TY - GEN
T1 - Peer Data Caching Algorithms in Large-Scale High-Mobility Pervasive Edge Computing Environments
AU - Huang, Yaodong
AU - Ye, Fan
AU - Yang, Yuanyuan
N1 - Publisher Copyright: © 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - Emerging innovative edge devices like drones, self-driving cars, phones/tablets and IoT nodes are revolutionizing our daily lives. Caching data among peer edge devices enables data sharing needed in many applications. In such applications, network scalability and node mobility bring many challenges. They change the topology and the resources in the network and make the network less robust. In this paper, we propose peer data caching strategies that consider the scale and mobility of these increasingly popular edge devices. We propose a grouping method creating a layered design to reduce the number of entities in each layer. We propose inter-group and intra-group optimization problems which proactively cache data onto best places to support robust and fast data access. We develop a 7-approximation algorithm for inter-group optimization and use uncapacitated facility location problems to solve intra-group optimization. We also transform the mobility of nodes into node behaviors to reduce the impact of mobility on the network. Our extensive simulation results show that our proposed strategies can apply to large-size and high-mobility networks, while achieving satisfactory results for data access.
AB - Emerging innovative edge devices like drones, self-driving cars, phones/tablets and IoT nodes are revolutionizing our daily lives. Caching data among peer edge devices enables data sharing needed in many applications. In such applications, network scalability and node mobility bring many challenges. They change the topology and the resources in the network and make the network less robust. In this paper, we propose peer data caching strategies that consider the scale and mobility of these increasingly popular edge devices. We propose a grouping method creating a layered design to reduce the number of entities in each layer. We propose inter-group and intra-group optimization problems which proactively cache data onto best places to support robust and fast data access. We develop a 7-approximation algorithm for inter-group optimization and use uncapacitated facility location problems to solve intra-group optimization. We also transform the mobility of nodes into node behaviors to reduce the impact of mobility on the network. Our extensive simulation results show that our proposed strategies can apply to large-size and high-mobility networks, while achieving satisfactory results for data access.
UR - https://www.scopus.com/pages/publications/85066506296
U2 - 10.1109/PCCC.2018.8711041
DO - 10.1109/PCCC.2018.8711041
M3 - Conference contribution
T3 - 2018 IEEE 37th International Performance Computing and Communications Conference, IPCCC 2018
BT - 2018 IEEE 37th International Performance Computing and Communications Conference, IPCCC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 37th IEEE International Performance Computing and Communications Conference, IPCCC 2018
Y2 - 17 November 2018 through 19 November 2018
ER -