An Effective Massive Sensor Network Data Access Scheme Based on Topology Control for the Internet of Things

Abstract

This paper considers the distributed access and control problem of massive wireless sensor networks’ data access center for the Internet of Things, which is an extension of wireless sensor networks and an element of its topology structure. In the context of the arrival of massive service access requests at a virtual data center, this paper designs a massive sensing data access and control mechanism to improve the access efficiency of service requests and makes full use of the available resources at the data access center for the Internet of things. Firstly, this paper proposes a synergistically distributed buffer access model, which separates the information of resource and location. Secondly, the paper divides the service access requests into multiple virtual groups based on their characteristics and locations using an optimized self-organizing feature map neural network. Furthermore, this paper designs an optimal scheduling algorithm of group migration based on the combination scheme between the artificial bee colony algorithm and chaos searching theory. Finally, the experimental results demonstrate that this mechanism outperforms the existing schemes in terms of enhancing the accessibility of service requests effectively, reducing network delay, and has higher load balancing capacity and higher resource utility rate.

RGCA: a Reliable GPU Cluster Architecture for Large-Scale Internet of Things Computing Based on Effective Performance-Energy Optimization

“…In IoT, the massive amount of data generated by a user's family is collected by the sensor network deployed in each home, and the collected data packets are decoded and then stored into the Data Access System for the Internet of Things (DASIoT) [13]. After DASIoT's transformation and control, this information is exchanged and communicated for the intelligent identification, location, tracking, supervision and management of the objects [14] and processes of the application system so that an intelligent network is created between man, the Internet and things.…”

RGCA: A Reliable GPU Cluster Architecture for Large-Scale Internet of Things Computing Based on Effective Performance-Energy Optimization

“…Our large-scale smart home cloud platform lab can access and store 48 M data per second in real-time from 420,000 households, enabling millions of bytes of data throughout per second. In IoT, the massive amount of data generated by a user’s family is collected by the sensor network deployed in each home, and the collected data packets are decoded and then transformed in the Data Access System for the Internet of Things (DASIoT) [ 15 ]. After DASIoT’s decoding and transformation, these data are transformed and communicated for the automatic detection, identification, tracking and control of the objects [ 16 ] and execution of the application system so that an intelligent network is established between humans, the Internet and things.…”