37,877 research outputs found
Wireless body sensor networks for health-monitoring applications
This is an author-created, un-copyedited version of an article accepted for publication in
Physiological Measurement. The publisher is
not responsible for any errors or omissions in this version of the manuscript or any version
derived from it. The Version of Record is available online at http://dx.doi.org/10.1088/0967-3334/29/11/R01
Quantifying Potential Energy Efficiency Gain in Green Cellular Wireless Networks
Conventional cellular wireless networks were designed with the purpose of
providing high throughput for the user and high capacity for the service
provider, without any provisions of energy efficiency. As a result, these
networks have an enormous Carbon footprint. In this paper, we describe the
sources of the inefficiencies in such networks. First we present results of the
studies on how much Carbon footprint such networks generate. We also discuss
how much more mobile traffic is expected to increase so that this Carbon
footprint will even increase tremendously more. We then discuss specific
sources of inefficiency and potential sources of improvement at the physical
layer as well as at higher layers of the communication protocol hierarchy. In
particular, considering that most of the energy inefficiency in cellular
wireless networks is at the base stations, we discuss multi-tier networks and
point to the potential of exploiting mobility patterns in order to use base
station energy judiciously. We then investigate potential methods to reduce
this inefficiency and quantify their individual contributions. By a
consideration of the combination of all potential gains, we conclude that an
improvement in energy consumption in cellular wireless networks by two orders
of magnitude, or even more, is possible.Comment: arXiv admin note: text overlap with arXiv:1210.843
Wireless industrial monitoring and control networks: the journey so far and the road ahead
While traditional wired communication technologies have played a crucial role in industrial monitoring and control networks over the past few decades, they are increasingly proving to be inadequate to meet the highly dynamic and stringent demands of todayâs industrial applications, primarily due to the very rigid nature of wired infrastructures. Wireless technology, however, through its increased pervasiveness, has the potential to revolutionize the industry, not only by mitigating the problems faced by wired solutions, but also by introducing a completely new class of applications. While present day wireless technologies made some preliminary inroads in the monitoring domain, they still have severe limitations especially when real-time, reliable distributed control operations are concerned. This article provides the reader with an overview of existing wireless technologies commonly used in the monitoring and control industry. It highlights the pros and cons of each technology and assesses the degree to which each technology is able to meet the stringent demands of industrial monitoring and control networks. Additionally, it summarizes mechanisms proposed by academia, especially serving critical applications by addressing the real-time and reliability requirements of industrial process automation. The article also describes certain key research problems from the physical layer communication for sensor networks and the wireless networking perspective that have yet to be addressed to allow the successful use of wireless technologies in industrial monitoring and control networks
HetHetNets: Heterogeneous Traffic Distribution in Heterogeneous Wireless Cellular Networks
A recent approach in modeling and analysis of the supply and demand in
heterogeneous wireless cellular networks has been the use of two independent
Poisson point processes (PPPs) for the locations of base stations (BSs) and
user equipments (UEs). This popular approach has two major shortcomings. First,
although the PPP model may be a fitting one for the BS locations, it is less
adequate for the UE locations mainly due to the fact that the model is not
adjustable (tunable) to represent the severity of the heterogeneity
(non-uniformity) in the UE locations. Besides, the independence assumption
between the two PPPs does not capture the often-observed correlation between
the UE and BS locations.
This paper presents a novel heterogeneous spatial traffic modeling which
allows statistical adjustment. Simple and non-parameterized, yet sufficiently
accurate, measures for capturing the traffic characteristics in space are
introduced. Only two statistical parameters related to the UE distribution,
namely, the coefficient of variation (the normalized second-moment), of an
appropriately defined inter-UE distance measure, and correlation coefficient
(the normalized cross-moment) between UE and BS locations, are adjusted to
control the degree of heterogeneity and the bias towards the BS locations,
respectively. This model is used in heterogeneous wireless cellular networks
(HetNets) to demonstrate the impact of heterogeneous and BS-correlated traffic
on the network performance. This network is called HetHetNet since it has two
types of heterogeneity: heterogeneity in the infrastructure (supply), and
heterogeneity in the spatial traffic distribution (demand).Comment: JSA
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