1,833 research outputs found
Efficient Cooperative Anycasting for AMI Mesh Networks
We have, in recent years, witnessed an increased interest towards enabling a
Smart Grid which will be a corner stone to build sustainable energy efficient
communities. An integral part of the future Smart Grid will be the
communications infrastructure which will make real time control of the grid
components possible. Automated Metering Infrastructure (AMI) is thought to be a
key enabler for monitoring and controlling the customer loads. %RPL is a
connectivity enabling mechanism for low power and lossy networks currently
being standardized by the IETF ROLL working group. RPL is deemed to be a
suitable candidate for AMI networks where the meters are connected to a
concentrator over multi hop low power and lossy links. This paper proposes an
efficient cooperative anycasting approach for wireless mesh networks with the
aim of achieving reduced traffic and increased utilisation of the network
resources. The proposed cooperative anycasting has been realised as an
enhancement on top of the Routing Protocol for Low Power and Lossy Networks
(RPL), a connectivity enabling mechanism in wireless AMI mesh networks. In this
protocol, smart meter nodes utilise an anycasting approach to facilitate
efficient transport of metering data to the concentrator node. Moreover, it
takes advantage of a distributed approach ensuring scalability
Efficient energy management for the internet of things in smart cities
The drastic increase in urbanization over the past few years requires sustainable, efficient, and smart solutions for transportation, governance, environment, quality of life, and so on. The Internet of Things offers many sophisticated and ubiquitous applications for smart cities. The energy demand of IoT applications is increased, while IoT devices continue to grow in both numbers and requirements. Therefore, smart city solutions must have the ability to efficiently utilize energy and handle the associated challenges. Energy management is considered as a key paradigm for the realization of complex energy systems in smart cities. In this article, we present a brief overview of energy management and challenges in smart cities. We then provide a unifying framework for energy-efficient optimization and scheduling of IoT-based smart cities. We also discuss the energy harvesting in smart cities, which is a promising solution for extending the lifetime of low-power devices and its related challenges. We detail two case studies. The first one targets energy-efficient scheduling in smart homes, and the second covers wireless power transfer for IoT devices in smart cities. Simulation results for the case studies demonstrate the tremendous impact of energy-efficient scheduling optimization and wireless power transfer on the performance of IoT in smart cities
State-of-the-art in Power Line Communications: from the Applications to the Medium
In recent decades, power line communication has attracted considerable
attention from the research community and industry, as well as from regulatory
and standardization bodies. In this article we provide an overview of both
narrowband and broadband systems, covering potential applications, regulatory
and standardization efforts and recent research advancements in channel
characterization, physical layer performance, medium access and higher layer
specifications and evaluations. We also identify areas of current and further
study that will enable the continued success of power line communication
technology.Comment: 19 pages, 12 figures. Accepted for publication, IEEE Journal on
Selected Areas in Communications. Special Issue on Power Line Communications
and its Integration with the Networking Ecosystem. 201
Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks
Future wireless networks have a substantial potential in terms of supporting
a broad range of complex compelling applications both in military and civilian
fields, where the users are able to enjoy high-rate, low-latency, low-cost and
reliable information services. Achieving this ambitious goal requires new radio
techniques for adaptive learning and intelligent decision making because of the
complex heterogeneous nature of the network structures and wireless services.
Machine learning (ML) algorithms have great success in supporting big data
analytics, efficient parameter estimation and interactive decision making.
Hence, in this article, we review the thirty-year history of ML by elaborating
on supervised learning, unsupervised learning, reinforcement learning and deep
learning. Furthermore, we investigate their employment in the compelling
applications of wireless networks, including heterogeneous networks (HetNets),
cognitive radios (CR), Internet of things (IoT), machine to machine networks
(M2M), and so on. This article aims for assisting the readers in clarifying the
motivation and methodology of the various ML algorithms, so as to invoke them
for hitherto unexplored services as well as scenarios of future wireless
networks.Comment: 46 pages, 22 fig
Quality and Availability of spectrum based routing for Cognitive radio enabled IoT networks
With the recent emergence and its wide spread applicability Internet of Things (IoT) is putting pressure on network resources and most importantly on availability of spectrum. Spectrum scarcity is the issue to be addressed in networking within IoT. Cognitive radio is the technology which addresses the problem of spectrum scarcity in an efficient way. Equipping the IoT devices with cognitive radio capability will lead to a new dimension called cognitive radio enabled IoT devices. To achieve ON-demand IoT solutions and interference free communications cognitive radio enabled IoT devices will become an effective platform for many applications. As there is high dynamicity in availability of spectrum it is challenging for designing an efficient routing protocol for secondary users in cognitive device networks. In this work we are going to estimate spectrum quality and spectrum availability based on two parameters called global information about spectrum usage and instant spectrum status information. Enhanced energy detector is used at each and every node for better probability of detection. For estimating spectrum quality and availability we are introducing novel routing metrics. To have restriction on the number of reroutings and to increase the performance of routing in our proposed routing metric only one retransmission is allowed. Then, two algorithms for routing are designed for evaluating the performance of routing and we find that the bit error rates of proposed algorithms (nodes are dynamic) have decreased a lot when compared to conventional methods (Nodes are static) and throughput of proposed algorithm also improved a lot
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