For several special features in the environment of Fog computing, which may be quite different from the centralized computing infrastructure currently available, the existed method of resource allocation used in the grid computing environment may not be suitable for these changes. In our paper, a new allocation algorithm based on Ant Colony Optimization (ACO) is proposed to satisfy the needs of Infrastructure as a Service (IaaS) supported by the Fog computing environment. When started, this algorithm first predicts the capability of the potentially available resource nodes; then, it analyzes some factors such as network qualities and response times to acquire a set of optimal compute nodes; finally, the tasks would be allocated to these suitable nodes. This algorithm has shorter response time and better performance than some of other algorithms which are based on Grid environment when running in the simulate Fog environment. This result is verified by the simulation in the Gridsim environment elaborated in the following section.


This new Fog computing and networking paradigm will fundamentally reshape end-to-end networking and computing architectures and the industry landscapes. This panel will discuss end-to-end software architectures for enabling Fog. This will include software architectures for dynamically distributing computing, storage, networking, and control services to where they will best meet user requirements, how Fog interfaces with the Cloud and with the Things, and how to secure the distributed service architecture. We will use real-world use cases to illustrate how an immersive Fog-based software architecture can support the emerging IoT needs that cannot be easily addressed by the existing computing and networking paradigm.


Nanxi Chen

Fu Song

Xiliang Luo

Yang Yang


A Fog computing system includes an initial request reception unit, a request reception unit, and a transmission unit. The initial request reception unit receives a connection request from a device. In a case where the device has tried to access a request reception unit, the request reception unit receives a service usage request and service identification information from the device and determines whether a back-end processing unit is present that both corresponds to the device and is configured to execute the service. If present, a service utilization preparation completion screen is transmitted to the device. If not present, an instance generation instruction is sent to a management unit and instruction to launch an instance generated to execute the service is sent. After the instance is launched and the back-end processing unit is realized, the service utilization preparation completion screen is transmitted to the device.


We can discussion paper on a Fog Computing Consumer Protocol. The protocol will require providers of cloud services to provide a range of information to consumers about (among other things) data ownership, privacy, data backups, how data can be retrieved from the service.


Fog computing and storage provides users with capabilities to store and process their data in third-party data centers. Organizations use the Fog in a variety of different service models (with acronyms such as SaaS, PaaS, and IaaS) and deployment models (private, public, hybrid, and community). Security concerns associated with Fog computing fall into two broad categories: security issues faced by Fog providers (organizations providing software-, platform-, or infrastructure-as-a-service via the Fog) and security issues faced by their customers (companies or organizations who host applications or store data on the Fog). The responsibility is shared, however. The provider must ensure that their infrastructure is secure and that their clients’ data and applications are protected, while the user must take measures to fortify their application and use strong passwords and authentication measures.


Xin Lou

Fu Song


Fog software is a part of a fog system that consists of data or Fog instructions, in contrast to the physical hardware from which the system is built. In fog science and software engineering, Fog software is all information processed by fog systems, programs and data. Fog software includes fog programs, libraries and related non-executable data, such as online documentation or digital media. Fog hardware and software require each other and neither can be realistically used on its own.


Fu Song


The emerging Internet of Things (IoT), 5G wireless systems, and a wide range of new applications such as embedded Artificial Intelligence (AI) have created the need for a new computing and networking paradigm – Fog. Rather than limiting computing to a small number of massive Clouds, Fog distributes computing, storage, control, and networking services closer to the end users along the Cloud-to-Thing continuum that can best meet user requirements. The immersive Fog can address many challenges that Cloud alone cannot effectively address, such as stringent latency requirements, limited processing and storage capabilities and battery life of a vast number of devices, network bandwidth constraints and costs, and many security and privacy concerns that arise from the emerging IoT.


Chun Shi

Shenghu Wang

Wuxiong Zhang

Mengying Zhang

Mingtuo Zhou