A Unified Solution for Gateway and In-Network Traffic Load Balancing in Multihop Data Collection Scenarios

Data collection is a fundamental task of wireless sensor networks to support a variety of applications, such as remote monitoring, and emergency response, where collected information is relayed to an infrastructure network via packet gateways for processing and decision making. In large-scale monitoring scenarios, data packets need to be relayed over multihop paths to the gateways, and sensors are often randomly deployed, causing local node density differences. As a result, imbalance in data traffic load on the gateways is likely to occur. Furthermore, due to dynamic network conditions and differences in sensor data generation rates, congestion on some data paths is also often experienced. Numerous studies have focused on the problem of in-network traffic load balancing, whereas a few works have aimed at equalizing the loads on gateways. However, there is a potential tradeoff between these two problems. In this paper, the dual objective of gateway and in-network load balancing is addressed, and the reactive and adaptive load-balancing (RALB) algorithm is presented. RALB is proposed as a generic solution for multihop networks and mesh topologies, particularly in large-scale remote monitoring scenarios, to balance traffic loads.