Practical unicast and convergecast scheduling schemes for cognitive radio networks

Cognitive Radio Networks (CRNs) have paved a road for Secondary Users (SUs) to opportunistically exploit unused spectrum without harming the communications among Primary Users (PUs). In this paper, practical unicast and convergecast schemes, which are overlooked by most of the existing works for CRNs, are proposed. We first construct a cell-based virtual backbone for CRNs. Then prove that SUs have positive probabilities to access the spectrum and the expected one hop delay is bounded by a constant, if the density of PUs is finite. According to this fact, we proposed a three-step unicast scheme and a two-phase convergecast scheme. We demonstrate that the induced delay from our proposed Unicast Scheduling (US) algorithm scales linearly with the transmission distance between the source and the destination. Furthermore, the expected delay of the proposed Convergecast Scheduling (CS) algorithm is proven to be upper bounded by $O(\log n + \sqrt{n/\log n})$ . To the best of our knowledge, this is the first study of convergecast in CRNs. Finally, the performance of the proposed algorithms is validated through simulations.     

Opportunity for Adult Bonding/Meaningful Neighborhood Roles and Life-Satisfaction among USA Middle School Students

This study investigated the relationship between adolescent life- satisfaction and bonding to adults/developing meaningful roles in the neighborhood within a pilot study of slightly modified version of the CDC Middle School Youth Risk Behavior Survey (MSYRBS) in a southern state in the USA. Overall, 43% of students reported that they were satisfied with their lives overall, and 34% reported that they experienced positive adult relationships and meaningful roles in their neighborhoods. After adjusting for socioeconomic status and family structure, differential associations were found between adolescent life satisfaction and bonding to adults/developing meaningful roles. Opportunities for adult bonding and meaningful roles in the neighborhood related to increased life satisfaction more strongly for Caucasian students than African-American students. Post-Hoc analyses suggest that the explanation for these differential relationships may involve socioeconomic status. *This research was conducted via the South Carolina Middle School Youth Risk Behaviour Survey funded by the CDC/Legacy Foundation, Atlanta, Georgia in cooperation with the South Carolina Department of Health & Environmental Control, Columbia, South Carolina.     

Using the institutional analysis and development (IAD) framework to analyze the acequias of El Río de las Gallinas,New Mexico

As population and economic growth increase urban water demands, and traditional irrigation plays a smaller role in direct subsistence in New Mexico, irrigators on small, traditional systems often feel threatened. This paper uses the Institutional Analysis and Development (IAD) framework to analyze the irrigation ditches of the Gallinas River, in San Miguel County, and aims to facilitate understanding of the persistent distrust some Gallinas irrigators feel toward city, state, and federal agencies. This distrust, sometimes due to a perception of differing property rights structures that result in what many irrigators feel is unfair treatment by various agencies, and sometimes to a simple lack of understanding, is often perpetuated by recounted stories of malfeasance. Degree of social capital, knowledge of water law, and technology vary greatly. While there are not many problems with outsiders, some of the larger ditches report very poor social capital.     

On the construction of k-connected m-dominating sets in wireless networks

Connected dominating sets (CDS) that serve as a virtual backbone are now widely used to facilitate routing in wireless networks. A k-connected m-dominating set (kmCDS) is necessary for fault tolerance and routing flexibility. In order to construct a kmCDS with the minimum size, some approximation algorithms have been proposed in literature. However, the proposed algorithms either only consider some special cases where k=1, 2 or k≤m, or not easy to implement, or cannot provide performance ratio. In this paper, we propose a centralized heuristic algorithm, CSAA, which is easy to implement, and two distributed algorithms, DDA and DPA, which are deterministic and probabilistic methods respectively, to construct a kmCDS for general k and m. Theoretical analysis and simulation results indicate that our algorithms are efficient and effective.