Power Management Strategies for Wired Communication Networks.

With the exponential traffic growth and the rapid expansion of communication infrastructures worldwide, energy expenditure of the Internet has become a major concern in IT-reliant society. This energy problem has motivated the urgent demands of new strategies to reduce the consumption of telecommunication networks, with a particular focus on IP networks. In addition to the development of a new generation of energy-efficient network equipment, a significant body of research has concentrated on incorporating power/energy-awareness into network control and management, which aims at reducing the network power/energy consumption by either dynamically scaling speeds of each active network component to make it capable of adapting to its current load or putting to sleep the lightly loaded network elements and reconfiguring the network. However, the fundamental challenge of greening the Internet is to achieve a balance between the power/energy saving and the demands of quality-of-service (QoS) performance, which is an issue that has received less attention but is becoming a major problem in future green network designs. In this dissertation, we study how energy consumption can be reduced through different power/energy- and QoS-aware strategies for wired communication networks. To sufficiently reduce energy consumption while meeting the desire QoS requirements, we introduce several different schemes combing power management techniques with different scheduling strategies, which can be classified into experimental power management (EPM) and algorithmic power management (APM). In these proposed schemes, the power management techniques that we focus on are speed scaling and sleep mode. When the network processor is active, its speed and supply voltage can be decreased to reduce the energy consumption (speed scaling), while when the processor is idle, it can be put in a low power mode to save the energy consumption (sleep mode). The resulting problem is to determine how and when to adjust speeds for the processors, and/or to put a device into sleep mode. In this dissertation, we first discuss three families of dynamic voltage/frequency scaling (DVFS) based, QoS-aware EPM schemes, which aim to reduce the energy consumption in network equipment by using different packet scheduling strategies, while adhering to QoS requirements of supported applications. Then, we explore the problem of energy minimization under QoS constraints through a mathematical programming model, which is a DVFS-based, delay-aware APM scheme combing the speed scaling technique with the existing rate monotonic scheduling policy. Among these speed scaling based schemes, up to 26.76% dynamic power saving of the total power consumption can be achieved. In addition to speed scaling approaches, we further propose a sleep-based, traffic-aware EPM scheme, which is used to reduce power consumption by greening routing light load and putting the related network equipment into sleep mode according to twelve flow traffic density changes in 24-hour of an arbitrarily selected day. Meanwhile, a speed scaling technique without violating network QoS performance is also considered in this scheme when the traffic is rerouted. Applying this sleep-based strategy can lead to power savings of up to 62.58% of the total power consumption

Urban Air Mobility Market Study

The Booz Allen Team explored market size and potential barriers to Urban Air Mobility (UAM) by focusing on three potential markets – Airport Shuttle, Air Taxi, and Air Ambulance. We found that the Airport Shuttle and Air Taxi markets are viable, with a significant total available market value in the U.S. of $500 billion, for a fully unconstrained scenario. In this unconstrained best-case scenario, passengers would have the ability to access and fly a UAM at any time, from any location to any destination, without being hindered by constraints such as weather, infrastructure, or traffic volume. Significant legal and regulatory, weather, certification, public perception, and infrastructure constraints exist, which reduce the market potential for these applications to only about 0.5$2.5 billion, in the near term. However, we determined that these constraints can be addressed through ongoing intra-governmental partnerships, government and industry collaboration, strong industry commitment, and existing legal and regulatory enablers. We found that the Air Ambulance market is not a viable market if served by electric vertical takeoff and landing (eVTOL) vehicles due to technology constraints but may potentially be viable if a hybrid VTOL aircraft are utilized

Issues in providing a reliable multicast facility

Issues involved in point-to-multipoint communication are presented and the literature for proposed solutions and approaches surveyed. Particular attention is focused on the ideas and implementations that align with the requirements of the environment of interest. The attributes of multicast receiver groups that might lead to useful classifications, what the functionality of a management scheme should be, and how the group management module can be implemented are examined. The services that multicasting facilities can offer are presented, followed by mechanisms within the communications protocol that implements these services. The metrics of interest when evaluating a reliable multicast facility are identified and applied to four transport layer protocols that incorporate reliable multicast

Joint Elastic Cloud and Virtual Network Framework for Application Performance-cost Optimization

International audienceCloud computing infrastructures are providing resources on demand for tackling the needs of large-scale distributed applications. To adapt to the diversity of cloud infras- tructures and usage, new operation tools and models are needed. Estimating the amount of resources consumed by each application in particular is a difficult problem, both for end users who aim at minimizing their costs and infrastructure providers who aim at control- ling their resources allocation. Furthermore, network provision is generally not controlled on clouds. This paper describes a framework automating cloud resources allocation, deploy- ment and application execution control. It is based on a cost estimation model taking into account both virtual network and nodes managed by the cloud. The flexible provisioning of network resources permits the optimization of applications performance and infrastructure cost reduction. Four resource allocation strategies relying on the expertise that can be cap- tured in workflow-based applications are considered. Results of these strategies are confined virtual infrastructure descriptions that are interpreted by the HIPerNet engine responsible for allocating, reserving and configuring physical resources. The evaluation of this framework was carried out on the Aladdin/Grid'5000 testbed using a real application from the area of medical image analysis

Catalyzing Privacy Law

The United States famously lacks a comprehensive federal data privacy law. In the past year, however, over half the states have proposed broad privacy bills or have established task forces to propose possible privacy legislation. Meanwhile, congressional committees are holding hearings on multiple privacy bills. What is catalyzing this legislative momentum? Some believe that Europe’s General Data Protection Regulation (GDPR), which came into force in 2018, is the driving factor. But with the California Consumer Privacy Act (CCPA) which took effect in January 2020, California has emerged as an alternate contender in the race to set the new standard for privacy.Our close comparison of the GDPR and California’s privacy law reveals that the California law is not GDPR-lite: it retains a fundamentally American approach to information privacy. Reviewing the literature on regulatory competition, we argue that California, not Brussels, is catalyzing privacy law across the United States. And what is happening is not a simple story of powerful state actors. It is more accurately characterized as the result of individual networked norm entrepreneurs, influenced and even empowered by data globalization. Our study helps explain the puzzle of why Europe’s data privacy approach failed to spur US legislation for over two decades. Finally, our study answers critical questions of practical interest to individuals—who will protect my privacy?—and to businesses—whose rules should I follow

Systems Analysis in Forestry and Forest Industries

The purpose of this book is to present a variety of articles revealing the state of the art of applications of systems analysis techniques to problems of the forest sector. Such applications cover a vast range of issues in forestry and the forest industry. They include the dynamics of the forest ecosystem, optimal forest management, the roundwood market, forest industrial strategy, regional and national forest sector policy as well as international trade in forest products. Forest industrial applications at mill level, such as optimal paper trimming, cutting, and production scheduling, are however, excluded