6.4.3
Model Validation
In Subsection 3.4.3, some examples are presented demonstrating how the manual model can be used to validate the obtained results. To perform this task, once the results are obtained from the automatic mode, the designer can remove one AP, and try to cover all of the users with the remaining APs. This is possible because the covered and uncovered users are shown with different colours.
6.4.4
Changing the Position of an AP
Suppose an AP is placed on one wall in a room. Later, it might be necessary to place a bookshelf where the AP is located. The manual mode can be used to slightly move this AP as long as the coverage status of the users provided by the other APs is preserved.
It should be noted that the aim is to include the features of manual mode in the optimi- sation model in order to conduct all the design functions automatically.
6.5
Generated Output
Once the operation is completed, the designer is able to observe the number of APs and their placement graphically, as shown in Figure 6.28 as well as the function value and the status of the coverage for evaluation purposes.
Figure 6.28: The graphical picture shows the number and placement of APs
table generated by the program is shown in Figure 6.29. As can be seen, the values of WLAN parameters chosen by the designers for the test, the function value, the coordinates of APs, and the time necessary for solving the problem are recorded each time the program is executed.
Figure 6.29: Tabulated results
Figure 6.30 also shows how the designer is able to save and export the results. This figure also shows that another file called data can be exported. The contents of this file include the coordinates and number of users as well as the parameter values when the building file (see Subsection 6.2.1) is used to import the necessary information.
Software for WLAN Planning 6.6. Conclusion
6.6
Conclusion
This chapter described the features and operation of an efficient software that we have developed to assist network designers in planning and evaluating wireless LAN systems. Immediate visual feedback on the coverage of users is provided, while taking little time to execute.
The software is written in C++ code, and can operate in automatic as well as manual mode. The automatic mode is based on the optimisation models developed and the algo- rithm used in this thesis to find the minimum number of APs and their placement and to enhance the physical security of the network. In manual mode, the designer is able to add extra APs when the structure of the building under test is changed to obtain full coverage without changing the positions of existed APs. In both modes, the designer is able to exam- ine and evaluate the design with different values of AP parameters and technology types.
Additional work currently underway involves extending the optimisation model to solve the capacity issue. Including different path loss models for different types of environments and buildings will provide designers with wider options. Many commercial buildings have computerised floor plans that can be imported into AutoCAD. Therefore, it will be advanta- geous for the software to be able to extract the building information from an AutoCAD file. In the case where the floor plan is not available electronically, it would be advantageous if the designer could draw the building plan in the design space provided by the software.
The reader will be able to download the software from the following web site for trial purposes:
Conclusion
In this research our goal was to find an answer to this paramount question: how can opti- misation be used to solve network planning (finding the optimal number and placement of access points), and physical security issue in wireless LANs?
The primary goal of a wireless LAN design is to provide reliable signal coverage for an expected level of performance in all demand areas. To provide coverage in all required areas through our optimisation model, test points/potential users are distributed in the design space in order to provide a tool for evaluating the loss or strength of signal at each point. To provide quality of coverage for mobile users, we added a constraint in the models for each potential user to receive a signal above a given threshold value.
To formulate the problem mathematically, we proposed two approaches in developing our optimisation model. In the first approach, we developed a multi-objective functions model based on path losses and power for free space environments. The minimisation of the first function improves the overall quality of the coverage and the minimisation of the second one ensures that even the worst location enjoys an acceptable level of signal coverage. To obtain a good coverage for all users, the two functions are combined by using a balancing parameter.
In the second approach, we followed a step-by-step procedure. In the first step, we developed an effective optimisation model based on path losses to save on the cost of de- ployment by finding the minimum number of APs.
On the second step, we added another objective function to the model to maximise the physical security of the network. In this model, first, potential unauthorised users are introduced in unsafe areas. Then, the model minimises the coverage for these intruders who
Conclusion and Further Research
the network is reinforced.
We developed and used an iterative scheme to find the minimum number of APs in order to save on the cost of deployment in both models. This scheme consists of incrementally increasing the number of APs until the coverage constraint is satisfied.
We used a nonsmooth optimisation algorithm to solve the multi-objective functions models. Since the objective functions in the second model are discontinuous due to ob- stacles, most of the existing algorithms cannot be applied to solve the problems at hand. We have used the Global Optimisation Algorithm (AGOP) developed at the University of Ballarat. The two optimisation algorithms used in this thesis have not been used by other approaches to solve the same problem.
We used obstacle free environments and WLAN parameters to test the multi-objective functions models. We found that the scheme produces satisfactory results in finding the minimum number of APs and their distribution. The algorithm is very fast in solving the problem. However, our tests show that the choice of the best possible value of the balancing parameter to satisfy the operation of both functions together is quite difficult.
Our second model is tested on several indoor buildings with a wide range of values of the parameters of WLANs. When our results are compared with other approaches, our model in most cases finds fewer APs. When we tested for security, satisfactory results (APs are moved away from intruders) are obtained in all cases. From the time point of view, the solution to the problem is found within a reasonable time.
Seamless coverage for the mobile users can be achieved when the coverage of the neigh- bouring APs are overlapping. We have observed that this can be made possible when all parts of the design space are treated as demand areas.
We have developed a software tool based on the proposed model and algorithm to as- sist designers in network planning in wireless LAN. In this software once the designers import the design requirements, the test can be conducted. Upon completion of the test, the software produces graphical and numerical results for evaluation and documentation purposes.
Further Study
This thesis introduces an optimisation model and algorithm, which essentially provides a solution to network planning problem in WLANs saving on the costs of deployment and enhancing physical security of the network. By extending the model to include the follow- ing research problems, designers will be able to complete the design through continuous optimisation techniques.
• To increase capacity in areas where large number of users are congregating to conduct critical activities, it is important to increase the number of APs. This can be achieved by assigning lower path loss threshold values (high receive threshold and low trans- mit power) to these areas. By assigning large threshold values to other areas, fewer numbers of APs are required. This method (assigning different path loss threshold value to different areas based on requirements) saves on the cost of deployment by not allocating large number of APs in the whole area.
• To work on three dimensional building floor plans in order to consider the loss of signal going through floors and ceilings. In this case the path loss model for multi- storey buildings can be included in the optimisation model.
• To include parameters to reflect the needs and movement of mobile users in different areas during the day in the model. Based on the observation of the results, designers will be able to assign the appropriate load to APs dynamically.
Appendix A
Overview of Wireless LAN
A wireless local area network (WLAN) is a flexible data communications system that can either replace or extend a wired LAN to provide added functionality. Wireless communi- cation is defined as the transmission of users data including e-mail messages, spreadsheets, telephone voice messages, file transfer, audio streaming, and video streaming without use of the physical connections. The popularity of WLANs has increased more and more and they have started to revolutionise our life the same way that personal computers did in 1980s. Using wireless devices to browse the Internet, to access data and to send messages will transform the way that we are working.
The operation of wireless communication is based on the principle of electromagnetic waves. Wireless communication between two points is established with the use of a trans- mitter and a receiver. The transmitter generates electrical oscillations at a radio frequency called the carrier frequency. Oscillations at a radio frequency can be modulated either via the amplitude, frequency or phase. The receiver detects these oscillations and transforms them into sounds or images. Interference between two signals can happen if two transmit- ters use the same carrier frequency or obstacles exist between the transmitter and receiver. The level of interference depends on many factors such as the distance between the trans- mitters and receivers, the geographical position of the transmitters, the power of the signal, the direction in which the signal is transmitted, and the weather conditions. In these situa- tions the quality of the signal received by the receiver can drop below an acceptable value.
A.1
Advantages and Disadvantages of Wireless LAN
Any new technology has advantages and disadvantages. This is true with wireless LAN communication system. The advantages of WLAN are: mobility, disaster recovery, in- creased reliability, flexibility, and cost effectiveness. The disadvantages are: health risks, radio signal interference, and security.