A Power Dissipation Comparison of the R-TDMA and the Slotted-Aloha Wireless MAC protocols

In this paper two wireless multiple-access protocols are compared by their power dissipation for the uplink traffic of a wireless networks. After briefly discussing the behaviour of the Slotted Aloha protocol (Abramson, 1985) and the R-TDMA protocol (Linnenbank, 1995), we estimate the energy that is dissipated by the protocols to trasmit a packet. We will show that for general loads, the power dissipation of the R-TDMA protocol is far less than that of the Slotted Aloha protocol

Evaluating power efficient algorithms for efficiency and carbon emissions in cloud data centers: a review

A data center comprises of servers, storage devices, cooling and power delivery equipment to support other components, exchange data and information to provide general services such as software-as-a-service (SaaS), Platform-as-a-Service (PaaS)and Internet-as-a-Service (IaaS). Data center require massive amount of computational power to drive complex systems. In return these massive systems bring many challenges and concerns including power dissemination and environmental sustainability. Higher power demand in data centers and changes in computing technology together to maximize data center performance has led to deploying multitude methods to estimate power intensity. Energy cost increment, global economic downturn, and global warming and other concerns have resulted in new research in achieving power efficient data centers. The research proposed in this paper evaluates three task scheduling algorthms RASA, TPPC, and PALB to get the most energy efficient task scheduling algorithms to be used in data centers for measuring their performance and efficiency. The three algorithms are evaluated for performance using three parameters; power efficiency, cost effectiveness, and amount of CO2 emissions. On top of that data center location and climate conditions are also considered and analyzed as parameters as they directly effect the operating costs, the amount of power consumption and CO2 emission. To minimize the power wasted by data center cooling systems is directly related to data center location and climate change. CloudSim simulator is used to implement the algorithms on an IaaS cloud infrastructure, to calculate the power consumption, and to analyze each algorithm's behavior for different parameters. The results generated clearly shows tha TPPC is the most efficient algorithm due to less amount of power consumption and low volume of CO2 emission; However its implementation cost is bit higher compare to PALB and RASA

Adaptive Wireless Networking

This paper presents the Adaptive Wireless Networking (AWGN) project. The project aims to develop methods and technologies that can be used to design efficient adaptable and reconfigurable mobile terminals for future wireless communication systems. An overview of the activities in the project is given. Furthermore our vision on adaptivity in wireless communications and suggestions for future activities are presented

Direct NN-body code on low-power embedded ARM GPUs

This work arises on the environment of the ExaNeSt project aiming at design and development of an exascale ready supercomputer with low energy consumption profile but able to support the most demanding scientific and technical applications. The ExaNeSt compute unit consists of densely-packed low-power 64-bit ARM processors, embedded within Xilinx FPGA SoCs. SoC boards are heterogeneous architecture where computing power is supplied both by CPUs and GPUs, and are emerging as a possible low-power and low-cost alternative to clusters based on traditional CPUs. A state-of-the-art direct $N$-body code suitable for astrophysical simulations has been re-engineered in order to exploit SoC heterogeneous platforms based on ARM CPUs and embedded GPUs. Performance tests show that embedded GPUs can be effectively used to accelerate real-life scientific calculations, and that are promising also because of their energy efficiency, which is a crucial design in future exascale platforms.Comment: 16 pages, 7 figures, 1 table, accepted for publication in the Computing Conference 2019 proceeding

Analysis of a Cone-Based Distributed Topology Control Algorithm for Wireless Multi-hop Networks

The topology of a wireless multi-hop network can be controlled by varying the transmission power at each node. In this paper, we give a detailed analysis of a cone-based distributed topology control algorithm. This algorithm, introduced in [16], does not assume that nodes have GPS information available; rather it depends only on directional information. Roughly speaking, the basic idea of the algorithm is that a node $u$ transmits with the minimum power $p_{u,\alpha}$ required to ensure that in every cone of degree $\alpha$ around $u$, there is some node that $u$ can reach with power $p_{u,\alpha}$. We show that taking $\alpha = 5\pi/6$ is a necessary and sufficient condition to guarantee that network connectivity is preserved. More precisely, if there is a path from $s$ to $t$ when every node communicates at maximum power, then, if $\alpha <= 5\pi/6$, there is still a path in the smallest symmetric graph $G_\alpha$ containing all edges $(u,v)$ such that $u$ can communicate with $v$ using power $p_{u,\alpha}$. On the other hand, if $\alpha > 5\pi/6$, connectivity is not necessarily preserved. We also propose a set of optimizations that further reduce power consumption and prove that they retain network connectivity. Dynamic reconfiguration in the presence of failures and mobility is also discussed. Simulation results are presented to demonstrate the effectiveness of the algorithm and the optimizations.Comment: 10 page

Теорія, методи та методики діагностики аеродинамічного стану зовнішнього обводу літального апарата у польоті

1. Розроблено: концепція, теорія, методи та методики діагностування аеродинамічного стану зовнішнього обводу ЛА у польоті, які дозволять підвищити безпеку польотів за рахунок своєчасного визначення місця, ступеня та моменту раптового пошкодження зовнішнього обво- ду ЛА з метою своєчасного реагування на виникнення особливих ситуацій у польоті. 2. Розроблено методики для проведення експериментальних досліджень: - комплексу- вання інформаційно-вимірювальних датчиків: лінійних прискорень та кутових швидкостей або прискорень; - оптимізації місць розміщення інформаційно-вимірювальних датчиків; - зчитуван- ня і виділення корисної інформації про стан зовнішнього обводу ЛА у польоті; - побудови «ба- зи класів» інтелектуального класифікатора, які дали основу для створення інтелектуальних сис- тем автоматичного діагностування (ІСАД), що забезпечує своєчасну реєстрацію зміни аеродинамічного стану зовнішнього обводу ЛА у польоті. Досліджено теоретично і експериментально підтверджено можливості створення ІСАД зміни аеродинамічного стану зовнішнього обводу ЛА у польоті

Performance Controlled Power Optimization for Virtualized Internet Datacenters

Modern data centers must provide performance assurance for complex system software such as web applications. In addition, the power consumption of data centers needs to be minimized to reduce operating costs and avoid system overheating. In recent years, more and more data centers start to adopt server virtualization strategies for resource sharing to reduce hardware and operating costs by consolidating applications previously running on multiple physical servers onto a single physical server. In this dissertation, several power efficient algorithms are proposed to effectively reduce server power consumption while achieving the required application-level performance for virtualized servers. First, at the server level this dissertation proposes two control solutions based on dynamic voltage and frequency scaling (DVFS) technology and request batching technology. The two solutions share a performance balancing technique that maintains performance balancing among all virtual machines so that they can have approximately the same performance level relative to their allowed peak values. Then, when the workload intensity is light, we adopt the request batching technology by using a controller to determine the time length for periodically batching incoming requests and putting the processor into sleep mode. When the workload intensity changes from light to moderate, request batching is automatically switched to DVFS to increase the processor frequency for performance guarantees. Second, at the datacenter level, this dissertation proposes a performance-controlled power optimization solution for virtualized server clusters with multi-tier applications. The solution utilizes both DVFS and server consolidation strategies for maximized power savings by integrating feedback control with optimization strategies. At the application level, a multi-input-multi-output controller is designed to achieve the desired performance for applications spanning multiple VMs, on a short time scale, by reallocating the CPU resources and DVFS. At the cluster level, a power optimizer is proposed to incrementally consolidate VMs onto the most power-efficient servers on a longer time scale. Finally, this dissertation proposes a VM scheduling algorithm that exploits core performance heterogeneity to optimize the overall system energy efficiency. The four algorithms at the three different levels are demonstrated with empirical results on hardware testbeds and trace-driven simulations and compared against state-of-the-art baselines

An FPGA implementation of an adaptive data reduction technique for wireless sensor networks

Wireless sensor networking (WSN) is an emerging technology that has a wide range of potential applications including environment monitoring, surveillance, medical systems, and robotic exploration. These networks consist of large numbers of distributed nodes that organize themselves into a multihop wireless network. Each node is equipped with one or more sensors, embedded processors, and low- power radios, and is normally battery operated. Reporting constant measurement updates incurs high communication costs for each individual node, resulting in a significant communication overhead and energy consumption. A solution to reduce power requirements is to select, among all data produced by the sensor network, a subset of sensor readings that is relayed to the user such that the original observation data can be reconstructed within some user-defined accuracy. This paper describes the implementation of an adaptive data reduction algorithm for WSN, on a Xilinx Spartan-3E FPGA. A feasibility study is carried out to determine the benefits of this solution.peer-reviewe

The micropulse framework for adaptive waking windows in sensor networks

In this paper we present MicroPulse, a novel framework for adapting the waking window of a sensing device S based on the data workload incurred by a query Q. Assuming a typical tree-based aggregation scenario, the waking window is defined as the time interval r during which S enables its transceiver in order to collect the results from its children. Minimizing the length of r enables S to conserve energy that can be used to prolong the longevity of the network and hence the quality of results. Our method is established on profiling recent data acquisition activity and on identifying the bottlenecks using an in-network execution of the Critical Path Method. We show through trace- driven experimentation with a real dataset that MicroPulse can reduce the energy cost of the waking window by three orders of magnitude