LBR: Load Balancing Routing Algorithm for Wireless Sensor Networks

Abstract

Abstract. Homogeneous wireless sensor networks (WSNs) are organized using identical sensor nodes, but the nature of WSNs operations results in an imbalanced workload on gateway sensor nodes which may lead to a hot-spot or routing hole problem. The routing hole problem can be considered as a natural result of the tree-based routing schemes that are widely used in WSNs, where all nodes construct a multi-hop routing tree to a centralized root, e.g., a gateway or base station. For example, sensor nodes on the routing path and closer to the base station deplete their own energy faster than other nodes, or sensor nodes with the best link state to the base station are overloaded with traffic from the rest of the network and experience a faster energy depletion rate than their peers. Routing protocols for WSNs are reliability-oriented and their use of reliability metric to avoid unreliable links makes the routing scheme worse. However, none of these reliability oriented routing protocols explicitly uses load balancing in their routing schemes. Since improving network lifetime is a fundamental challenge of WSNs, we present, in this chapter, a novel, energy-wise, load balancing routing (LBR) algorithm that addresses load balancing in an energy efficient manner by maintaining a reliable set of parent nodes. This allows sensor nodes to quickly find a new parent upon parent loss due to the existing of node failure or energy hole. The proposed routing algorithm is tested using simulations and the results demonstrate that it outperforms the MultiHopLQI reliability based routing algorithm.

Reliable data delivery in low energy ad hoc sensor networks

“…RLBR appropriately adapts such situations and does its best to be aware of energy levels of the relay sensor nodes. This dynamic adaptation strategy can alleviate the energy-hole problem as stated in [7] and [8]. It also aims for load balancing between relay sensor nodes in terms of balanced energy usage, and minimising energy dissipation for packet transmissions by means of adaptive beaconing and in-network aggregation of data packets.…”

“…It has been shown in [6], [7] and [8] that the network lifetime is extended if the rate of energy across the network is uniformly dissipated. For example, if a selected route is the preferred path and all routed data packets consistently relayed through relay sensor nodes along this selected route, these relay sensor nodes will deplete their batteries faster and eventually die off earlier than their peer nodes on other routes.…”

“…The work in this paper is built on our existing work stated in [10][12] [13][18] which focuses on TinyOS-based indoor WSNs, but it also aims to improve the performance of the RLBR protocol by extending the experiments for outdoor TinyOS-based WSN testbed with interference-prone channels. RLBR employs Channel State Information (CSI) e.g., RSSI and LQI, link estimation based on packet transmissions e.g., success reception ratio (PRR) and packet error ratio (PER), and residual energy capacity including other parameters, e.g., source id, CRC, hop count, aggregation load, and latency to form a cost function for selecting the most reliable and energyefficient route towards the base station.…”

Reliable routing for low-power smart space communications

“…• Imbalanced workload on relay nodes • Topological bottleneck tree-based routing • Network partitioning and routing-hole problem [9] Problem Statement …”

Reliable routing scheme for indoor sensor networks

“…RLBR scheme allows a child sensor node dynamically searches for a new reliable parent node with more residual energy. This dynamic adaptation strategy can alleviate the energy-hole problem as stated in [10] [23]. The experimental work done in this paper aims to investigate the indoor performance of RLBR scheme in terms of reliability, packet delivery, and energy efficiency.…”