Solar-aware clustering in wireless sensor networks

Abstract

Eiiergy conservation plays a crucial in wireless sensor networks since such networks are designed to be placed in hostile and non-accessible areas. While battery-driven sensors will run out of battery sooner or late< the use of renewable energy sources such as solar power or gravitation may extend the lifetime of a sensor network. We propose to utilize solar power in wireless sensor networks and extend LEACH a well-known cluster-based protocol for sensor networks to become solar-aware. The presented simulation results show that making LEACH solar-aware significantly extends the lifetime of sensor networks.

A Clustering Protocol for Periodic Data Acquisition in Wireless Sensor Networks

“…We run CP-PDA with two different d T : 500ms (scene 1) and 300ms (scene 2). Based on the formula (10), (11) and (12), the value of related parameters is given in Table 1. Figure 2 shows the transmission cycle of nodes in the first 15 rounds in one sample of the simulation.…”

Reliable low-energy group formation for infrastructure-less public safety networks

“…The previous studies have investigated minimizing the total energy of the network in wireless sensor networks (WSNs) [16][17][18][19][20][21]. In WSNs, low-energy adaptive clustering hierarchy-centralized (LEACH-C) [18] proposed a …”

“…Several improvements have been proposed to enhance LEACH-C by considering residual energy [19], a re-clustering frequency [20], and solar cells [21]. In [23][24][25], LEACH-C has been improved by replacing simulated annealing with K-means clustering [26], which has been proved to be efficient for most clustering tasks in machine learning fields.…”

A Modelling Framework for Energy Harvesting Aware Wireless Sensor Networks

“…Consider an energy harvester based on solar cells, the amount of energy being harvested, not only depends on the efficiency of the solar cell technology, but also on the time of day, local weather conditions (e.g., clouds), shadows from building, trees, etc.. For these conditions, the energy-aware algorithms presented above, cannot be used as they assume residual battery energy to be monotonically decreasing. A few energy harvesting aware algorithms have been proposed to address these issues, such as Islam et al (2007); Lattanzi et al (2007); Lin et al (2007); Voigt et al (2004;; Zeng et al (2006). They do not make the assumption of monotonically decreasing residual battery energy, and hence, can account for both discharging and charging the battery.…”

“…The clustering routing approach used in Islam et al (2007); Voigt et al (2004) assumes that all nodes are able to reach the base station directly. A partial energy harvesting ability is used in Voigt et al (2003), where excess harvested energy can not be stored and the nodes are only battery powered during night.…”