3 research outputs found
Mobile Edge Cloud: Opportunities and Challenges
Mobile edge cloud is emerging as a promising technology to the internet of
things and cyber-physical system applications such as smart home and
intelligent video surveillance. In a smart home, various sensors are deployed
to monitor the home environment and physiological health of individuals. The
data collected by sensors are sent to an application, where numerous algorithms
for emotion and sentiment detection, activity recognition and situation
management are applied to provide healthcare- and emergency-related services
and to manage resources at the home. The executions of these algorithms require
a vast amount of computing and storage resources. To address the issue, the
conventional approach is to send the collected data to an application on an
internet cloud. This approach has several problems such as high communication
latency, communication energy consumption and unnecessary data traffic to the
core network. To overcome the drawbacks of the conventional cloud-based
approach, a new system called mobile edge cloud is proposed. In mobile edge
cloud, multiple mobiles and stationary devices interconnected through wireless
local area networks are combined to create a small cloud infrastructure at a
local physical area such as a home. Compared to traditional mobile distributed
computing systems, mobile edge cloud introduces several complex challenges due
to the heterogeneous computing environment, heterogeneous and dynamic network
environment, node mobility, and limited battery power. The real-time
requirements associated with the internet of things and cyber-physical system
applications make the problem even more challenging. In this paper, we describe
the applications and challenges associated with the design and development of
mobile edge cloud system and propose an architecture based on a cross layer
design approach for effective decision making.Comment: 4th Annual Conference on Computational Science and Computational
Intelligence, December 14-16, 2017, Las Vegas, Nevada, USA. arXiv admin note:
text overlap with arXiv:1810.0704
A Mobile Ad hoc Cloud Computing and Networking Infrastructure for Automated Video Surveillance System
Mobile automated video surveillance system involves application of real-time
image and video processing algorithms which require a vast quantity of
computing and storage resources. To support the execution of mobile automated
video surveillance system, a mobile ad hoc cloud computing and networking
infrastructure is proposed in which multiple mobile devices interconnected
through a mobile ad hoc network are combined to create a virtual supercomputing
node. An energy efficient resource allocation scheme has also been proposed for
allocation of realtime automated video surveillance tasks. To enable
communication between mobile devices, a Wi-Fi Direct based mobile ad hoc cloud
networking infrastructure has been developed. More specifically, a routing
layer has been developed to support communication between Wi-Fi Direct devices
in a group and multi-hop communication between devices across the group. The
proposed system has been implemented on a group of Wi-Fi Direct-enabled Samsung
mobile devices.Comment: Technical Reports, 14 Page
An Energy-Efficient Resource Management System for a Mobile Ad Hoc Cloud
Recently, mobile ad hoc clouds have emerged as a promising technology for
mobile cyber-physical system applications, such as mobile intelligent video
surveillance and smart homes. Resource management plays a key role in
maximizing resource utilization and application performance in mobile ad hoc
clouds. Unlike resource management in traditional distributed computing
systems, such as clouds, resource management in a mobile ad hoc cloud poses
numerous challenges owing to the node mobility, limited battery power, high
latency, and the dynamic network environment. The real-time requirements
associated with mobile cyber-physical system applications make the problem even
more challenging. Currently, existing resource management systems for mobile ad
hoc clouds are not designed to support mobile cyber-physical system
applications and energy-efficient communication between application tasks. In
this paper, we propose a new energy-efficient resource management system for
mobile ad hoc clouds. The proposed system consists of two layers: a network
layer and a middleware layer. The network layer provides ad hoc network and
communication services to the middleware layer and shares the collected
information in order to allow efficient and robust resource management
decisions. It uses (1) a transmission power control mechanism to improve energy
efficiency and network capacity, (2) link lifetimes to reduce communication and
energy consumption costs, and (3) link quality to estimate data transfer times.
The middleware layer is responsible for the discovery, monitoring, migration,
and allocation of resources. It receives application tasks from users and
allocates tasks to nodes on the basis of network and node-level information.Comment: 19 Page