Wireless Sensor Networks (WSN) consists of sensor nodes equipped with radios for wireless communication. The overall goal of the sensor networks is to gather data. The terminal point for the data is usually a specific node, called the sink. Nodes collaborate to relay data when direct communication between source and sink is impossible.
One of the main issues in WSN is energy consumption. Depleted nodes cannot collect data and the value of the accumulated data at the sink is therefore degraded. Since nodes forward traffic towards the sink, a depleted node may lead to network partitioning, thereby causing part of the network to be unavailable for the sink.
This study investigates the energy consumption related to the radio, and suggests algorithms to reduce the consumption. During operation, the radios switch between different states such as receiving, transmitting, idle and sleep. The amount of energy consumed varies with the radio state. The investigation reveals that the energy consumed to receive packets can have a substantial impact on the total consumption. In order to reduce the energy consumed in receiving, a simple algorithm has been developed that can function as an add-on to common communication protocols. The algorithm enables nodes to enter the sleep state rather than receive traffic that is not addressed to them.
The second topic addressed is the balance of energy consumption among the nodes. Balancing the energy consumption is a means to achieve an even residual-energy level among the nodes. The goal is to avoid early depletion of nodes, thereby preserving network availability. A broad range of different balancing algorithms has been presented in the literature and these have been classified, analyzed and compared. In addition, new balancing algorithms have been suggested. The routing protocol for Low Power and Lossy network (RPL) was used as the basis for assessment and improvements have been suggested. The findings are that, by introducing a minor change in the RPL algorithm, a significant balancing effect can be achieved. However, the best balancing effect is achieved if nodes always transmit data toward the next-hop node with the highest residual-energy level.
The third topic addressed is path recovery algorithms. Radio links may break or a node may die, either due to faults or to the already mentioned energy depletion. Link and node errors may lead to network partitioning. Such errors should be corrected in order to restore network connectivity. Various path-recovery algorithms have been proposed in this respect. This study analyses some suggested algorithms and suggests a few new recovery algorithms. The path recovery algorithms are categorized as either global or local. In global path recovery, the paths are generally recovered during periodic global network updates. Thus, high path-restoration delay may result in networks where the global updates are infrequently run. The local recovery algorithms, on the other hand, are triggered by path breaks and have a local scope. Thus, the local algorithms result in low delay and affect a limited number of nodes. By minimizing the number of affected nodes, the energy consumed during the process is reduced. However, the study findings show that the percentage of disconnected paths that are recovered is lower when using energy-efficient local recovery algorithms than when using global recovery algorithms. The possible trade-offs between local and global recovery are discussed.