1,720,963 research outputs found
Building a green connected future: smart (Internet of) Things for smart networks
Get PDFThe vision of Internet of Things (IoT) promises to reshape society by creating a future where we will be surrounded by a smart environment that is constantly aware of the users and has the ability to adapt to any changes. In the IoT, a huge variety of smart devices is interconnected to form a network of distributed agents that continuously share and process information. This communication paradigm has been recognized as one of the key enablers of the rapidly emerging applications that make up the fabric of the IoT. These networks, often called wireless sensor networks (WSNs), are characterized by the low cost of their components, their pervasive connectivity, and their self-organization features, which allow them to cooperate with other IoT elements to create large-scale heterogeneous information systems. However, a number of considerable challenges is arising when considering the design of large-scale WSNs. In particular, these networks are made up by embedded devices that suffer from severe power constraints and limited resources. The advent of low-power sensor nodes coupled with intelligent software and hardware technologies has led to the era of green wireless networks. From the hardware
perspective, green sensor nodes are endowed with energy scavenging capabilities to overcome energy-related limitations. They are also endowed with low-power
triggering techniques, i.e., wake-up radios, to eliminate idle listening-induced communication costs. Green wireless networks are considered a fundamental vehicle
for enabling all those critical IoT applications where devices, for different reasons, do not carry batteries, and that therefore only harvest energy and store it for future
use. These networks are considered to have the potential of infinite lifetime since they do not depend on batteries, or on any other limited power sources. Wake-up radios, coupled with energy provisioning techniques, further assist on overcoming the physical constraints of traditional WSNs. In addition, they are particularly important
in green WSNs scenarios in which it is difficult to achieve energy neutrality due to limited harvesting rates. In this PhD thesis we set to investigate how different data forwarding mechanisms can make the most of these green wireless networks-enabling technologies, namely, energy harvesting and wake-up radios. Specifically, we present a number of cross-layer routing approaches with different forwarding design choices and study their
consequences on network performance. Among the most promising protocol design techniques, the past decade has shown the increasingly intensive adoption of techniques based on various forms of machine learning to increase and optimize the performance of WSNs. However, learning techniques can suffer from high computational costs as nodes drain a considerable percentage of their energy budget to run sophisticated software procedures, predict accurate information and determine optimal decision. This thesis addresses also the problem of local computational requirements of learning-based data forwarding strategies by investigating their impact on the performance of the network. Results indicate that local computation can be a major source of energy consumption; it’s impact on network performance should not be neglected
A Comparative Performance Evaluation of Wake-Up Radio-Based Data Forwarding for Green Wireless Networks
No full textThe advent of low-power sensor nodes coupled with intelligent software and hardware technologies has led to the era of green wireless networks. From the hardware perspective, green sensor nodes are endowed with energy scavenging capabilities to overcome energy-related limitations. They are also endowed with low-power triggering techniques, i.e., wake-up radios, to eliminate idle listening-induced communication costs. In this paper, we present a comparative performance evaluation of three different data forwarding strategies for green wireless networks, namely, CTP-WUR, GREENROUTES, and WHARP, which have been shown to outperform previous state-of-art solutions. Through GreenCastalia-based simulations we analyze and provide insights into the impact on performance of diverse forwarding design choices, ranging from traditional tree-based routing (CTP- WUR), to end-to-end energy-driven route selection (GREENROUTES), to the use of sophisticated learning models (WHARP). Results show that tree- based routing obtains lesser packet delivery radio than WHARP, thus indicating that including energy harvesting awareness in route selection results in performance advantages. However, the proactive nature of route computation of CTP-WUR results in faster packet delivery and lower energy consumption, requesting further optimization of the cross-layer forwarding of GREENROUTES and WHARP
Can Everybody be Happy in the Cloud? Delay, Profit and Energy-Efficient Scheduling for Cloud Services
Get PDFThe rapid development of Cloud Computing provides consumers and service providers with a wide range of opportunities and challenges. Considering the substantial infrastructure investments being made by cloud providers, the reduction of operating expenses (OPEX) while maximizing the profit of the provided services is of great importance. One way to achieve this is by maximizing the efficiency of resource utilization. However, profit maximization does not necessarily coincide with the improvement of a user’s Quality of Service (QoS); users generating higher profit for the provider may be scheduled first, causing high delays to low-paying users. Further, the contradictory nature of users’ and providers’ needs also extends to the energy consumption problem, as the minimization of service delays could cause cloud resources to be constantly “on”, leading to high energy consumption, high costs for providers and undue environmental impact. The objective of our work is to analyze this multidimensional trade-off. We first investigate the problem of efficient resource allocation strategies for time-varying traffic, and propose a new algorithm, MinDelay, which aims at achieving the minimum service delay while taking into account provider’s profit. Then, we propose E-MinDelay, an energy-efficient approach for CPU-intensive tasks in cloud systems. Furthermore, we propose an improved version of the Energy Conscious Task Consolidation (ECTC) algorithm, which combines task consolidation and migration techniques with E-MinDelay. Our results demonstrate that energy consumption and service delays corresponding to profit loss can be simultaneously decreased using an efficient scheduling algorithm
Wake-up radio-based data forwarding for green wireless networks
Get PDFThis paper presents G-WHARP, for Green Wake-up and HARvesting-based energy-Predictive forwarding, a wake-up radio-based forwarding strategy for wireless networks equipped with energy harvesting capabilities (green wireless networks). Following a learning-based approach, G-WHARP blends energy harvesting and wake-up radio technology to maximize energy efficiency and obtain superior network performance. Nodes autonomously decide on their forwarding availability based on a Markov Decision Process (MDP) that takes into account a variety of energy-related aspects, including the currently available energy and that harvestable in the foreseeable future. Solution of the MDP is provided by a computationally light heuristic based on a simple threshold policy, thus obtaining further computational energy savings. The performance of G-WHARP is evaluated via GreenCastalia simulations, where we accurately model wake-up radios, harvestable energy, and the computational power needed to solve the MDP. Key network and system parameters are varied, including the source of harvestable energy, the network density, wake-up radio data rate and data traffic. We also compare the performance of G-WHARP to that of two state-of-the-art data forwarding strategies, namely GreenRoutes and CTP-WUR. Results show that G-WHARP limits energy expenditures while achieving low end-to-end latency and high packet delivery ratio. Particularly, it consumes up to 34% and 59% less energy than CTP-WUR and GreenRoutes, respectively
A Real-time testbed environment for Cyber-Physical Security on the power grid
Get PDFThe trustworthiness and security of cyber-physical systems (CPSs), such as the power grid, are of paramount importance to ensure their safe operation, performance, and economic efficiency. The aim of many cyber-physical security techniques, such as network intrusion detection systems (NIDSs) for CPSs, is to ensure continuous reliable operation even in exposed network environments. But the validation of such methods goes well beyond standard network analysis, since meaningful tests must also integrate realistic understanding of the physical systems behavior and response to the network activity. Our goal in this paper is to showcase an example of a testbed environment that can support such validation. In it, real network traffic, emulating and industrial control network, interacts with simulated physical models in real-time, extending and leveraging "hardware-in-the-loop" and "cyber-in-the-loop" capabilities. The testbed is a bridge between theory and practice and offers a number of features, including network communications, data management, as well as the virtualization of cyber-physical state analytics performed by the NIDS. The traffic is captured by real network taps and is forwarded to a real data management environment, receiving also the data reports from the simulated industrial control environment. To illustrate the capabilities of our testbed we show how the data are cross-checked by a "physics aware" NIDS, identifying network traffic that does not comply with its cyber-physical security rules
A hybrid network IDS for protective digital relays in the power transmission grid
Get PDFIn this paper, we propose a novel use of network intrusion detection systems (NIDSs) tailored to detect attacks against networks that support hybrid controllers that implement power grid protection schemes. In our approach, we implement specification-based intrusion detection signatures based on the execution of the hybrid automata that specify the communication rules and physical limits that the system should obey. To validate our idea, we developed an experimental framework consisting of a simulation of the physical system and an emulation of the master controller, which serves as the digital relay that implements the protection mechanism. Our Hybrid Control NIDS (HC-NIDS) continuously monitors and analyzes the network traffic exchanged within the physical system. It identifies traffic that deviates from the expected communication pattern or physical limitations, which could place the system in an unsafe mode of operation. Our experimental analysis demonstrates that our approach is able to detect a diverse range of attack scenarios aimed at compromising the physical process by leveraging information about the physical part of the power system
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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