TY - GEN
T1 - Deployment Planning in Vehicular Supported Cellular Networks
AU - Lavi, Nadav
AU - Sherzer, Eliran
AU - Levy, Hanoch
N1 - Publisher Copyright: © 2020 ACM.
PY - 2020/5/18
Y1 - 2020/5/18
N2 - We consider the planning problem of a unique cellular model in which parked vehicles, termed Vehicular Relay Nodes (VeRNs), assist the network by relaying data to and from users. VeRNs can lower cellular network load and provide a scalable solution to the explosive growth in data demand. The VeRN model presents a new paradigm that significantly differs from toady's cellular deployments that are based solely on fixed infrastructure. Consequently, known deployment planning methods are inapplicable. The complexity arises from utilizing vehicles which adds stochastic resource variables to the stochastic data demand variables, as well as from the deployment structure/topology and the cost trade-offs between fixed resources, stochastic resources, and user demand. We present a holistic solution for this unique deployment planning problem. Our solution is based on the combination of three methodologies, which enables us establishing the convexity, and thus greediness properties of the problem. This allows focusing the analysis on deriving marginal values, instead of full system analysis. We further propose an approach to approximate the marginal values supported by effective state space bounds. Numerical results show that the method is efficient, and addresses various distribution settings.
AB - We consider the planning problem of a unique cellular model in which parked vehicles, termed Vehicular Relay Nodes (VeRNs), assist the network by relaying data to and from users. VeRNs can lower cellular network load and provide a scalable solution to the explosive growth in data demand. The VeRN model presents a new paradigm that significantly differs from toady's cellular deployments that are based solely on fixed infrastructure. Consequently, known deployment planning methods are inapplicable. The complexity arises from utilizing vehicles which adds stochastic resource variables to the stochastic data demand variables, as well as from the deployment structure/topology and the cost trade-offs between fixed resources, stochastic resources, and user demand. We present a holistic solution for this unique deployment planning problem. Our solution is based on the combination of three methodologies, which enables us establishing the convexity, and thus greediness properties of the problem. This allows focusing the analysis on deriving marginal values, instead of full system analysis. We further propose an approach to approximate the marginal values supported by effective state space bounds. Numerical results show that the method is efficient, and addresses various distribution settings.
KW - Cellular Deployment Optimization
KW - Resource Allocation and Assignment
KW - Stochastic Analysis
KW - Vehicular Relay Nodes
UR - http://www.scopus.com/inward/record.url?scp=85086142420&partnerID=8YFLogxK
U2 - https://doi.org/10.1145/3388831.3388855
DO - https://doi.org/10.1145/3388831.3388855
M3 - منشور من مؤتمر
T3 - ACM International Conference Proceeding Series
SP - 64
EP - 71
BT - Proceedings of the 13th EAI International Conference on Performance Evaluation Methodologies and Tools, VALUETOOLS 2020
T2 - 13th EAI International Conference on Performance Evaluation Methodologies and Tools, VALUETOOLS 2020
Y2 - 18 May 2020 through 20 May 2020
ER -