scholarly journals End‐to‐end delay optimisation for IEEE 802.11 string topology multi‐hop wireless networks in overhead transmission line system

2020 ◽  
Author(s):  
Chanjuan Zhao ◽  
Wei Sun ◽  
Zhao Fang ◽  
Jianping Wang ◽  
Qiyue Li ◽  
...  
Keyword(s):  
Wireless Networks ◽  
Transmission Line ◽  
Ieee 802.11 ◽  
String Topology ◽  
Line System ◽  
Overhead Transmission Line ◽  
End To End Delay ◽  
End To End

End-to-End Delay Analysis for IEEE 802.11 String-Topology Multi-Hop Networks

2015 ◽  
Vol E98.B (7) ◽  
pp. 1284-1293 ◽  
Author(s):  
Kosuke SANADA ◽  
Jin SHI ◽  
Nobuyoshi KOMURO ◽  
Hiroo SEKIYA
Keyword(s):  
Ieee 802.11 ◽  
Delay Analysis ◽  
String Topology ◽  
End To End Delay ◽  
End To End

scholarly journals Minimizing end-to-end delay in multi-hop wireless networks with optimized transmission scheduling

2019 ◽  
Vol 89 ◽  
pp. 236-248 ◽  
Author(s):  
Antonio Capone ◽  
Yuan Li ◽  
Michał Pióro ◽  
Di Yuan
Keyword(s):  
Wireless Networks ◽  
Transmission Scheduling ◽  
End To End Delay ◽  
End To End

scholarly journals A New Wireless VoIP Signaling Device Supporting SIP and H.323 Protocols

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Salma Rattal ◽  
Abdelmajid Badri ◽  
Mohammed Moughit
Keyword(s):  
Wireless Networks ◽  
Wireless Network ◽  
Ieee 802.11 ◽  
Packet Loss ◽  
Quality Service ◽  
High Quality ◽  
Transmission Rates ◽  
Great Demand ◽  
End To End Delay ◽  
High Quality Service

Nowadays, VoIP is a technology with a great demand and wireless networks are increasingly deployed. Each of these has its own technology constraints. For VoIP, it is very important to take into consideration the need to provide a high quality service according to well-defined standard transmission (jitter, end-to-end delay, MOS, and packet loss). However, wireless networks (IEEE 802.11) are based on radio which undergoes a number of technical constraints to achieve theoretical transmission rates; among these constraints the number of users of the networks, the distance between the client and the access, and the amount of data transmitted point are included. In this term, a study is made by simulating wireless network in OPNET Modeler with a fairly large number of VoIPs (15 users) whose signaling is handled via a new node that was created specifically to manage the signaling tasks under SIP and H.323 in order to minimize the number of nodes in the network and avoid the congestion. In this paper, two scenarios are compared; the first contains a number of VoIP users with SIP and H.323 signaling handled by the new created device; the second scenario is similar to the first except that the distance between the stations is remarkably lower.

scholarly journals Real-Time Communications in Large-Scale Wireless Networks

2008 ◽  
Vol 2008 ◽  
pp. 1-16 ◽  
Author(s):  
Liang Song ◽  
Dimitrios Hatzinakos
Keyword(s):  
Wireless Networks ◽  
Real Time ◽  
Large Scale ◽  
Visual Sensor ◽  
Broadband Internet ◽  
Multihop Wireless ◽  
Data Packets ◽  
End To End Delay ◽  
End To End ◽  
Qos Performance

There is an emerging need for realizing real-time quality of service (QoS) over multihop wireless communications in large-scale wireless networks. The applications can include wireless mesh infrastructure for broadband Internet access supporting multimedia services, visual sensor networks for surveillance, and disaster-relief networks. However, a number of challenges still exist as revealed by recent works, where the dataflow QoS performance such as throughput and end-to-end delay can degrade fast with the number of wireless hops. We propose to use large-scale cognitive networking methods to resolve the wireless multihop challenges. By the cognitive-networking concept, data packets travel along opportunistically available paths in the network with opportunistically available spectrum in every hop. Reliable end-to-end communications can be achieved for real-time services, where we show that (1) dataflow throughput can be independent of any number of wireless hops, (2) end-to-end delay and delay variance increase linearly with the number of wireless hops, and (3) delay variance decreases to zero with higher network density. These results are supported by analysis, simulations, and experiments.

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