Performance Analysis of Content-Centric Networking on an Arbitrary Network Topology

2018 ◽  
Vol E101.B (1) ◽  
pp. 24-34 ◽  
Author(s):  
Ryo NAKAMURA ◽  
Hiroyuki OHSAKI
Keyword(s):  
Performance Analysis ◽  
Network Topology ◽  
Content Centric Networking

Performance analysis of a novel 5G architecture via Content-Centric Networking

2017 ◽  
Vol 25 ◽  
pp. 328-331 ◽  
Author(s):  
Zhuo Li ◽  
Yankai Liu ◽  
Yutong Chen ◽  
Yaping Xu ◽  
Kaihua Liu
Keyword(s):  
Performance Analysis ◽  
Content Centric Networking

scholarly journals Performance Parameter of AODV and DSR Potocol by Varying Nodes Mobility

2019 ◽  
Vol 9 (1) ◽  
pp. 4103-4105
Keyword(s):  
Performance Analysis ◽  
Wireless Network ◽  
Network Topology ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Dynamic Routing ◽  
Performance Parameter ◽  
Transmission Range ◽  
Host Mobility ◽  
A Performance

MANET is a cluster of nodes that are mobile which transfer the packet within a limited transmission range. It is decentralized and infrastructure less wireless network. Due to host mobility requirement for a robust dynamic routing protocol is needed, since a random and dynamic difference in the network topology is there. This paper presents a performance analysis between two routing protocols AODV and DSR. In terms of throughput, PDR and delay both protocols AODV and DSR is compared.

scholarly journals Intelligent Content-Centric Networking Routing Strategy: A Bacterial Quorum Inspired Pattern

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Hong Yang ◽  
Xiong Guo ◽  
Chi Zhang ◽  
Mengliang Li
Keyword(s):  
Energy Efficiency ◽  
Quorum Sensing ◽  
Network Topology ◽  
Load Balance ◽  
Dynamic Change ◽  
Mobile Internet ◽  
Information Measurement ◽  
Content Centric Networking ◽  
Routing Strategy ◽  
Bacterial Quorum

In recent years, the Content-Centric Networking (CCN) has attracted much attention from the global Internet experts; in particular, it has demonstrated the outstanding effect on the application in the field of Internet of Things (IoT). At present, the routing technique of ICN is subjected to the dynamic change of network environment with the development of mobile Internet. Therefore, this paper proposes an Intelligent CCN routing strategy based on Bacterial Quorum pattern (ICBQ). The ICBQ tries to simulate the behaviors of bacteria, including quorum sensing and adaptive chemotaxis. Meanwhile, the quorum sensing can obtain the parameter information on bandwidth, delay, and error rate to facilitate the subsequent forwarding of packets. The adaptive chemotaxis can select the optimal interface to forward the packets through the information measurement. The simulation is driven based on the real Netflix dataset over the GTS network topology, and the experimental results show that the proposed ICBQ has better performance in terms of routing success rate, routing delay, load balance, and energy efficiency.

scholarly journals Performance Analysis of Edge Computing in IoT

2020 ◽  
Vol 26 (1) ◽  
pp. 72-77
Author(s):  
Julius Skirelis ◽  
Dalius Navakauskas
Keyword(s):  
Performance Analysis ◽  
Network Topology ◽  
System Performance ◽  
State Of The Art ◽  
Edge Computing ◽  
Network Bandwidth ◽  
Network Parameters ◽  
Network Topologies ◽  
Considerable Impact ◽  
Art Research

Upcoming 5G technology and the demand for near real-time response services raise the need for optimizing current IoT solutions. The aim of this paper is to model and execute the performance analysis of network structures suitable for Edge Computing in IoT. The prior research into different topology and parameter sets have not provided sufficient clarity, on which parameters had a considerable impact on overall system performance; therefore, repetitive simulations were performed to express dispersion of alternating values, as well as determining its confidence intervals. The paper presents Edge Computing service simulation setup on known and newly derived network topologies with different complexity varying network bandwidth and network delay parameters. The experimental investigation has revealed that the IoT configuration network is more sensitive to network topology, while the Internet configuration is more sensitive to network parameters. The discussion on the results received debates possible causes of performance differences in network parameters and device configurations, the comparison to similar state-of-the-art research results has also been presented. Finally, conclusions with recommendations based on the results acquired have been provided.

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