This work is devoted to the study of a network on chip [3] model: IPNoSys (Integrated On-chip Network Processing System), having as main objective to obtain an optimal configuration of the network, comparing performance and power consumption. In this work, the platform IPNoSys shall be subject to execution of a set of synchronous dataflow generic applications. The term “generic” means that they...

Contiki’s Cooja is a very popular wireless sensor network (WSN) simulator, but it lacks support for modelling sensing coverage, focusing instead on network connectivity and protocol performance. However, in practice, it is the ability of a sensor network to provide a satisfactory level of coverage that defines its ultimate utility for end-users. We introduce WSN-Maintain, a Cooja-based tool for...

With regard to the subject of sensor network node optimization, a strategy for wireless sensor network coverage optimization based on improved fish swarm algorithm is proposed in this paper. The improved algorithm is targeted on network coverage, node utilization rate and energy consumption balance, which makes use of the ergodic property of chaotic motion to overcome the disadvantage that arti...

For the sensor network to operate successfully, the active nodes should maintain both sensing coverage and network connectivity. Furthermore, scheduling sleep intervals plays critical role for energy efficiency of wireless sensor networks. Traditional methods for sensor scheduling use either sensing coverage or network connectivity, but rarely both. In this paper, we use random scheduling for s...

Wireless network coverage planning is crucial for mobile operators and fixed wireless providers to estimate the performance of their networks plan future antenna mast deployments. To generate accurate maps target buildings, traditional tools either require manual input Customer-Premises Equipment (CPE) locations or need compute received signal strength from nearby Access Points (APs) all geoloc...