356 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
A game-theoretic approach to computation offloading in mobile cloud computing
We consider a three-tier architecture for mobile and pervasive computing
scenarios, consisting of a local tier ofmobile nodes, a middle tier (cloudlets) of nearby
computing nodes, typically located at the mobile nodes access points but characterized by a limited amount of resources, and a remote tier of distant cloud servers, which have
practically infinite resources. This architecture has been proposed to get the benefits of
computation offloading from mobile nodes to external servers while limiting the use
of distant servers whose higher latency could negatively impact the user experience.
For this architecture, we consider a usage scenario where no central authority exists
and multiple non-cooperative mobile users share the limited computing resources of
a close-by cloudlet and can selfishly decide to send their computations to any of the
three tiers. We define a model to capture the users interaction and to investigate the
effects of computation offloading on the users’ perceived performance. We formulate
the problem as a generalized Nash equilibrium problem and show existence of an
equilibrium.We present a distributed algorithm for the computation of an equilibrium
which is tailored to the problem structure and is based on an in-depth analysis of
the underlying equilibrium problem. Through numerical examples, we illustrate its
behavior and the characteristics of the achieved equilibria
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