Faculty of Criminology, Justice and Policy Studies

Users of Social Networking Sites (SNSs) like Facebook, MySpace, LinkedIn, or Twitter face two problems 1) their online social friendships and activities are scattered across SNSs. It is difficult for them to keep track of all their friends and the information about their friends online social activities. 2) they are often overwhelmed by the huge amount of social data (friends updates and other activities). To solve these two problems, this research proposes an approach, named SocConnect. Soc- Connect allows users to create personalized social and semantic contexts for their social data. Users can blend their friends across different social networking sites and group them in different ways. They can also rate friends and/or their activities as favourite, neutral or disliked. SocConnect also can recommend unread friend updates to the user based on user previous ratings on activi- ties and friends, using machine learning techniques. The results from one pilot studies show that users like SocConnects functionalities are needed and liked by the users. An evaluation of the effectiveness of several machine learning algorithms demonstrated that , and machine learning can be usefully applied in predicting the interest level of users in their social network activities, thus helping them deal with the network overload.

Measuring human behavioral patterns has broad application across different sciences. An individuals social, proximal and geographical contact patterns can have significant importance in Delay Tolerant Networking (DTN) and epidemiological modeling. Recent advances in computer science have not only provided the opportunity to record these behaviors with considerably higher temporal resolution and phenomenological accuracy, but also made it possible to record specific aspects of the behaviors which have been previously difficult to measure.<p> This thesis presents a data collection system using tiny sensors which is capable of recording humans proximal contacts and their visiting pattern to a set of geographical locations. The system also collects information on participants health status using weekly surveys. The system is tested on a population of 36 participants and 11 high-traffic public places. The resulting dataset offers rich information on human proximal and geographic contact patterns cross-linked with their health information.<p> In addition to the basic analysis of the dataset, the collected data is applied to two different applications. In DTNs the dataset is used to study the importance of public places as relay nodes, and described an algorithm that takes advantage of stationary nodes to improve routing performance and load balancing in the network. In epidemiological modeling, the collected dataset is combined with data on H1N1 infection spread over the same time period and designed a model on H1N1 pathogen transmission based on these data. Using the collected high-resolution contact data as the models contact patterns, this work represents the importance of contact density in addition to contact diversity in infection transmission rate. It also shows that the network measurements which are tied to contact duration are more representative of the relation between centrality of a person and their chance of contracting the infection.

Users of Social Networking Sites (SNSs) like Facebook, MySpace, LinkedIn, or Twitter face two problems 1) their online social friendships and activities are scattered across SNSs. It is difficult for them to keep track of all their friends and the information about their friends online social activities. 2) they are often overwhelmed by the huge amount of social data (friends updates and other activities). To solve these two problems, this research proposes an approach, named SocConnect. Soc- Connect allows users to create personalized social and semantic contexts for their social data. Users can blend their friends across different social networking sites and group them in different ways. They can also rate friends and/or their activities as favourite, neutral or disliked. SocConnect also can recommend unread friend updates to the user based on user previous ratings on activi- ties and friends, using machine learning techniques. The results from one pilot studies show that users like SocConnects functionalities are needed and liked by the users. An evaluation of the effectiveness of several machine learning algorithms demonstrated that , and machine learning can be usefully applied in predicting the interest level of users in their social network activities, thus helping them deal with the network overload.

The objectives of this thesis are to investigate the challenges on video streaming, to explore and compare different video streaming mechanisms, and to develop video streaming algorithms that maximize visual quality. To achieve these objectives, we first investigate scalable video multicasting schemes by comparing layered video multicasting with replicated stream video multicasting. Even though it has been generally accepted that layered video multicasting is superior to replicated stream multicasting, this assumption is not based on a systematic and quantitative comparison. We argue that there are indeed scenarios where replicated stream multicasting is the preferred approach. We also consider the problem of providing perceptually good quality of layered VBR video. This problem is challenging, because the dynamic behavior of the Internet's available bandwidth makes it difficult to provide good quality. Also a video encoded to provide a consistent quality exhibits significant data rate variability. We are, therefore, faced with the problem of accommodating the mismatch between the available bandwidth variability and the data rate variability of the encoded video. We propose an optimal quality adaptation algorithm that minimizes quality variation while at the same time increasing the utilization of the available bandwidth. Finally, we investigate the transmission control protocol (TCP) for a transport layer protocol in streaming packetized media data. Our approach is to model a video streaming system and derive relationships under which the system employing the TCP protocol achieves desired performance. Both simulation results and the Internet experimental results validate this model and demonstrate the buffering delay requirements achieve desired video quality with high accuracy. Based on the relationships, we also develop realtime estimation algorithms of playout buffer requirements.

The rise in the popularity of smartphones such as Blackberry and iPhone creates a strain on the world's mobile networks. The extensive use of these mobile devices leads to increasing congestion and higher rate of node failures. This increasing demand of mobile wireless clients forces network providers to upgrade their wireless networks with more efficient and more reliable services to meet the demands of their customers. Therefore, there is a growing interest in strategies to resolve the problem and reduce the stress on the wireless networks. One strategy to reduce the strain on the wireless networks is to utilize cooperative communication. The purpose of this thesis is to provide more efficient and reliable solutions for direct information exchange problems. First, algorithms are presented to increase the efficiency of cooperative communication in a network where the clients can communicate with each other through a broadcast channel. These algorithms are designed to minimize the total transmission cost so that the communication will be less expensive and more efficient. Second, we consider a setting in which several clients exchange data through a relay. Our algorithms have provable performance guarantees. We also verify the performance of the algorithms in practical settings through extensive simulations.

Internet of Things (IoT) is a scenario that theorizes objects and people as potential nodes in an ever-growing wireless network. This idea pushes the development of low-cost wireless technologies that can run on portable power sources for months, or even years. One candidate technique that has shown promising results in this area thru the last years is BluetoothLow Energy (BLE). This thesis studies various techniques to enable and maintain large scale mesh networks over BLE communication. The initial study puts focus on an existing flooding based BLE mesh protocol. The thesis later presents an improved protocol that reduces power consumption with respect to the packet delivery ratio. Other enhancements which are added to the improved protocol are a self-adapting procedure and a packet routing algorithm. Simulations show that the improved protocol can save up to 50 % of the power consumption for a device, compared to the original protocol. / Sakernas Internet (IoT) är ett scenario som skisserar objekt och människor som potentiella noder i ett ständigt växande trådlöst nätverk. Denna vision driver utvecklingen av trådlösa lågkostnadsteknologier som kan köras på portabla strömkällor i flera månader. En kandiderande teknik som har visat goda resultat inom detta område är Bluetooth Low Energy (BLE). Detta uppsatsarbete studerar flera tekniker för att möjliggöra och upprätthålla storskaliga meshnätverk över BLE-kommunikation. Den inledande studien granskar ett existerande översvämningsbaserat meshprotokoll för BLE. Uppsatsarbetet presenterar därefter ett förbättrat protokoll som reducerar strömförbrukningen med avseende på kvoten mellan antalet mottagna paket genom antalet skickade paket. Ytterliggare upprustningar som tillkommer i det förbättrade protokollet är en procedur för självanpassning, samt en algorithm för dirigering av paket. Simuleringar visar att det förbättrade protokollet kan spara upp till 50 % av strömkonsumptionen för en enhet, jämfört med originalprotokollet.

There are currently over 900 million Facebook users worldwide (and counting). With increased use of social networking comes new concerns for personal privacy and control of social networking information. More and more, Facebook activity trickles its way into offline contexts, perhaps none more so than the employment context. A new trend in the hiring process is social networking background checks, where some employers go so far as to request a candidate’s Facebook password. Not only this, but the frequency of Facebook activity resulting in employment law disputes is increasing, and has even been found to constitute sufficient grounds for discipline and termination. This thesis examines the current privacy protection given to social networking information in the context of the employment relationship, highlights problems with the current legal landscape in this regard, and offers an emerging theory, New Virtualism, as a conceptual basis for the regulation of this issue going forward.

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Business management is characterised by fast and ever–expanding development. Culture and generation play an increasingly important role in the management of businesses worldwide. Although studies have been conducted on the subjects of culture and generation, little attention has been paid to culture and generation as a combination of diversity characteristics. As more managers are realising the challenges that arise when managing diverse work environments, the modern manager must question old assumptions about how diverse people work together. In this modern age, it is important to understand diversity issues on all levels of management. Networks are based on people's backgrounds, and understanding the link between networking and diversity is becoming increasingly important. In a culturally complex country such as South Africa, experiencing the impact of diversity on a daily basis can be anticipated. Culture and generation are two terms that encompass all dimensions of diversity. This study investigates the different networking practices found among diverse cultural and generational groups at a Gauteng mine. The generational classification used in this study is based on the fact that generations differ from country to country; therefore, the classification used in this study is relevant to South African generations. Seven hypotheses were formulated pertaining to differences among cultural and generational groups with regard to networking practices. Furthermore, four cultural–generational groups were identified, namely Black Generation X'ers, Black Baby Boomers, White Generation X'ers and White Baby Boomers. Data was collected from Kusasalethu mine employees. The original sample frame comprised 3630 employees from which a sample was chosen that complied with the criteria for culture, age / generation and education. A total of 1046 employees remained from which the sample elements were chosen by making use of probability, systematic proportionate stratified sampling. Self–completion questionnaires were used for collecting the data. A total of 289 questionnaires were completed which constituted a 100% response rate. The questionnaire used was intended to obtain feedback from respondents regarding their cultural and generational diversity, as well as preferences pertaining to their networking practices. The results from the survey were used to determine the differences between diverse cultures and generations with regards to networking practices. The findings, supported by the rejection of the first null–hypothesis, indicated that there are indeed a number of salient differences between Black Generation X'ers, Black Baby Boomers, White Generation X'ers and White Baby Boomers. Specifically, the results indicated that White Baby Boomers incline to rarely use the medium of SMS when networking while this group also makes use of telephones when networking more often than Black Generation X'ers. Furthermore, Black Baby Boomers more frequently use e–mails when networking while Black Generation X'ers indicated that they rarely use e–mail as network medium. It was found that White Baby Boomers make use of one–on–one face–to–face methods more often when networking than Black Generation X'ers and White Generation X'ers. The largest number of differences was between Black Generation X'ers and White Baby Boomers. The respondents all indicated that they incline to value good relationships at work highly, that they agree that informal work environments are conducive to more effective networking practices, that they frequently have good influences on their families and that they network more during spare time than at work. The results also indicated that the mediums that are used most often when networking include the cell phone and one–on–one face–to–face methods. Respondents tended to rate sharing experiences and exchanging work ideas as very important aims for networking. By dividing diverse workforces into smaller, more manageable units or homogeneous groups, diversity management can be simplified. This is an ability for which managers can be trained and which should be applied correctly within a business environment. In view of the results, it is recommended that managers of diverse workforces should identify different generations and cultures as a way to manage them more effectively. Furthermore, managers should ensure that work environments that are conducive to good relationship building and informality need to be created. Additionally, conflict between Black Generation X'ers and White Baby Boomers should be handled cautiously with a view to ensure that effective solutions are achieved to such conflicts. Preferences with regard to network mediums should be noted, as such awareness may lead to more effective networking / communication within businesses. Management's approach to meetings needs to be reviewed for each group, because differences exist in terms of preferences in this regard. A working environment conducive to exchanging ideas and experiences should be created. Lastly, as all groups value good relationships at work, a climate that encourages openness and conflict resolution should be created. / Thesis (M.Com. (Business Management))--North-West University, Potchefstroom Campus, 2012.