Survey: energy efficient protocols using radio scheduling in wireless sensor network

An efficient energy management scheme is crucial factor for design and implementation of any sensor network. Almost all sensor networks are structured with numerous small sized, low cost sensor devices which are scattered over the large area. To improvise the network performance by high throughput with minimum energy consumption, an energy efficient radio scheduling MAC protocol is effective solution, since MAC layer has the capability to collaborate with distributed wireless networks. The present survey study provides relevant research work towards radio scheduling mechanism in the design of energy efficient wireless sensor networks (WSNs). The various radio scheduling protocols are exist in the literature, which has some limitations. Therefore, it is require developing a new energy efficient radio scheduling protocol to perform multi tasks with minimum energy consumption (e.g. data transmission). The most of research studies paying more attention towards to enhance the overall network lifetime with the aim of using energy efficient scheduling protocol. In that context, this survey study overviews the different categories of MAC based radio scheduling protocols and those protocols are measured by evaluating their data transmission capability, energy efficiency, and network performance. With the extensive analysis of existing works, many research challenges are stated. Also provides future directions for new WSN design at the end of this survey

An energy-efficient adaptive sampling scheme for wireless sensor networks

Wireless sensor networks are new monitoring platforms. To cope with their resource constraints, in terms of energy and bandwidth, spatial and temporal correlation in sensor data can be exploited to find an optimal sampling strategy to reduce number of sampling nodes and/or sampling frequencies while maintaining high data quality. Majority of existing adaptive sampling approaches change their sampling frequency upon detection of (significant) changes in measurements. There are, however, applications that can tolerate (significant) changes in measurements as long as measurements fall within a specific range. Using existing adaptive sampling approaches for these applications is not energy-efficient. Targeting this type of applications, in this paper, we propose an energy-efficient adaptive sampling technique ensuring a certain level of data quality. We compare our proposed technique with two existing adaptive sampling approaches in a simulation environment and show its superiority in terms of energy efficiency and data quality