8,149 research outputs found
From serendipity to sustainable Green IoT: technical, industrial and political perspective
Recently, Internet of Things (IoT) has become one of the largest electronics market for hardware production due to its fast evolving application space. However, one of the key challenges for IoT hardware is the energy efficiency as most of IoT devices/objects are expected to run on batteries for months/years without a battery replacement or on harvested energy sources. Widespread use of IoT has also led to a largescale rise in the carbon footprint. In this regard, academia, industry and policy-makers are constantly working towards new energy-efficient hardware and software solutions paving the way for an emerging area referred to as green-IoT. With the direct integration and the evolution of smart communication between physical world and computer-based systems, IoT devices are also expected to reduce the total amount of energy consumption for the Information and Communication Technologies (ICT) sector.
However, in order to increase its chance of success and to help at reducing the overall energy consumption and carbon emissions a comprehensive investigation into how to achieve green-IoT is required. In this context, this paper surveys the green perspective of the IoT paradigm and aims to contribute at establishing a global approach for green-IoT environments. A comprehensive approach is presented that focuses not only on the specific solutions but also on the interaction among them, and highlights the precautions/decisions the policy makers need to take. On one side, the ongoing European projects and standardization efforts as well as industry and academia based solutions are presented and on the other side, the challenges, open issues, lessons learned and the role of policymakers towards green-IoT are discussed.
The survey shows that due to many existing open issues (e.g., technical considerations, lack of standardization, security and privacy, governance and legislation, etc.) that still need to be addressed, a realistic implementation of a sustainable green-IoT environment that could be universally accepted and deployed, is still missing
A European research roadmap for optimizing societal impact of big data on environment and energy efficiency
We present a roadmap to guide European research efforts towards a socially
responsible big data economy that maximizes the positive impact of big data in
environment and energy efficiency. The goal of the roadmap is to allow
stakeholders and the big data community to identify and meet big data
challenges, and to proceed with a shared understanding of the societal impact,
positive and negative externalities, and concrete problems worth investigating.
It builds upon a case study focused on the impact of big data practices in the
context of Earth Observation that reveals both positive and negative effects in
the areas of economy, society and ethics, legal frameworks and political
issues. The roadmap identifies European technical and non-technical priorities
in research and innovation to be addressed in the upcoming five years in order
to deliver societal impact, develop skills and contribute to standardization.Comment: 6 pages, 2 figures, 1 tabl
Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions
Traditional power grids are being transformed into Smart Grids (SGs) to
address the issues in existing power system due to uni-directional information
flow, energy wastage, growing energy demand, reliability and security. SGs
offer bi-directional energy flow between service providers and consumers,
involving power generation, transmission, distribution and utilization systems.
SGs employ various devices for the monitoring, analysis and control of the
grid, deployed at power plants, distribution centers and in consumers' premises
in a very large number. Hence, an SG requires connectivity, automation and the
tracking of such devices. This is achieved with the help of Internet of Things
(IoT). IoT helps SG systems to support various network functions throughout the
generation, transmission, distribution and consumption of energy by
incorporating IoT devices (such as sensors, actuators and smart meters), as
well as by providing the connectivity, automation and tracking for such
devices. In this paper, we provide a comprehensive survey on IoT-aided SG
systems, which includes the existing architectures, applications and prototypes
of IoT-aided SG systems. This survey also highlights the open issues,
challenges and future research directions for IoT-aided SG systems
Big Data and the Internet of Things
Advances in sensing and computing capabilities are making it possible to
embed increasing computing power in small devices. This has enabled the sensing
devices not just to passively capture data at very high resolution but also to
take sophisticated actions in response. Combined with advances in
communication, this is resulting in an ecosystem of highly interconnected
devices referred to as the Internet of Things - IoT. In conjunction, the
advances in machine learning have allowed building models on this ever
increasing amounts of data. Consequently, devices all the way from heavy assets
such as aircraft engines to wearables such as health monitors can all now not
only generate massive amounts of data but can draw back on aggregate analytics
to "improve" their performance over time. Big data analytics has been
identified as a key enabler for the IoT. In this chapter, we discuss various
avenues of the IoT where big data analytics either is already making a
significant impact or is on the cusp of doing so. We also discuss social
implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski
(eds.) Big Data Analysis: New algorithms for a new society, Springer Series
on Studies in Big Data, to appea
Isolating SDN Control Traffic with Layer-2 Slicing in 6TiSCH Industrial IoT Networks
Recent standardization efforts in IEEE 802.15.4-2015 Time Scheduled Channel
Hopping (TSCH) and the IETF 6TiSCH Working Group (WG), aim to provide
deterministic communications and efficient allocation of resources across
constrained Internet of Things (IoT) networks, particularly in Industrial IoT
(IIoT) scenarios. Within 6TiSCH, Software Defined Networking (SDN) has been
identified as means of providing centralized control in a number of key
situations. However, implementing a centralized SDN architecture in a Low Power
and Lossy Network (LLN) faces considerable challenges: not only is controller
traffic subject to jitter due to unreliable links and network contention, but
the overhead generated by SDN can severely affect the performance of other
traffic. This paper proposes using 6TiSCH tracks, a Layer-2 slicing mechanism
for creating dedicated forwarding paths across TSCH networks, in order to
isolate the SDN control overhead. Not only does this prevent control traffic
from affecting the performance of other data flows, but the properties of
6TiSCH tracks allows deterministic, low-latency SDN controller communication.
Using our own lightweight SDN implementation for Contiki OS, we firstly
demonstrate the effect of SDN control traffic on application data flows across
a 6TiSCH network. We then show that by slicing the network through the
allocation of dedicated resources along a SDN control path, tracks provide an
effective means of mitigating the cost of SDN control overhead in IEEE
802.15.4-2015 TSCH networks
Algorithms for advance bandwidth reservation in media production networks
Media production generally requires many geographically distributed actors (e.g., production houses, broadcasters, advertisers) to exchange huge amounts of raw video and audio data. Traditional distribution techniques, such as dedicated point-to-point optical links, are highly inefficient in terms of installation time and cost. To improve efficiency, shared media production networks that connect all involved actors over a large geographical area, are currently being deployed. The traffic in such networks is often predictable, as the timing and bandwidth requirements of data transfers are generally known hours or even days in advance. As such, the use of advance bandwidth reservation (AR) can greatly increase resource utilization and cost efficiency. In this paper, we propose an Integer Linear Programming formulation of the bandwidth scheduling problem, which takes into account the specific characteristics of media production networks, is presented. Two novel optimization algorithms based on this model are thoroughly evaluated and compared by means of in-depth simulation results
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