652 research outputs found
Wi-Fi Offload: Tragedy of the Commons or Land of Milk and Honey?
Fueled by its recent success in provisioning on-site wireless Internet
access, Wi-Fi is currently perceived as the best positioned technology for
pervasive mobile macro network offloading. However, the broad transitions of
multiple collocated operators towards this new paradigm may result in fierce
competition for the common unlicensed spectrum at hand. In this light, our
paper game-theoretically dissects market convergence scenarios by assessing the
competition between providers in terms of network performance, capacity
constraints, cost reductions, and revenue prospects. We will closely compare
the prospects and strategic positioning of fixed line operators offering Wi-Fi
services with respect to competing mobile network operators utilizing
unlicensed spectrum. Our results highlight important dependencies upon
inter-operator collaboration models, and more importantly, upon the ratio
between backhaul and Wi-Fi access bit-rates. Furthermore, our investigation of
medium- to long-term convergence scenarios indicates that a rethinking of
control measures targeting the large-scale monetization of unlicensed spectrum
may be required, as otherwise the used free bands may become subject to
tragedy-of-commons type of problems.Comment: Workshop on Spectrum Sharing Strategies for Wireless Broadband
Services, IEEE PIMRC'13, to appear 201
A Taxonomy for Management and Optimization of Multiple Resources in Edge Computing
Edge computing is promoted to meet increasing performance needs of
data-driven services using computational and storage resources close to the end
devices, at the edge of the current network. To achieve higher performance in
this new paradigm one has to consider how to combine the efficiency of resource
usage at all three layers of architecture: end devices, edge devices, and the
cloud. While cloud capacity is elastically extendable, end devices and edge
devices are to various degrees resource-constrained. Hence, an efficient
resource management is essential to make edge computing a reality. In this
work, we first present terminology and architectures to characterize current
works within the field of edge computing. Then, we review a wide range of
recent articles and categorize relevant aspects in terms of 4 perspectives:
resource type, resource management objective, resource location, and resource
use. This taxonomy and the ensuing analysis is used to identify some gaps in
the existing research. Among several research gaps, we found that research is
less prevalent on data, storage, and energy as a resource, and less extensive
towards the estimation, discovery and sharing objectives. As for resource
types, the most well-studied resources are computation and communication
resources. Our analysis shows that resource management at the edge requires a
deeper understanding of how methods applied at different levels and geared
towards different resource types interact. Specifically, the impact of mobility
and collaboration schemes requiring incentives are expected to be different in
edge architectures compared to the classic cloud solutions. Finally, we find
that fewer works are dedicated to the study of non-functional properties or to
quantifying the footprint of resource management techniques, including
edge-specific means of migrating data and services.Comment: Accepted in the Special Issue Mobile Edge Computing of the Wireless
Communications and Mobile Computing journa
Energy saving market for mobile operators
Ensuring seamless coverage accounts for the lion's share of the energy
consumed in a mobile network. Overlapping coverage of three to five mobile
network operators (MNOs) results in enormous amount of energy waste which is
avoidable. The traffic demands of the mobile networks vary significantly
throughout the day. As the offered load for all networks are not same at a
given time and the differences in energy consumption at different loads are
significant, multi-MNO capacity/coverage sharing can dramatically reduce energy
consumption of mobile networks and provide the MNOs a cost effective means to
cope with the exponential growth of traffic. In this paper, we propose an
energy saving market for a multi-MNO network scenario. As the competing MNOs
are not comfortable with information sharing, we propose a double auction
clearinghouse market mechanism where MNOs sell and buy capacity in order to
minimize energy consumption. In our setting, each MNO proposes its bids and
asks simultaneously for buying and selling multi-unit capacities respectively
to an independent auctioneer, i.e., clearinghouse and ends up either as a buyer
or as a seller in each round. We show that the mechanism allows the MNOs to
save significant percentage of energy cost throughout a wide range of network
load. Different than other energy saving features such as cell sleep or antenna
muting which can not be enabled at heavy traffic load, dynamic capacity sharing
allows MNOs to handle traffic bursts with energy saving opportunity.Comment: 6 pages, 2 figures, to be published in ICC 2015 workshop on Next
Generation Green IC
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