Decentralized decision-making and urban planning: A case study of density for benefit agreements in Toronto and Vancouver
This article compares the design and implementation of density for benefit agreements (DBAs), a form of density “bonusing” in Toronto and Vancouver. The cities identify many of the same priorities for benefits secured from developers, but in practice they prioritize widely different benefits. By comparing practice in Toronto and Vancouver, this article demonstrates how institutional differences and the decentralization of policy decision-making in major cities can affect urban planning decision-making.
Mobile Edge Computing application domains such as vehicular networks, unmanned aerial vehicles, data analytics tasks at the edge and augmented reality have recently emerged. Under such domains, while mobile nodes are moving and have certain tasks to be offloaded to Edge Servers, choosing an appropriate time and an ideally suited server to guarantee the quality of service can be challenging. We tackle the offloading decision making problem by adopting the principles of Optimal Stopping Theory to minimize the execution delay in a sequential decision manner. A performance evaluation is provided by using real data sets compared with the optimal solution. The results show that our approach significantly minimizes the execution delay for task execution and the results are very close to the optimal solution.