Computing server power modeling in a data center: survey,taxonomy and performance evaluation

Data centers are large scale, energy-hungry infrastructure serving the increasing computational demands as the world is becoming more connected in smart cities. The emergence of advanced technologies such as cloud-based services, internet of things (IoT) and big data analytics has augmented the growth of global data centers, leading to high energy consumption. This upsurge in energy consumption of the data centers not only incurs the issue of surging high cost (operational and maintenance) but also has an adverse effect on the environment. Dynamic power management in a data center environment requires the cognizance of the correlation between the system and hardware level performance counters and the power consumption. Power consumption modeling exhibits this correlation and is crucial in designing energy-efficient optimization strategies based on resource utilization. Several works in power modeling are proposed and used in the literature. However, these power models have been evaluated using different benchmarking applications, power measurement techniques and error calculation formula on different machines. In this work, we present a taxonomy and evaluation of 24 software-based power models using a unified environment, benchmarking applications, power measurement technique and error formula, with the aim of achieving an objective comparison. We use different servers architectures to assess the impact of heterogeneity on the models' comparison. The performance analysis of these models is elaborated in the paper

TimeTrader: Exploiting Latency Tail to Save Datacenter Energy for On-line Data-Intensive Applications

Datacenters running on-line, data-intensive applications (OLDIs) consume significant amounts of energy. However, reducing their energy is challenging due to their tight response time requirements. A key aspect of OLDIs is that each user query goes to all or many of the nodes in the cluster, so that the overall time budget is dictated by the tail of the replies' latency distribution; replies see latency variations both in the network and compute. Previous work proposes to achieve load-proportional energy by slowing down the computation at lower datacenter loads based directly on response times (i.e., at lower loads, the proposal exploits the average slack in the time budget provisioned for the peak load). In contrast, we propose TimeTrader to reduce energy by exploiting the latency slack in the sub- critical replies which arrive before the deadline (e.g., 80% of replies are 3-4x faster than the tail). This slack is present at all loads and subsumes the previous work's load-related slack. While the previous work shifts the leaves' response time distribution to consume the slack at lower loads, TimeTrader reshapes the distribution at all loads by slowing down individual sub-critical nodes without increasing missed deadlines. TimeTrader exploits slack in both the network and compute budgets. Further, TimeTrader leverages Earliest Deadline First scheduling to largely decouple critical requests from the queuing delays of sub- critical requests which can then be slowed down without hurting critical requests. A combination of real-system measurements and at-scale simulations shows that without adding to missed deadlines, TimeTrader saves 15-19% and 41-49% energy at 90% and 30% loading, respectively, in a datacenter with 512 nodes, whereas previous work saves 0% and 31-37%.Comment: 13 page

Дослідження системи операційного менеджменту організації, на прикладі Apple Computer, Inc

The object of investigation is the process of managing of operating activities of Apple, Inc. The aim of the work is to formulate theoretical approaches and to develop practical recommendations on directions of improvement of operating management at the organization. Research methods cover methods of analysis, synthesis, comparison, detailing, system approach. This master’s research paper analyzes the operational management of Apple, Inc. and provides recommendations for it’s improvement. In particular, the main directions of solving the problems of operational management of the company have been outlined, the proposals on improvement of expansion distribution network and organization of innovative activity of the Apple Inc. have been made.Об'єкт дослідження ‒ процес управління операційною діяльністю компанії Apple, Inc. Мета дослідження - формування теоретичних підходів та розробка практичних рекомендацій щодо напрямів вдосконалення системи операційного менеджменту компанії Apple, Inc. Методи дослідження: методи аналізу, синтезу, порівняння, деталізації, системний підхід. У роботі проведено аналіз операційного менеджменту Apple, Inc., а також викладені рекомендації щодо його вдосконалення. Зокрема, окреслено основні напрями вирішення проблем операційного менеджменту компанії, внесено пропозиції щодо розширення дистриб’юторської мережі, а також вдосконалення організації інноваційної діяльності Apple Inc.Introduction 6 CHAPTER 1 THE THEORETICAL FRAMEWORK OF OPERATIONAL MANAGEMENT 8 1.1 Meanings and definition of operational management 8 1.2 Principles and methods of operations management 12 1.3 Factors affecting the Operations activity of Apple Inc. company 21 CHAPTER 2 RESEARCH AND ANALYSIS 31 2.1 Сompany introduction 31 2.2 SWOT - analysis of Apple Inc. Company 46 2.3 Analysis of operation management at Apple Inc 50 CHAPTER 3 RECOMMENDATIONS FOR IMPROVING OF OPERATIONAL MANAGEMENT AT THE APPLE INC 63 3.1 The main directions of solving operational management problems of the company 63 3.2 Recommendations concerning improvements of Distribution in the organization 65 3.3 Recommendations concerning improvements of innovative activity at the organization 67 CHAPTER 4 SPECIAL PART 73 4.1 Current trends in the field 73 4.2 Company policy in the market 75 CHAPTER 5 RATIONALE FOR RECOMMENDATIONS 77 5.1 Statement for recommendations at Company 77 CHAPTER 6 OCCUPATIONAL HEALTH AND SAFETY AT THE ENTERPRISE 79 6.1 The aim of occupational health 79 6.2 Organization of occupational health and safety at the enterprise 86 CHAPTER 7 ENVIRONMENTAL ISSUES 92 7.1 Environmental issues in the field 92 7.2 Еnvironmental factors 94 Conclusions 96 References 98 Appendices 10