Fog Computing Networks Research Articles

UCAA: User-Centric User Association and Resource Allocation in Fog Computing Networks

In recent years, with the eruptive popularity of mobile Internet and the emergence of various new IoT applications, fog computing is proposed to shift the cloud computing services towards the edge, making up for its lack of mobility support and high delay. Fog computing is customized for scenarios with scarce resources and unpredictable environments, but there is no user-centric joint optimization fog computing models designed for such scenarios. In this paper, we aim to maximize the user experience and overall system performance by jointly optimizing user association and resource allocation in the scenarios mentioned above, which can be formulated as a mix-integer non-linear programming problem. To solve the NP-hard problem, we propose a low-complexity two-step interactive optimal algorithm, named UCAA algorithm. For the user association problem, we propose a semi-definite programming based algorithm, and then further propose a Kuhn-Munkres algorithm based user association decision approximation algorithm. For the resource allocation problem, we first prove that it can be decoupled into two sub-problems, ie., transmission power selection problem and computing resource allocation problem, and solve them individually, in addition, we have given a rigorous proof that the optimal solution of the two sub-problems is the optimal solution to the original problem as well. The numerical results show that the proposed UCAA algorithm achieves better performance than conventional algorithms in terms of the value of average user-centric utility, especially in case of more user equipments (UEs), fewer fog nodes, limited computing capacity of fog nodes, lower delay tolerance, lower local computation capacity, etc., which presented to illustrate that the UCAA algorithm can significantly improve user experience and system performance in the considering fog computing scenarios.

A Blockchain-SDN-Enabled Internet of Vehicles Environment for Fog Computing and 5G Networks

The goal of intelligent transport systems (ITSs) is to enhance the network performance of vehicular ad hoc networks (VANETs). Even though it presents new opportunities to the Internet of Vehicles (IoV) environment, there are some security concerns including the need to establish trust among the connected peers. The fifth-generation (5G) communication system, which provides reliable and low-latency communication services, is seen as the technology to cater for the challenges in VANETs. The incorporation of software-defined networks (SDNs) also ensures an effective network management. However, there should be monitoring and reporting services provided in the IoV. Blockchain, which has decentralization, transparency, and immutability as some of its properties, is designed to ensure trust in networking platforms. In that regard, this article analyzes the combination of blockchain and SDN for the effective operation of the VANET systems in 5G and fog computing paradigms. With managerial responsibilities shared between the blockchain and the SDN, it helps to relieve the pressure off the controller due to the ubiquitous processing that occurs. A trust-based model that curbs malicious activities in the network is also presented. The simulation results substantially guarantee an efficient network performance, while also ensuring that there is trust among the entities.

Intelligent attack defense scheme based on DQL algorithm in mobile fog computing

Fog computing is a technology that can expands the network computing mode of cloud computing and extends network computing from the network center to the network edge. It adds fog layer between cloud data center layer and Internet of Things (IoT) device layer, and provides data storage, processing, forwarding and other functions for devices using the network edge. In mobile fog computing (MFC) networks, fog nodes communicate with end users through wireless networks. Malicious users can choose different attack modes to attack legitimate users. There is a lack of research on the subjective choice of attack modes for malicious users in current work. To solve this problem, an intelligent attack defense scheme based on Double Q-learning (DQL) algorithm in MFC is proposed. Firstly, the security model involving malicious users in MFC is described. Based on Prospect Theory (PT), a static method of subjective zero-sum game between malicious users and legitimate users is constructed. Secondly, a dynamic subjective game scheme based on DQL algorithm is proposed to resist intelligent attacks. The simulation results show that compared with the Q-learning-based method for resisting intelligent attacks, the proposed method can enhance the security of MFC network and enhance the protection performance.

Feasibility Study of 60 GHz Millimeter-Wave Technologies for Hyperconnected Fog Computing Applications

This paper conducts the feasibility study for discussing about the interference impacts in advanced fog computing (FC) networks with 60 GHz millimeter-wave wireless technology. With the concept of FC, cloud computing services can be utilized with local computing devices ( FC devices ) those are located nearby user terminals [edge devices (EDs)] for low-latency communications. Since EDs can be densely deployed in urban areas, wireless hyperconnection should be supportable in FC networks. For the system, 60 GHz millimeter-wave technology can be used as one of wireless networking methods because it can provide: 1) high rates for visual information delivery and 2) high directionality for spatial reuse in hyperconnected FC networks. Therefore, this performance simulation study under the consideration of interference impacts determines whether utilizing 60 GHz millimeter-wave wireless technology for hyperconnected FC networks is feasible or not. Under the consideration of various interference scenarios, the interference impacts are calculated. As presented in simulation-based performance evaluation results, we verify that 1.5 Gb/s high rate can be supportable even though more than 1000 EDs are deployed in the 100 m-by-100 m size small-scale networks (upper bound). Therefore, we confirm that hyperconnection can be realized with 60 GHz millimeter-wave technology for FC networks.

A Cooperative-Based Model for Smart-Sensing Tasks in Fog Computing

Fog computing (FC) is currently receiving a great deal of focused attention. FC can be viewed as an extension of cloud computing that services the edges of networks. A cooperative relationship among applications to collect data in a city is a fundamental research topic in FC. When considering the green cloud, people or vehicles with smart-sensor devices can be viewed as users in FC and can forward sensing data to the data center. In a traditional sensing process, rewards are paid according to the distances between the users and the platform, which can be seen as the existing solution. Because users with smart-sensing devices tend to participate in tasks with high rewards, the number of users in suburban regions is smaller, and data collection is sparse and cannot satisfy the demands of the tasks. However, there are many users in urban regions, which makes data collection costly and of low quality. In this paper, a cooperative-based model for smartphone tasks, named a cooperative-based model for smart-sensing tasks (CMST), is proposed to promote the quality of data collection in FC networks. In the CMST scheme, we develop an allocation method focused on improving the rewards in suburban regions. The rewards to each user with a smart sensor are distributed according to the region density. Moreover, for each task there is a cooperative relationship among the users; they cooperate with one another to reach the volume of data that the platform requires. Extensive experiments show that our scheme improves the overall data-coverage factor by 14.997% to 31.46%, and the platform cost can be reduced by 35.882%.

Baseline Parametric Survey on Causes of Traffic Congestion in Datacenter Networks

Distributed cloud datacenters are currently used as deployment environment for large-scale web-facing enterprise analytic cloud applications. In the era of cloud computing, these networks allow unprecedented scalability in response to dynamic and unpredictable grid workloads. However, grid applications need to scale beyond the limits of single-tenanted datacenter to multi-tenanted datacenter sites providing regulatory service level compliance, efficient Quality of Service (QoS) and increased fault tolerance at all times. Following the complex hierarchical design structure of emerging cloud networks such as Internet of Things (IoT) and Fog Computing Networks (FCNs), congestion crisis becomes a critical consideration for future expansion of these networks. This paper carried out a Baseline Parametric Survey (BPS) to ascertain major factors of DCN traffic congestion in selected production networks in Nigeria. From the survey, it was observed that the absence of an intelligent load balancer, bandwidth size, network traffic type, and network switch butter capacity, number of users on the network, segmentation and routing devices all contribute to network congestion incidence. The deductions from this work can be used to implement a Fog internet layer for smarter data off-loading in today’s internet of everything.