We describe a highly scalable distributed solution based on ADMM.
We compare the hybrid solution to an existing distributed solution using simulation and analysis.
Then, a distributed solution under the pricing framework via an efficient price-updating algorithm is proposed.
Graph-theoretic conditions are established under which the proposed methodology provides a distributed solution.
As a result, both the decentralized collection or storage of these datasets as well as accompanying distributed solution methods are either necessary or at least highly desirable.
This paper develops a decentralized distributed solution approach based on multi-agent systems (MAS) to manage the emergency vehicles.
Thus, in this paper, we propose a distributed solution, called Connectivity Restoration for Multi-Channel WSNs (CR-MC), to recover from a connectivity loss for multichannel WSNs.
In a case study, it is shown that a distributed solution is able to improve service availability significantly and to avoid large-scale outages.
Finally, we propose a centralized solution based on the classical convex programming method, as well as a partially distributed solution based on the Lagrangian dual decomposition technique.
Even though centralized solutions may lead to better solutions in terms of network efficiency, the dynamic nature of DSA networks make the distributed solution approaches more attractive.
Opposite to other proactive solutions which focus on popular content, we propose a distributed solution that targets less popular, personalised or dynamic content requests by prefetching data in small cells based on aggregated user mobility prediction information.
