Traffic Simulation in SAGIN Air Segment Containing Ad Hoc Network of Flying Drones

The purpose of this article is to simulate data transmission and calculate traffic parameters in SAGIN air segment for which Ad Hoc network of flying drones is considered as a model. Traffic modeling is based on the manet-routing-compare example from the ns3 simulator library, which has been supplemented with the code for calculation packet losses, throughput/goodput, and message transmission delays. The program allowed considering drones movement at both low and high speeds from 3.6 km/h to 72 km/h. The dependences of traffic losses on data transmission power, transaction sizes and data transmission rate are obtained and analyzed. The distribution of the average effective arrival rate λ and the throughput/goodput for drones has been studied. Comparing traffic characteristics in models with different numbers of drones allows judging how the required quality of service can be achieved by choosing the right transmission parameters.

Approbation of the stochastic group virus protection model

The article discusses the implementation in Java of the stochastic collaborative virus defense model developed within the framework of the Distributed Object-Based Stochastic Hybrid Systems (DOBSHS) model and its analysis. The goal of the work is to test the model in conditions close to the real world on the way to introducing its use in the practical environment. We propose a method of translating a system specification in the SHYMaude language, intended for the specification and analysis of DOBSHS models in the rewriting logic framework, into the corresponding Java implementation. The resulting Java system is deployed on virtual machines, the virus and the group virus alert system are modeled stochastically. To analyze the system we use several metrics, such as the saturation time of the virus propagation, the proportion of infected nodes upon reaching saturation and the maximal virus propagation speed. We use Monte Carlo method with the computation of confidence intervals to obtain estimates of the selected metrics. We perform analysis on the basis of the sigmoid virus propagation graph over time in the presence of the defense system. We implemented two versions of the system using two protocols for transmitting messages between nodes, TCP/IP and UDP. We measured the influence of the protocol type and the associated costs on the defense system effectiveness. To assess the potential of cost reduction associated with the use of different message transmission protocols, we performed analysis of the original DOBSHS model modified to model message transmission delays. We measured the influence of other model parameters important for the next steps towards the practical use of the model. To address the system scalability, we propose a hierarchical approach to the system design to make possible its use with a large number of nodes.

Collision-Aware Routing Using Multi-Objective Seagull Optimization Algorithm for WSN-Based IoT

In recent trends, wireless sensor networks (WSNs) have become popular because of their cost, simple structure, reliability, and developments in the communication field. The Internet of Things (IoT) refers to the interconnection of everyday objects and sharing of information through the Internet. Congestion in networks leads to transmission delays and packet loss and causes wastage of time and energy on recovery. The routing protocols are adaptive to the congestion status of the network, which can greatly improve the network performance. In this research, collision-aware routing using the multi-objective seagull optimization algorithm (CAR-MOSOA) is designed to meet the efficiency of a scalable WSN. The proposed protocol exploits the clustering process to choose cluster heads to transfer the data from source to endpoint, thus forming a scalable network, and improves the performance of the CAR-MOSOA protocol. The proposed CAR-MOSOA is simulated and examined using the NS-2.34 simulator due to its modularity and inexpensiveness. The results of the CAR-MOSOA are comprehensively investigated with existing algorithms such as fully distributed energy-aware multi-level (FDEAM) routing, energy-efficient optimal multi-path routing protocol (EOMR), tunicate swarm grey wolf optimization (TSGWO), and CoAP simple congestion control/advanced (CoCoA). The simulation results of the proposed CAR-MOSOA for 400 nodes are as follows: energy consumption, 33 J; end-to-end delay, 29 s; packet delivery ratio, 95%; and network lifetime, 973 s, which are improved compared to the FDEAM, EOMR, TSGWO, and CoCoA.

Compensation for Delays and Losses of Packages in Dynamic Online Games

A couple of decades ago, data rates on the network were measured in kilobytes per second, and even then, online game developers had some problems with the packet loss and transmission delays. Now the transfer rate is hundreds of times higher, and the problem of delay compensation is even more relevant.For many dynamic online games, a transmission delay of as little as 20 ms can be quite noticeable, negatively affecting the gameplay and emotions of the game, which can repel players.The problem is exacerbated by the fact that along with the need to compensate for the time of delivery of packets, on the client side there are other non-network factors that are beyond the control of developers, which make the total delay 5-10 ms longer. Because of this, the desire to get rid of network delays as much and as well as possible becomes a necessity, and developers are forced to look for optimal ways to solve this problem.The problem statement is as follows: to review the causes of delays in online games and possible solu- tions, as well as the advantages and disadvantages of certain approaches. The problem is considered at the 4 levels of the TCP / IP network model, as well as at the application level. The approaches are given for the most commonly used protocols for each layer, but basic ideas can be easily transferred to other implementations.The main causes of delays under consideration: propagation delay, router queue delay, transmission delay, and processing delays.This article shows the impact of network delays on the online games and the ways to compensate for them, along with the theory of data transmission protocols in the network and the ways to solve the problems that arise in the development of algorithms.Recommendations for solving the compensation problem can be taken into account when designing and launching online shooters, strategies, etc. Thanks to the given receptions it is possible to minimize the general delay on the transfer of packets in a network, thanks to which the game on the client looks as if the player plays in the Single Player mode.

Local dendritic balance enables learning of efficient representations in networks of spiking neurons

How can neural networks learn to efficiently represent complex and high-dimensional inputs via local plasticity mechanisms? Classical models of representation learning assume that feedforward weights are learned via pairwise Hebbian-like plasticity. Here, we show that pairwise Hebbian-like plasticity works only under unrealistic requirements on neural dynamics and input statistics. To overcome these limitations, we derive from first principles a learning scheme based on voltage-dependent synaptic plasticity rules. Here, recurrent connections learn to locally balance feedforward input in individual dendritic compartments and thereby can modulate synaptic plasticity to learn efficient representations. We demonstrate in simulations that this learning scheme works robustly even for complex high-dimensional inputs and with inhibitory transmission delays, where Hebbian-like plasticity fails. Our results draw a direct connection between dendritic excitatory–inhibitory balance and voltage-dependent synaptic plasticity as observed in vivo and suggest that both are crucial for representation learning.

A Novel Key Distribution Scheme Based on Transmission Delays

With the development of IoT (Internet of Things), the demand for security is increasing day by day. However, the traditional key distribution scheme is high in cost and complicated in calculation, so a lightweight key distribution scheme is urgently needed. In this paper, a novel key distribution scheme based on transmission delay is proposed. Based on the experimental observation, we find that the statistical characteristics of their transmission delays are about the same if any two terminals transmit the equal-length packets on the Internet and are different for different transmission paths. Accordingly, we propose a method to customize transmission delays. On the Internet, we have deployed 7 forwarding hosts. By randomly determining the forwarding path of packets, we can get customized transmission delay sets. Then, these sets are processed, respectively, by correcting outlier, normalizing, quantizing, encoding, and reconciling so as to be able to realize key distribution between two sides. Next, we design a key distribution protocol and a key distribution system, which consists of a Management Center, a Packet Forwarding Network, and Users. Finally, we reason the security of the key distribution protocol with formal analysis tools.

Time for Space and the Stability of Prospective Control: Reaching-to-Grasp Gibson

Gibson formulated an approach to goal-directed behavior using prospective information in the context of visually guided locomotion and manual behavior. The former was Gibson's paradigm case, but it is the rapidity of targeted reaching that has provided the special challenge for stable control. Recent treatments of visually guided reaching assume that internal forward models are required to generate stable behavior given delays caused by neural transmission times. Internal models are representations of the sort eschewed by Gibson in favor of prospective information. Reaching is usually described as guided using relative distances of hand and target, but prospective information is usually temporal rather than spatial. We describe proportional rate control models that incorporate time dimensioned prospective information and show they remain stable in the face of delays. The use of time-dimensioned prospective information removes the need for internal models for stable behavior despite neural transmission delays and allows Gibson's approach to prevail.

Transmission Delay-Based Uplink Multi-User Scheduling in IEEE 802.11ax Networks

As the demands for uplink traffic increase, improving the uplink throughput has attracted research attention in IEEE 802.11 networks. To avoid excessive competition among stations and enhance the uplink throughput performance, the IEEE 802.11ax standard supports uplink multi-user transmission scenarios, in which AP triggers certain stations in a network to transmit uplink data simultaneously. The performance of uplink multi-user transmissions highly depends on the scheduler, and station scheduling is still an open research area in IEEE-802.11ax-based networks. In this paper, we propose a transmission delay-based uplink multi-user scheduling method. The proposed method consists of two steps. In the first step, the proposed method makcreateses station clusters so that stations in each cluster have similar expected transmission delays. The transmission delay-based station clustering increases the ues of uplink data channels during the uplink multi-user transmission scenario specified in IEEE 802.11ax. In the second step, the proposed method selects cluster for uplink multi-user transmissions. The cluster selection can be performed with a proportional fair-based approach. With the highly channel-efficient station cluster, the proposed scheduling method increases network throughput performance. Through the IEEE 802.11ax standard compliant simulations, we verify the network throughput performance of the proposed uplink scheduling method.