Extending Demand Response to Tenants in Cloud Data Centers via Non-intrusive Workload Flexibility Pricing

Participating in demand response programs is a promising tool for reducing energy costs in data centers by modulating energy consumption. Towards this end, data centers can employ a rich set of resource management knobs, such as workload shifting and dynamic server provisioning. Nonetheless, these knobs may not be readily available in a cloud data center (CDC) that serves cloud tenants/users, because workloads in CDCs are managed by tenants themselves who are typically charged based on a usage-based or flat-rate pricing and often have no incentive to cooperate with the CDC operator for demand response and cost saving. Towards breaking such "split incentive" hurdle, a few recent studies have tried market-based mechanisms, such as dynamic pricing, inside CDCs. However, such mechanisms often rely on complex designs that are hard to implement and difficult to cope with by tenants. To address this limitation, we propose a novel incentive mechanism that is not dynamic, i.e., it keeps pricing for cloud resources unchanged for a long period. While it charges tenants based on a Usage-based Pricing (UP) as used by today's major cloud operators, it rewards tenants proportionally based on the time length that tenants set as deadlines for completing their workloads. This new mechanism is called Usage-based Pricing with Monetary Reward (UPMR). We demonstrate the effectiveness of UPMR both analytically and empirically. We show that UPMR can reduce the CDC operator's energy cost by 12.9% while increasing its profit by 4.9%, compared to the state-of-the-art approaches used by today's CDC operators to charge their tenants

Energy Portfolio Optimization of Data Centers

Data centers have diverse options to procure electricity. However, the current literature on exploiting these options is very fractured. Specifically, it is still not clear how utilizing one energy option may affect selecting other energy options. To address this open problem, we propose a unified energy portfolio optimization framework that takes into consideration a broad range of energy choices for data centers. Despite the complexity and nonlinearity of the original models, the proposed analysis boils down to solving tractable linear mixed-integer stochastic programs. Using experimental electricity market and Internet workload data, various insightful numerical observations are reported. It is shown that the key to link different energy options with different short- and long-term profit characteristics is to conduct risk management at different time horizons. Also, there is a direct relationship between data centers' service-level agreement parameters and their ability to exploit certain energy options. The use of on-site storage and the deployment of geographical workload distribution can particularly help data centers in utilizing high-risk energy choices, such as offering ancillary services or participating in wholesale electricity markets

The Effect of Job Stress on Nurses' Caring Behaviors and Quality of Life Related to Their Health in Coronavirus Pandemic

Introduction: Stressed people are physically, psychologically, and behaviorally damaged. This study aimed to investigate the effect of job stress on nurses' caring behaviors and quality of life related to their health during Coronavirus pandemic.Methods: The present study is an applied and analytical research conducted cross-sectionally in 2021. The study's statistical population was 740 nurses from the hospitals of Mazandaran University of Medical Sciences. The authors randomly selected a sample of 253 nurses using Cochran's formula. The data collection tool was a standard questionnaire. The structural equation model test analyzed the collected data to measure the research hypotheses using SPSS 22 and Amos 22 softwareResults: The standard coefficient value between stress and caring behavior is -0.47, and the significant value (t-value) is greater than 1.96 (equal to 5.350) at 95% level; therefore, the relationship between these two variables was found significant. Moreover, the standard coefficient value between job stress and quality of work life is -0.55, and the significant value (t-value) is greater than 1.96 (equal to 6.488) at the 95% level, showing a significant relationship between these two variables.Conclusion: Considering the obtained results, it is necessary to develop effective strategies, such as staff participation in decision-making, supervisory support, and reducing work pressure for improving working conditions and reducing nurses’ occupational stress

Role of L- and T-Type Calcium Channels in Regulation of Absence Seizures in WAG/Rij Rats

In chronic experiments on five groups of WAG/Rij rats (a genetic model of absence epilepsy; six animals in each group), we recorded EEG activity from the S1po cortical area through implanted electrodes and subjected the cortex to the action of four agents affecting L- and T-type calcium channels (injections through an implanted cannula). A blocker of L-type channels, verapamil hydrochloride, an agonist of these channels, Bay K8644, an antagonist of T-type calcium channels, L-ascorbate, and an agonist of the latter channels, PMA, were used. The parameters of 7- to 10-Hz spike-wave discharges, SWDs, spontaneously generated in the cortex of this rat strain (frequency of SWDs, mean duration of the latter, and their number) were measured within the baseline interval (before injections) and within three subsequent 20-min-long post-injection intervals. Normal saline was injected in the control group. There were no significant differences in the mean peak frequency in SWDs between all examined groups (P > 0.05 in all cases). Verapamil significantly (by more than 40%; P < 0.05) decreased the mean SWD duration throughout the entire period of post-injection observation. The dynamics of the Bay K8644 effects were rather similar, but the intensity of SWD duration changes was somewhat smaller. Both the above agents in the doses used dramatically decreased the number (frequency of appearance) of SWDs within the observation period. L-ascorbate also suppressed SWD generation. The duration of these phenomena decreased mildly, while their number dropped dramatically. In the PMA group, the number of SWDs increased significantly (by 50%, P < 0.05) within the first 20-min-long interval, but this was not observed within subsequent intervals. These findings confirm that blocking or activating of L- and T-type Ca2+ channels in the S1po area (cortical focus area) can significantly control generation of SWDs during absence seizures. Possible mechanisms underlying actions of the tested agents are discussed.У хронічних експериментах на п’яти групах щурів лінії WAG/Rij (генетична модель абсанс-епілепсії; шість тварин у кожній групі) ми відводили ЕЕГ-активність від кортикальної зони S1po через імплантовані електроди і піддавали кору дії чотирьох агентів, що впливають на кальцієві канали L- та T-типів (ін’єкції через імплантовану канюлю). Використовували блокатор кальцієвих каналів L-типу верапамілу гідрохлорид, агоніст цих каналів Bay K8644, антагоніст кальцієвих каналів T-типу L-аскорбат та агоніст останніх каналів PMA. Вимірювали параметри розрядів пік-хвиля (РПХ, частота 7–10 Гц), котрі спонтанно генеруються у корі головного мозку щурів указаної лінії (частоту в межах РПХ, середню тривалість останніх та їх кількість) протягом інтервалу порівняння (перед ін’єкціями) та трьох послідовних 20-хвилинних інтервалів після ін’єкцій. Щурам контрольної групи ін’єкували фізіологічний розчин. Істотних різниць між величинами частоти в межах РПХ у всіх досліджених групах не спостерігалося (P > 0.05 у всіх випадках). Верапаміл істотно (більш ніж на 40 %; P < 0.05) зменшував середню тривалість РПХ протягом усього періоду спостереження після ін’єкцій. Динаміка ефектів Bay K8644 була вельми подібною, але інтенсивність скорочення тривалості РПХ – дещо меншою. Обидва вказані агенти у використаних дозах зумовлювали драматичне зменшення кількості (тобто частоти виникнення) РПХ протягом усього періоду спостереження. L-аскорбат також істотно пригнічував генерацію РПХ. Тривалість цих феноменів зменшувалася помірно, а їх кількість скорочувалася дуже сильно. У групі РМА кількість РПХ протягом першого 20-хвилинного інтервалу спостереження істотно зростала (на 50 % , P < 0.05), але цього не спостерігалося в межах наступних інтервалів. Наші результати підтверджують, що блокування або активація кальцієвих каналів L- та T-типів у фокальній кортикальній зоні S1po здатні істотно контролювати генерацію РПХ під час прояву абсансних судом. Обговорюються можливі механізми дії тестованих агентів

Optimal Operation of Data Centers in Future Smart Grid

The emergence of cloud computing has established a growing trend towards building massive, energy-hungry, and geographically distributed data centers. Due to their enormous energy consumption, data centers are expected to have major impact on the electric grid by significantly increasing the load at locations where they are built. However, data centers also provide opportunities to help the grid with respect to robustness and load balancing. For instance, as data centers are major and yet flexible electric loads, they can be proper candidates to offer ancillary services, such as voluntary load reduction, to the smart grid. Also, data centers may better stabilize the price of energy in the electricity markets, and at the same time reduce their electricity cost by exploiting the diversity in the price of electricity in the day-ahead and real-time electricity markets. In this thesis, such potentials are investigated within an analytical profit maximization framework by developing new mathematical models based on queuing theory. The proposed models capture the trade-off between quality-of-service and power consumption in data centers. They are not only accurate, but also they posses convexity characteristics that facilitate joint optimization of data centers' service rates, demand levels and demand bids to different electricity markets. The analysis is further expanded to also develop a unified comprehensive energy portfolio optimization for data centers in the future smart grid. Specifically, it is shown how utilizing one energy option may affect selecting other energy options that are available to a data center. For example, we will show that the use of on-site storage and the deploymentof geographical workload distribution can particularly help data centers in utilizing high-risk energy options such as renewable generation. The analytical approach in this thesis takes into account service-level-agreements, risk management constraints, and also the statistical characteristics of the Internet workload and the electricity prices. Using empirical data, the performance of our proposed profit maximization models for data centers are evaluated, and the capability of data centers to benefit from participation in a variety of Demand Response programs is assessed

Transactive Energy to Thwart Load Altering Attacks on Power Distribution Systems

The automatic generation control mechanism in power generators comes into operation whenever an over-supply or under-supply of energy occurs in the power grid. It has been shown that the automatic generation control mechanism is highly vulnerable to load altering attacks. In this type of attack, the power consumption of multiple electric loads in power distribution systems is remotely altered by cyber attackers in such a way that the automatic generation control mechanism is disrupted and is hindered from performing its pivotal role. The existing literature on load altering attacks has studied implementation, detection, and location identification of these attacks. However, no prior work has ever studied design of an attack-thwarting system that can counter load altering attacks, once they are detected in the power grid. This paper addresses the above shortcoming by proposing an attack-thwarting system for countering load altering attacks. The proposed system is based on provoking real-time adjustment in power consumption of the flexible loads in response to the frequency disturbances caused by the load altering attacks. To make the adjustments in-proportion to the frequency disturbances, the proposed attack-thwarting system uses a transactive energy framework to establish a coordination between the flexible loads and the power grid operator

Optimal risk-aware power procurement for data centers in day-ahead and real-time electricity markets

Abstract — With the growing trend in the amount of power consumed by data centers, finding ways to cut their electricity bills has become an important and challenging problem. In this paper, our focus is on the cost reduction that data centers may achieve by exploiting the diversity in the price of electricity in day-ahead and real-time electricity markets. Based on a stochas-tic optimization framework, we propose to jointly select a data center’s service rate and its power demand bids to the day-ahead and real-time electricity markets. In our analysis, we take into account service-level-agreements, risk management constraints, and statistical characteristics of workload and electricity prices. Using empirical electricity price and Internet workload data and through computer simulations, we show that by directly participating in the day-ahead and real-time electricity markets, data centers can significantly reduce their energy expenditure