Maximum Outage Capacity in Dense Indoor Femtocell Networks with Joint Energy and Spectrum Utilization

We consider a multiple femtocell deployment in a small area which shares spectrum with the underlaid macrocell. We design a joint energy and radio spectrum scheme which aims not only for co-existence with the macrocell, but also for an energy-efficient implementation of the multi-femtocells. Particularly, aggregate energy usage on dense femtocell channels is formulated taking into account the cost of both the spectrum and energy usage. We investigate an energy-and-spectral efficient approach to balance between the two costs by varying the number of active sub-channels and their energy. The proposed scheme is addressed by deriving closed-form expressions for the interference towards the macrocell and the outage capacity. Analytically, discrete regions under which the most promising outage capacity is achieved by the same size of active sub-channels are introduced. Through a joint optimization of the sub-channels and their energy, properties can be found for the maximum outage capacity under realistic constraints. Using asymptotic and numerical analysis, it can be noticed that in a dense femtocell deployment, the optimum utilization of the energy and the spectrum to maximize the outage capacity converges towards a round-robin scheduling approach for a very small outage threshold. This is the inverse of the traditional greedy approach. © 2012 IEEE.

Utilization of organophosphonates by environmental microorganisms

A survey of the utilization by environmental micro-organisms of a range of compounds containing the carbon-phosphorus (C-P) bond was carried out. Elective culture studies indicated that 15 of 19 alkylphosphonates tested served only as a sole source of phosphorus for microbial growth. Their metabolism did not lead to the extracellular release of inorganic phosphate. However, four organophosphonates - phosphonoacetate, phosphonoalanine, 2-aminoethylphosphonate and phosphonomycin - supported microbial growth when supplied as either a phosphorus source or as a carbon and energy source, with near-quantitative inorganic phosphate release. Four of five amino alkylphosphonates tested were also utilized as a nitrogen source in the presence of 1 mmol l(-1) inorganic phosphate. In a subsequent screening programme, 99% of bacterial isolates tested were able to utilize 2-aminoethylphosphonate as a sole phosphorus source, 61% as a nitrogen source, 10% as a source of nitrogen and phosphorus, and 2% as a source of carbon, nitrogen and phosphorus; 2% of isolates used phosphonoalanine as a nitrogen source. These results suggest that the uptake and metabolism of organophosphonates by bacteria is less 'tightly' regulated by phosphorus starvation than has previously been supposed.

Strategies for Energy-Efficient Resource Management of Hybrid Programming Models

Many scientific applications are programmed using hybrid programming models that use both message passing and shared memory, due to the increasing prevalence of large-scale systems with multicore, multisocket nodes. Previous work has shown that energy efficiency can be improved using software-controlled execution schemes that consider both the programming model and the power-aware execution capabilities of the system. However, such approaches have focused on identifying optimal resource utilization for one programming model, either shared memory or message passing, in isolation. The potential solution space, thus the challenge, increases substantially when optimizing hybrid models since the possible resource configurations increase exponentially. Nonetheless, with the accelerating adoption of hybrid programming models, we increasingly need improved energy efficiency in hybrid parallel applications on large-scale systems. In this work, we present new software-controlled execution schemes that consider the effects of dynamic concurrency throttling (DCT) and dynamic voltage and frequency scaling (DVFS) in the context of hybrid programming models. Specifically, we present predictive models and novel algorithms based on statistical analysis that anticipate application power and time requirements under different concurrency and frequency configurations. We apply our models and methods to the NPB MZ benchmarks and selected applications from the ASC Sequoia codes. Overall, we achieve substantial energy savings (8.74 percent on average and up to 13.8 percent) with some performance gain (up to 7.5 percent) or negligible performance loss.

A Reliability Assessment Approach for the Urban Energy System and Its Application in Energy Hub Planning

With the increasing utilization of combined heat and power plants (CHP), electrical, gas, and thermal systems are becoming tightly integrated in the urban energy system (UES). However, the three systems are usually planned and operated separately, ignoring their interactions and coordination. To address this issue, the coupling point of different systems in the UES is described by the energy hub model. With this model, an integrated load curtailment method is proposed for the UES. Then a Monte Carlo simulation based approach is developed to assess the reliability of coordinated energy supply systems. Based on this approach, a reliability-optimal energy hub planning method is proposed to accommodate higher renewable energy penetration. Numerical studies indicate that the proposed approach is able to quantify the UES reliability with different structures. Also, optimal energy hub planning scheme can be determined to ensure the reliability of the UES with high renewable penetration.