Special Issue on Emerging Edge-of-Things Computing for Smart Cities: Recent Advances and Future Trends
摘要截稿:
全文截稿: 2018-10-30
影响因子: 5.91
期刊难度:
CCF分类: B类
中科院JCR分区:
• 大类 : 计算机科学 - 1区
• 小类 : 计算机:信息系统 - 1区
Overview
Due to recent advances in processing, information and communication technology, there are a variety of networked sensor-based systems and devices deployed on the scale of towns, cities, and even countries. It represents an excellent opportunity to support everyday life activities. Such smart environments are actually leading to Smart Cities that can support the activities of their inhabitants by improving quality of life and ensuring sustainability in many areas such as Smart healthcare, Smart transportation, and Smart home. The main features of a Smart City include a high degree of information technology integration and a comprehensive application of computation resources. Internet of Things (IoT) is the underlying technology to build Smart Cities since they enable everyday entities/objects to communicate and collaborate with each other through the Internet, in order to achieve intelligent recognition, location tracking, monitoring and management. With the technical support from IoT, Smart City can be instrumented, interconnected and intelligent.
However, a wide-scale realization of IoT for Smart Cities is hindered due to the significant constraints of IoT-enabled devices and sensors in terms of memory, processing resources, energy, or communication bandwidth. The rise of Cloud-assisted Internet of Things or Cloud-of-Things (CoT) paradigm for Smart Cities 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 IoT data. Currently, the CoT paradigm is facing increasing difficulty to handle the Big data that IoT generates from various Smart Cities services and applications. 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 an Edge Computing infrastructure between IoT systems and Cloud computing. This new paradigm termed as Edge-of-Things (EoT) computing, operates closer to the IoT data source and allows 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, intelligence and storage capabilities on a smaller scale in real-time. Thus, it enables efficient Smart City service delivery with low response time avoiding delays and network failures that may interrupt or delay the decision process and service delivery.
While researchers and practitioners have been making progress within the area of EoT computing, there still exist several issues that need further research efforts in both academia and industry, especially for the development of efficient, scalable, and reliable Smart City based on Edge-of-Things computing. Some of these issues are: new edge network architecture and middleware platform in Smart Cities considering emerging technologies such as 5G wireless networks, software defined network and semantic computing; edge analytics for Big data in Smart Cities; Blockchain in EoT, machine learning approach for Edge analytics in Smart Cities; and context-aware service management on the edge with effective quality of service (QoS) support.
Topics of Interest
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 to significantly improve the field of Smart City. Therefore, the suggested topics of interest for this special issue include, but are not limited to:
- Novel Edge-of-Things computing architecture and middleware for Smart Cities
- Energy-aware and mobility-aware resource scheduling in edge computing for Smart Cities
- Intelligent and agent based algorithms for Edge of Things computing for Smart Cities
- Big data edge analytics architectures and machine learning methods for Smart City services
- Security, privacy and blockchain in Edge-of-Things Computing for Smart Cities
- Standards and Interoperability in edge-of-things computing for Smart Cities
- Emerging edge-of-things computing systems for Smart Cities