Abstract:
Road-side unit (RSU) plays an important role in providing connectivity among the vehicles on the road. In rural areas,
RSUs are powered using renewable energy, such as solar or wind
energy. Hence, the energy consumption across such RSUs should
be efficient i.e., energy consumption at RSUs should be minimized
and no RSU gets over-utilized while others are under-utilized. The
amount of energy consumption depends upon the scheduling of
different kinds of data requests at RSU. In this paper, we propose
a scheduling architecture for minimizing energy consumption at
RSU and attaining uniform energy consumption across neighboring RSUs. This, in turn, increases the request fulfillment
percentage at RSUs. The proposed architecture categorizes the
incoming request as a Traditional (less computation) or a Smart
request (high computation). Two approaches - Hard-deadline Less
Computation requirement Approach (HLCA) and Soft-deadline
High Computation requirement Approach (SHCA) are proposed
for addressing Traditional and Smart data requests, respectively.
In HLCA approach, the receiving RSU uses the scheduling
metric to select the servicing RSU for request fulfillment. We
prove by analysis, how scheduling metric helps in minimizing
and achieving uniform energy consumption across the RSUs.
In SHCA approach, Fog computing is used for handling high
computation requests. Energy consumption at RSUs is further
optimized by using Auction game-based relay vehicle selection
mechanism. Simulation results demonstrate that our proposed
approaches achieve uniform energy consumption across multiple
RSUs and 10% more efficient than scheduling algorithms for
single RSU model such as Nearest Fastest Set Scheduler (NFS).
