Priority Transmission of SIP Signaling Flows in Case of IP Link Congestion

2009 ◽  
Author(s):  
J. Barakovic ◽  
H. Bajric ◽  
M. Kos
Keyword(s):  
Link Congestion

Surviving switch failures in cloud datacenters

2021 ◽  
Vol 51 (2) ◽  
pp. 2-9
Author(s):  
Rachee Singh ◽  
Muqeet Mukhtar ◽  
Ashay Krishna ◽  
Aniruddha Parkhi ◽  
Jitendra Padhye ◽  
...  
Keyword(s):  
Operating System ◽  
Network Traffic ◽  
Survival Rates ◽  
Cloud Provider ◽  
Significant Heterogeneity ◽  
Power Losses ◽  
Software Bugs ◽  
Hardware Impairments ◽  
Link Congestion

Switch failures can hamper access to client services, cause link congestion and blackhole network traffic. In this study, we examine the nature of switch failures in the datacenters of a large commercial cloud provider through the lens of survival theory. We study a cohort of over 180,000 switches with a variety of hardware and software configurations and find that datacenter switches have a 98% likelihood of functioning uninterrupted for over 3 months since deployment in production. However, there is significant heterogeneity in switch survival rates with respect to their hardware and software: the switches of one vendor are twice as likely to fail compared to the others. We attribute the majority of switch failures to hardware impairments and unplanned power losses. We find that the in-house switch operating system, SONiC, boosts the survival likelihood of switches in datacenters by 1% by eliminating switch failures caused by software bugs in vendor switch OSes.

Routing algorithm of minimizing maximum link congestion on grid networks

2014 ◽  
Vol 21 (5) ◽  
pp. 1713-1732 ◽  
Author(s):  
Jun Xu ◽  
Jianfeng Yang ◽  
Chengcheng Guo ◽  
Yann-Hang Lee ◽  
Duo Lu
Keyword(s):  
Routing Algorithm ◽  
Grid Networks ◽  
Link Congestion

scholarly journals Congested Link Inference Algorithms in Dynamic Routing IP Network

2017 ◽  
Vol 2017 ◽  
pp. 1-17
Author(s):  
Yu Chen ◽  
Zhe-min Duan
Keyword(s):  
Markov Property ◽  
Variable Structure ◽  
Dynamic Routing ◽  
Simplified Model ◽  
Maximum A Posteriori ◽  
A Posteriori ◽  
Bayesian Network Model ◽  
Inference Algorithms ◽  
Ip Network ◽  
Link Congestion

The performance descending of current congested link inference algorithms is obviously in dynamic routing IP network, such as the most classical algorithm CLINK. To overcome this problem, based on the assumptions of Markov property and time homogeneity, we build a kind of Variable Structure Discrete Dynamic Bayesian (VSDDB) network simplified model of dynamic routing IP network. Under the simplified VSDDB model, based on the Bayesian Maximum A Posteriori (BMAP) and Rest Bayesian Network Model (RBNM), we proposed an Improved CLINK (ICLINK) algorithm. Considering the concurrent phenomenon of multiple link congestion usually happens, we also proposed algorithm CLILRS (Congested Link Inference algorithm based on Lagrangian Relaxation Subgradient) to infer the set of congested links. We validated our results by the experiments of analogy, simulation, and actual Internet.

Enhanced Service Discovery Model for Wireless Mesh Networks

2018 ◽  
Vol 22 (1) ◽  
pp. 44-53 ◽  
Author(s):  
Lungisani Ndlovu ◽  
◽  
Okuthe P. Kogeda ◽  
Manoj Lall
Keyword(s):  
Wireless Mesh Networks ◽  
Service Discovery ◽  
Mesh Networks ◽  
Service Selection ◽  
Cost Effective ◽  
Ant Colony ◽  
Area Network ◽  
Wireless Mesh ◽  
Proposed Model ◽  
Link Congestion

Wireless mesh networks (WMNs) are the only cost-effective networks that support seamless connectivity, wide area network (WAN) coverage, and mobility features. However, the rapid increase in the number of users on these networks has brought an upsurge in competition for available resources and services. Consequently, factors such as link congestion, data collisions, link interferences, etc. are likely to occur during service discovery on these networks. This further degrades their quality of service (QoS). Therefore, the quick and timely discovery of these services becomes an essential parameter in optimizing the performance of service discovery on WMNs. In this paper, we present the design and implementation of an enhanced service discovery model that solves the performance bottleneck incurred by service discovery on WMNs. The proposed model integrates the particle swarm optimization (PSO) and ant colony optimization (ACO) algorithms to improve QoS. We use the PSO algorithm to assign different priorities to services on the network. On the other hand, we use the ACO algorithm to effectively establish the most cost-effective path whenever each transmitter has to be searched to identify whether it possesses the requested service(s). Furthermore, we design and implement the link congestion reduction (LCR) algorithm to define the number of service receivers to be granted access to services simultaneously. We simulate, test, and evaluate the proposed model in Network Simulator 2 (NS2), against ant colony-based multi constraints, QoS-aware service selection (QSS), and FLEXIble Mesh Service Discovery (FLEXI-MSD) models. The results show an average service discovery throughput of 80%, service availability of 96%, service discovery delay of 1.8 s, and success probability of service selection of 89%.

An incremental optimal routing strategy for scale-free networks

2014 ◽  
Vol 25 (09) ◽  
pp. 1450044 ◽  
Author(s):  
Zhong-Yuan Jiang
Keyword(s):  
Traffic Load ◽  
Traffic Model ◽  
Optimal Routing ◽  
Traffic Dynamics ◽  
Shortest Path Routing ◽  
Scale Free ◽  
Routing Strategy ◽  
Traffic Capacity ◽  
Real Complex ◽  
Link Congestion

The link congestion based traffic model can more accurately reveal the traffic dynamics of many real complex networks such as the Internet, and heuristically optimizing each link's weight for the shortest path routing strategy can strongly improve the traffic capacity of network. In this work, we propose an optimal routing strategy in which the weight of each link is regulated incrementally to enhance the network traffic capacity by minimizing the maximum link betweenness of any link in the network. We also estimate more suitable value of the tunable parameter β for the efficient routing strategy under the link congestion based traffic model. The traffic load of network can be significantly balanced at the expense of increasing a bit average path length or average traffic load.

Analysis of RBQ: a new cooperative web caching mechanism that adapts to link congestion

2003 ◽  
Author(s):  
Eugenio M. de la Rosa ◽  
John H. Hartman ◽  
Terril Hurst
Keyword(s):  
Web Caching ◽  
Caching Mechanism ◽  
Link Congestion

scholarly journals SIMULASI ANTRIAN PAKET DATA JARINGAN DENGAN MEKANISME DROP TAIL

2016 ◽  
Vol 8 (2) ◽  
pp. 151 ◽  
Author(s):  
Misbahul Fajri
Keyword(s):  
Buffer Management ◽  
Congestion Avoidance ◽  
Packet Losses ◽  
Congestion Collapse ◽  
And Control ◽  
Link Congestion

Perkembangan penggunaan komputer dengan akses jaringan serta layanannya cepat berkembang dari masa ke masa, ini membuat kepadatan trafik data pada jaringan internet maupun intranet. Kemacetan jaringan internet pertama kali dialami pada akhir tahun 80-an, pada saat itu belum adanya mekanisme yang menangani hal tersebut. kemudian ditemukannya teorinya yaitu Congestion Avoidance and Control. Congestion adalah  pengumpulan paket melebihi kapasitas bandwidth yang tersedia pada link, congestion akan mengakibatkan penurun kinerja jaringan diantaranya; multiple packet losses, utilitas link yang rendah (low throughput), delay antrian yang tinggi, dan kemacetan yang parah (congestion collapse).  Penanganan kepadata jaringan sangat penting, ini membuat banyaknya metode-metode baru yang muncul dari metode sederhana sampai yang canggih, semuanya itu mempunyai kekurangan dan kelebihan, serta karakateristik masing-masing, ini menjadikan riset yang menantang untuk dipelajari dan dikembangkan, termaksud dalam penelitian ini.  Pada penelitian ini dengan menggunakan simulator OPNET dibuat topologi jaringan bottlenect yang akan diimplemetasikan metode AQM klasik FIFO (Drop Tail) dengan trafik layanan seperti, FTP. Sehingga dapat dilihat penggunaan buffer pada router dalam penanganan antrian, juga berapa banyak trafik droped dan trafik sendnya, serta delay. Hasilnya dapat dilihat bahwa Drop Tail adalah solusi yang bekerja dengan baik dalam mengatasi antrian dalam buffer management dengan ditunjukkan 3 karakteristik yang baik yaitu pada Packet Dropped, Pengiriman Ulang, dan  Buffer Usage.

scholarly journals Multicast Optimization And Recovery In Multihoming Environment

2021 ◽  
Author(s):  
Frank Levstek
Keyword(s):  
Steiner Tree ◽  
Multicast Tree ◽  
Link Failure ◽  
Recovery Model ◽  
Point Model ◽  
Rendezvous Point ◽  
Simulation Results ◽  
Conventional Optimization ◽  
Link Congestion ◽  
Novel Algorithm

Reliability of multicasting is increasingly becoming an important issue as the number of end users continues to grow, their demand for reliable service increases. This thesis proposes a novel algorithm for creating a recovery model while optimizing both inter and intra domain bandwidth. This is achieved by creating a centralized rendezvous point within the intra domain topology. The rendezvous point will create a static multicast tree and it will avoid link congestion during inter-domain link failure. This algorithm also reduces link congestion surrounding the border routers. This is achieved by shifting the root of the multicast tree from the border router to the rendezvous point. This rendezvous point is then selected based on an optimization algorithm to reduce bandwidth congestion. A Steiner tree was used to optimize the intra domain links. The simulation results indicate up to 30% increase over conventional optimization algorithms which do not consider a rendezvous point model.

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