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Published on Feb 02, 2016

Abstract

The objective:

Maximizing network throughput while providing fairness is one of the key challenges in wireless LANs (WLANs). This goal is typically achieved when the load of access points (APs) is balanced.

Recent studies on operational WLANs, however, have shown that AP load is often substantially uneven. To alleviate such imbalance of load, several load balancing schemes have been proposed. These schemes commonly require proprietary software or hardware at the user side for controlling the user-AP association.

In this paper we present a new load balancing technique by controlling the size of WLAN cells (i.e., AP's coverage range), which is conceptually similar to cell breathing in cellular networks.

The proposed scheme does not require any modification to the users neither the IEEE 802.11 standard. It only requires the ability of dynamically changing the transmission power of the AP beacon messages.

We develop a set of polynomial time algorithms that find the optimal beacon power settings which minimize the load of the most congested AP. We also consider the problem of network-wide min-max load balancing

Proposed System:



We address the problem of min-max load balancing. This is a strong NP-hard problem. In it is proved that there exists no algorithm that guarantees any coordinate wise approximation ratio, and the approximation ratio of any prefix-sum approximation algorithm is at least (logn), where n is the number of APs.

In this paper, we solve a variant of this min-max problem, termed min-max priority load balancing, whose optimal solution can be calculated in polynomial time for both knowledge models.

Here, the AP load is defined as an ordered pair of the aggregated load contributions of its associated users and a unique AP priority

Hardware Requirements :

System : Pentium IV 2.4 GHz.

Hard Disk : 40 GB.

Floppy Drive : 1.44 Mb.

Monitor : 15 VGA Colour.

Mouse : Logitech.

Ram : 256 Mb

Software Requirements :

Operating System : - Windows Xp Professional.

Front End :-Visual Studio Dot Net 2005.

Coding Language : - C#.

Database :-Sql 2000