LiveWSN: A memory-efficient, energy-efficient, reprogrammable, and fault-tolerant platform for wireless sensor network

Abstract

Memory optimization, energy conservation, over-the-air reprogramming, and fault tolerance are the critical challenges for the proliferation of the wireless sensor network. To address these challenges, a new wireless sensor network platform termed LiveWSN is presented in this article. In LiveWSN, several new design concepts are implemented, such as the hierarchical shared-stack scheduling and the pre-linking native-code reprogramming. By doing so, the data memory cost of the LiveWSN scheduling system can be optimized by 25% if compared with that of the traditional multithreaded MANTIS OS. Moreover, the application reprogramming code size can be decreased by 72.6% if compared with that of the Contiki dynamic-linking reprogramming. In addition to the new design concepts, the new research approach which addresses the energy conservation and fault tolerance challenges by combining the software technique and the multicore hardware technique is applied in LiveWSN. By means of the multi-core hardware infrastructure, the lifetime of the LiveWSN nodes can be prolonged by 34% if compared with the single-core Live node. Moreover, the fault-tolerant performance of the wireless sensor network node can be optimized significantly. With the above features, LiveWSN becomes memory efficient, energy efficient, reprogrammable, and fault tolerant, and it can run on the high resourceconstrained nodes to execute the outdoor real-time wireless sensor network applications.

Energy and Delay Optimization of Heterogeneous Multicore Wireless Multimedia Sensor Nodes by Adaptive Genetic‐Simulated Annealing Algorithm

“…Since different microcontrollers have differential features and are good at executing a given kind of WMSN tasks [22][23][24], each WMSN task can be scheduled to the microcontroller which is the most energy efficient to run it. By doing this, the energy resources can be utilized more efficiently.…”