We propose a routing scheme called energy-efficient beaconless geographic routing with energy supply (EBGRES) for wireless sensor networks. EBGRES provides loop-free, fully stateless, energy-efficient source-to-sink routing with minimal communication overhead without the help of prior neighborhood knowledge. It locally determines the duty-cycle of each node, based on an estimated energy budget for each period, which includes the currently available energy, the predicted energy consumption and the energy expected from the harvesting device. In EBGRES, each node sends out the data packet first rather than a control message. By sending a data packet first, EBGRES performs the neighbor selection only among those neighbors that successfully received the data packet. EBGRES uses a three-way (DATA/ACK/SELECT) handshake and a timer-assignment function, the Discrete Dynamic Forwarding Delay (DDFD). We investigate the lower and upper bounds on hop count and the upper bound on energy consumption under EBGRES for source-to-sink routing. We further demonstrate the expected total energy consumption along a route toward the sink with the proposed EBGRES approach including a lower bound on energy consumption when the node density increases. a cost effective, ubiquitous, commonly known, and well understood powering technology. However, they present specific challenges that include finite useful life, replacement cost, and disposal concerns. Although they are an ideal solution for many applications, there are many other applications where batteries fail to fit application requirements: for example, the asset is not available to replace the batteries, the cost of battery replacement is too expensive over the life of the product, the device is in a hazardous environment, or the device is embedded and a continuous power supply is required. Applications with these needs provide a good fit for receiving power via ambient energy harvesting [8].Unlike the microprocessor industry or the communication hardware industry, where the computation capability or the line rate has been continuously improved (almost doubled every 18 months), battery technology has been relatively unchanged for many years [8]. Ambient energy harvesting as a power solution has steadily gained momentum in recent years, especially with significant progress in the functionality of low power embedded electronics such as wireless sensor nodes. We define an energy harvesting node as any system that draws part or all of its energy from the environment such as solar energy, temperature variations, kinetic energy or vibrations. A key distinction of this energy from that stored in the battery is that this energy is potentially infinite, although there may be a limit on the rate at which it can be used. Energy harvesting sensor nodes have either an onboard energy harvesting component as shown in Figure 1, or a sensor node can be connected to an energy harvesting device/component to form one device. In our research we look at solar-based energy harvesting, which has a diurnal ch...
Mobile nodes within Wireless Sensor Networks (WSNs) open up new challenges such as improved energy efficiency, coverage, target tracking, and fault tolerance. We propose a novel Chain-Based Relocation Approach (CBRA) to relocate mobile sensor nodes from their initial positions within a Region Of Interest (ROI) to cover a particular event happening outside the initial deployment zone called Center a Of Interest (COI). CBRA uses a grid quorum-based solution to propagate the redundant nodes present within the ROI. We propose an energybased redundant node selection procedure to ensure a balanced energy consumption among the redundant nodes regardless of the location of the redundant nodes with respect to the COI. We evaluate the performance of the CBRA solution using the WSNet simulator. Simulation results show that the network energy consumption and the relocation time increase as the distance separating the COI from the ROI increases. Moreover, the whole network energy consumption improves with the network density while the relocation time decreases with increasing speed of sensor nodes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.