A New Collaborative Approach for Consignment Balancing in Wireless Sensor Networks via Mu-Mimo

Abstract

A three-layer framework is proposed for mobile data collection in wireless sensor networks, which includes the sensor layer, cluster head layer, and mobile collector (called Sensor) layer. The framework employs  distributed  load  balanced  clustering  and  dual  data uploading, which is referred to as LBC-DDU. The objective is to achieve good scalability, long network lifetime and low  data  collection  latency.  At  the  sensor  layer,  a distributed load balanced clustering (LBC) algorithm is proposed for sensors to self-organize themselves into clusters. In contrast to existing clustering methods, our scheme generates multiple cluster heads in each cluster to balance the work load and facilitate dual data uploading. At the cluster head layer, the inter-cluster transmission range is carefully chosen to guarantee the connectivity among the clusters. Multiple cluster heads within a cluster cooperate with each other to perform energy-saving inter- cluster            communications.       Through                           inter-cluster transmissions, cluster head information is forwarded to Sensor for its moving trajectory planning. At the mobile collector layer, Sensor is equipped with two antennas, which enables two cluster heads to simultaneously upload data to Sensor in each time by utilizing multi-user multiple-input and multiple-output (MU-MIMO) technique.