Following the progression in Internet of Things (IoT) and 5G communication networks, the traditional cloud computing model have shifted to fog computing. Fog computing provides mobile computing, network control and storage to the network edges to assist latency critical and computation-intensive applications. Moreover, security features are improved in fog paradigm by processing critical data on edge devices instead of data centres outside the control plane of users. However, fog network deployment imposes many challenges including resource allocation, privacy of users, non-availability of programming model and testing software and support for the heterogenous networks. This article highlights these challenges and their potential solutions in detail. This article also discusses threetier fog network architecture, its standardization and benefits in detail. The proposed resource allocation mechanism for three tier fog networks based on swap matching is described. Results show that by practicing the proposed resource allocation mechanism, maximum throughput with reduced latency is achieved.

With the explosive growth of high-speed wireless data demand and the number of mobile devices, fog radio access networks (F-RAN) with multi-layer network structure becomes a hot topic in recent research. Meanwhile, due to the rapid growth of mobile communication traffic, high cost and the scarcity of wireless resources, it is especially important to develop an efficient radio resource management mechanism. In this paper, we focus on the shortcomings of resource waste, and we consider the actual situation of base station dynamic coverage and user requirements. We propose a spectrum pricing and allocation scheme based on Stackelberg game model under F-RAN framework, realizing the allocation of resource on demand. This scheme studies the double game between the users and the operators, as well as between the traditional operators and the virtual operators, maximizing the profits of the operators. At the same time, spectrum reuse technology is adopted to improve the utilization of network resource. By analyzing the simulation results, it is verified that our proposed scheme can not only avoid resource waste, but also effectively improve the operator’s revenue efficiency and overall network resource utilization.

Fog computing is introduced to relieve the problems triggered by the long distance between the cloud and terminal devices. In this paper, considering the mobility of terminal devices represented as mobile multimedia users (MMUs) and the continuity of requests delivered by them, we propose an online resource allocation scheme with respect to deciding the state of servers in fog nodes distributed at different zones on the premise of satisfying the quality of experience (QoE) based on a Stackelberg game. Specifically, a multi-round of a predictably\unpredictably dynamic scheme is derived from a single-round of a static scheme. The optimal allocation schemes are discussed in detail, and related experiments are designed. For simulations, comparing with non-strategy schemes, the performance of the dynamic scheme is better at minimizing the cost used to maintain fog nodes for providing services.

With the dawning of the Internet of Everything (IoE) era, more and more novel applications are being deployed. However, resource constrained devices cannot fulfill the resource-requirements of these applications. This paper investigates the computation offloading problem of the coexistence and synergy between fog computing and cloud computing in IoE by jointly optimizing the offloading decisions, the allocation of computation resource and transmit power. Specifically, we propose an energy-efficient computation offloading and resource allocation (ECORA) scheme to minimize the system cost. The simulation results verify the proposed scheme can effectively decrease the system cost by up to 50% compared with the existing schemes, especially for the scenario that the computation resource of fog computing is relatively small or the number of devices increases.

In recent years, with the rapid development of sensing technology and deployment of various Internet of Everything devices, it becomes a crucial and practical challenge to enable real-time search queries for objects, data, and services in the Internet of Everything. Moreover, such efficient query processing techniques can provide strong facilitate the research on Internet of Everything security issues. By looking into the unique characteristics in the IoE application environment, such as high heterogeneity, high dynamics, and distributed, we develop a novel search engine model, and build a dynamic prediction model of the IoE sensor time series to meet the real-time requirements for the Internet of Everything search environment. We validated the accuracy and effectiveness of the dynamic prediction model using a public sensor dataset from Intel Lab.

To satisfy the increasing demands of high-speed transmission, high-efficiency computing, and real-time communications in the high-dynamic and heterogeneous networks, the Contact Plan Design (CPD) has attracted continuous attention in recent years, especially for the spatial-node-based Internet of Everything (IoE). In this paper, we study the NP-hardness of contact scheduling and the attenuation of atmospheric precipitation in the spatial-node-based IoE. Two heuristic computing methods for contact plan design are proposed by comprehensively considering the time-varying topology, the intermittent connectivity, and the adaptive transmission in different weather conditions, which are named Contact Plan Design-Particle Swarm Optimization (CPD-PSO) and Contact Plan Design-Greedy algorithm with the Minimum Delivery Time (CPD-GMDT) separately. For the population-based algorithm, CPD-PSO not only solves the CPD problem with a limited-resource condition, but also dynamically adjusts the search scope to ensure the continuous searching capability of the algorithm. For the CPD-GMDT that makes CP decisions based on the current state, the algorithm uses the idea of greedy algorithm to schedule Satellite-Platform Links (SPLs) and Inter Satellite Links (ISLs) respectively using the strategies of optimal matching and load balancing. The simulation results show that the proposed CPD-PSO outperforms Contact Plan Design-Genetic Algorithm (CPD-GA) in terms of fitness and delivery time, and CPD-GMDT presents better overall delay than Fair Contact Plan (FCP).

To accommodate the asymmetric characteristic of Internet traffic, we propose a flexible node architecture based on multi-flow optical transponders (MF-OTP) under the integrated Cloud-Fog framework. The proposed MF-OTP architecture is flexible in the following two degrees. Firstly, it can be flexibly adjusted to transmit either downstream or upstream traffic according to the timely traffic demand distribution. Secondly, it allows multiple sub-channels using flexible (i.e., same/different) modulation formats to serve the same traffic demand. To evaluate the efficiency of the flexible MT-OTP in serving asymmetric traffic, we propose two integer linear programming (ILP) models to address the routing, modulation and spectrum assignment (RMSA), with one aiming at minimizing the required number of sub-channels and another aiming at maximizing the volume of traffic transmission. Numerical simulations are conducted and the results show that the proposed models based on the flexible MF-OTP architecture requires less number of sub-channels and can serve more traffic demands.

With the emergence of advanced vehicular applications, the challenge of satisfying computational and communication demands of vehicles has become increasingly prominent. Fog computing is a potential solution to improve advanced vehicular services by enabling computational offloading at the edge of network. In this paper, we propose a fog-cloud computational offloading algorithm in Internet of Vehicles (IoV) to both minimize the power consumption of vehicles and that of the computational facilities. First, we establish the system model, and then formulate the offloading problem as an optimization problem, which is NP-hard. After that, we propose a heuristic algorithm to solve the offloading problem gradually. Specifically, we design a predictive combination transmission mode for vehicles, and establish a deep learning model for computational facilities to obtain the optimal workload allocation. Simulation results demonstrate the superiority of our algorithm in energy efficiency and network latency.

In this paper, the system performance of a decode-and-forward (DF) full-duplex (FD) adaptive relaying network over the Rician fading environment is proposed, analyzed and demonstrated. In the first stage, the system is presented with the energy harvesting and information transmission processes. After that, the analytical expressions of the achievable throughput, the outage probability, and symbol error ratio (SER) were proposed, analyzed and demonstrated. Finally, the analytical results are also demonstrated by Monte-Carlo simulation in comparison with the closed-form expressions in the influence of the key system parameters. The results show that the analytical and simulated results match for all possible parameter values.

Dynamic spectrum access (DSA) based on cognitive radios (CR) technique is an effective approach to address the “spectrum scarcity” issue. However, traditional CR-enabled DSA system employs only single DSA strategy, which might not be suited to the dynamic network environment. In this paper, we propose a multi-strategy DSA (MS-DSA) system, where the primary and the secondary system share spectrum resources with multiple DSA strategies simultaneously. To analyze the performance of the proposed MS-DSA system, we model it as a continuous-time Markov chain (CTMC) and derive the expressions to compute the corresponding performance metrics. Based on this, we define a utility function involving the concerns of effective throughput, interference quantity on primary users, and spectrum leasing cost. Two optimization schemes, named as spectrum allocation and false alarm probability selection, are proposed to maximize the utility function. Finally, numerical simulations are provided to validate our analysis and demonstrate that the performance can be significantly improved caused by virtues of the proposed MS-DSA system.

In this paper, we propose cooperative relay networks with non-orthogonal multiple access in order to design a near-optimal power allocation strategy. Like other next generation wireless technologies, spatially multiplexed transmissions are achieved by relay nodes which enables decode-and-forward relaying of a new superposition code after reception from the source. It is worth noting that, since it is hard to exactly prove the proposed PA scheme, due the fact that it is one kind of the approximate conjectures. Therefore, mathematical and numerical methods have been used to clarify the feasibility of the proposal. Numerical results indicate that it is able to asymptotically achieve the optimal sum rate at the higher signal-to-noise ratio region with the proposed strategy applied instead of negligible performance loss.

In this paper, we propose a dual-threshold based secure On-Off transmission scheme, where signals are transmitted only if the channel condition can guarantee secure and reliable communication. First, we present a dynamic access strategy to increase access efficiency, which provides an access region for the intended user. Then, we propose an emission control policy to transmit signals according to the current channel condition, which declines the influence of channel estimation errors and guarantees qualities of communication links. Furthermore, we give a comprehensive performance analysis for the proposed scheme in terms of connection outage probability (COP) and secrecy outage probability (SOP), and present a dual-threshold optimization model to further support the performance. Numerical results verify that the secure On-Off transmission scheme can increase the system secure energy efficiency and guarantee reliable and secure communication.

The paper aims at designing of two stage cascaded ultra-wideband (UWB) low noise amplifier (LNA) by using negative image amplifier technique. The objective of this article is to show the performance improvement using negative image amplifier technique and realization of negative valued lumped elements into microstrip line geometry. The innovative technique to realize the negative lumped elements are carried out by using Richard’s Transformation and transmission line calculation. The AWR microwave office tool is used to obtain characteristics of UWB LNA design with hybrid microwave integrated circuit (HMIC) technology. The 2-stage cascaded LNA design using negative image amplifier technique achieves average gain of 23dB gain and low noise Figure of less than 2dB with return loss less than -8dB for UWB 3-10GHz. The Proper bias circuit is extracted using DC characteristics of transistor at biasing point 2V, 20mA and discussed in detail with LNA layout. The negative image matching technique is applied for both input and output matching network. This work will be useful for all low power UWB wireless receiver applications.

Stochastic geometry is widely employed to model cellular network. But in most existing works, base stations (BSs) are modelled following a homogeneous Poisson point process (PPP) for one-tier network, or several independent homogeneous PPP for multi-tier network, which ignore the dependence among BSs. In this paper, a three-tier UDN (Ultra dense network) with Macrocell BSs (MBS) for basic coverage, Picocell BSs (PBSs) deployed outside the coverage area of MBSs for compensating coverage holes, and Femtocell BSs (FBSs) surrounding MBSs for capacity improvement modelled by point process with inter-tier dependence is proposed. The tier association probability, the coverage probability and area spectrum efficiency (ASE) are derived. Simulation results validate our derivation, and results show that the proposed network model has 25%-45% performance gain in ASE.

With the broad reach of Internet, online reviews have become an important source of electronic Word-of-Mouth. Fraud reviews that are deliberately posted by businesses are a type of online reviews. This paper discusses the incentives of fraud reviews and the effect of fraud reviews on consumer behavior through empirical research. Using book download data at Amazon, we find that a book is more likely to manipulate fraud reviews when it has few online reviews posted by real consumers, higher proportion of negative reviews, longer average length of negative reviews, lower average rating scored by real users and higher price. And fraud reviews change the review environment and have a significant impact on the consumer purchasing decisions. More number, higher proportion, longer word count and higher promotion of rating of fraud reviews lead to higher sales. The results also show consumers can discern the manipulation of fraud reviews to a certain extent.

Wireless sensor network is an important technical support for ubiquitous communication. For the serious impacts of network failure caused by the unbalanced energy consumption of sensor nodes, hardware failure and attacker intrusion on data transmission, a low energy consumption distributed fault detection mechanism in wireless sensor network (LEFD) is proposed in this paper. Firstly, the time correlation information of nodes is used to detect fault nodes in LEFD, and then the spatial correlation information is adopted to detect the remaining fault nodes, so as to check the states of nodes comprehensively and improve the efficiency of data transmission. In addition, the nodes do not need to exchange information with their neighbor nodes in the initial detection process since LEFD adopts the data sensed by node itself to detect some types of faults, thus reducing the energy consumption of nodes effectively. Finally, LEFD also considers the nodes that may have transient faults. Performance analysis and simulation results show that the proposed detection mechanism can improve the transmission performance and reduce the energy consumption of network effectively.