Los tratados internacionales relativos a la protección de zonas

Network simulation is a popular method for analysing the performance a network system [24]. Network simulations can be achieved either through analytical modelling or computer simulation

14 or the combination of both methods [24]. Considering that this project utilised the computer simulation concept, network simulation here focuses on the idea of software for simulating network performance and analysing how this performance helps the network users. Simulation offers the ability to parameterize a system’s attribute through modelling to study the system’s performance in a controlled manner. Being under control, the modelled system’s measurements are made to be nonintrusive and deterministic [25]. Simulation has been used, over time as the means for testing systems performance due to the factors presented by cost, time, specification inaccuracies and errors due to implementation [25]. To accurately measure and test a system’s performance, the real system’s attributes are abstracted into a mathematical model and run through simulation scenarios that simplify and mimic the actual intention of the system. In the field of telecommunications, for example, two unique types of simulation are used to measure, evaluate and test the performance of new or existing systems. These are; link level simulations and system level simulations. This study used the system level simulation method to evaluate the two proposed algorithms. These simulators are Vienna LTE and ICS Designer. They are further described in Chapters Four and Six, respectively.

System level simulation is very crucial in the study of new and existing mobile network technologies and their performance. It is the most effective means of evaluating the performance and predicting the impact of the network and its technologies [26, 27]. System level simulations help researchers and industry experts to test and optimise their algorithms and procedure pre- deployment. Most importantly, system level simulations allow the investigation and measurement of the impact algorithmic decisions on the performance metrics of the network to ascertain how they affect the users’ perceptions of the network, upon deployment [26, 27]. In this regard, system level simulation is the best option when it comes to issues concerning network planning and resource management, considering that these are very important to network

15 reliability and greatly, general terms; affect the network performance as perceived by the users. In system level simulation, the physical layer of the network is abstracted by simplified models that depict the essential characteristics of the network, thus, resulting in a system with high accuracy and low complexity in implementation which also contributes to reducing the amount of required computational power, in such instances [26].

Scientific researchers depend on mostly software to harness the powers of computing which are ubiquitous in science research domains. Developing this software for them to use for particular research, however, presents very daunting tasks which range from the knowledge of programming to as far as the legal expertise required for licensing such software [28]. This also gives rise to different confusion, therefore, leading institutions set aside technology transfer offices that are capable of handling the complex legal aspect [28]. The intellectual property for a simulator (software, in this case) has to be granted by the owners before it is considered to be a valid research tool for any scientist, which is if the researcher did not create the software. The intellectual properties of a software licence are usually characterised by proprietary and open- source licence [28].

Proprietary License – these are commercial packages in which the end users are given a restricted click-through access to achieve the intended results. By such agreement, the users are bound to the intellectual property’s owners defined goals and access levels and at such are forbidden from copying, redistributing or creating a derivative of the simulator [28, 29]. Based on such agreements, the researchers are therefore not given permission to access the codes of the software for whatever reason since the agreement rests exclusive rights on the person, people or organisation with the copyright ownership [28, 29].

16 Open-Source License – open-source license, on the other hand, is intended to overcome the restrictions placed on research by the proprietary license owners. These kinds of software give maximum degree of interaction and usability to the users. In open-source software, the users get open, non-discriminatory access to all levels of the software which are grant free thus enabling them to modify the codes [30, 31] such that it suits their research purposes. Researchers using open-source software have the ability to create different derivatives of the software and for redistribution. The advantage here is that this kind of license promotes innovation and further enhancements to the software [28, 30] and comes at no cost to the end users [32]. Some of the major product of open-source licencing come under the different derivatives of the of the GNU agreements [28]. An open-source license fundamentally enables collaboration within the scientific research community thereby allowing for a greater degree of transparency and increases credibility within the scientific community [31] as well as improving productivity in scientific research that especially requires the use of software for data analysis [33]. The Vienna LTE Simulator which was used to evaluate the performance of the CRAA is based on the GNU agreement and also encourages reproducibility which is in tandem with the findings of [31].