LOAD SHARING VERSUS SERVICE BALANCING IN INTEGRATED NETWORKS

2005 ◽  
Vol 06 (01) ◽  
pp. 35-50 ◽  
Author(s):  
SUSAN J. LINCKE ◽  
CYNTHIA S. HOOD

As third and fourth generation cellular/wireless networks evolve, operators must learn to efficiently manage diverse services, and multiple networks consisting of varying technologies, cell sizes, and frequency bands. Architectural studies on integrated heterogeneous networks suggest that vertical handovers can be used to increase network efficiency. We propose that carefully-controlled load distribution can also promote Quality of Service (QoS) goals for the diverse services. This study compares session overflow and session placement algorithms in order to determine their effects on efficiency and QoS.

Author(s):  
Farnaz Farid ◽  
Seyed Shahrestani ◽  
Chun Ruan

The quality of service (QoS) evaluation of heterogeneous networks is an interesting area of research. The traditional QoS evaluation methods usually use a set of network-centric parameters for the performance evaluation of these networks. As a result, using such methods it is not possible to report a comprehensive performance review of networks that would include diverse applications and technologies. To resolve this issue, in this research, a novel approach has been proposed that applies dynamic significance weights and unified metrics of the QoS-related parameters to various applications and technologies present within a heterogeneous network. The result analysis shows that by applying this methodical approach, the performance evaluation of heterogeneous networks can be carried out systematically and efficiently.


2007 ◽  
Vol 45 (2) ◽  
pp. 88-95 ◽  
Author(s):  
David Griffin ◽  
Jason Spencer ◽  
Jonas Griem ◽  
Mohamed Boucadair ◽  
Pierrick Morand ◽  
...  

2001 ◽  
Vol 8 (6) ◽  
pp. 18-24 ◽  
Author(s):  
M. Alam ◽  
R. Prasad ◽  
J.R. Farserotu

Author(s):  
Marion Olubunmi Adebiyi ◽  
Egbe Egbe Adeka ◽  
Florence A. Oladeji ◽  
Roseline Oluwaseun Ogundokun ◽  
Micheal Olaolu Arowolo ◽  
...  

<span>Wireless networks came into the computing world replacing the costlier and more complex wired method of connecting numerous equipment in the same or different location via the use of cables. It provides the user devices a connection to one another and the greater internet via connections to access points. Generally, 802.11 access point products follow a default strongest signal first approach in selecting user devices or nodes to connect to the access point or overlapping access points. This standard does not make provisions for even distribution of load and hence the quality of service and the throughput in areas of congestion would be reduced. This article brings forward two algorithms used in load balancing and they include round-robin technique and the weighted round-robin technique to be used in the simulation of the distribution of the load amongst the access points with the results collated and compared to clearly show which algorithm is best suited to be used as a standard for access point load distribution.</span>


2009 ◽  
Vol 32 (12) ◽  
pp. 1355-1370 ◽  
Author(s):  
E. Mingozzi ◽  
G. Stea ◽  
M.A. Callejo-Rodríguez ◽  
J. Enríquez-Gabeiras ◽  
G. García-de-Blas ◽  
...  

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
J. J. Escudero-Garzás ◽  
C. Bousoño-Calzón

The trend in wireless networks is that several wireless radio access technologies (RATs) coexist in the same area, forming heterogeneous networks in which the users may connect to any of the available RATs. The problem of associating a user to the most suitable RAT, known as network selection problem (NSP), is of capital importance for the satisfaction of the users in these emerging environments. However, also the satisfaction of the operator is important in this scenario. In this work, we propose that a connection may be served by more than one RAT by using multi-RAT terminals. We formulate the NSP with multiple RAT association based on utility functions that take into consideration both user’s satisfaction and provider’s satisfaction. As users are characterized according to their expected quality of service, our results exhaustively analyze the influence of the user’s profile, along with the network topology and the type of applications served.


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