978 research outputs found
Cognitive Connectivity Resilience in Multi-layer Remotely Deployed Mobile Internet of Things
Enabling the Internet of things in remote areas without traditional
communication infrastructure requires a multi-layer network architecture. The
devices in the overlay network are required to provide coverage to the underlay
devices as well as to remain connected to other overlay devices. The
coordination, planning, and design of such two-layer heterogeneous networks is
an important problem to address. Moreover, the mobility of the nodes and their
vulnerability to adversaries pose new challenges to the connectivity. For
instance, the connectivity of devices can be affected by changes in the
network, e.g., the mobility of the underlay devices or the unavailability of
overlay devices due to failure or adversarial attacks. To this end, this work
proposes a feedback based adaptive, self-configurable, and resilient framework
for the overlay network that cognitively adapts to the changes in the network
to provide reliable connectivity between spatially dispersed smart devices. Our
results show that if sufficient overlay devices are available, the framework
leads to a connected configuration that ensures a high coverage of the mobile
underlay network. Moreover, the framework can actively reconfigure itself in
the event of varying levels of device failure.Comment: To appear in IEEE Global Communications Conference (Globecom 2017
Relaying in the Internet of Things (IoT): A Survey
The deployment of relays between Internet of Things (IoT) end devices and gateways can improve link quality. In cellular-based IoT, relays have the potential to reduce base station overload. The energy expended in single-hop long-range communication can be reduced if relays listen to transmissions of end devices and forward these observations to gateways. However, incorporating relays into IoT networks faces some challenges. IoT end devices are designed primarily for uplink communication of small-sized observations toward the network; hence, opportunistically using end devices as relays needs a redesign of both the medium access control (MAC) layer protocol of such end devices and possible addition of new communication interfaces. Additionally, the wake-up time of IoT end devices needs to be synchronized with that of the relays. For cellular-based IoT, the possibility of using infrastructure relays exists, and noncellular IoT networks can leverage the presence of mobile devices for relaying, for example, in remote healthcare. However, the latter presents problems of incentivizing relay participation and managing the mobility of relays. Furthermore, although relays can increase the lifetime of IoT networks, deploying relays implies the need for additional batteries to power them. This can erode the energy efficiency gain that relays offer. Therefore, designing relay-assisted IoT networks that provide acceptable trade-offs is key, and this goes beyond adding an extra transmit RF chain to a relay-enabled IoT end device. There has been increasing research interest in IoT relaying, as demonstrated in the available literature. Works that consider these issues are surveyed in this paper to provide insight into the state of the art, provide design insights for network designers and motivate future research directions
Edge Intelligence for Empowering IoT-based Healthcare Systems
The demand for real-time, affordable, and efficient smart healthcare services
is increasing exponentially due to the technological revolution and burst of
population. To meet the increasing demands on this critical infrastructure,
there is a need for intelligent methods to cope with the existing obstacles in
this area. In this regard, edge computing technology can reduce latency and
energy consumption by moving processes closer to the data sources in comparison
to the traditional centralized cloud and IoT-based healthcare systems. In
addition, by bringing automated insights into the smart healthcare systems,
artificial intelligence (AI) provides the possibility of detecting and
predicting high-risk diseases in advance, decreasing medical costs for
patients, and offering efficient treatments. The objective of this article is
to highlight the benefits of the adoption of edge intelligent technology, along
with AI in smart healthcare systems. Moreover, a novel smart healthcare model
is proposed to boost the utilization of AI and edge technology in smart
healthcare systems. Additionally, the paper discusses issues and research
directions arising when integrating these different technologies together.Comment: This paper has been accepted in IEEE Wireless Communication Magazin
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