Survivability modeling and analysis on 3D mobile ad-hoc networks

Most existing work on survivability in mobile ad-hoc networks(MANETs) focuses on two dimensional(2D) networks.However,many real applications run in three dimensional(3D) networks,e.g.,climate and ocean monitoring,and air defense systems.The impact on network survivability due to node behaviors was presented,and a quantitative analysis method on survivability was developed in 3D MANETs by modeling node behaviors and analyzing 3D network connectivity.Node behaviors were modeled by using a semi-Markov process.The node minimum degree of 3D MANETs was discussed.An effective approach to derive the survivability of k-connected networks was proposed through analyzing the connectivity of 3D MANETs caused by node misbehaviors,based on the model of node isolation.The quantitative analysis of node misbehaviors on the survivability in 3D MANETs is obtained through mathematical description,and the effectiveness and rationality of the proposed approach are verified through numerical analysis.The analytical results show that the effect from black and gray attack on network survivability is much severer than other misbehaviors.

Decentralized content sharing in mobile ad-hoc networks:A survey

The evolution of smart mobile devices has significantly impacted the way we generate and share contents and introduced a huge volume of Internet traffic.To address this issue and take advantage of the short-range communication capabilities of smart mobile devices,the decentralized content sharing approach has emerged as a suitable and promising alternative.Decentralized content sharing uses a peer-to-peer network among colocated smart mobile device users to fulfil content requests.Several articles have been published to date to address its different aspects including group management,interest extraction,message forwarding,participation incentive,and content replication.This survey paper summarizes and critically analyzes recent advancements in decentralized content sharing and highlights potential research issues that need further consideration.

Optimization of Route Repair in Mobile Ad-hoc Network

A main shortcoming of mobile Ad-hoc network's reactive routing protocols is the large volume of far-reaching control traffic required to support the route discovery (RD) and route repair (RR) mechanism. Using a random mobility model, this paper derives the probability equation of the relative distance (RDIS) between any two mobile hosts in an ad-hoc network. Consequently, combining with average equivalent hop distance (AEHD), a host can estimate the routing hops between itself and any destination host each time the RD/RR procedure is triggered, and reduce the flooding area of RD/RR messages. Simulation results show that this optimized route repair (ORR) algorithm can significantly decrease the communication overhead of RR process by about 35%.

A Collaborative Approach for Secured Routing in Mobile Ad-Hoc Network

Mobile computing is the most powerful application for network com-munication and connectivity,given recent breakthroughs in thefield of wireless networks or Mobile Ad-hoc networks(MANETs).There are several obstacles that effective networks confront and the networks must be able to transport data from one system to another with adequate precision.For most applications,a frame-work must ensure that the retrieved data reflects the transmitted data.Before driv-ing to other nodes,if the frame between the two nodes is deformed in the data-link layer,it must be repaired.Most link-layer protocols immediately disregard the frame and enable the high-layer protocols to transmit it down.In other words,because of asset information must be secured from threats,information is a valu-able resource.In MANETs,some applications necessitate the use of a network method for detecting and blocking these assaults.Building a secure intrusion detection system in the network,which provides security to the nodes and route paths in the network,is a major difficulty in MANET.Attacks on the network can jeopardize security issues discovered by the intrusion detection system engine,which are then blocked by the network’s intrusion prevention engine.By bringing the Secure Intrusion Detection System(S-IDS)into the network,a new technique for implementing security goals and preventing attacks will be developed.The Secure Energy Routing(SER)protocol for MANETs is introduced in this study.The protocol addresses the issue of network security by detecting and preventing attacks in the network.The data transmission in the MANET is forwarded using Elliptical Curve Cryptography(ECC)with an objective to improve the level of security.Network Simulator–2 is used to simulate the network and experiments are compared with existing methods.

Performance Analysis under MAC Layer Misbehavior Attack in Mobile Ad-Hoc Networks

This work presents a multi-criteria analysis of the MAC （media access control） layer misbehavior of the IEEE （Institute of Electrical and Electronics Engineers） 802.11 standard, whose principle is to cheat at the protocol to increase the transmission rate by greedy nodes at the expense of the other honest nodes. In fact, IEEE 802.11 forces nodes for access to the channel to wait for a back off interval, randomly selected from a specified range, before initiating a transmission. Greedy nodes may wait for smaller back-off intervals than honest nodes, and then obtaining an unfair assignment. In the first of our works a state of art on the research on IEEE 802.11 MAC layer misbehavior are presented. Then the impact of this misbehavior at the reception is given, and we will generalize this impact on a large scale. An analysis of the correlation between the throughput and the inter-packets time is given. Afterwards, we will define a new metric for measuring the performance and capability of the network.

Impact of Mobility on Delay-Throughput Performance in Multi-Service Mobile Ad-Hoc Networks

Mobile Ad-Hoc network is a collection of mobile nodes in communication without using infrastructure. Despite the importance of type of the exchanged data between the knots on the QoS of the MANETs, the mul-tiservice data were not treated by the larger number of previous researches. In this paper we propose an adaptive method which gives the best performances in terms of delay and throughput. We have studied the impact, respectively, of mobility models and the density of nodes on the performances (End-to-End Delay, Throughput and Packet Delivery ratio) of routing protocol (On-Demand Distance Vector) AODV by using in the first a multiservice VBR (MPEG-4) and secondly the Constant Bit Rate (CBR) traffic. Finally we com-pare the performance on both cases. Experimentally, we considered the three mobility models as follows Random Waypoint, Random Direction and Mobgen Steady-State. The experimental results illustrate that the behavior of AODV change according to the model and the used traffics.

Multi-Agent Deep Reinforcement Learning for Cross-Layer Scheduling in Mobile Ad-Hoc Networks

Due to the fading characteristics of wireless channels and the burstiness of data traffic,how to deal with congestion in Ad-hoc networks with effective algorithms is still open and challenging.In this paper,we focus on enabling congestion control to minimize network transmission delays through flexible power control.To effectively solve the congestion problem,we propose a distributed cross-layer scheduling algorithm,which is empowered by graph-based multi-agent deep reinforcement learning.The transmit power is adaptively adjusted in real-time by our algorithm based only on local information(i.e.,channel state information and queue length)and local communication(i.e.,information exchanged with neighbors).Moreover,the training complexity of the algorithm is low due to the regional cooperation based on the graph attention network.In the evaluation,we show that our algorithm can reduce the transmission delay of data flow under severe signal interference and drastically changing channel states,and demonstrate the adaptability and stability in different topologies.The method is general and can be extended to various types of topologies.

Location aided probabilistic broadcast algorithm for mobile Ad-hoc network routing

On-demand routing protocols are widely used in mobile Ad-hoc network （MANET）. Flooding is an important dissemination scheme in routing discovering of on-demand routing protocol. However, in high-density MANET redundancy flooding packets lead to dramatic deterioration of the performance which calls broadcast storm problem （BSP）. A location-aided probabilistic broadcast （LAPB） algorithm for routing in MANET is proposed to reduce the number of routing packets produced by flooding in this paper. In order to reduce the redundancy packets, only nodes in a specific area have the probability, computed by location information and neighbor knowledge, to propagate the routing packets. Simulation results demonstrate that the LAPB algorithm can reduce the packets and discovery delay （DD） in the routing discovery phase.

Toward path reliability by using adaptive multi-path routing mechanism for multimedia service in mobile Ad-hoc network

Traditional multi-path routing mechanisms aim to establish complete node or link disjoint paths. However, under some circumstances if multiple paths cannot be established based on the current network topology, the traditional multi-path routing mechanism will degenerate into single path routing mechanism, thus the advantages of multi-path routing cannot be exhibited. To enhance the end-to-end path reliability, an adaptive multi-path routing mechanism with path segment is proposed, in which multi-path can be established at part of the end-to-end path. In this way the reliability of the path can be enhanced. This path segment mechanism can divide the end-to-end path into several short segments, and a parallel forwarding mechanism is proposed for guaranteeing the quality of service of multimedia services over the wireless network. Simulations show that the network performance metrics such as the packet delivery ratio, the end-to-end delay and the number of route discoveries are all improved by using the adaptive multi-path routing mechanism.

Survivability Evaluation in Large-Scale Mobile Ad-Hoc Networks

Survivability refers to the ability of a network system to fulfill critical services in a timely manner to end users in the presence of failures and/or attacks. In order to establish a highly survivable system, it is necessary to measure its survivability to evaluate the performance of the system＇s services under adverse conditions. According to survivability requirements of large-scale mobile ad-hoc networks （MANETs）, we propose a novel model for quantitative evaluation on survivability. The proposed model considers various types of faults and connection states of mobile hosts, and uses the continuous time Markov chain （CTMC） to describe the survivability of MANETs in a precise manner. We introduce the reliability theory to perform quantitative analysis and survivability evaluation of segment-by-segment routing （SSR）, multipath-based segment-by-segment routing （MP-SSR）, and segment-by-segment-based multipath routing （SS-MPR） in large-scale MANETs. The proposed model can be used to analyze the network performance much more easily than a simulation-based approach. Numerical validation shows that the proposed model can be used to obtain a better evaluation result on the survivability of large-scale MANETs.

基于MobileNetV3Small-ECA的水稻病害轻量级识别研究

为实现水稻病害的轻量化识别与检测,使用ECA注意力机制改进MobileNetV3Small模型,并使用共享参数迁移学习对水稻病害进行智能化轻量级识别和检测。在PlantVillage数据集上进行预训练,将预训练得到的共享参数迁移到对水稻病害识别模型上微调优化。在开源水稻病害数据集上进行试验测试,试验结果表明,在非迁移学习下,识别准确率达到97.47%,在迁移学习下识别准确率达到99.92%,同时参数量减少26.69%。其次,通过Grad-CAM进行可视化,本文方法与其他注意力机制CBAM和SENET相比,ECA模块生成的结果与图像中病斑的位置和颜色更加一致,表明网络可以更好地聚焦水稻病害的特征,并且通过可视化和各水稻病害分析了误分类原因。本文方法实现了水稻病害识别模型的轻量化,使其能够在移动设备等资源受限的场景中部署,达到快速、高效、便携的目的。同时开发了基于Android的水稻病害识别系统,方便于在边缘端进行水稻病害识别分析。

Collision Avoidance in Mobile Wireless Ad-Hoc Networks with Enhanced MACAW Protocol Suite

Jamming attack is quite serious threat for Mobile networks that collapses all necessary communication infrastructure. Since mobile nodes in Mobile Ad Hoc Networks (MANET) communicate in a multi-hop mode, there is always a possibility for an intruder to launch a jamming attack in order to intercept communication among communication nodes. In this study, a network simulation has been carried out in order to explore and evaluate the possible impacts of jamming attack on MACAW protocol. Ad-hoc network modelling is used to provide communication infrastructure among mobile nodes in order to modelling the simulation scenarios. In simulation model, these nodes have used AODV routing protocol which is designed for MANET while second scenario contains simulated MACAW node models for comparison. On the other hand, this paper is the first study that addresses performance evaluation of MACAW protocol under a constant Jamming Attack. The performance of MACAW protocol is simulated through OPNET Modeler 14.5 software.

Survey on Simulation for Mobile Ad-Hoc Communication for Disaster Scenarios

Mobile ad-hoc communication is a demonstrated solution to mitigate the impact of infrastructure failures during large-scale disasters. A very complex issue in this domain is the design validation of software applications that support decision-making and communication during natural disasters. Such disasters are irreproducible, highly unpredictable, and impossible to scale down, and thus extensive assessments cannot be led in situ. In this context, simulation constitutes the best approach towards the testing of software solutions for natural disaster responses. The present survey reviews mobility models, ad-hoc network architectures, routing protocols and network simulators. Our aim is to provide guidelines for software developers with regards to the performance evaluation of their applications by means of simulation.

Power Adjusting Algorithm： A New Cross-Layer Power Saving Mechanism for Mobile Ad-Hoc Networks

Power saving is one of the key issues in Mobile Ad-Hoc Networks （MANETs）. It can be realized in Medium Access Control （MAC） layer and network layer. However, previous attentions were mainly paid to MAC layer or network layer with the aim of improving the channel utilization by adopting variable-range transmission power control. In this paper we focus on the power saving in both MAC layer and network layer, and propose a Power Adjusting Algorithm （PAA）. In the presence of host＇s mobility, PAA is designed to conserve energy by adjusting the transmission power to maintain the route＇s connectivity and restarting the route discovery periodically to find a new route with better energy efficiency dynamically. After analyzing the operations of PAA, we find that the length of route discovery restarting period is a critical argument which will affect power saving, and an energy consumption model is abstracted to find the optimal value of the restarting period by analyzing the energy consumption of this algorithm. PAA can handle the mobility of MANET by adjusting the transmission power and in the meantime save energy by restarting route discovery periodically to balance the energy consumption on route discovery and packet delivering. Simulation results show that, PAA saves nearly 40% energy compared with Dynamic Source Routing protocol when the maximum speed of mobile hosts is larger than 8 m/s.

Air-Ground Collaborative Mobile Edge Computing:Architecture,Challenges,and Opportunities

By pushing computation,cache,and network control to the edge,mobile edge computing(MEC)is expected to play a leading role in fifth generation(5G)and future sixth generation(6G).Nevertheless,facing ubiquitous fast-growing computational demands,it is impossible for a single MEC paradigm to effectively support high-quality intelligent services at end user equipments(UEs).To address this issue,we propose an air-ground collaborative MEC(AGCMEC)architecture in this article.The proposed AGCMEC integrates all potentially available MEC servers within air and ground in the envisioned 6G,by a variety of collaborative ways to provide computation services at their best for UEs.Firstly,we introduce the AGC-MEC architecture and elaborate three typical use cases.Then,we discuss four main challenges in the AGC-MEC as well as their potential solutions.Next,we conduct a case study of collaborative service placement for AGC-MEC to validate the effectiveness of the proposed collaborative service placement strategy.Finally,we highlight several potential research directions of the AGC-MEC.

Dependent task assignment algorithm based on particle swarm optimization and simulated annealing in ad-hoc mobile cloud

In order to solve the problem of efficiently assigning tasks in an ad-hoc mobile cloud( AMC),a task assignment algorithm based on the heuristic algorithm is proposed. The proposed task assignment algorithm based on particle swarm optimization and simulated annealing( PSO-SA) transforms the dependencies between tasks into a directed acyclic graph( DAG) model. The number in each node represents the computation workload of each task and the number on each edge represents the workload produced by the transmission. In order to simulate the environment of task assignment in AMC,mathematical models are developed to describe the dependencies between tasks and the costs of each task are defined. PSO-SA is used to make the decision for task assignment and for minimizing the cost of all devices,which includes the energy consumption and time delay of all devices.PSO-SA also takes the advantage of both particle swarm optimization and simulated annealing by selecting an optimal solution with a certain probability to avoid falling into local optimal solution and to guarantee the convergence speed. The simulation results show that compared with other existing algorithms,the PSO-SA has a smaller cost and the result of PSO-SA can be very close to the optimal solution.

Leveraging User-Generated Comments and Fused BiLSTM Models to Detect and Predict Issues with Mobile Apps

In the last decade, technical advancements and faster Internet speeds have also led to an increasing number ofmobile devices and users. Thus, all contributors to society, whether young or old members, can use these mobileapps. The use of these apps eases our daily lives, and all customers who need any type of service can accessit easily, comfortably, and efficiently through mobile apps. Particularly, Saudi Arabia greatly depends on digitalservices to assist people and visitors. Such mobile devices are used in organizing daily work schedules and services,particularly during two large occasions, Umrah and Hajj. However, pilgrims encounter mobile app issues such asslowness, conflict, unreliability, or user-unfriendliness. Pilgrims comment on these issues on mobile app platformsthrough reviews of their experiences with these digital services. Scholars have made several attempts to solve suchmobile issues by reporting bugs or non-functional requirements by utilizing user comments.However, solving suchissues is a great challenge, and the issues still exist. Therefore, this study aims to propose a hybrid deep learningmodel to classify and predict mobile app software issues encountered by millions of pilgrims during the Hajj andUmrah periods from the user perspective. Firstly, a dataset was constructed using user-generated comments fromrelevant mobile apps using natural language processing methods, including information extraction, the annotationprocess, and pre-processing steps, considering a multi-class classification problem. Then, several experimentswere conducted using common machine learning classifiers, Artificial Neural Networks (ANN), Long Short-TermMemory (LSTM), and Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) architectures, toexamine the performance of the proposed model. Results show 96% in F1-score and accuracy, and the proposedmodel outperformed the mentioned models.

Attention-relation network for mobile phone screen defect classification via a few samples

How to use a few defect samples to complete the defect classification is a key challenge in the production of mobile phone screens.An attention-relation network for the mobile phone screen defect classification is proposed in this paper.The architecture of the attention-relation network contains two modules:a feature extract module and a feature metric module.Different from other few-shot models,an attention mechanism is applied to metric learning in our model to measure the distance between features,so as to pay attention to the correlation between features and suppress unwanted information.Besides,we combine dilated convolution and skip connection to extract more feature information for follow-up processing.We validate attention-relation network on the mobile phone screen defect dataset.The experimental results show that the classification accuracy of the attentionrelation network is 0.9486 under the 5-way 1-shot training strategy and 0.9039 under the 5-way 5-shot setting.It achieves the excellent effect of classification for mobile phone screen defects and outperforms with dominant advantages.

Adaptive Trajectory Tracking Control for Nonholonomic Wheeled Mobile Robots:A Barrier Function Sliding Mode Approach

The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-based adaptive sliding mode control(BFASMC)method to provide high-precision,fast-response performance and robustness for NWMRs.Compared with the conventional adaptive sliding mode control,the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances bounds.Another advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier function.The benefit is that the overestimation of control gain can be eliminated,resulting in chattering reduction.Moreover,a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the actuator.The stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the prespecified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances.

IRS Assisted UAV Communications against Proactive Eavesdropping in Mobile Edge Computing Networks

In this paper,we consider mobile edge computing(MEC)networks against proactive eavesdropping.To maximize the transmission rate,IRS assisted UAV communications are applied.We take the joint design of the trajectory of UAV,the transmitting beamforming of users,and the phase shift matrix of IRS.The original problem is strong non-convex and difficult to solve.We first propose two basic modes of the proactive eavesdropper,and obtain the closed-form solution for the boundary conditions of the two modes.Then we transform the original problem into an equivalent one and propose an alternating optimization(AO)based method to obtain a local optimal solution.The convergence of the algorithm is illustrated by numerical results.Further,we propose a zero forcing(ZF)based method as sub-optimal solution,and the simulation section shows that the proposed two schemes could obtain better performance compared with traditional schemes.