Dynamic resource scheduling in cloud radio access network with mobile cloud computing

Nowadays, by integrating the cloud radio access network (C-RAN) with the mobile cloud computing (MCC) technology, mobile service provider (MSP) can efficiently handle the increasing mobile traffic and enhance the capabilities of mobile users' devices to provide better quality of service (QoS). But the power consumption has become skyrocketing for MSP as it gravely affects the profit of MSP. Previous work often studied the power consumption in C-RAN and MCC separately while less work had considered the integration of C-RAN with MCC. In this paper, we present a unifying framework for optimizing the power-performance tradeoff of MSP by jointly scheduling network resources in C-RAN and computation resources in MCC to minimize the power consumption of MSP while still guaranteeing the QoS for mobile users. Our objective is to maximize the profit of MSP. To achieve this objective, we first formulate the resource scheduling issue as a stochastic problem and then propose a Resource onlIne sCHeduling (RICH) algorithm using Lyapunov optimization technique to approach a time average profit that is close to the optimum with a diminishing gap (1/V) for MSP while still maintaining strong system stability and low congestion to guarantee the QoS for mobile users. With extensive simulations, we demonstrate that the profit of RICH algorithm is 3.3× (18.4×) higher than that of active (random) algorithm

Diazido­bis(2,2′-biimidazole)cobalt(II)

In the title compound, [Co(N3)2(C6H6N4)2], the CoII atom lies on a centre of inversion and is bonded to two azide ions and two bidentate 2,2′-biimidizole ligands, giving a slightly distorted octa­hedral CoN6 coordination geometry. In the crystal structure, inter­molecular N—H⋯N hydrogen bonds exist between the 2,2′-biimidizole ligands and the azide ions, linking the complexes into sheets

Dynamic Resource Scheduling in Mobile Edge Cloud with Cloud Radio Access Network

Nowadays, by integrating the cloud radio access network (C-RAN) with the mobile edge cloud computing (MEC) technology, mobile service provider (MSP) can efficiently handle the increasing mobile traffic and enhance the capabilities of mobile devices. But the power consumption has become skyrocketing for MSP and it gravely affects the profit of MSP. Previous work often studied the power consumption in C-RAN and MEC separately while less work had considered the integration of C-RAN with MEC. In this paper, we present an unifying framework for the power-performance tradeoff of MSP by jointly scheduling network resources in C-RAN and computation resources in MEC to maximize the profit of MSP. To achieve this objective, we formulate the resource scheduling issue as a stochastic problem and design a new optimization framework by using an extended Lyapunov technique. Specially, because the standard Lyapunov technique critically assumes that job requests have fixed lengths and can be finished within each decision making interval, it is not suitable for the dynamic situation where the mobile job requests have variable lengths. To solve this problem, we extend the standard Lyapunov technique and design the VariedLen algorithm to make online decisions in consecutive time for job requests with variable lengths. Our proposed algorithm can reach time average profit that is close to the optimum with a diminishing gap (1/V) for the MSP while still maintaining strong system stability and low congestion. With extensive simulations based on a real world trace, we demonstrate the efficacy and optimality of our proposed algorithm

Anti-apoptotic and neuroprotective effects of Tetramethylpyrazine following spinal cord ischemia in rabbits

BACKGROUND: Tetramethylpyrazine (TMP) is one of the most important active ingredients of a Chinese herb Ligusticum wallichii Franchat, which is widely used in many ischemia disorders treatments. However, the exact mechanism by which TMP protects the spinal cord ischemia/reperfusion (I/R) injury is still unknown. For this purpose, rabbits were randomly divided into sham group, control group and TMP group. After the evaluation of neurologic function, the spinal cords were immediately removed for biochemical and histopathological analysis. Apoptosis was measured quantitatively by the terminal transferase UTP nick end-labeling (TUNEL) method and confirmed by electron microscopic examination, the expression of Bax and Bcl-2 was immunohistochemically evaluated and quantified by Western blot analysis. RESULTS: Neurologic outcomes in the TMP-group were significantly better than those in the control group (P < 0.05). TMP decreased spinal cord malondialdehyde (MDA) levels and ameliorated the down regulation of spinal cord superoxide dismutase (SOD) activity. TMP significantly reduced the loss of motoneurons and TUNEL-positive rate. Greater Bcl-2 and attenuated Bax expression was found in the TMP treating rabbits. CONCLUSION: These findings suggest that TMP has protective effects against spinal cord I/R injury by reducing apoptosis through regulating Bcl-2 and Bax expression

Maximizing the Profit of Cloud Broker with Priority Aware Pricing

A practical problem facing Infrastructure-as-a-Service (IaaS) cloud users is how to minimize their costs by choosing different pricing options based on their own demands. Recently, cloud brokerage service is introduced to tackle this problem. But due to the perishability of cloud resources, there still exists a large amount of idle resource waste during the reservation period of reserved instances. This idle resource waste problem is challenging cloud broker when buying reserved instances to accommodate users' job requests. To solve this challenge, we find that cloud users always have low priority jobs (e.g., non latency-sensitive jobs) which can be delayed to utilize these idle resources. With considering the priority of jobs, two problems need to be solved. First, how can cloud broker leverage jobs' priorities to reserve resources for profit maximization? Second, how to fairly price users' job requests with different priorities when previous studies either adopt pricing schemes from IaaS clouds or just ignore the pricing issue. To solve these problems, we first design a fair and priority aware pricing scheme, PriorityPricing, for the broker which charges users with different prices based on priorities. Then we propose three dynamic algorithms for the broker to make resource reservations with the objective of maximizing its profit. Experiments show that the broker's profit can be increased up to 2.5× than that without considering priority for offline algorithm, and 3.7× for online algorithm

Resolution of secondary pulmonary alveolar proteinosis following treatment of rhinocerebral aspergillosis

SummaryPulmonary alveolar proteinosis can be secondary to inhaled dust exposure, malignancy, and chronic pulmonary infections. However, pulmonary alveolar proteinosis secondary to extrapulmonary aspergillosis has never been reported. We report herein a case of pulmonary alveolar proteinosis secondary to invasive rhinocerebral aspergillosis. Neither immune modulators nor whole lung lavage was applied during the treatment course. The severe respiratory distress subsided, hypoxia resolved, and radiological infiltrates improved following the successful treatment of invasive rhinocerebral aspergillosis alone

Bis{μ-2,2′-[ethane-1,2-diylbis(nitrilo­methyl­idyne)]diphenolato}bis­[(thio­cyanato)manganese(III)]

The reported structure is a monoclinic polymorph of the title compound, [Mn2(C16H14N2O2)2(NCS)2], which has been characterized previously in an ortho­rhom­bic form. Each MnIII atom is chelated by a tetra­dentate 2,2′-[ethane-1,2-diylbis(nitrilo­methyl­idyne)]diphenolate ligand and by the N atom of a thio­cyanate anion, in a square-pyramidal arrangement. The complexes form centrosymmetric dimers, with an Mn—O contact of 2.557 (3) Å trans to each thio­cyanate anion, completing a distorted octa­hedral coordination geometry