An energy-efficient cuckoo search algorithm for virtual machine placement in cloud computing data centers

The Journal of Supercomputing - The advent of virtualization technology has created a huge potential application for cloud computing. In virtualization, a large hardware resource is often broken...     

Comparative light and scanning electron microscopy in authentication of adulterated traded medicinal plants

The medicinal plants are utilized globally considering the cheap and chemical free source, but their correct identification and authentication is prerequisite for safety and efficacy of plant‐based medicines. The present study encompassed traded medicinal plants (16) with high therapeutic value from diverse families like Brassicaceae, Berberidaceae, Malvaceae, Salicaceae, Myrtaceae, Papilionaceae, Ascelpiadaceae, Colchicaceae, Violaceae, and Vitaceae for detailed microscopic study of characters that is, morphology, pollen shape and sizes, P/E ratio, pore length and width, spine length, colpi dimensions, and exine sculpture pattern. The plants showed noteworthy differences in microscopy of Wattakaka volubilis having pollinia, translator and corpusculum like structures while pores were visible in Colchicum luteum, Alcea rosea, and Hibiscus syriacus. The spines were observed in Centipeda minima, A. rosea, and H. syriacus being dimorphic spines in A. rosea and monomorphic in H. syriacus. The exine sculpturing pattern was reticulate in mostly studied plants however distinctive exine pattern was noted in Berberis aristata and Berberis lyceum. The highest polar diameter, equatorial diameter and exine thickness among studied plants were observed in H. syriacus (161 μm), C. luteum (50 μm) and Vitis jacquemontii (1.10), respectively. Thus, microscopy of medicinal plants in addition to other taxonomic evidence offers a supportive skill in authentication, consequently utilization by local consumers and pharmaceutical industries.     

A health-based life cycle impact assessment (LCIA) for cement manufacturing: a comparative study of China and Canada

Life cycle impact assessment methodology was applied to the cement manufacturing sectors in China and Canada for comparative purposes. Primary air emissions of NO _x , SO₂, PM, and CO were evaluated in terms of intensity per tonne of Portland cement and in respect of their contribution to winter smog. The Eco-Indicator 99 impact category for respiratory effects on humans caused by inorganic substances was used as surrogate for winter smog. Impact was assessed in disability-adjusted life years (DALYs), and damage, normalization, and weighting factors followed the egalitarian perspective. Results indicate some ambiguity for emission intensities with China outperforming Canada in NO _x and SO₂ while underperforming in PM and CO. However, in terms of impact to human health, China was more than double that of Canada at 14.2 DALYs per tonne of Portland cement. Highlighted by energy-intensive and trade-exposed industry like cement, environmental performance, and emissions leakage (associated with offshoring production) can have serious ramifications on regional air quality. Modernization and innovation in combination with a strong regulatory framework needs to be implemented in both emerging markets and developed markets to minimize emissions leakage and pollution loading.     

Water use in unconventional oil and gas development: an assessment on water use metric evaluation and selection

This study identifies five data input categories essential to quantifying water use and the environmental impacts via water use metrics (i.e., Water Footprints) when evaluating water use during upstream unconventional oil and gas. Published water use metrics, which included provisions for addressing each of the five categories, were selected for evaluation. The selected metrics were compared and evaluated against data parameters defined within each of the input categories. Finally, a decision tree for method selection, which differentiates between assessment mechanisms, impact indicator, and result units, is presented to facilitate method selection of future studies of water use in unconventional oil and gas development.     

Cuckoo search based resource optimization of datacenters

With advancements in virtualization technology, datacenters are often faced with the challenge of managing large numbers of virtual machine (VM) requests. Due to this large amount of VM requests, it has become practically impossible to search all possible VM placements in order to find a solution that best optimizes certain design objectives. As a result, managers of datacenters have resorted to the employment of heuristic optimization algorithms for VM placement. In this paper, we employ the cuckoo search optimization (CSO) algorithm to solve the VM placement problem of datacenters. Firstly, we use the CSO to optimize the datacenter for the minimization of the number of physical machines used for placement. Secondly, we implement a multiobjective CSO algorithm to simultaneously optimize the power consumption and resource wastage of the datacenter. Simulation results show that both CSO algorithms outperform the reordered grouping genetic algorithm (RGGA), the grouping genetic algorithm (GGA), improved least-loaded (ILL) and improved FFD (IFFD) methods of VM placement.     

Anonymous proximity mobile payment (APMP)

The growth of wireless networks and the increasing popularity of mobile devices present an significant opportunity to empower them as a payment device. Unfortunately, several problems hinder the widespread acceptance of mobile payments, for example, privacy protection and user anonymity. Measures to ensure anonymity in payment systems must be considered as an important factor in privacy and system acceptance. We propose a new measure to enhance the level of anonymity in mobile payments where users can customize their anonymity, according to their personal preferences. We rely on IPAS (Implicit Password Authentication System) (Almuairfi et al. 2011) for dispute resolution to support our proposed idea.     

Binary particle swarm optimization (BPSO) based state assignment for area minimization of sequential circuits

State assignment (SA) for finite state machines (FSMs) is one of the main optimization problems in the synthesis of sequential circuits. It determines the complexity of its combinational circuit and thus area, delay, testability and power dissipation of its implementation. Particle swarm optimization (PSO) is a non-deterministic heuristic that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. PSO optimizes a problem by having a population of candidate solutions called particles, and moving them around in the search-space according to a simple mathematical formulae. In this paper, we propose an improved binary particle swarm optimization (BPSO) algorithm and demonstrate its effectiveness in solving the state assignment problem in sequential circuit synthesis targeting area optimization. It will be an evident that the proposed BPSO algorithm overcomes the drawbacks of the original BPSO algorithm. Experimental results demonstrate the effectiveness of the proposed BPSO algorithm in comparison to other BPSO variants reported in the literature and in comparison to Genetic Algorithm (GA), Simulated Evolution (SimE) and deterministic algorithms like Jedi and Nova.     

N-Body Simulation Inspired by Metaheuristics Optimization

The N-body problem in classical physics, is the calculation of force of gravitational attraction of heavenly bodies towards each other. Solving this problem for many heavenly bodies has always posed a challenge to physicists and mathematicians. Large number of bodies, huge masses, long distances and exponentially increasing number of equations of motion of the bodies have been the major hurdles in solving this problem for large and complex galaxies. Advent of high performance computational machines have mitigated the problem to much extent, but still for large number of bodies it consumes huge amount of resources and days for computation. Conventional algorithms have been able to reduce the computational complexity from to by splitting the space into a tree or mesh network, researchers are still looking for improvements. In this research work we propose a novel solution to N-body problem inspired by metaheuristics algorithms. The proposed algorithm is simulated for various time periods of selected heavenly bodies and analyzed for speed and accuracy. The results are compared with that of conventional algorithms. The outcomes show about 50% time saving with almost no loss in accuracy. The proposed approach being a metaheuristics optimization technique, attempts to find optimal solution to the problem, searching the entire space in a unique and efficient manner in a very limited amount of time.     

Rethinking investment planning and optimizing net zero emission buildings

Increased awareness of climate change has precipitated more stringent mitigation targets. Public sector institutions in Canada are committed to becoming carbon neutral to attain a leadership position in climate change mitigation-related initiatives. Recent statistics reveal that buildings account for the majority of the corporate carbon footprint of public sector institutions. Hence, there is an increasing interest towards developing net zero energy and net zero emission buildings to comply with climate action targets. With limited financial resources, public sector institutions must optimize investments into building energy retrofits by considering lifecycle cost (LCC), overall energy performance, and related greenhouse gas (GHG) emission. The aim of this paper is to develop an investment planning approach for net zero emission buildings (NZEB). First, an investment planning approach for NZEB is proposed. A typical recreational centre building in British Columbia, Canada, was used as the archetype to demonstrate the concept. Second, innovative and proven building energy retrofits were analysed using energy simulation software to assess the impact on energy consumption reduction, GHG emissions, and LCC. Third, impacts of geographical location, tariff regimes, and grid emission factors on energy retrofits were studied by locating the same building in other provinces of Canada. This study revealed that net zero energy investment has a strong correlation to the grid emission factor. The proposed approach in this paper will assist building managers and owners in retrofitting and budget planning.