Novel model of a AlGaN/GaN high electron mobility transistor based on an artificial neural network

In this paper we present a novel approach to modeling AlGaN/GaN high electron mobility transistor （HEMT） with an artificial neural network （ANN）. The AlGaN/GaN HEMT device structure and its fabrication process are described. The circuit-based Neuro-space mapping （neuro-SM） technique is studied in detail. The EEHEMT model is implemented according to the measurement results of the designed device, which serves as a coarse model. An ANN is proposed to model AIGaN/CaN HEMT based on the coarse model. Its optimization is performed. The simulation results from the model are compared with the measurement results. It is shown that the simulation results obtained from the ANN model of A1GaN/GaN HEMT are more accurate than those obtained from the EEHEMT model.

Virtual reality mobility model for wireless ad hoc networks

For wireless ad hoc networks simulation, node＇s mobility pattern and traffic pattern are two key elements. A new simulation model is presented based on the virtual reality collision detection algorithm in obstacle environment, and the model uses the path planning method to avoid obstacles and to compute the node＇s moving path. Obstacles also affect node＇s signal propagation. Considering these factors, this study implements the mobility model for wireless ad hoc networks. Simulation results show that the model has a significant impact on the performance of protocols.

A Spatio-temporal Data Model for Road Network in Data Center Based on Incremental Updating in Vehicle Navigation System

The technique of incremental updating,which can better guarantee the real-time situation of navigational map,is the developing orientation of navigational road network updating.The data center of vehicle navigation system is in charge of storing incremental data,and the spatio-temporal data model for storing incremental data does affect the efficiency of the response of the data center to the requirements of incremental data from the vehicle terminal.According to the analysis on the shortcomings of several typical spatio-temporal data models used in the data center and based on the base map with overlay model,the reverse map with overlay model (RMOM) was put forward for the data center to make rapid response to incremental data request.RMOM supports the data center to store not only the current complete road network data,but also the overlays of incremental data from the time when each road network changed to the current moment.Moreover,the storage mechanism and index structure of the incremental data were designed,and the implementation algorithm of RMOM was developed.Taking navigational road network in Guangzhou City as an example,the simulation test was conducted to validate the efficiency of RMOM.Results show that the navigation database in the data center can response to the requirements of incremental data by only one query with RMOM,and costs less time.Compared with the base map with overlay model,the data center does not need to temporarily overlay incremental data with RMOM,so time-consuming of response is significantly reduced.RMOM greatly improves the efficiency of response and provides strong support for the real-time situation of navigational road network.

Spatio-Temporal Cellular Network Traffic Prediction Using Multi-Task Deep Learning for AI-Enabled 6G

Spatio-temporal cellular network traffic prediction at wide-area level plays an important role in resource reconfiguration,traffic scheduling and intrusion detection,thus potentially supporting connected intelligence of the sixth generation of mobile communications technology(6G).However,the existing studies just focus on the spatio-temporal modeling of traffic data of single network service,such as short message,call,or Internet.It is not conducive to accurate prediction of traffic data,characterised by diverse network service,spatio-temporality and supersize volume.To address this issue,a novel multi-task deep learning framework is developed for citywide cellular network traffic prediction.Functionally,this framework mainly consists of a dual modular feature sharing layer and a multi-task learning layer(DMFS-MT).The former aims at mining long-term spatio-temporal dependencies and local spatio-temporal fluctuation trends in data,respectively,via a new combination of convolutional gated recurrent unit(ConvGRU)and 3-dimensional convolutional neural network(3D-CNN).For the latter,each task is performed for predicting service-specific traffic data based on a fully connected network.On the real-world Telecom Italia dataset,simulation results demonstrate the effectiveness of our proposal through prediction performance measure,spatial pattern comparison and statistical distribution verification.

Analysis of reactive routing protocols for mobile ad hoc networks in Markov models

Mobile ad hoc networks （MANETs） have become a hot issue in the area of wireless networks for their non-infrastructure and mobile features. In this paper, a MANET is modeled so that the length of each link in the network is considered as a birthdeath process and the space is reused for n times in the flooding process, which is named as an n-spatiai reuse birth-death model （n-SRBDM）. We analyze the performance of the network under the dynamic source routing protocol （DSR） which is a famous reactive routing protocol. Some performance parameters of the route discovery are studied such as the probability distribution and the expectation of the flooding distance, the probability that a route is discovered by a query packet with a hop limit, the probability that a request packet finds a τ-time-valid route or a symmetric-valid route, and the average time needed to discover a valid route. For the route maintenance, some parameters are introduced and studied such as the average frequency of route recovery and the average time of a route to be valid. We compare the two models with spatial reuse and without spatial reuse by evaluating these parameters. It is shown that the spatial reuse model is much more effective in routing.

The Research on QoS Model Design in Mobile Ad Hoc Networks

Wireless Ad Hoc Networks is a special kind of wireless communication network. With the great development of multimedia applications, how to provide QoS guarantee in the MAC layer is the hot topic in wireless ad hoc network (MANET). This paper designed a QoS model in MANET. The feasibility and reliability of this model is analyzed and verified. Compared with the traditional model, the proposed approach is improved in MAC layer in order to achieve high control rate of low-priority transactions.

Personalized Privacy Protecting Model in Mobile Social Network

With the rapid development of the new generation of information technology,the analysis of mobile social network big data is getting deeper and deeper.At the same time,the risk of privacy disclosure in social network is also very obvious.In this paper,we summarize the main access control model in mobile social network,analyze their contribution and point out their disadvantages.On this basis,a practical privacy policy is defined through authorization model supporting personalized privacy preferences.Experiments have been conducted on synthetic data sets.The result shows that the proposed privacy protecting model could improve the security of the mobile social network while keeping high execution efficiency.

Mobility Conscious Medium Access Control Scheme for Wireless Sensor Networks: A Conceptual Approach

Mobility in Wireless Sensor Network (WSN) presents distinctive challenges in Medium Access Control (MAC) scheme. Numerous MAC protocols for sensor networks assume that sensor nodes are static and focus primarily on energy efficiency. This work seeks to develop an improved mobility conscious medium access control scheme for wireless sensor networks with a view to enhance energy conservation on mobile sensor nodes. On this note, mobility patterns of different scenarios are modelled using Gauss Markov Mobility Model (GMMM) to determine the position and distance of the sensor nodes and how they are correlated in time.

Performance Evaluation of Routing Protocols on the Reference Region Group Mobility Model for MANET

Group mobility is prevalent in many mobile ad hoc network (MANET) applications, such as disaster recovery, military operations, searching and rescue activities. Group partition, as an inherent phenomenon in group mobility, may occur when mobile nodes move in diverse mobility patterns and it causes the network to be partitioned into disconnected components. It may result in severe link disconnections, which interrupts network communications. To address this concern, we proposed a novel group mobility model in this paper, namely the Reference Region Group Mobility model, which can be used to mimic group operations in MANETs, i.e. group partitions and mergers. Based on this model, a comprehensive study on the impact of group partitions to the performance of network routing protocols are carried out by evaluating two well-known routing protocols, namely the Ad Hoc On-demand Distance Vector Routing protocol (AODV) and the Dynamic Source Routing protocol (DSR). The simulation results reflect that group partitions have a significant impact to the performance of network routing protocols.

Mathematical Model Validation of Search Protocols in MP2P Networks

Broadcasting is a basic technique in Mobile ad-hoc network(MANET),and it refers to sending a packet from one node to every other node within the transmission range.Flooding is a type of broadcast where the received packet is retransmitted once by every node.The naive flooding technique,floods the network with query messages,while the random walk technique operates by contacting the subsets of every node’s neighbors at each step,thereby restricting the search space.One of the key challenges in an ad-hoc network is the resource or content discovery problem which is about locating the queried resource.Many earlier works have mainly focused on the simulation-based analysis of flooding,and its variants under a wired network.Although,there have been some empirical studies in peer-to-peer(P2P)networks,the analytical results are still lacking,especially in the context of P2P systems running over MANET.In this paper,we describe how P2P resource discovery protocols perform badly over MANETs.To address the limitations,we propose a new protocol named ABRW(Address Broadcast Random Walk),which is a lightweight search approach,designed considering the underlay topology aimed to better suit the unstructured architecture.We provide the mathematical model,measuring the performance of our proposed search scheme with different widely popular benchmarked search techniques.Further,we also derive three relevant search performance metrics,i.e.,mean no.of steps needed to find a resource,the probability of finding a resource,and the mean no.of message overhead.We validated the analytical expressions through simulations.The simulation results closely matched with our analyticalmodel,justifying our findings.Our proposed search algorithm under such highly dynamic self-evolving networks performed better,as it reduced the search latency,decreased the overall message overhead,and still equally had a good success rate.

EXTENDED MONTE CARLO LOCALIZATION ALGORITHM FOR MOBILE SENSOR NETWORKS

A real-world localization system for wireless sensor networks that adapts for mobility and irregular radio propagation model is considered. The traditional range-based techniques and recent range-free localization schemes are not well competent for localization in mobile sensor networks, while the probabilistic approach of Bayesian filtering with particle-based density representations provides a comprehensive solution to such localization problem. Monte Carlo localization is a Bayesian filtering method that approximates the mobile node's location by a set of weighted particles. In this paper, an enhanced Monte Carlo localization algorithm-Extended Monte Carlo Localization (Ext-MCL) is proposed, i.e., the traditional Monte Carlo localization algorithm is improved and extended to make it suitable for the practical wireless network environment where the radio propagation model is irregular. Simulation results show the proposal gets better localization accuracy and higher localizable node number than previously proposed Monte Carlo localization schemes not only for ideal radio model, but also for irregular one.

Analytical Comparison of Resource Search Algorithms in Non-DHT Mobile Peer-to-Peer Networks

One of the key challenges in ad-hoc networks is the resource discovery problem.How efciently&quickly the queried resource/object can be resolved in such a highly dynamic self-evolving network is the underlying question?Broadcasting is a basic technique in the Mobile Ad-hoc Networks(MANETs),and it refers to sending a packet from one node to every other node within the transmission range.Flooding is a type of broadcast where the received packet is retransmitted once by every node.The naive ooding technique oods the network with query messages,while the random walk scheme operates by contacting subsets of each node’s neighbors at every step,thereby restricting the search space.Many earlier works have mainly focused on the simulation-based analysis of ooding technique,and its variants,in a wired network scenario.Although,there have been some empirical studies in peer-to-peer(P2P)networks,the analytical results are still lacking,especially in the context of mobile P2P networks.In this article,we mathematically model different widely used existing search techniques,and compare with the proposed improved random walk method,a simple lightweight approach suitable for the non-DHT architecture.We provide analytical expressions to measure the performance of the different ooding-based search techniques,and our proposed technique.We analytically derive 3 relevant key performance measures,i.e.,the avg.number of steps needed to nd a resource,the probability of locating a resource,and the avg.number of messages generated during the entire search process.

Research on Link Duration for Mobile Multihop Communication Networks

Mobile multihop communication network is an important branch of modern mobile communication system, and is an important technical support for ubiquitous communication. The random movement of the nodes makes the networking be more flexible, but the frequently changing topology will decrease the link duration between nodes significantly, which will increase the packets loss probability and affect the network communication performance. Aiming at the problem of declining link duration caused by nomadic characteristics in mobile multihop communication network, four link duration models for possible moving states are established based on different features in real networking process in this paper, which will provide reliable criterion for the optimal routing selection. Model analysis and simulation results show that the reliable route established by the proposed model will effectively extend the link duration, and can enhance the global stability of the mobile multihop information transmission, so as to provide new option to transmission reliability improvement for the mobile communication network.

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%.

DTMC-based Modeling and Analysis of Obstacle Ad hoc Networks

One of the main characteristics of Ad hoc networks is node mobility, which results in constantly changing in network topologies. Consequently, the ability to forecast the future status of mobility nodes plays a key role in QOS routing. We propose a random mobility model based on discretetime Markov chain, called ODM. ODM provides a mathematical framework for calculating some parameters to show the future status of mobility nodes, for instance, the state transition probability matrix of nodes, the probability that an edge is valid, the average number of valid-edges and the probability of a request packet found a valid route. Furthermore, ODM can account for obstacle environment. The state transition probability matrix of nodes can quantify the impact of obstacles. Several theorems are given and proved by using the ODM. Simulation results show that the calculated value can forecast the future status of mobility nodes.

Anonymous data collection scheme for cloud-aided mobile edge networks

With the rapid spread of smart sensors,data collection is becoming more and more important in Mobile Edge Networks(MENs).The collected data can be used in many applications based on the analysis results of these data by cloud computing.Nowadays,data collection schemes have been widely studied by researchers.However,most of the researches take the amount of collected data into consideration without thinking about the problem of privacy leakage of the collected data.In this paper,we propose an energy-efficient and anonymous data collection scheme for MENs to keep a balance between energy consumption and data privacy,in which the privacy information of senors is hidden during data communication.In addition,the residual energy of nodes is taken into consideration in this scheme in particular when it comes to the selection of the relay node.The security analysis shows that no privacy information of the source node and relay node is leaked to attackers.Moreover,the simulation results demonstrate that the proposed scheme is better than other schemes in aspects of lifetime and energy consumption.At the end of the simulation part,we present a qualitative analysis for the proposed scheme and some conventional protocols.It is noteworthy that the proposed scheme outperforms the existing protocols in terms of the above indicators.

A Secure and Energy-Balanced Routing Scheme for Mobile Wireless Sensor Network

Mobile wireless sensor network (MWSN) has the features of self-organization, multiple-hop and limited energy resources. It is vulnerable to a wide set of security attacks, including those targeting the routing protocol functionality. In this paper, the existing security problems and solutions in MWSN are summarized, and then a trust management system based on neighbor monitoring is proposed. In the trust management system, the trust value is calculated by the neighbor monitoring mechanism, and the direct trust value and the indirect trust value are combined to establish the distributed trust model to detect the malicious nodes. The consistency check algorithm is capable of defending against the attacks on the trust model. In addition, because of the limited energy of the sensor nodes, the energy-balanced algorithm is introduced to prolong the lifespan of MWSN. The residual energy and energy density are considered in the routing decision. Finally, the simulation experiments show that the proposed algorithm can detect the malicious nodes effectively and achieve the energy-balanced goal to prolong the lifespan of MWSN.

ILSM:Incorporated Lightweight Security Model for Improving QOS in WSN

In the network field,Wireless Sensor Networks(WSN)contain prolonged attention due to afresh augmentations.Industries like health care,traffic,defense,and many more systems espoused the WSN.These networks contain tiny sensor nodes containing embedded processors,TinyOS,memory,and power source.Sensor nodes are responsible for forwarding the data packets.To manage all these components,there is a need to select appropriate parameters which control the quality of service of WSN.Multiple sensor nodes are involved in transmitting vital information,and there is a need for secure and efficient routing to reach the quality of service.But due to the high cost of the network,WSN components have limited resources to manage the network.There is a need to design a lightweight solution that ensures the quality of service in WSN.In this given manner,this study provides the quality of services in a wireless sensor network with a security mechanism.An incorporated hybrid lightweight security model is designed in which random waypoint mobility(RWM)model and grey wolf optimization(GWO)is used to enhance service quality and maintain security with efficient routing.MATLAB version 16 andNetwork Stimulator 2.35(NS2.35)are used in this research to evaluate the results.The overall cost factor is reduced at 60%without the optimization technique and 90.90%reduced by using the optimization technique,which is assessed by calculating the signal-to-noise ratio,overall energy nodes,and communication overhead.