DQN-Based Proactive Trajectory Planning of UAVs in Multi-Access Edge Computing

The main aim of future mobile networks is to provide secure, reliable, intelligent, and seamless connectivity. It also enables mobile network operators to ensure their customer’s a better quality of service (QoS). Nowadays, Unmanned Aerial Vehicles (UAVs) are a significant part of the mobile network due to their continuously growing use in various applications. For better coverage, cost-effective, and seamless service connectivity and provisioning, UAVs have emerged as the best choice for telco operators. UAVs can be used as flying base stations, edge servers, and relay nodes in mobile networks. On the other side, Multi-access Edge Computing (MEC) technology also emerged in the 5G network to provide a better quality of experience (QoE) to users with different QoS requirements. However, UAVs in a mobile network for coverage enhancement and better QoS face several challenges such as trajectory designing, path planning, optimization, QoS assurance, mobility management, etc. The efficient and proactive path planning and optimization in a highly dynamic environment containing buildings and obstacles are challenging. So, an automated Artificial Intelligence (AI) enabled QoS-aware solution is needed for trajectory planning and optimization. Therefore, this work introduces a well-designed AI and MEC-enabled architecture for a UAVs-assisted future network. It has an efficient Deep Reinforcement Learning (DRL) algorithm for real-time and proactive trajectory planning and optimization. It also fulfills QoS-aware service provisioning. A greedy-policy approach is used to maximize the long-term reward for serving more users with QoS. Simulation results reveal the superiority of the proposed DRL mechanism for energy-efficient and QoS-aware trajectory planning over the existing models.     

Multi-Criteria Fuzzy-Based Decision Making Algorithm to Optimize the VHO Performance in Hetnets

Despite the seemingly exponential growth of mobile and wireless communication, this same technology aims to offer uninterrupted access to different wireless systems like Radio Communication, Bluetooth, and Wi-Fi to achieve better network connection which in turn gives the best quality of service (QoS). Many analysts have established many handover decision systems (HDS) to enable assured continuous mobility between various radio access technologies. Unbroken mobility is one of the most significant problems considered in wireless communication networks. Each application needs a distinct QoS, so the network choice may shift appropriately. To achieve this objective and to choose the finest networks, it is important to select a best decision making algorithm that chooses the most effective network for every application that the user requires, dependent on QoS measures. Therefore, the main goal of the proposed system is to provide an enhanced vertical handover (VHO) decision making program by using a Multi-Criteria Fuzzy-Based algorithm to choose the best network. Enhanced Multi-Criteria algorithms and a Fuzzy-Based algorithm is implemented successfully for optimal network selection and also to minimize the probability of false handover. Furthermore, a double packet buffer is utilized to decrease the packet loss by 1.5% and to reduce the number of handovers up to 50% compared to the existing systems. In addition, the network setup has an optimized mobility management system to supervise the movement of the mobile nodes.     

Location management for packet switched services in 3G partnership project networks

In order for third-generation partnership project (3GPP) networks to cope with the rapid growth of IP data traffic, the location management requires further enhancement to accommodate the burst data traffic characteristics of packet switched (PS) services. The universal mobile telecommunication system (UMTS) location management solutions for PS services in 3GPP networks has been investigated, and an inactivity counter mechanism in PS domain to reduce the location management cost of inactivate users has been proposed. An analytical model accommodating diverse call and mobility characteristics of user equipment to evaluate the performance of the inactivity counter mechanism has also been developed. Using the proposed model, the performance of the inactivity counter mechanism in UMTS terrestrial radio access network recommended by 3GPP is investigated, the cost reduction obtained by the proposed mechanism when compared with the original location strategy used in the PS domain is then analysed, which also shows the effect of system parameters and users' mobility and service patterns on the location management costs.     

Mobility model for heterogeneous wireless networks and its application in common radio resource management

User distribution and mobility behaviour vary based on environment types and characteristics. Heterogeneous wireless networks (HWNs) are deployed to utilise these characteristics and serve users with better quality. For efficient resource management in HWN environment, an understanding of multi-mode user mobility behaviour is paramount. Here, a multi-mode user mobility model is proposed in the context of wireless local area network (WLAN) coverage in the hotspot, overlaid on a macrocell of wireless wide area network (WWAN). An expression for microcell residence time of multi-mode users in HWNs is derived, based on the cell residence time in the constituting WLAN and WWAN. The boundary-crossing probabilities of moving into microcell, moving out of microcell and moving out of macrocell during a call for different types of hotspot topologies are also derived analytically. The numerical results obtained using the analytical expressions for boundary-crossing probability are validated by simulation results. The significance of the proposed mobility model is demonstrated through its application in common radio resource management (CRRM). Numerical results show that the mobility-based CRRM scheme exhibits a lower rate of unnecessary vertical handoffs than that achieved by the dasiaWLAN' if coveragedasia scheme that does not use mobility information for resource management.     

An Optimized Algorithm for Resource Allocation for D2D in Heterogeneous Networks

With the emergence of 5G mobile multimedia services, end users’ demand for high-speed, low-latency mobile communication network access is increasing. Among them, the device-to-device (D2D) communication is one of the considerable technology. In D2D communication, the data does not need to be relayed and forwarded by the base station, but under the control of the base station, a direct local link is allowed between two adjacent mobile devices. This flexible communication mode reduces the processing bottlenecks and coverage blind spots of the base station, and can be widely used in dense user communication scenarios such as heterogeneous ultra-dense wireless networks. One of the important factors which affects the quality-of-service (QoS) of D2D communications is co-channel interference. In order to solve this problem of co-channel interference, this paper proposes a graph coloring based algorithm. The main idea is to utilize the weighted priority of spectrum resources and enables multiple D2D users to reuse the single cellular user resource. The proposed algorithm also provides simpler power control. The heterogeneous pattern of interference is determined using different types of interferences and UE and the priority of color is acquired. Simulation results show that the proposed algorithm effectively reduced the co-channel interference, power consumption and improved the system throughput as compared with existing algorithms.     

Two-level single-chain pointer forwarding strategy: a new scheme for location management in mobile communication

A new strategy called 'two-level single-chain pointer (TLSCP) Forwarding strategy is proposed to reduce location management cost for mobile users. A two-level hierarchy of level-1 and level-2 pointer forwarding chains that are reduced to a single chain in a distributed database environment to locate a mobile user is used in this strategy. An analytical model is developed to evaluate the signalling and location tracking cost. Performance analysis shows that the proposed TLSCP scheme significantly reduces the network signalling traffic cost for mobile users with low mobility.     

Cooperative wireless networks for better green services

During the last two decades, mobile communication systems (such as GSM, GPRS and 3G networks), wireless broadcasting networks, wireless local area networks (WLAN or WiFi), and wireless sensor networks have been successfully developed and widely deployed through different technological routes for providing a variety of communication services in different application scenarios. While making tremendous contributions to social progress and economic growth, these heterogeneous wireless networks consume a lot of energy in achieving overlapped service coverage, and at the same time, generate strong electromagnetic interference (EMI) and radiation pollution, especially in big cities with high building density and user population. In order to guarantee the overall return on investment (ROI), improve user experience and quality of service (QoS), save energy, reduce EMI and radiation pollution, and enable the sustainable deployment of new profitable applications and services, this paper proposes a cross-network cooperation mechanism to effectively share network resources and infrastructures, and then adaptively control and match multi-network energy distribution characteristics according to actual user/service requirements in different geographic areas. Some idle or lightly-loaded Base Stations (BS or BSs) will be temporally turned off for saving energy and reducing EMI. Initial simulation results show the proposed approach can significantly improve the overall energy efficiency and QoS performance across multiple cooperative wireless networks.     

A cross-layer adaptive algorithm for multimedia QoS fairness in WLAN environments using neural networks

The authors address the problem of providing fair multimedia quality-of-service (QoS) in IEEE 802.11 distributed co-ordination function-based wireless local area networks in the infrastructure mode where mobile hosts experience heterogeneous channel conditions due to mobility and fading effects. It was observed that unequal link qualities can pose significant unfairness of channel sharing, which may thereby lead to the degradation of multimedia QoS performed in adverse conditions. A cross-layer adaptation scheme that provides fair QoS by online adjusting the multidimensional medium access control layer backoff parameters in accordance with the application-layer QoS requirements as well as the physical-layer channel conditions was proposed. The solution is based on an optimisation approach, which utilises neural networks to learn the cross-layer function. Simulation results demonstrate that the proposed adaptation scheme can tackle heterogeneous channel conditions and random joining (or leaving) of hosts to achieve fair QoS in terms of throughput and packet delay.     

Cross-layer cooperation for accurate admission control decisions in mobile ad hoc networks

Mobile ad hoc networks (MANETs) are unpredictable by nature. Providing any kind of reliability for quality of service (QoS) in such networks is challenging. Quantifying available resources accurately, avoiding interference with ongoing QoS traffic and adapting to QoS violations caused by nodes' mobility are the main concerns for the design of an efficient admission control protocol in MANETs. Adaptive admission control (AAC), a novel admission control protocol which uses robust and accurate resource estimation and prediction techniques for relevant admission decisions has been proposed. Furthermore, AAC uses statistical QoS provision to counteract the QoS threatening mobility. Through simulations, we show that our proposed scheme outperforms existing approaches in terms of correctness and overall performance.     

Comparison between hybridized algorithm of GA–SA and ABC,GA, DE and PSO for vertical-handover in heterogeneous wireless networks

Genetic algorithms (GAs) and simulated annealing (SA) have emerged as leading methods for search and optimization problems in heterogeneous wireless networks. In this paradigm, various access technologies need to be interconnected; thus, vertical handovers are necessary for seamless mobility. In this paper, the hybrid algorithm for real-time vertical handover using different objective functions has been presented to find the optimal network to connect with a good quality of service in accordance with the user’s preferences. As it is, the characteristics of the current mobile devices recommend using fast and efficient algorithms to provide solutions near to real-time. These constraints have moved us to develop intelligent algorithms that avoid slow and massive computations. This was to, specifically, solve two major problems in GA optimization, i.e. premature convergence and slow convergence rate, and the facilitation of simulated annealing in the merging populations phase of the search. The hybrid algorithm was expected to improve on the pure GA in two ways, i.e., improved solutions for a given number of evaluations, and more stability over many runs. This paper compares the formulation and results of four recent optimization algorithms: artificial bee colony (ABC), genetic algorithm (GA), differential evolution (DE), and particle swarm optimization (PSO). Moreover, a cost function is used to sustain the desired QoS during the transition between networks, which is measured in terms of the bandwidth, BER, ABR, SNR, and monetary cost. Simulation results indicated that choosing the SA rules would minimize the cost function and the GA–SA algorithm could decrease the number of unnecessary handovers, and thereby prevent the ‘Ping-Pong’ effect.     

Mobile agent based approach for QoS routing

A mobile agent based on-demand quality of service (QoS) unicast routing scheme for supporting multimedia applications is proposed that considers bandwidth, delay and packet loss as QoS metrics for feasible path computation. A mobile agent is employed to find multiple QoS paths and select a best path among them to preserve resources so as to increase call success ratio and network bandwidth utilisation as well as adapt to network dynamics. The scheme is simulated in various network scenarios (sparse and dense networks) to verify performance and operation effectiveness, and compared with RSVP-based QoS routing by using an internet routing protocol. The results demonstrate significant improvements in call success ratio and network bandwidth utilisation compared with RSVP-based QoS routing, both in case of sparse and dense networks. Benefits of the agent-based scheme are adaptability, flexibility, and support for component-based software engineering features such as software reuse, customisation and maintainability     

基于用户体验的老年人移动交互界面设计研究

为解决老年人医疗软件交互界面用户体验满意度较低、操作效率不高等问题，提出一种以用户为中心的老年人医疗移动交互界面开发方法来优化用户体验。首先采用焦点小组法对老年人医疗交互界面的主要设计要素展开分析，并通过正交实验，明确实验所需的交互界面设计方案，运用因子分析获取用户评价指标中的关键项目，并架构评价层级体系，通过联合分析获取医疗移动交互界面各设计要素及其类型的效用值，得出老年用户对医疗移动APP交互界面设计要素的偏好，并获取最优设计要素，从而制定相应的设计策略。依据老年人对用户体验各设计指标的诉求偏好，有效地对老年人医疗APP的用户体验进行优化，并设计出界面交互原型，进而为设计师开发出符合老年人用户体验的APP提供参考。     

User Profile System Based on Sentiment Analysis for Mobile Edge Computing

Emotions of users do not converge in a single application but are scattered across diverse applications. Mobile devices are the closest media for handling user data and these devices have the advantage of integrating private user information and emotions spread over different applications. In this paper, we first analyze user profile on a mobile device by describing the problem of the user sentiment profile system in terms of data granularity, media diversity, and server-side solution. Fine-grained data requires additional data and structural analysis in mobile devices. Media diversity requires standard parameters to integrate user data from various applications. A server-side solution presents a potential risk when handling individual privacy information. Therefore, in order to overcome these problems, we propose a general-purposed user profile system based on sentiment analysis that extracts individual emotional preferences by comparing the difference between public and individual data based on particular features. The proposed system is built based on a sentiment hierarchy, which is created by using unstructured data on mobile devices. It can compensate for the concentration of single media, and analyze individual private data without the invasion of privacy on mobile devices.     

An Attention-Based Friend Recommendation Model in Social Network

In social networks, user attention affects the user’s decision-making, resulting in a performance alteration of the recommendation systems. Existing systems make recommendations mainly according to users’ preferences with a particular focus on items. However, the significance of users’ attention and the difference in the influence of different users and items are often ignored. Thus, this paper proposes an attention-based multi-layer friend recommendation model to mitigate information overload in social networks. We first constructed the basic user and item matrix via convolutional neural networks (CNN). Then, we obtained user preferences by using the relationships between users and items, which were later inputted into our model to learn the preferences between friends. The error performance of the proposed method was compared with the traditional solutions based on collaborative filtering. A comprehensive performance evaluation was also conducted using large-scale real-world datasets collected from three popular location-based social networks. The experimental results revealed that our proposal outperforms the traditional methods in terms of recommendation performance.     

Prediction of Web Services Reliability Based on Decision Tree Classification Method

With the development of the service-oriented computing (SOC), web service has an important and popular solution for the design of the application system to various enterprises. Nowadays, the numerous web services are provided by the service providers on the network, it becomes difficult for users to select the best reliable one from a large number of services with the same function. So it is necessary to design feasible selection strategies to provide users with the reliable services. Most existing methods attempt to select services according to accurate predictions for the quality of service (QoS) values. However, because the network and user needs are dynamic, it is almost impossible to accurately predict the QoS values. Furthermore, accurate prediction is generally timeconsuming. This paper proposes a service decision tree based post-pruning prediction approach. This paper first defines the five reliability levels for measuring the reliability of services. By analyzing the quality data of service from the network, the proposed method can generate the training set and convert them into the service decision tree model. Using the generated model and the given predicted services, the proposed method classifies the service to the corresponding reliability level after discretizing the continuous attribute of service. Moreover, this paper applies the post-pruning strategy to optimize the generated model for avoiding the over-fitting. Experimental results show that the proposed method is effective in predicting the service reliability.     

ESAP: Efficient and secure authentication protocol for roaming user in mobile communication networks

The Global System for Mobile communication (GSM) network is proposed to mitigate the security problems and vulnerabilities observed in the mobile telecommunication system. However, the GSM network is vulnerable to different kinds of attacks such as redirection attack, impersonation attack and Man in-the Middle (MiTM) attack. The possibility of these attacks makes the wireless mobile system vulnerable to fraudulent access and eavesdropping. Different authentication protocols of GSM were proposed to overcome the drawbacks but many of them lead to network signalling overload and increases the call set-up time. In this paper, an efficient and secure authentication and key agreement protocol (ESAP-AKA) is proposed to overcome the flaws of existing authentication protocol for roaming users in the GSM network. The formal verification of the proposed protocol is presented by BAN logic and the security analysis is shown using the AVISPA tool. The security analysis shows that the proposed protocol avoids the different possible attacks on the communication network. The performance analysis based on the fluid flow mobility model shows that the proposed protocol reduces the communication overhead of the network by reducing a number of messages. On an average, the protocol reduces 60% of network signalling congestion overhead as compared with other existing GSM-AKA protocols. Moreover, the protocol not only removes the drawbacks of existing protocols but also accomplishes the needs of roaming users.     

基于Hooked理论的移动短视频应用设计策略研究

目的将Hooked理论导入移动短视频应用设计,以期改善目前短视频应用中存在的创作率低、互动性弱、参与度下滑等问题,激发用户的能动性和创造性,提升产品的互动体验。方法基于碎片化、个性化、社群化的移动短视频时代特性,分析Hooked理论导入移动短视频应用的意义,结合用户调研结果,以触发、行动、多变的酬赏以及用户投入四个步骤为主线,提出移动短视频应用设计策略,包括利用用户的压力、孤独感来触发用户使用,优化创作路径、推理用户行为,多变的成就达成机制以及价值存储与虚荣指标外显。结论通过Hooked理论的运用,加强了产品与用户行为的结合,有助于把握短视频产品的时代特征,减小用户创作阻力,满足多样化互动需求,打造出更富吸引力的移动短视频应用平台。     

Deep Q-Learning Based Computation Offloading Strategy for Mobile Edge Computing

To reduce the transmission latency and mitigate the backhaul burden of the centralized cloud-based network services, the mobile edge computing (MEC) has been drawing increased attention from both industry and academia recently. This paper focuses on mobile users’ computation offloading problem in wireless cellular networks with mobile edge computing for the purpose of optimizing the computation offloading decision making policy. Since wireless network states and computing requests have stochastic properties and the environment’s dynamics are unknown, we use the model-free reinforcement learning (RL) framework to formulate and tackle the computation offloading problem. Each mobile user learns through interactions with the environment and the estimate of its performance in the form of value function, then it chooses the overhead-aware optimal computation offloading action (local computing or edge computing) based on its state. The state spaces are high-dimensional in our work and value function is unrealistic to estimate. Consequently, we use deep reinforcement learning algorithm, which combines RL method Q-learning with the deep neural network (DNN) to approximate the value functions for complicated control applications, and the optimal policy will be obtained when the value function reaches convergence. Simulation results showed that the effectiveness of the proposed method in comparison with baseline methods in terms of total overheads of all mobile users.     

Research on Sensor Network Coverage Enhancement Based on Non-Cooperative Games

Coverage is an important issue for resources rational allocation, cognitive tasks completion in sensor networks. The mobility, communicability and learning ability of smart sensors have received much attention in the past decade. Based on the deep study of game theory, a mobile sensor non-cooperative game model is established for the sensor network deployment and a local information-based topology control (LITC) algorithm for coverage enhancement is proposed. We both consider revenue of the monitoring events and neighboring sensors to avoid nodes aggregation when formulating the utility function. We then prove that the non-cooperative game is an exact potential game in which Nash Equilibrium exists. The proposed algorithm focuses on the local information of the neighboring sensors and decides sensors’ next action based on the actions of the other sensors, which maximizes its own utility function. We finally evaluate the performance of the proposed method through simulations. Simulation results demonstrate that the proposed algorithm can enlarge the coverage of the entire monitoring area while achieving effective coverage of the events.     

天基多媒体移动通信网的QoS综合评判模型

简要分析了天基网上多媒体通信的QoS要求，阐述了其QoS的主要参数指标。基于多元信息处理技术与层次判决提出了天基多媒体移动通信网（MWAN）的QoS综合评判模型，结合实例说明了具体的评判过程，该模型具有简洁、可操作性强的特点，可供从事卫星移动通信、多媒本通信相关人员参考。