701 research outputs found
UAV-Empowered Disaster-Resilient Edge Architecture for Delay-Sensitive Communication
The fifth-generation (5G) communication systems will enable enhanced mobile
broadband, ultra-reliable low latency, and massive connectivity services. The
broadband and low-latency services are indispensable to public safety (PS)
communication during natural or man-made disasters. Recently, the third
generation partnership project long term evolution (3GPPLTE) has emerged as a
promising candidate to enable broadband PS communications. In this article,
first we present six major PS-LTE enabling services and the current status of
PS-LTE in 3GPP releases. Then, we discuss the spectrum bands allocated for
PS-LTE in major countries by international telecommunication union (ITU).
Finally, we propose a disaster resilient three-layered architecture for PS-LTE
(DR-PSLTE). This architecture consists of a software-defined network (SDN)
layer to provide centralized control, an unmanned air vehicle (UAV) cloudlet
layer to facilitate edge computing or to enable emergency communication link,
and a radio access layer. The proposed architecture is flexible and combines
the benefits of SDNs and edge computing to efficiently meet the delay
requirements of various PS-LTE services. Numerical results verified that under
the proposed DR-PSLTE architecture, delay is reduced by 20% as compared with
the conventional centralized computing architecture.Comment: 9,
Vehicular Fog Computing Enabled Real-time Collision Warning via Trajectory Calibration
Vehicular fog computing (VFC) has been envisioned as a promising paradigm for
enabling a variety of emerging intelligent transportation systems (ITS).
However, due to inevitable as well as non-negligible issues in wireless
communication, including transmission latency and packet loss, it is still
challenging in implementing safety-critical applications, such as real-time
collision warning in vehicular networks. In this paper, we present a vehicular
fog computing architecture, aiming at supporting effective and real-time
collision warning by offloading computation and communication overheads to
distributed fog nodes. With the system architecture, we further propose a
trajectory calibration based collision warning (TCCW) algorithm along with
tailored communication protocols. Specifically, an application-layer
vehicular-to-infrastructure (V2I) communication delay is fitted by the Stable
distribution with real-world field testing data. Then, a packet loss detection
mechanism is designed. Finally, TCCW calibrates real-time vehicle trajectories
based on received vehicle status including GPS coordinates, velocity,
acceleration, heading direction, as well as the estimation of communication
delay and the detection of packet loss. For performance evaluation, we build
the simulation model and implement conventional solutions including cloud-based
warning and fog-based warning without calibration for comparison. Real-vehicle
trajectories are extracted as the input, and the simulation results demonstrate
that the effectiveness of TCCW in terms of the highest precision and recall in
a wide range of scenarios
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
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