905 research outputs found
Fuzzy Fractional-Order PID Congestion Control Based on African Buffalo Optimization in Computer Networks
Congestion is the primary factor that slows down data transfer in communication networks. Transmission Control Protocol and Active Queue Management (TCP/AQM) collaborated to resolve this issue. The fuzzy-Fractional-Order-PID (FFOPID) controller is developed in this paper to control the linearized TCP/AQM model. The strategy is founded on a combination of fractional-order PID and fuzzy logic controllers. The primary objective of the proposed controller is to maintain the queue length of the router within the appropriate queue threshold for a congestion model. The control parameters are tuned using African Buffalo optimisation (ABO). The suggested controller is compared to other controllers (PID, Fuzzy-PID, and Fractional-order PID) to demonstrate the controller's efficiency, and all of these controllers are optimised using African Buffalo Optimisation (ABO). In MATLAB (R2017b), the simulation of the linearized model is introduced. Comparing the results of the Fuzzy-Fractional-Order-PID controller with those of other controllers in the same network scenarios reveals that the Fuzzy-FOPID is robust for a wide variety of TCP flows
Open FPGA-based development platform for fuzzy systems with applications to communications
Soft computing techniques are gaining momentum as tools
for network traffic modeling, analysis and control. Efficient
hardware implementations of these techniques that can
achieve real-time operation in high-speed communications
equipment is however an open problem. This paper describes
a platform for the development of fuzzy systems with applications
to communications systems, namely network traffic
analysis and control. An FPGA development board with PCI
interface is employed to support an open platform that comprises
open CAD tools as well as IP cores. For the development
process, we set up a methodology and a CAD tools
chain that cover from initial specification in a high-level language
to implementation on FPGA devices. PCI compatible
fuzzy inference modules are implemented as SoPC based on
the open WISHBONE interconnection architecture. We outline
results from the design and implementation of fuzzy analyzers
and regulators for network traffic. These systems are
shown to satisfy operational and architectural requirements
of current and future high-performance routing equipment.Ministerio de Educación y Ciencia TEC2005-04359/MICJunta de Andalucía TIC2006-63
Simulation Model of Enhancing Performance of TCP/AQM Networks by Using Matlab
Internet networks are becoming more crowded every day due to the rapid development of modern life, which causes an increase in the demand for data circulating on the Internet. This creates several problems, such as buffer overflow of intermediate routers, and packet loss and time delay in packet delivery. The solution to these problems is to use a TCP/AQM system. The simulation results showed that there were differences in performance between the different controllers used. The proposed methods were simulated along with the required conditions in nonlinear systems to determine the best performance. It was found that the use of optimization Department of Electro-mechanical Engineering, University of Technology - Iraq tools (GA, FL) with a controller could achieve the best performance. The simulation results demonstrated the ability of the proposed methods to control the behavior of the system. The controller systems were simulated using Matlab/Simulink. The simulation results showed that the performance was better with the use of GA-PIDC compared to both FL-PIDC and PIDC in terms of stability time, height, and overrun ratio for a network with a variable queue that was targeted for comparison. The results were: the bypass ratio was 0, 3.3 and 21.8 the settling time was 0.002, 0.055, and 0.135; and the rise time was 0.001, 0.004 and 0.008 for GA-PIDC, FL-PIDC and PIDC, respectively. These results made it possible to compare the three control techniques
Simulation Model of Enhancing Performance of TCP/AQM Networks by Using Matlab
Internet networks are becoming more crowded every day due to the rapid development of modern life, which causes an increase in the demand for data circulating on the Internet. This creates several problems, such as buffer overflow of intermediate routers, and packet loss and time delay in packet delivery. The solution to these problems is to use a TCP/AQM system. The simulation results showed that there were differences in performance between the different controllers used. The proposed methods were simulated along with the required conditions in nonlinear systems to determine the best performance. It was found that the use of optimization Department of Electro-mechanical Engineering, University of Technology - Iraq tools (GA, FL) with a controller could achieve the best performance. The simulation results demonstrated the ability of the proposed methods to control the behavior of the system. The controller systems were simulated using Matlab/Simulink. The simulation results showed that the performance was better with the use of GA-PIDC compared to both FL-PIDC and PIDC in terms of stability time, height, and overrun ratio for a network with a variable queue that was targeted for comparison. The results were: the bypass ratio was 0, 3.3 and 21.8 the settling time was 0.002, 0.055, and 0.135; and the rise time was 0.001, 0.004 and 0.008 for GA-PIDC, FL-PIDC and PIDC, respectively. These results made it possible to compare the three control techniques
Proportional-integral genetic algorithm controller for stability of TCP network
The life development and increase the number of internet users imposed an increase in data circulating on the internet network and then make the network more congestion. As a result of all this, some problems arose such as time delay in packets delivery, loss of packets, and exceed the buffer capacity for the middle routers. To overcome those problems, transmission control protocol and active queue management (TCP/AQM) have been used. AQM is the main approach used to control congestion and overcome those problems to improve network performance. This work proposes to use the proportional-integral (PI) controller with a genetic algorithm (GA) as an active queue manager for routers of the Internet. The simulation results show a good performance for managing the congestion with using proportional-integral genetic algorithm (GA-PI) controller better than the PI controller
Resource Management Techniques in Cloud-Fog for IoT and Mobile Crowdsensing Environments
The unpredictable and huge data generation nowadays by smart devices from IoT and mobile Crowd Sensing applications like (Sensors, smartphones, Wi-Fi routers) need processing power and storage. Cloud provides these capabilities to serve organizations and customers, but when using cloud appear some limitations, the most important of these limitations are Resource Allocation and Task Scheduling. The resource allocation process is a mechanism that ensures allocation virtual machine when there are multiple applications that require various resources such as CPU and I/O memory. Whereas scheduling is the process of determining the sequence in which these tasks come and depart the resources in order to maximize efficiency. In this paper we tried to highlight the most relevant difficulties that cloud computing is now facing. We presented a comprehensive review of resource allocation and scheduling techniques to overcome these limitations. Finally, the previous techniques and strategies for allocation and scheduling have been compared in a table with their drawbacks
Resource Management Techniques in Cloud-Fog for IoT and Mobile Crowdsensing Environments
The unpredictable and huge data generation nowadays by smart devices from IoT and mobile Crowd Sensing applications like (Sensors, smartphones, Wi-Fi routers) need processing power and storage. Cloud provides these capabilities to serve organizations and customers, but when using cloud appear some limitations, the most important of these limitations are Resource Allocation and Task Scheduling. The resource allocation process is a mechanism that ensures allocation virtual machine when there are multiple applications that require various resources such as CPU and I/O memory. Whereas scheduling is the process of determining the sequence in which these tasks come and depart the resources in order to maximize efficiency. In this paper we tried to highlight the most relevant difficulties that cloud computing is now facing. We presented a comprehensive review of resource allocation and scheduling techniques to overcome these limitations. Finally, the previous techniques and strategies for allocation and scheduling have been compared in a table with their drawbacks
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Intelligent based Packet Scheduling Scheme using Internet Protocol/Multi-Protocol Label Switching (IP/MPLS) Technology for 5G. Design and Investigation of Bandwidth Management Technique for Service-Aware Traffic Engineering using Internet Protocol/Multi-Protocol Label Switching (IP/MPLS) for 5G
Multi-Protocol Label Switching (MPLS) makes use of traffic engineering (TE)
techniques and a variety of protocols to establish pre-determined highly
efficient routes in Wide Area Network (WAN). Unlike IP networks in which
routing decision has to be made through header analysis on a hop-by-hop
basis, MPLS makes use of a short bit sequence that indicates the forwarding
equivalence class (FEC) of a packet and utilises a predefined routing table to
handle packets of a specific FEC type. Thus header analysis of packets is not
required, resulting in lower latency. In addition, packets of similar
characteristics can be routed in a consistent manner. For example, packets
carrying real-time information can be routed to low latency paths across the
networks. Thus the key success to MPLS is to efficiently control and distribute
the bandwidth available between applications across the networks.
A lot of research effort on bandwidth management in MPLS networks has
already been devoted in the past. However, with the imminent roll out of 5G,
MPLS is seen as a key technology for mobile backhaul. To cope with the 5G
demands of rich, context aware and multimedia-based user applications, more
efficient bandwidth management solutions need to be derived.
This thesis focuses on the design of bandwidth management algorithms, more
specifically QoS scheduling, in MPLS network for 5G mobile backhaul. The
aim is to ensure the reliability and the speed of packet transfer across the
network. As 5G is expected to greatly improve the user experience with
innovative and high quality services, users’ perceived quality of service (QoS)
needs to be taken into account when deriving such bandwidth management
solutions. QoS expectation from users are often subjective and vague. Thus
this thesis proposes the use of fuzzy logic based solution to provide service aware and user-centric bandwidth management in order to satisfy
requirements imposed by the network and users.
Unfortunately, the disadvantage of fuzzy logic is scalability since dependable
fuzzy rules and membership functions increase when the complexity of being
modelled increases. To resolve this issue, this thesis proposes the use of neuro-fuzzy to solicit interpretable IF-THEN rules.The algorithms are
implemented and tested through NS2 and Matlab simulations. The
performance of the algorithms are evaluated and compared with other
conventional algorithms in terms of average throughput, delay, reliability, cost,
packet loss ratio, and utilization rate.
Simulation results show that the neuro-fuzzy based algorithm perform better
than fuzzy and other conventional packet scheduling algorithms using IP and
IP over MPLS technologies.Tertiary Education Trust Fund (TETFUND
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