IEEE Infocom 2014-Workshop on Green Cognitive Communications and Computer Networking (GCCCN).
As a key enabler of Internet of things, cellular
network based Machine-to-Machine (M2M) communications have
been growing rapidly in recent years, being used in a wide range
of services such as security, metering, health, remote control,
tracking, and so on. A critical issue in M2M communications
is the energy efficiency as typically the machine devices are
powered by batteries of low capacity and thus, it is the key to
optimize their consumption.
To achieve higher energy efficiency,
this paper proposes the adoption of contexts through a generic
context-aware framework for M2M communications. With this
framework, machine devices dynamically adapt their settings
depending on a series of characteristics such as data reporting
mode, QoS features, and network conditions to achieve higher
energy efficiency and extend the operating lifetime of M2M
networks. Simulation results are provided for four commonly
used M2M applications.
The results demonstrate considerable
energy savings and operating lifetime extension on the network
when the proposed context-aware framework is used. Thus, it
is shown that contexts play an important role on the energy
efficiency of M2M systems.
Costa and G. W. Miao, “Context-Aware Machine-to-Machine” in IEEE Infocom 2014-Workshop on Green Cognitive Communications and Computer Networking (GCCCN).