In Multi-task learning (MTL), a joint model is trained to simultaneously make predictions for
several tasks. Joint training reduces computation costs and improves data efficiency; …

In this paper, a fair scheme to allocate subcarrier, rate, and power for multiuser orthogonal
frequency-division multiple-access systems is proposed. The problem is to maximize the …

Load balancing in the cloud computing environment has an important impact on the
performance. Good load balancing makes cloud computing more efficient and improves …

In this paper, we present a game theoretic framework for obtaining a user-optimal load
balancing scheme in heterogeneous distributed systems. We formulate the static load …

Fog computing, as a promising technique, is with huge advantages in dealing with large
amounts of data and information with low latency and high security. We introduce a …

This paper proposes a cooperation strategy among rational nodes in a wireless cooperative
relaying network as an effort to solve two basic problems, ie, when to cooperate and how to …

In this paper, we present a game theoretic approach to solve the static load balancing
problem for single-class and multi-class (multi-user) jobs in a distributed system where the …

Computational grids are promising next-generation computing platforms for large-scale
problems in science and engineering. Grids are large-scale computing systems composed …

Summary form only given. This article realizes the vision of mobile grid computing by
proposing a fair pricing strategy and an optimal, static job allocation scheme. Mobile devices …

A grid differs from traditional high performance computing systems in the heterogeneity of
the computing nodes as well as the communication links that connect the different nodes …