Computationally intensive tasks of IoT applications can be offloaded to powerful devices in
the edge. Code offloading reduces energy consumption and increases performance …

With the rapid growth of mobile devices, more and more time sensitive tasks are emerging.
This kind of task often has strict requirements on delay. Edge computing solves this problem …

Edge computing is an emerging paradigm to enable low-latency applications, like mobile
augmented reality, because it takes the computation on processing devices that are closer to …

Edge computing is a promising solution to enable low-latency Internet of Things (IoT)
applications, by shifting computation from remote data centers to local devices, less powerful …

End users can mutually share their computing resources in ad-hoc computing environments
with code offloading. This augments the computational power of resource-constrained …

The growing popularity of Deep Neural Networks (DNNs) in a variety of domains, including
computer vision, natural language processing, and predictive analytics, has led to an …

Computation offloading is a useful technique to circumvent device restrictions and bring
novel, computationally-intensive applications to a heterogeneous and diverse device …

These days, the popularity of technologies such as machine learning, augmented reality,
and big data analytics is growing dramatically. This leads to a higher demand of …

Mobile ad-hoc computing enables applications to offload computationally intensive tasks to
end-user devices in proximity. Many state-of-the-art applications such as face recognition …

In recent years, the demand for computing power has increased considerably due to the
popularity of applications that involve computationally intensive tasks such as machine …