1,090 research outputs found
Study on Energy Consumption and Coverage of Hierarchical Cooperation of Small Cell Base Stations in Heterogeneous Networks
The demand for communication services in the era of intelligent terminals is
unprecedented and huge. To meet such development, modern wireless
communications must provide higher quality services with higher energy
efficiency in terms of system capacity and quality of service (QoS), which
could be achieved by the high-speed data rate, the wider coverage and the
higher band utilization. In this paper, we propose a way to offload users from
a macro base station(MBS) with a hierarchical distribution of small cell base
stations(SBS). The connection probability is the key indicator of the
implementation of the unload operation. Furthermore, we measure the service
performance of the system by finding the conditional probability-coverage
probability with the certain SNR threshold as the condition, that is, the
probability of obtaining the minimum communication quality when the different
base stations are connected to the user. Then, user-centered total energy
consumption of the system is respectively obtained when the macro base
station(MBS) and the small cell base stations(SBS) serve each of the users. The
simulation results show that the hierarchical SBS cooperation in heterogeneous
networks can provide a higher system total coverage probability for the system
with a lower overall system energy consumption than MBS.Comment: 6 pages, 7 figures, accepted by ICACT201
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
Do we all really know what a fog node is? Current trends towards an open definition
Fog computing has emerged as a promising technology that can bring cloud applications closer to the physical IoT devices at the network edge. While it is widely known what cloud computing is, how data centers can build the cloud infrastructure and how applications can make use of this infrastructure, there is no common picture on what fog computing and particularly a fog node, as its main building block, really is. One of the first attempts to define a fog node was made by Cisco, qualifying a fog computing system as a “mini-cloud” located at the edge of the network and implemented through a variety of edge devices, interconnected by a variety, mostly wireless, communication technologies. Thus, a fog node would be the infrastructure implementing the said mini-cloud. Other proposals have their own definition of what a fog node is, usually in relation to a specific edge device, a specific use case or an application. In this paper, we first survey the state of the art in technologies for fog computing nodes, paying special attention to the contributions that analyze the role edge devices play in the fog node definition. We summarize and compare the concepts, lessons learned from their implementation, and end up showing how a conceptual framework is emerging towards a unifying fog node definition. We focus on core functionalities of a fog node as well as in the accompanying opportunities and challenges towards their practical realization in the near future.Postprint (author's final draft
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