Average Packet Loss Research Articles

ST-DeLTA: A Novel Spatial-Temporal Value Network Aided Deep Learning Based Intelligent Network Traffic Control System

Deep learning has emerged as a popular Artificial Intelligence (AI) technique to make conventional cyber physical systems become intelligent and sustainable. Recently, deep learning has been widely used in the network domain. With the aid of powerful deep neural networks, the communication network can carry out packets forwarding actions intelligently to avoid possible failure and congestion. However, with the high computing cost and process limitation in only the static network scenario, the existing deep learning based network traffic control algorithms cannot satisfy the sustainable requirement of next generation large scale dynamic network. To conquer the existing problems, a novel spatial-temporal value network aided deep learning based intelligent traffic control algorithm referred as ST-DeLTA is proposed in this paper. In ST-DeLTA, the value matrix and spatial temporal training model (ST model) are employed to intelligently extract the spatial as well as temporal features of traffic patterns and make adaptive packets forwarding decision in large scale and dynamic networks. The mathematical analysis gives the computing cost reduction of our proposal, and the computer simulation demonstrates that our proposal has significantly better training and network performance compared with traditional algorithms in terms of training accuracy, transmission throughput, and average packets loss rate.

ROTOS: A Reconfigurable and Cost-Effective Architecture for High-Performance Optical Data Center Networks

Fast and high capacity optical switching techniques have the potential to enable low latency and high throughput optical data center networks (DCNs) to afford the rapid increasing traffic boosted by multiple applications. Flexibility of the DCN is of key importance to provide adaptive and dynamic bandwidth and capacity to handle the variable traffic patterns of heterogeneous applications. Aiming at improving the network performance and the system flexibility of optical DCNs, we propose and investigate a novel optical DCN architecture named ROTOS based on reconfigurable optical top of rack (ToR) and fast optical switches. In the proposed DCN architecture, the novel optical flexible ToRs employing multiple transceivers (TRXs) and a wavelength selective switch (WSS) are reconfigured by the software-defined networking (SDN) control plane. The bandwidth can be dynamically allocated to the dedicated optical links on-demand according to the desired oversubscription (OV) and intra-/inter-cluster traffic matrix. Numerical investigations of the novel architecture under realistic traffic model indicate that dynamically allocating the TRXs and elastically controlling the WSS, a packet loss below 1E-5 and a server-to-server latency lower than 3 μs can be guaranteed for different traffic patterns at load of 0.4. With respect to the DCN with static interconnections, the average packet loss of ROTOS decreases two orders of magnitude and the average server-to-server latency performance improves by 21.5%. Scalability investigation to a large number of servers shows limited (11%) performance degradation as the network scale from 2560 to 40960 servers. Additionally, the dynamic bandwidth allocation of the DCN is experimentally validated. Network performance results show a packet loss of 0.05 and 5.85 μs end-to-end latency at the load of 0.8. Finally, investigations on the cost and power consumption confirm that the ROTOS DCN architecture has 28.4% lower cost and 35.0% better improvement for power efficiency with respect to the electrical switch based DCNs.

A lightweight load balancing and route minimizing solution for routing protocol for low-power and lossy networks

Routing Protocol for Low-Power and Lossy Networks (RPL) is considered as one of the essential information forwarding options for the Internet of Thing appliances, which possesses a flexible design. However, RPL suffers from the lack of an applicable load balancing mechanism in massive traffic scenarios. Uneven traffic distribution leads to congestion and deteriorates packet losses, delay periods, power consumption handling, and finally, reduces network lifetime. The present study proposed a scheme named “Lightweight Load Balancing and Route Minimizing solution for RPL” (L2RMR), compromising a novel Objective Function (OF) and a new routing metric based on the minimization of path routes. Also, a Probability Function was introduced, which prevents from creating the general Herd Decampment Phenomenon (HDP) problem. The proposed solution enables delayed parent joining for the nodes in order to achieve a lower rank instead of a greedy thundering, leading to multiple instabilities in the network topology. The present study evaluated L2RMR performance using the Contiki-Cooja simulator. To this end, L2RMR was examined under scenarios, including variable network sizes, transmission rates, and density. The simulation results revealed that this mechanism could enhance the average Packet Loss Ratio, End-to-End Delay, and energy consumption criteria in an environment incorporated with RPL and other comparative approaches.

Redundancy Gateway Menggunakan Metode Failover dan Load Sharing Gateway

Failure to transfer data packets on a network becomes a big threat, both caused by link failures and heavy traffic loads. To maintain stability in the network, the VRRP gateway redundancy protocol is applied. From the results of the research conducted, it takes an average time to failover for 3.75ms from the master router to the backup router and an average packet loss that occurs as many as 3 packets and the average time needed to failover from the backup router back to master router for 1.37ms and 1.5 packet loss occurred. The results of load sharing research are able to make 1 router device as a master router in 2 VRID at once. Implementing both Failover and Load Sharing methods can improve connectivity in the network by ensuring connectivity can run stably and equally. Failover is used as a backup gateway redundancy and load sharing is used to divide the gateway load equally.

VNE strategy based on chaos hybrid flower pollination algorithm considering multi-criteria decision making

With the development of science and technology and the need for multi-criteria decision making (MCDM), the optimization problem to be solved becomes extremely complex. The theoretically accurate and optimal solutions are often difficult to obtain. Therefore, meta-heuristic algorithms based on multi-point search have received extensive attention. The flower pollination algorithm (FPA) is a new swarm intelligence meta-heuristic algorithm, which can effectively control the balance between global search and local search through a handover probability, and gradually attracts the attention of researchers. However, the algorithm still has problems that are common to optimization algorithms. For example, the global search operation guided by the optimal solution is easy to lead the algorithm into local optimum, and the vector-guided search process is not suitable for solving some problems in discrete space. Moreover, the algorithm does not consider dynamic multi-criteria decision problems well. Aiming at these problems, the design strategy of hybrid flower pollination algorithm for virtual network embedding problem is discussed. Combining the advantages of the genetic algorithm and FPA, the algorithm is optimized for the characteristics of discrete optimization problems. The cross-operation is used to replace the cross-pollination operation to complete the global search and replace the mutation operation with self-pollination operation to enhance the ability of local search. Moreover, a life cycle mechanism is introduced as a complement to the traditional fitness-based selection strategy to avoid premature convergence. A chaos optimization strategy is introduced to replace the random sequence-guided crossover process to strengthen the global search capability and reduce the probability of producing invalid individuals. In addition, a two-layer BP neural network is introduced to replace the traditional objective function to strengthen the dynamic MCDM ability. Simulation results show that the proposed method has good performance in link load balancing, revenue???cost ratio, VN requests acceptance ratio, mapping average quotation, average time delay, average packet loss rate, and the average running time of the algorithm.

Enhanced Medium Access for Traffic Management in Smart-Cities’ Vehicular-Cloud

We propose an enhanced vehicular-cloud medium access control framework. The framework is utilizing the Long Term Evolution-Advanced (LTE-A) for better QoS and more reliable transportation telecommunication applications. It decreases the communication delay in real-time traffic applications while maintaining the highest network resource utilization. The objective of the proposed approach is to improve the connection quality between the vehicle and the base station (BS). The proposed approach integrates a Voice-Batch Markovian Arrival Process (V-BMAP) with IEEE 802.16 to analyze various reliability metrics, such as energy consumption, delay, throughput and the average packet loss. The archived results show that the proposed approach is superior in comparison to other potential alternatives in the literature.

SDN enabled flexible optical data center network with dynamic bandwidth allocation based on photonic integrated wavelength selective switch.

Optical switching techniques featuring the fast and large capacity have the potential to enable low latency and high throughput optical data center networks (DCN) to afford the rapid increasing of traffic-boosted applications. Flexibility of the DCN is of key importance to provide adaptive and dynamic bandwidth to handle the variable traffic patterns generated by the heterogeneous applications while optimizing the network resources. Aiming at providing the flexible bandwidth for optical DCNs, we propose and experimentally investigate a software-defined networking (SDN) enabled reconfigurable optical DCN architecture based on novel optical top of rack (OToR) switch exploiting photonic-integrated wavelength selective switch. Experimental results show that the optical bandwidth per link can be automatically reallocated under the management of the deployed SDN control plane according to the variable traffic patterns. With respect to the network with inflexible interconnections, the average packet loss of the reconfigurable DCN decreases 1 order of magnitude and the server-to-server latency performance improves of 42.2%. Scalability investigation illustrates limited (11.7%) performance degradation as the reconfigurable network scale from 2560 to 40960 servers. Both the numerical and experimental assessments validate the proposed DCN with reconfigurable bandwidth feature and lower latency variations with respect to the inflexible DCNs.

Server Room Temperature and Monitoring System Using Fuzzy Based on RobotDyn Microcontroller

Server role becomes very important to provide service to clients. Therefore the performance of the server needs to be maintained. The performance of the server is not only influenced by the technology of the hardware but also influenced by server room ideal temperature and humidity condition. Monitoring and adjusting temperature condition is not possible to be done continuously manually because of limited human resources. One of the solutions is using a system based on the Internet of Things (IoT). This research proposed a prototype of server room temperature and humidity real-time monitoring system using RobotDyn ATmega+ESP8266 microcontroller and the Blynk IoT platform. The prototype also can maintain the temperature of server room on ideal condition by controlling Air Conditioner using Fuzzy logic Mamdani Method and infrared communication. The result of this research a prototype that can read temperature and humidity of server room accurately realtive error for temperature is 0,81% and relative error for humidity is 4,52%. Quality of Service for data transmission from prototype to Blynk Platform is very good, with average delay 127.54ms, average packet loss ratio 0.54%, average packet delivery ratio 99.46%, and average throughput 10.5 kbps. Control System that built using fuzzy logic Mamdani Method can automatically control the value of Air Conditioner temperature output that adjust the condition of server room with maximum range for control Air Conditioner is 4 meters and 45° from Air Conditioner’s transmitter

Peer to Peer Communication in GUI interface using Lora Technology

Abstract Long Range module (Sx1278) is a very popular chip widely used in IOT because of its low power consumption with long range (with almost 1Km in urban areas) to send data in the form of small chunk of packets based on wide area radio technology as it just broadcast the messages similar to radio transmission broadcast. It’s most popular application in almost all sectors of industry ranging from smart cities, smart agriculture, smart healthcare and many more. But the main problem with Lora Technology is that the average packet loss while sending the data is almost 50%, i.e. there is 0.5 probability that packet will not be received at the receiving end. To increase reliability and security of the data we are sending, we have proposed a basic logic to make sending-receiving of packets more reliable using the concept of serialization of packets and securing them (using AES algorithm) implemented using GUI interface (chat app) using python3.

Enhancing the Quality of Service of Cloud Computing in Big Data using Virtual Private Network and Firewall in Dense Mode

Cloud Computing entails accessing and storing programs and data over the internet instead of the hard drive of a personal computer. Over the Internet, it is the practice of software and hardware to pass a service. Cloud gives the ability to consumers to access big data and use applications from every device that can have access to the internet, however, the key problem is security and this can be solvable by a firewall and Virtual Private Network. Recently, research has been accomplished in deploying firewalls and Virtual Private Networks with parameters of throughput and load in sparse mode. In this paper, an examination of firewall and Virtual Private Network is considered based on average throughput, average packet loss and average end-to-end delay in dense mode. To examine the performance of cloud computing without Firewall and Virtual Private Network, with firewall only, and with firewall and Virtual Private Network is the research goal. The simulation results have shown that Firewall and Virtual Private Network offers better security through a wide investigation with slight distress in the cloud performance.

Towards Industrial Ultra-Wideband Networks: Experiments for Machine Vibration Monitoring

We discuss the potential of ultra-wideband (UWB) technology for realizing use cases in industry 4.0 and demonstrate the implementation of an UWB sensor network with off-the-shelf transceivers for machine vibration monitoring. We propose a flexible medium access layer tailored for industrial sensing and show how the choice of its parameters is affected by the propagation environment and hardware constraints. Our real-world experiments reveal that links up to 20 meters can be achieved in industrial environments with an average packet loss rate in the order of 10 -6 for typical links. A comparison with a commercial vibration monitoring system based on IEEE 802.15.4 spread spectrum shows that UWB attains a twenty-times higher throughput for similar link ranges.

Data Collection Algorithm of a 3D Wireless Sensor Network That Weighs Node Coverage Rate and Lifetime

Considering the movement of a sink node in this study to solve the data transmission problem of sensor nodes in a 3D network environment, we propose a Data Collection Algorithm of a 3D wireless sensor network (DCA_3D) that weighs node coverage rate and lifetime. DCA_3D establishes a data collection optimization model that weighs node coverage rate and lifetime with the constraints of the sink node’s moving path selection, data flow, energy consumption, and link transmission. Subsequently, DCA_3D calculates the fitness value of the sink node’s moving path by solving the data collection optimization model with the known sink node’s moving path. Then it uses a modified artificial bee colony algorithm to solve the moving path selection problem of the sink node, and finally obtains the optimal scheme. In the scheme, sink node can find the optimal moving path, whereas the sensor node can find the optimal data communication path. The simulation results show that regardless of the moving path length of the sink node, the maximum data collection hops of the sink node and the number of static sensor nodes change, DCA_3D can find the optimal moving path of the sink node. It can improve the coverage rate of the sensor nodes, the network lifetime and average data transmission amount, and reduce the average energy consumption variance and the average packet loss rate. DCA_3D outperforms the state-of-arts such as RAND, GREED, EDG_3D, and ANT.

A Hybrid Downlink Scheduling Approach for Multi-Traffic Classes in LTE Wireless Systems

The developments in wireless technology and applications in recent years have increased the interest in downlink scheduling and resource allocations among researchers. Moreover, fair scheduling and balanced Quality of Service (QoS) delivery for various forms of traffic are needed for Long-Term Evolution (LTE) wireless systems. This paper proposes hybrid QoS-aware downlink scheduling approaches that aim to address different traffic classes and balance the QoS delivery with improvements to the overall system performance under channel and bandwidth constraints. Moreover, this research introduces a taxonomy that classifies the scheduling algorithms into four main classes: delay aware, queue aware, target bit-rate aware and hybrid aware. The latter class is the scheduling class that is proposed in this paper; it considers channel, queue and delay parameters in its scheduling metric. Using simulations, we compare and analyze different downlink scheduling rules for their network-centric performance metrics, e.g., average packet loss ratio, average throughput, average packet delay, system fairness, and system spectral efficiency. The simulation results show that the queue-aware and delay-aware scheduling rules deliver the best QoS performance for video traffic classes, whereas our proposed hybrid scheduling rules deliver balanced QoS for various types of traffic classes. Employing QoS balancing scheduling rules in an LTE downlink is suggested to provide high QoS delivery for different traffic classes.

A Reliable Communication and Load Balancing Scheme for Resource-Limited Networks

Sensor-cloud infrastructure provides a storage platform for the massive sensed data, that is flexible and re-configurable, for various application areas which are monitored through the resource-limited networks such as wireless sensor networks (WSNs), ad hoc networks, and Internet of things (IoT). Due to their overwhelming characteristics, these networks are used in different application areas to assist human beings in their daily-life activities. However, these networks have different challenging issues such as reliability in communication and processing, storage of the massive data, efficient utilization of on-board battery, maximum lifetime achievement, minimum possible average packet loss ratio, and reliable routing mechanisms. Although various communication and load balancing mechanisms have been proposed in the literature to resolve this issue, however, these schemes are either application specific or overlay complex. In this paper, a reliable communication and load balancing scheme for the resource-limited networks is presented to resolve these issues, particularly with available resources. To achieve these goals, the proposed scheme bounds every sensing device $C_{i}$ to compute the transmission capabilities of its neighboring devices that is residual energy $E_{r}$ , hop count $H_{c}$ , round trip time ( $RTT_{i}$ ), and processing cost. Initially, to guarantee reliable wireless communication, a source device prefers a neighboring device $C_{i}$ with minimum $H_{c}$ value over those having maximum $H_{c}$ values. Moreover, this scheme bounds every device $C_{i}$ to find four shortest & reliable paths and forward maximum packets on two of these paths preferably on the most reliable and optimal route. Therefore, unlike the traditional shortest path scheme, devices $C_{i}$ reside on these paths do not deplete their on-board battery more rapidly than others. To further improve the reliability of the proposed scheme, the assigned weight-age factors are fine-tuned if one or two of the neighboring devices $C_{i}$ consume 80% of their on-board battery, that is now maximum weight-age is assigned to the residual energy $E_{r}$ and minimum to $H_{c}$ value respectively. Simulation results show the exceptional performance of the proposed reliable communication and load balancing scheme against the field-proven schemes in terms of average packet delivery ratio, average throughput, end-to-end delay, and overall network lifetime.

Deep Q-Learning for Routing Schemes in SDN-Based Data Center Networks

In order to adapt to the rapid development of cloud computing, big data, and other technologies, the combination of data center networks and SDN is proposed to make network management more convenient and flexible. With this advantage, routing strategies have been extensively studied by researchers. However, the strategies in the controller mainly rely on manual design, the optimal solutions are difficult to be obtained in the dynamic network environment. So the strategies based on artificial intelligence (AI) are being considered. This paper proposes a novel routing strategy based on deep Q-learning (DQL) to generate optimal routing paths autonomously for SDN-based data center networks. To satisfy the different demands of mice-flows and elephant-flows in data center networks, deep Q networks are trained for them respectively to achieve low latency and low packet loss rate for mice-flows as well as high throughput and low packet loss rate for elephant-flows. Furthermore, with the consideration of the distribution of traffic and the limited resources of data center networks and SDN, we choose port rate and flow table utilization to describe the network state. Simulation results show that compared with Equal-Cost Multipath (ECMP) routing and Selective Randomized Load Balancing (SRL)+FlowFit, the proposed routing scheme can reduce both the average delay of mice-flows and average packet loss rate, while increase the average throughput of elephant-flows.

Modeling and parameter optimization of statistical priority-based multiple access protocol

The Statistical Priority-based Multiple Access Protocol (SPMA) is the de facto standard for Tactical Target Network Technology (TTNT) and has also been implemented in ad hoc networks. In this paper, we present a non-preemptive M/M/1/K queuing model to analyze the performance of different priorities in SPMA in terms of average packet loss rate and delay. And based on this queuing model, we designed a percentile scoring system combined with Q-learning algorithm to optimize the protocol parameters. The simulation results show that our theoretical model is closely matched with the reality, and the proposed algorithm improves the efficiency and accuracy in finding the optimal parameter set of SPMA protocol.

Hybrid Model based on Peltier and Piezoelectric Human Energy Harvesting for WBAN Application

Wireless body area network (WBAN) is developed as a result of Wireless personal area network (WPAN), in which various interconnected Body Node (BN) communicates near and around human body. There are many differences between the WBAN and WPAN i.e distribution, density and mobility. Due to redundant nodes, BN in WBAN are less dense. In WBAN, Body node are implanted inside and on human body to measure physiological signals using different sensors i.e Electro cardio graph (ECG), electroencephalogram (EEG), Blood pressure, temperature etc) of body which collects data and send it to sink node. Earlier researchers have used either piezoelectric harvester, solar or temperature gradient based. But in this paper optimization technique using combination of Peltier and Piezoelectric human energy harvesting is studied. By developing an algorithm, extensive simulation can be performed considering four human body gestures (relaxing, walking, running and fast running). Overall Quality of Service (QoS) including average (packet loss, end-to-end delay, throughput) and overall detection efficiency is studied.

Machine Learning Aided Load Balance Routing Scheme Considering Queue Utilization

Due to the rapid development of network techniques, packet-switched systems experience high-speed growth of traffic, which imposes a heavy and unbalanced burden on the routers. Hence, efficient routing schemes are required in order to achieve load balance. By decoupling the control plane and the data plane, Software-Defined Network (SDN) shows its flexibility and extensibility to achieve the automatic management of network resources. Based on the SDN architecture, we propose a pair of machine learning aided load balance routing schemes considering the queue utilization (QU), which divide the routing process into three steps, namely the dimension reduction, the QU prediction, as well as the load balance routing. To the best of our knowledge, it is the first time that principal component analysis (PCA) is used for the dimension reduction of the substrate network. Furthermore, QU prediction is conducted with the aid of neural network algorithms for the sake of coping with the network congestion resulting from burst traffic. Finally, simulation results show that our proposed routing schemes considering QU predicted by the machine learning algorithms outperform the traditional Bellman–Ford (BF) routing strategy in terms of the average packet loss ratio, the worst throughput and the average delay.

Randomized Link Repair Reactive Routing Protocol for Vehicular Ad Hoc Network

Background and Objective: Vehicular Ad hoc Network (VANET) now-a-days is popular research area due to numerous challenges such as congestion control, network management, and security issues. Methods: VANET is a subtype of Mobile Ad hoc Network (MANET), therefore, allows a vehicle to exchange information with neighboring vehicles and with roadside infrastructure units. High mobility of vehicles results to frequent link breakages. The existing VANET routing protocols follow a trivial link repair mechanism. Therefore, there is a need to compute stable and reliable routes for vehicular communication as well as frequently repair the broken links. Ad hoc On-demand Distance Vector (AODV) routing protocol is a reactive routing protocol which is suitable for very dynamic environment such as VANET. In this paper, an improved Randomized Link Repair based AODV (RLRAODV) routing protocol is proposed which uses the multiple route reply packets for data transmission through alternate paths during link failure. The proposed methodology also reduces the network congestion overhead generated due to broadcasting of route request packets. Results and Conclusion: The simulation analysis shows that RLR-AODV gives better performance with respect to performance parameters such as average end-to-end delay, average packet delivery ratio, and average packet loss ratio as compared to AODV and AOMDV.

ANALISIS CAKUPAN LAYANAN WI-FI GEDUNG PASCASARJANA UNIVERSITAS UDAYANA

The main changes in the telecommunication during these present days come mainly from wired technology to wireless technology. The Wireless LAN (WLAN) configuration consists of an access point, connected to users using air medium. The postgraduate building of Universitas Udayana has been equipped with a wireless network, supporting the study activities within the building. This research explains regarding the signal level quality and the Quality of Service (QoS) by analyzing the Wi-Fi coverage. The measurements were divided into two models, with and without barriers. The highest result comes to -42 dBm, conversely, the lowest is -82 dBm. Thus, the results show that the throughput value is 3.97 Mbps. Within the maximum bandwidth of 10 Mbps, the average packet-loss is not more than 3%. The delay measurement provides a result of not more than 100 ms, and the jitter obtained is 0.04. According to the digital floor plan, the calculation results of the coverage area match the signal level measurement.