4,606 research outputs found
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
Mobile Edge Computing Empowers Internet of Things
In this paper, we propose a Mobile Edge Internet of Things (MEIoT)
architecture by leveraging the fiber-wireless access technology, the cloudlet
concept, and the software defined networking framework. The MEIoT architecture
brings computing and storage resources close to Internet of Things (IoT)
devices in order to speed up IoT data sharing and analytics. Specifically, the
IoT devices (belonging to the same user) are associated to a specific proxy
Virtual Machine (VM) in the nearby cloudlet. The proxy VM stores and analyzes
the IoT data (generated by its IoT devices) in real-time. Moreover, we
introduce the semantic and social IoT technology in the context of MEIoT to
solve the interoperability and inefficient access control problem in the IoT
system. In addition, we propose two dynamic proxy VM migration methods to
minimize the end-to-end delay between proxy VMs and their IoT devices and to
minimize the total on-grid energy consumption of the cloudlets, respectively.
Performance of the proposed methods are validated via extensive simulations
- …