A 3D multi-objective optimization planning algorithm for wireless sensor networks

The complexity of planning a wireless sensor network is dependent on the aspects of optimization and on the application requirements. Even though Murphy's Law is applied everywhere in reality, a good planning algorithm will assist the designers to be aware of the short plates of their design and to improve them before the problems being exposed at the real deployment. A 3D multi-objective planning algorithm is proposed in this paper to provide solutions on the locations of nodes and their properties. It employs a developed ray-tracing scheme for sensing signal and radio propagation modelling. Therefore it is sensitive to the obstacles and makes the models of sensing coverage and link quality more practical compared with other heuristics that use ideal unit-disk models. The proposed algorithm aims at reaching an overall optimization on hardware cost, coverage, link quality and lifetime. Thus each of those metrics are modelled and normalized to compose a desirability function. Evolutionary algorithm is designed to efficiently tackle this NP-hard multi-objective optimization problem. The proposed algorithm is applicable for both indoor and outdoor 3D scenarios. Different parameters that affect the performance are analyzed through extensive experiments; two state-of-the-art algorithms are rebuilt and tested with the same configuration as that of the proposed algorithm. The results indicate that the proposed algorithm converges efficiently within 600 iterations and performs better than the compared heuristics

Wireless Sensor Network Application for Environmental Impact Analysis and Control

Traditional Wireless Sensor Networks (WSNs) applications take advantage of the new low cost low power consuming integrated sensors that appear with the evolution of Micro Electromechanical Systems (MEMS). This kind of sensors is suitable for WSNs, due to the reduced size, their interfaces and their low power consumption. However, during the last years, WSNs have found new niches of application where such sensors are not usable, due to the nature of the parameter to be measured. In these scenarios, new approaches must be taken in order to satisfy the requirements. But new problems appear, like cost and size increase. In this paper, an application where parameters like gas concentration, conductivity or pH have to be measured in a coffee factory is presented. The drawbacks of such a solution are highlighted, and the solution in the field of the wireless sensor networks adopted is detailed

A BDD proposal for Probabilistic Switching Activity Estimation

Switching activity computation is a essential stage for dynamic power estimation. Binary decision diagrams (BDD) are widely used in probabilistic activity estimation. However, the BDD size used for switching activity increases significantly in respect to the logic function BDDs. In this paper we propose a new BDD structure for activity computations in which important size reductions are achieved with no accuracy loss. The proposal includes the definition of a BDD activity operator. This operator has been implemented in a BDD package and then, in an automated tool. This implementation has permitted the analysis of several circuits and has corroborated the size reductions and the accuracy of the result

Testbed infrastructure for debugging, analyzing and optimizing WSN nodes based on a modular HW-SW architecture

The Internet of Things has emerged as one of the key aspects to the future of the Wireless Sensor Networ ks and their impact in new applications in real environments. This concept poses new challenges in the implementation, testing and assessment of efficient, robust and reliable technologies and prototypes under this paradigm. In this way, the run-time remote interaction with the deployment of hundreds of in-f ield nodes in which developers have to be able to control and manage the wireless network anywhere at any time also implies new objectives to be achieved in order to adapt or even create new HW-SW platforms. In this work, the design and implementation of a complete testbed infrastructure as a support tool for improving the effectiveness and the applicability of sensor nodes to real applications is presented, focused on the m odular architecture of the Cookie hardware platform and aiming to help developers to integrate and optimize the whole WSN system to the final applications in the real world

Method for run time hardware code profiling for algorithm acceleration

In this paper we propose a method for run time profiling of applications on instruction level by analysis of loops. Instead of looking for coarse grain blocks we concentrate on fine grain but still costly blocks in terms of execution times. Most code profiling is done in software by introducing code into the application under profile witch has time overhead, while in this work data for the position of a loop, loop body, size and number of executions is stored and analysed using a small non intrusive hardware block. The paper describes the system mapping to runtime reconfigurable systems. The fine grain code detector block synthesis results and its functionality verification are also presented in the paper. To demonstrate the concept MediaBench multimedia benchmark running on the chosen development platform is use

A reliable support tool for monitoring, testing and debugging wireless sensor cookie nodes

In this work a WSN Support Tool for developing, testing, monitoring and debugging new application prototypes in a reliable and robust way is proposed, by combining a Hardware -Software Integration Platform with the implementation of a parallel communication channel that helps users to interact to the experiments in runtime without interfering in the operation of the wireless network. As a pre-deployment tool, prototypes can be validated in a real environment before implementing them in the final application, aiming to increase the effectiveness and efficiency of the technology. This infrastructure is the support of CookieLab: a WSN testbed based on the Cookie Nodes Platform

Testbed architecture and framework for debugging wireless sensor networks

The Internet of Things has emerged as one of the key aspects for the future of the Wireless Sensor Networks and their impact on new applications in real environments. This concept poses new challenges in the implementation, testing and debugging of efficient, robust and reliable technologies under this paradigm, specially in a pre-deployment stage where HW-SW platform prototypes are to be optimized prior to their inclusion in actual deployments. In this work, the design and implementation of a complete testbed infrastructure as a support tool for improving the effectiveness and the applicability of sensor nodes to real systems is presented, focused on the modular architecture of the Cookie platform and aiming to help developers to integrate and improve the whole WSN operation to final real-world scenarios

Adaptive reconfigurable voting for enhanced reliability in medium-grained fault tolerant architectures

The impact of SRAM-based FPGAs is constantly growing in aerospace industry despite the fact that their volatile configuration memory is highly susceptible to radiation effects. Therefore, strong fault-handling mechanisms have to be developed in order to protect the design and make it capable of fighting against both soft and permanent errors. In this paper, a fully reconfigurable medium-grained triple modular redundancy (TMR) architecture which forms part of a runtime adaptive on-board processor (OBP) is presented. Fault mitigation is extended to the voting mechanism by applying our reconfiguration methodology not only to domain replicas but also to the voter itself. The proposed approach takes advantage of adaptive configuration placement and modular property of the OBP, thus allowing on-line creation of different medium-grained TMRs and selection of their granularity level. Consequently, we are able to narrow down the fault-affected area thus making the error recovery process faster and less power consuming. The conventional hardware based voting is supported by the ICAP-based one in order to additionally strengthen the reconfigurable intermediate voting. In addition, the implementation methodology ensures using only one memory footprint for all voters and their voting adaptations thus saving storing resources in expensive rad-hard memories

A Novel Method for Radio Propagation Simulation Based on Automatic 3D Environment Reconstruction

In this paper, a novel method to simulate radio propagation is presented. The method consists of two steps: automatic 3D scenario reconstruction and propagation modeling. For 3D reconstruction, a machine learning algorithm is adopted and improved to automatically recognize objects in pictures taken from target regions, and 3D models are generated based on the recognized objects. The propagation model employs a ray tracing algorithm to compute signal strength for each point on the constructed 3D map. Our proposition reduces, or even eliminates, infrastructure cost and human efforts during the construction of realistic 3D scenes used in radio propagation modeling. In addition, the results obtained from our propagation model proves to be both accurate and efficien

Ultra Low Power FPGA-Based Architecture for Wake-up Radio in Wireless Sensor Networks

In this paper the capabilities of ultra low power FPGAs to implement Wake-up Radios (WuR) for ultra low energy Wireless Sensor Networks (WSNs) are analyzed. The main goal is to evaluate the utilization of very low power configurable devices to take advantage of their speed, flexibility and low power consumption instead of the more common approaches based on ASICs or microcontrollers. In this context, energy efficiency is a key aspect, considering that usually the instant power consumption is considered a figure of merit, more than the total energy consumed by the application