scholarly journals QoS Aware and Fault Tolerance Based Software-Defined Vehicular Networks Using Cloud-Fog Computing

Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 401
Author(s):  
Sidra Abid Syed ◽  
Munaf Rashid ◽  
Samreen Hussain ◽  
Fahad Azim ◽  
Hira Zahid ◽  
...  
Keyword(s):  
Fault Tolerance ◽  
Response Time ◽  
Communication Systems ◽  
Vehicular Networks ◽  
Heuristic Algorithms ◽  
Fog Computing ◽  
Research Work ◽  
Tolerance Mechanism ◽  
Proposed Model ◽  
Sdn Controller

Software-defined network (SDN) and vehicular ad-hoc network (VANET) combined provided a software-defined vehicular network (SDVN). To increase the quality of service (QoS) of vehicle communication and to make the overall process efficient, researchers are working on VANET communication systems. Current research work has made many strides, but due to the following limitations, it needs further investigation and research: Cloud computing is used for messages/tasks execution instead of fog computing, which increases response time. Furthermore, a fault tolerance mechanism is used to reduce the tasks/messages failure ratio. We proposed QoS aware and fault tolerance-based software-defined V vehicular networks using Cloud-fog computing (QAFT-SDVN) to address the above issues. We provided heuristic algorithms to solve the above limitations. The proposed model gets vehicle messages through SDN nodes which are placed on fog nodes. SDN controllers receive messages from nearby SDN units and prioritize the messages in two different ways. One is the message nature way, while the other one is deadline and size way of messages prioritization. SDN controller categorized in safety and non-safety messages and forward to the destination. After sending messages to their destination, we check their acknowledgment; if the destination receives the messages, then no action is taken; otherwise, we use a fault tolerance mechanism. We send the messages again. The proposed model is implemented in CloudSIm and iFogSim, and compared with the latest models. The results show that our proposed model decreased response time by 50% of the safety and non-safety messages by using fog nodes for the SDN controller. Furthermore, we reduced the execution time of the safety and non-safety messages by up to 4%. Similarly, compared with the latest model, we reduced the task failure ratio by 20%, 15%, 23.3%, and 22.5%.

scholarly journals Architecture Design of Aviation Fault-tolerant Computer Based on ARINC659 Bus Technology

2018 ◽  
Vol 179 ◽  
pp. 03025
Author(s):  
Gang An ◽  
Yu Li ◽  
Xin Li
Keyword(s):  
Fault Tolerance ◽  
Computer Architecture ◽  
Computer System ◽  
Communication Systems ◽  
Fault Tolerant ◽  
High Reliability ◽  
Architecture Design ◽  
Tolerance Mechanism ◽  
Computer Communication ◽  
Computer Based

The ARINC659 backplane bus is suitable for high safety and high reliability requirements of aircraft on-board computer communication systems. This paper analyzes the structure of ARINC 659 serial backplane bus and the bus fault tolerance mechanism. On the basis of backplane bus, a 4 degree of aviation fault-tolerant computer is designed. Moreover, the computer architecture and computer system of the instruction branch and monitoring branch are designed in the computer channel. The fault-tolerant management of the computer is realized by bus fault tolerance, redundancy voting between computers and the monitoring of the instruction and monitoring branches.

scholarly journals Generic Controller Adaptive Load Balancing (GCALB) for SDN Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Wael Hosny Fouad Aly
Keyword(s):  
Fault Tolerance ◽  
Load Balancing ◽  
Response Time ◽  
Fault Tolerant ◽  
High Reliability ◽  
Tolerance Mechanisms ◽  
New Era ◽  
Proposed Model ◽  
New Strategies

Fault tolerance is an important aspect of network resilience. Fault-tolerance mechanisms are required to ensure high availability and high reliability in different environments. The beginning of software-defined networking (SDN) has both presented new challenges and opened a new era to develop new strategies, standards, and architectures to support fault tolerance. In this paper, a study of fault tolerance is performed for two architectures: (1) a single master with multiple slave controllers and (2) multiple slave controllers. The proposed model is called a Generic Controller Adaptive Load Balancing (GCALB) model for SDNs. GCALB adapts the load among slave controllers based on a GCALB algorithm. Mininet simulation tool is utilized for the experimentation phase. Controllers are implemented using floodlights. Experiment results were conducted using GCALB when master controller is taking the responsibility of distributing switches among four and five slave controllers as a case study. Throughput and response time metrics are used to measure performance. GCALB is compared with two reference algorithms: (1) HyperFlow (Kreutz et al., 2012), and (2) Enhanced Controller Fault Tolerant (ECFT) (Aly and Al-anazi, 2018). Results are promising as the performance of GCALB increased by 15% and 12% when compared to HyperFlow and by 13% and 10% when compared to ECFT in terms of throughput and response time.

scholarly journals V2V Communication using fog Computing for Safe Commute

2020 ◽  
Vol 9 (2) ◽  
pp. 581-585
Keyword(s):  
Cloud Computing ◽  
Communication Systems ◽  
Vehicular Networks ◽  
Fog Computing ◽  
Traffic Monitoring ◽  
Distributed Network ◽  
Safety Measures ◽  
Idle State ◽  
V2v Communication ◽  
Communication Capability

In this real-world, there is a great necessity to satisfy the demands in all the communication systems to experience the best ever convenience and flexibility. Advancement in the IoT concept in the form of IoV has been a solution to overcome all the difficulties experienced during driving vehicles. The complete potential of IoV addresses many challenges of traffic monitoring and road safety measures by forming a distributed network of vehicles and collaborate between heterogeneous vehicular systems. IoV refers to the integration of networks that transmit information periodically between vehicles to vehicles, vehicles to roadside units and it is intended to play an essential role in this. The prevailing solutions like VANET, Vehicular Cloud Computing (VFC), and Mobile Cloud Computing are not ideal as there is high latency and delay in responsiveness. The collaboration of vehicular networks and fog computing forms a promising paradigm called Vehicular Fog Computing (VFC) which serves as a effective yet alternative method for VANETS’s. This paradigm consists of multiple near-end devices to carry out communication and computation of every vehicle. This paper presents certain scenarios of moving and idle state of vehicles by adapting VFC methods, wherein as a result of this communication and computation infrastructure, it showcases the capabilities of VFC. The objective here is to present four different scenarios of a vehicle in motion and in idle state, which brings out an interesting relationship between the communication capability and connectivity of the vehicles.

scholarly journals A proposed model for frequency tuned antennas used in mobile communication systems

2021 ◽  
Vol 11 (2) ◽  
pp. 1367
Author(s):  
Amin H. Al Ka'bi ◽  
Magid M. Rady
Keyword(s):  
Resonant Frequency ◽  
Mobile Devices ◽  
Communication Systems ◽  
Research Work ◽  
Electromagnetic Properties ◽  
Wireless Communication Systems ◽  
Significant Shift ◽  
Ferrite Material ◽  
Proposed Model ◽  
Wide Range

The antenna is considered as one of the most fundamental elements in wireless communication systems, especially in mobile devices. Desirable specifications of antennas include covering wide range of operating frequencies, while maintaining high quality of system performance over the whole range of operating frequencies. Therefore, the ability of tuning the resonant frequency of the antenna without altering its physical dimensions would be highly recommended in up-and-coming designs of antennas in mobile devices. This research work proposes a model for tuning the operating frequency of the inverted F-antenna over a reasonably wide range of frequencies, via altering the electromagnetic properties of its ferrite material. In this proposed model, it will be shown that the electronic control of the permeability of the ferrite material of the antenna leads effectively to a significant shift in its resonant frequency, and hence to an overall improvement in the performance of the communication system.

scholarly journals Fault Tolerance Mechanism for Internet of Things (IoT) by Solving Nature Inspired Computing Algorithm (NIC)

2021 ◽  
Vol 9 (2) ◽  
pp. 308-312
Author(s):  
A. Prasanth Rao, Et. al.
Keyword(s):  
Genetic Algorithm ◽  
Fault Tolerance ◽  
Internet Of Things ◽  
Research Work ◽  
Cluster Head ◽  
Life Time ◽  
Base Station ◽  
Sensor Nodes ◽  
Tolerance Mechanism ◽  
Network Efficiency

In clustering approach the sensor nodes are grouped to form a cluster. The nodes of a clustering network have low powered battery capability and limited processing capabilities. These nodes continuously exchange the data to cluster head which is in turn transforming the data to its base station. Few of these nodes in network may be faulty or may not support life time processing data due to its low power battery. All these sensor nodes measure the temperature, humidity, sound and pollution from environment and collected data is send to cloud for further processing. The fault tolerance mechanism of these nodes is solved by applying genetic algorithm by implementing chromosome technique to identify and avoid fault nodes in the network.  This proposed research work increases detection of fault nodes in a network, increase network efficiency, lifetime and reach energy optimization results in Internet of Things (IoT) concept. The performance evaluation shows that the data accuracy in Genetic Algorithm (GA) is higher when compared with Direct Diffusion (DD) Algorithm and Ad-hoc on demand Distance Vector (AODV) Algorithm.

Simulation and Emulation Tools for Fog Computing

2020 ◽  
Vol 13 ◽  
Author(s):  
Simar Preet Singh ◽  
Rajesh Kumar ◽  
Anju Sharma ◽  
S. Raji Reddy ◽  
Priyanka Vashisht
Keyword(s):  
Quality Of Service ◽  
Programming Languages ◽  
Traffic Management ◽  
Fog Computing ◽  
Research Work ◽  
Research Experience ◽  
Computing Paradigm ◽  
Quality Of Service Parameters ◽  
User Friendly

Background: Fog computing paradigm has recently emerged and gained higher attention in present era of Internet of Things. The growth of large number of devices all around, leads to the situation of flow of packets everywhere on the Internet. To overcome this situation and to provide computations at network edge, fog computing is the need of present time that enhances traffic management and avoids critical situations of jam, congestion etc. Methods: For research purposes, there are many methods to implement the scenarios of fog computing i.e. real-time implementation, implementation using emulators, implementation using simulators etc. The present study aims to describe the various simulation and emulation tools for implementing fog computing scenarios. Results: Review shows that iFogSim is the simulator that most of the researchers use in their research work. Among emulators, EmuFog is being used at higher pace than other available emulators. This might be due to ease of implementation and user-friendly nature of these tools and language these tools are based upon. The use of such tools enhance better research experience and leads to improved quality of service parameters (like bandwidth, network, security etc.). Conclusion: There are many fog computing simulators/emulators based on many different platforms that uses different programming languages. The paper concludes that the two main simulation and emulation tools in the area of fog computing are iFogSim and EmuFog. Accessibility of these simulation/emulation tools enhance better research experience and leads to improved quality of service parameters along with the ease of their usage.

Multi Disease-Prediction Framework Using Hybrid Deep Learning: An Optimal Prediction Model (Preprint)

2020 ◽  
Author(s):  
Anusha Ampavathi ◽  
Vijaya Saradhi T
Keyword(s):  
Feature Extraction ◽  
Big Data ◽  
Deep Learning ◽  
Weight Function ◽  
Optimization Algorithm ◽  
Large Scale ◽  
Heuristic Algorithms ◽  
Disease Prediction ◽  
Health Care Decisions ◽  
Proposed Model

UNSTRUCTURED Big data and its approaches are generally helpful for healthcare and biomedical sectors for predicting the disease. For trivial symptoms, the difficulty is to meet the doctors at any time in the hospital. Thus, big data provides essential data regarding the diseases on the basis of the patient’s symptoms. For several medical organizations, disease prediction is important for making the best feasible health care decisions. Conversely, the conventional medical care model offers input as structured that requires more accurate and consistent prediction. This paper is planned to develop the multi-disease prediction using the improvised deep learning concept. Here, the different datasets pertain to “Diabetes, Hepatitis, lung cancer, liver tumor, heart disease, Parkinson’s disease, and Alzheimer’s disease”, from the benchmark UCI repository is gathered for conducting the experiment. The proposed model involves three phases (a) Data normalization (b) Weighted normalized feature extraction, and (c) prediction. Initially, the dataset is normalized in order to make the attribute's range at a certain level. Further, weighted feature extraction is performed, in which a weight function is multiplied with each attribute value for making large scale deviation. Here, the weight function is optimized using the combination of two meta-heuristic algorithms termed as Jaya Algorithm-based Multi-Verse Optimization algorithm (JA-MVO). The optimally extracted features are subjected to the hybrid deep learning algorithms like “Deep Belief Network (DBN) and Recurrent Neural Network (RNN)”. As a modification to hybrid deep learning architecture, the weight of both DBN and RNN is optimized using the same hybrid optimization algorithm. Further, the comparative evaluation of the proposed prediction over the existing models certifies its effectiveness through various performance measures.

scholarly journals Full snapshot reconstruction in hybrid architecture antenna arrays

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Maria Trigka ◽  
Christos Mavrokefalidis ◽  
Kostas Berberidis
Keyword(s):  
Antenna Array ◽  
Antenna Arrays ◽  
Communication Systems ◽  
Linear Array ◽  
Research Work ◽  
Hybrid Architecture ◽  
Angle Of Arrival ◽  
Music Algorithm ◽  
Array Structures ◽  
Signal Sources

AbstractIn the context of this research work, we study the so-called problem of full snapshot reconstruction in hybrid antenna array structures that are utilized in mmWave communication systems. It enables the recovery of the snapshots that would have been obtained if a conventional (non-hybrid) uniform linear antenna array was employed. The problem is considered at the receiver side where the hybrid architecture exploits in a novel way the antenna elements of a uniform linear array. To this end, the recommended scheme is properly designed so as to be applicable to overlapping and non-overlapping architectures. Moreover, the full snapshot recoverability is addressed for two cases, namely for time-varying and constant signal sources. Simulation results are also presented to illustrate the consistency between the theoretically predicted behaviors and the simulated results, and the performance of the proposed scheme in terms angle-of-arrival estimation, when compared to the conventional MUSIC algorithm and a recently proposed hybrid version of MUSIC (H-MUSIC).

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