Stiff changes in the first- and second-order spatial gradients were lessened by continuously moving nodes in a non-stiff manner.
This paper exploits some recent modeling achievements [3] to study the novel topic of WAVE connectivity offered by roadside and moving nodes in a urban setting.
However, in a MU network with rapidly moving nodes (e.g., users in cars/trains in long-term evolution (LTE) systems), the resultant time-selectivity of the channel impulse response (CIR) introduces a large number of channel parameters.
This is because that although 7 moving nodes can result in more 0.000002 energy consumption, 5 moving nodes have more number of neighbors and cost more energy.
However, for practical broadband relay networks where the source and the relay can all be moving nodes, e.g., mobile terminals in moving cars or high-speed trains.
The extended Lloyd's algorithm then moves nodes around, which results in a refinement around the fixed node.
There are, however, a couple issues that I would like the authors to address: Even though I didn't think moving nodes around was necessary in the demo it was still the first thing I wanted to do (e.g., clicking on node and dragging it into a new position) and I can imagine other graphs where this might feel a bit more urgent.
Even though I didn't think moving nodes around was necessary in the demo it was still the first thing I wanted to do (e.g., clicking on node and dragging it into a new position) and I can imagine other graphs where this might feel a bit more urgent.
When the moving time is 80 s and the number of moving nodes is 10, energy consumption has the maximum, since the larger number of moving nodes can result in more energy consumption.
Consider the scenario that a static sensor node harvests energy and transmits information to a moving node, as shown in Fig. 1.
