A vehicular ad hoc network (VANET) is an emerging and promising wireless technology aimed to improve traffic safety and provide comfort to road users. However, the high mobility of vehicles and frequent topology changes pose a considerable challenge to the reliable delivery of safety applications. Clustering is one of the control techniques used in VANET to make the frequent topology changes less dynamic. Nevertheless, research has shown that most of the existing clustering algorithms focus on cluster head (CH) election with very few addressing other critical issues such as cluster formation and maintenance. This has led to unstable clusters which could affect the timely delivery of safety applications. In this study, enhanced weight-based clustering algorithm (EWCA) was developed to address these challenges. We considered any vehicle moving on the same road segment with the same road ID and within the transmission range of its neighbour to be suitable for the cluster formation process. This was attributed to the fact that all safety messages are expected to be shared among the vehicles within the vicinity irrespective of their relative speedto avoid any hazardous situation. To elect a CH, we identified some metrics on the basis of the vehicle mobility information. Each vehicle was associated with a predefined weight value based on its relevance. A vehicle with the highest weight value was elected as the primary cluster head (PCH). We also introduced a secondary cluster head (SeCH) as a backup to the PCH to improve the cluster stability. SeCH took over the leadership whenever the PCH was not suitable for continuing with the leadership. The simulation results of the proposed approach showed a better performance with an increase of approximately40%– 45% in the cluster stability when compared with the existing approaches. Similarly, cluster formation messages were significantly minimized, hence reducing the communication overhead to the system and improving the reliable delivery of the safety applications.

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This paper investigates factors that influence Zambian higher education lecturer’s attitude towards integrating ICTs in research and teaching. To determine these factors, we used online administered survey with a total of 163 respondents from public and private higher education institutions in Zambia. Quantitative data analysis based on descriptive and inferential statistics was used in this study. Inferential analysis was employed to investigate the relationships among variables using Pearson correlation analysis and completely randomized design. The results revealed that lack of adequate Internet bandwidth is among the major barrier or obstacle for assimilating ICTs in research and teaching for Zambian higher education lecturers. Additionally, training lecturers on the use of ICTs e.g. email, PowerPoint presentations, electronic boards and its advantages is the most important incentive to motivate lecturers to incorporate ICTs in research and teaching. Therefore, this study contributes to literature on factors that influence higher education lecturers’ attitude towards integrating ICTs in research and teaching. This study also demonstrates a positive correlation between the important factors that influence lecturers in integrating ICTs in research and teaching.

Vehicular Ad hoc Network (VANET) is an emerging and promising technology, which allows vehicles to communicate and share resources. These resources use applications that have to meet high reliability and delay constraints. However, to implement these applications, VANET relies on medium access control (MAC) protocol. Many approaches have been proposed in literature using Time Division Multiple Access (TDMA) scheme to enhance the efficiency of MAC protocol. Nevertheless, this technique is faced with some challenges including access and merging collisions due to inefficient time slot allocation strategy and hidden terminal problem. In this paper, we relatively examined the most prominent TDMA MAC protocols proposed in the literature from the year 2010 to 2017. We classify them based on scheduling strategy and the technique they adopt. We also comparatively analysed them based on different parameters and performance metrics used.Finally, some open issues are presented for future deployment.