809 research outputs found
Joint Service Caching and Task Offloading for Mobile Edge Computing in Dense Networks
Mobile Edge Computing (MEC) pushes computing functionalities away from the
centralized cloud to the network edge, thereby meeting the latency requirements
of many emerging mobile applications and saving backhaul network bandwidth.
Although many existing works have studied computation offloading policies,
service caching is an equally, if not more important, design topic of MEC, yet
receives much less attention. Service caching refers to caching application
services and their related databases/libraries in the edge server (e.g.
MEC-enabled BS), thereby enabling corresponding computation tasks to be
executed. Because only a small number of application services can be cached in
resource-limited edge server at the same time, which services to cache has to
be judiciously decided to maximize the edge computing performance. In this
paper, we investigate the extremely compelling but much less studied problem of
dynamic service caching in MEC-enabled dense cellular networks. We propose an
efficient online algorithm, called OREO, which jointly optimizes dynamic
service caching and task offloading to address a number of key challenges in
MEC systems, including service heterogeneity, unknown system dynamics, spatial
demand coupling and decentralized coordination. Our algorithm is developed
based on Lyapunov optimization and Gibbs sampling, works online without
requiring future information, and achieves provable close-to-optimal
performance. Simulation results show that our algorithm can effectively reduce
computation latency for end users while keeping energy consumption low
The edge cloud: A holistic view of communication, computation and caching
The evolution of communication networks shows a clear shift of focus from
just improving the communications aspects to enabling new important services,
from Industry 4.0 to automated driving, virtual/augmented reality, Internet of
Things (IoT), and so on. This trend is evident in the roadmap planned for the
deployment of the fifth generation (5G) communication networks. This ambitious
goal requires a paradigm shift towards a vision that looks at communication,
computation and caching (3C) resources as three components of a single holistic
system. The further step is to bring these 3C resources closer to the mobile
user, at the edge of the network, to enable very low latency and high
reliability services. The scope of this chapter is to show that signal
processing techniques can play a key role in this new vision. In particular, we
motivate the joint optimization of 3C resources. Then we show how graph-based
representations can play a key role in building effective learning methods and
devising innovative resource allocation techniques.Comment: to appear in the book "Cooperative and Graph Signal Pocessing:
Principles and Applications", P. Djuric and C. Richard Eds., Academic Press,
Elsevier, 201
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