The advent of the Internet of Things (IoT) introduces a variety of challenges. One of the most frequent challenges is the consumption of resources (e.g., power and memory). The consumption of resources is considered an important aspect when it comes to the general performance of the system. Therefore, it is important to consider this kind of issue before designing such systems or applications. This research aims to assess the number of resources consumed when having hybrid objects (static and dynamic) in the Internet of Things (IoT). The objects considered in this work can be devices such as sensors, smartphones, or other sensing objects that can be used in exchanging data (resources). The settings of the experiments performed in this work vary including colorful parameters (i.e., object deployment, movement patterns, and routing protocols) and a combination of them. In this work, 4 groups of experiments are designed considering different parameters. The simulations are evaluated in terms of two metrics; the amount of data exchanged and covered areas. These two metrics are used as indicators to measure the consumption of resources. The findings showed that the Gaussian strategy in deploying the static and mobile nodes in the IoT can reduce the consumption of resources (e.g., memory and power) and cover more areas within the simulation environment regardless of the movement pattern and the routing protocols used.
The Iraqi political arena has witnessed a dramatic change after the year of 2003. It moved from the dominated republican system to a democratic system. This movement in the political system has affected the situation in Iraq in terms of economic, education, industrial, trading, to mention a few. This paper analyses the Iraqi parliament representatives' affiliations in terms of their coalitions they formed in the elections. Moreover, this study tries enabling us to deeply understand how the Iraqi parliament representatives are connected to each other and the relations among them. It also provides us with information on how different provinces adopted different coalitions regardless their religion and other tendencies. Several political networks were generated and visualized based on the concepts of complex networks. Each network represents a particular political aspect of the current Iraqi parliament. This study also reveals a new trend of forming coalitions in Iraq and the strategy followed by the representatives in attaching to coalitions. Finally, we believe this is the first kind of work that uses this approach of analysis in understanding the trend of Iraqi politicians.
Before the year of 2003, the Iraqi political arena was dominated by one-party regime. This party was the main and the only party that controlled all the joints of the country such as the education, economic, and industry sectors. After 2003, the whole political system of the country was transitioned from being a single-party to a multiparty regime. These parties formed coalitions and compete with each other to win the major offices in Iraq. In this paper, we involve the concepts of complex network in investigating and understanding the political performance of the current Iraqi parties in terms of political collaboration. We aim to generate and visualize a political network for the Iraqi parties and involve some measurements in the analysis. Using this measurement, we plan to evaluate the parties and the coalitions formed by these parties. We also plan to highlight some of the influential parties' leaders.
Data science has become a dominant tool in many different disciplines. Many methods and approaches are available and can be used in analyzing data. Network science approach is currently considered a powerful tool that is able to visualize and analyze complex data through investigating the relations among data objects. This kind of methods considers data as nodes that are connected by edges among them, and these connections are created based on a particular strategy. In this work, we generate a network model for the Iraqi parties using the IHEC public dataset. The model consists of nodes and edges connecting them. The performance of the generated network model was evaluated using two-level of measurements; Network-Level measurements (i.e., density, average degree, degree distribution, average path length, and average clustering coefficient) and Node-Level measurements (i.e., betweenness centrality and degree centrality). The visualization and the analysis of the network showed interesting facts about the collaboration patterns among the Iraqi parties. This work also showed that network science is useful in analyzing complex and highly related data. It can also reveal some hidden patterns that might be existed within the data.
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