Smart city applications: mobility, energy, public administration & governance, economy, health, security and environment.
Last updated by Dou Sun in 2017-08-05
Special Issue on Computation Intelligence for Energy Internet
Submission Date: 2018-05-01

Energy crisis and carbon emission have become two global concerns. As a very promising solution, Energy Internet recently emerges to be able to tackle these challenges. Energy Internet is a radically new power generation and usage paradigm by exploiting the Internet principle to develop a revolutionary vision of smart grid. In Energy Internet, intelligent computation and communications are crucial in both operating and maintaining smart energy systems. In this sense, incorporating computation intelligence becomes the natural feature in all components as well as the whole energy system. Energy Internet applications using intelligent platforms typically need to be connected with users located remotely by using Internet of Things (IoT) and Cloud. This will transform energy system into intelligent designs and systems. New intelligent models, architectures, approaches, algorithms and solutions are needed to cope with the ever-increasing complexity of problems in energy systems, such as sensing intelligence, communications intelligence, machine learning, deep learning, and data mining. Specifically, real-time monitoring and controlling are faced with great challenges in order to collect precise energy management data. New machine learning and knowledge discovery methods are imperative to integrate, process and analyze sensing data from computation sensors for intelligent control and real-time decision making. Further, safeguards are needed to build trust in the data, which is instrumental for making critical decisions for the development of Energy Internet. This special issue will be dedicated to research and advances on the issues in Computation Intelligence for Energy Internet. Original papers describing new and previously unpublished works will be selected addressing all aspects of computation intelligence in Energy Internet. The papers will go through the usual review process, and then further reviewed by the editorial team to ensure quality of publication. The topics of interest in this special issue include, but are not limited to: - Energy Internet system and architecture with computation intelligence - Computation intelligence for Energy Internet applications, e.g., power grid, Vehicle-to-Grid, PV systems, wind farm, buildings, and energy storage - Design and analysis of real-time systems in Energy Internet - Intelligent M2M communications in Energy Internet - Cloud/Fog based intelligence for Energy Internet - Computation security and privacy in Energy Internet - Intelligent algorithms and optimization for Energy Internet - Machine Learning and deep learning for Energy Internet - Big data analysis intelligence for Energy Internet - Data mining and knowledge discovery for Energy Internet - Innovative forecasting methods in Energy Internet
Last updated by Dou Sun in 2017-08-05
Special Issue on Smart Data in Future Internet Technologies and Cloud Computing
Submission Date: 2018-05-15

The fast growing data volume has enabled multiple application to become “smart” in implementations. The Internet technologies combining distributed computing settings such as cloud computing have further increased the performance of the system. The benefits of using data-driven applications have a strong impact on various industries, including the financial industry, manufacturing, consulting agency, and healthcare. One of the vital issues in data-driven applications is to find out efficient methods of optimizations in both executions and outputs sides. The challenges are varied, which could include but are limited to speeding up the data mining efficiency in big data, secure data transmissions among multiple stakeholders, adoptable network designs for multi-channel communications, etc. Using data wisely is considered one of the potential solutions to the potential risks or restrictions in the field. This special issue aims to gather recent quality work in the topic of smart data in future Internet technologies as well as cloud computing and provide the work with a discussion and evaluation forum. The principal focus of this special issue will address new techniques in the field of data mining in the network and cloud context. Scope: Topics of particular interest include, but are not limited to: - Cloud workload profiling and centralized control solution - Self-service cloudlet and clustered edge servers - Analytics applications - Scientific computing and data management - Cloud metering, implementation, and monitoring - Network-based big data management and analytics - Smart storage and data analytics in clouds - Cyber threat intelligence and defense - Data-driven service management automation - Security and fault tolerance for embedded or ubiquitous systems - Cloud security and privacy issues - Sensor network security issues in mobile cloud computing - Embedded networks and sensor network optimizations - Cloud computing and networking models - Ambient intelligence and intelligent service systems in cloud system
Last updated by Dou Sun in 2017-10-29
Special Issue on Technological innovations in Digital transformation
Submission Date: 2018-05-31

It is widely acknowledged that organizations have suffered a large evolution at the social, economic and technological levels where the traditional barriers of transferring information and knowledge have been progressively eliminated. This evolution allowed the elimination of silos, the breaking down of hierarchies, the connection of internal and external stakeholders and the empowering of employees. In this context, the integration of technological innovations, such as Big Data – Analytics, Cloud Computing, Mobile Connectivity, and Social, the four pillars of digital transformation, in business practice can enable significant competitive advantage. According to Earley Information Science digital transformation (DT), is today a top priority for executives, being that (1) 125000 enterprises expect revenue from their digital initiatives to increase by 80% by 2020; (2) DT initiatives will more than double by 2020, from 22% to almost 50% and, (3) only 27% of businesses have a coherent digital strategy for creating customer value in place. The main purpose of digital transformation is to obtain benefits of digital technologies, such as productivity improvements, cost reductions and innovation. Nevertheless, for these results to be achieved, a total organizational commitment is required. From the organizations’ point of view, DT can be seen as a deep and accelerating transformation with regard to processes, activities, competencies and models, in order to take advantage of the changes and opportunities offered by the inclusion of digital technologies into an organization. However, this advantage is only possible if the information systems of the organizations are aligned with these new technologies. Thus, the Future Generation Computer Systems journal is seeking manuscripts for a special issue entitled “Big Data, Cloud, Mobile and Social in Digital transformation”. This issue will have as broad a scope as possible with respect how DT can be used to attain this goal. We also would like to attract papers that discuss the impact of the DT in the everyday life citizens, enterprises and governments. This special issue will include full-papers resulting from: - Extended papers presented at the WorldCist'18 - 6th World Conference on Information Systems and Technologies ( to be held at Naples, Italy, 27 - 29 March 2018. For this special issue will be selected some best papers from the tracks “A) Information and Knowledge Management (IKM)”; “D) Software Systems, Architectures, Applications and Tools (SSAAT)”; “H) Big Data Analytics and Applications (BDAA)”. - Other original research contributions focusing on the aims and scope of this special issue.
Last updated by Dou Sun in 2017-10-29
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