Energy-efficient task allocation for distributed applications in Wireless Sensor Networks

We consider the scenario of a sensing, computing and communicating infrastructure with a a programmable middleware that allows for quickly deploying different applications running on top of it so as to follow the changing ambient needs. We then face the problem of setting up the desired application in case of hundreds of nodes, which consists in identifying which actions should be performed by each of the nodes so as to satisfy the ambient needs while minimizing the application impact on the infrastructure battery lifetime. We approach the problem by considering every possible decomposition of the application's sensing and computing operations into tasks to be assigned to the each infrastructure component. The contribution of energy consumption due to the performance of each task is then considered to compute a cost function, allowing us to evaluate the viability of each deployment solution. Simulation results show that our framework results in considerable energy conservation with respect to sink-oriented or cluster-oriented deployment approaches, particularly for networks with high node densities, non-uniform energy consumption and initial energy, and complex actions

Implementation of Low Power and Area Efficient 2-Bit/Step Asynchronous SAR ADC using Successively Activated Comparators

A low power (0.4-09V) 2-Bit/Step successive approximation register (SAR) analog to digital converter (ADC) is conferred. A 2-Bit/Step operation technique is proposed which implementing a dynamic threshold configuring comparator instead of number of digital to analog converters (DACs). Area and power is reduced by successively activated comparators. Here the second comparator is activated reflecting the preceding comparator’s results. Because the second comparator threshold is configured dynamically for every cycle, only two comparators are required instead of three. By successively activating the comparators, the number of DAC settling is halved, so the power and area overhead is very small and the performance will be increased. The proposed ADC was implemented in a 90nm technology achieved a gain of 35.4 db, power of 0.89 ?w and the conversion time of 0.32ns with a supply voltage of 0.4v. The total core area of this ADC is 7.74 ?m2

Ad-hoc wireless sensor networks for exploration of solar-system bodies

In this work, we evaluate the exploration of the solar system by ad-hoc wireless sensor networks (WSN), i.e. networks where all nodes (either moving or stationary) can both provide and relay data. The two aspects of self-organization and localization are the major challenges to overcome to achieve a reliable network for a variety of missions. We point out the diversity of environmental and operational constrains that would have to face WSN used for space exploration. The first group of scenarios we evaluated concerns nodes moving relative to each other either above or on the surface of a solar system object. These scenarios enable collecting data simultaneously over a large surface. The second group of scenarios we considered concerns the use of nodes fixed in or on the ground of an asteroid or planet. We considered both physical and chemical sensing of the atmosphere, surface ground and soil as candidates for such networks. Emerging highly integrated technologies are investigated in order to make a distinction between the elements that can be common for a variety of missions and the others that are specific to an exploration scenario. Finally, we compare the specific requirements of WSN for space exploration with those of WSN designed for terrestrial applications

Deployment of Distributed Applications in Wireless Sensor Networks

The increase in computation and sensing capabilities as well as in battery duration of commercially available Wireless Sensors Network (WSN) nodes are making the paradigm of an horizontal ambient intelligence infrastructure feasible. Accordingly, the sensing, computing and communicating infrastructure is set with a programmable middleware that allows for quickly deploying different applications running on top of it so as to follow the changing ambient needs. In this scenario, we face the problem of setting up the desired application in complex scenarios with hundreds of nodes, which consists of identifying which actions should be performed by each of the nodes so as to satisfy the ambient needs while minimizing the application impact on the infrastructure battery lifetime. Accordingly, we approach the problem by considering every possible decomposition of the application’s sensing and computing operations into tasks to be assigned to each infrastructure component. The contribution of energy consumption due to the performance of each task is then considered to compute a cost function, allowing us to evaluate the viability of each deployment solution. Simulation results show that our framework results in considerable energy conservation with respect to sink-oriented or cluster-oriented deployment approaches, particularly for networks with high node densities, non-uniform energy consumption and initial energy, and complex actions