The mobile edge computing framework offers the opportunity to reduce the energy that
devices must expend to complete computational tasks. The extent of that energy reduction …

When multiple users seek to offload computational tasks to their access point, the nature of
the multiple access scheme, and the optimization of its parameters, play a critical role in the …

Computation offloading enables energy-limited devices to expand the scope of the
computational tasks that they can complete within specified latency requirements. However …

When multiple devices seek to offload computational tasks to their access point, the nature
of the multiple access scheme plays a critical role in the system performance. For a system …

By offering shared computational facilities to which mobile devices can offload their
computational tasks, the mobile edge computing framework is expanding the scope of …

The opportunity to offload computational tasks to computing resources embedded in the
network infrastructure enables mobile users to expand the scope of the applications that can …

The shared computational resources provided by the mobile cloud computing paradigm
offer the opportunity for mobile devices to reduce the energy expended, or the latency …

The Mobile Edge Computing framework provides small scale devices with the opportunity to
offload their computational tasks to computing infrastructure at a network access point …

Multi-user computation offloading inherently involves the allocation of communication
resources among the offloading devices. Since the devices require timely results, that …

Offloading computational tasks to a shared computation resource is a promising approach
for mobile users to reduce the energy consumption and the latency of the applications they …