Many WSN deployments require the devices to run for long periods (months) using a combination of duty cycling and renewable energy sources (e.g., solar panels). This technical report is the first comprehensive study of end-to-end data collection from a solar-powered Sun SPOT over a period of multiple weeks.

We ran our experiment for nearly a month and collected sensor data into a mySQL database for later analysis and visualization. This experiment helped us uncover and fix several issues that caused disruptions in data collection — the occasional inability of the device to enter deep sleep, the resulting clock reset due to premature battery exhaustion, and loss of connectivity to the database after long periods of inactivity. The report offers important lessons in the design of a sensor data collection framework and lists both recommended best practices as well as potential pitfalls to avoid.

The report by Vipul Gupta is available here and some comments are on his blog here.

In this paper Bhaskaran Raman and Kameswari Chebrolu from Indian Institute of Technology, Bombay, present a critique of the field of WSN. They say that literature in this domain falls into two main, distinct categories: (1) algorithms or protocols, and (2) application-centric system design. A striking observation is that references across these two categories are minimal, and superficial at best. They argue that this is not accidental, and is the result of three main flaws in the former category of work. Going forward, an application-driven, bottom-up approach is required for meaningful articulation and subsequent solution of any networking issues in WSNs.

The paper is available here. Enjoy the reading!

Today’s typical sensor nodes run on batteries, thus have a limited lifetime. Solar energy harvesting is an interesting complement or alternative. There are several systems built with unique set of requirements. However, not much has been done to formalize application driven constrains, model and systematize micro-solar design of energy subsystems.

We just stumbled over some neat research from Jaein Jeong et al, from UC Berkeley, that shed some light on this topic.

The authors develop a taxonomy of the micro-solar design space identifying key components, design choices, interactions, challenges, and trade-offs. Based on the analysis of two different systems (Heliomote and Trio) they propose design guidelines for future micro-solar powered systems (see paper, talk).

Furthermore, they present a systematic approach that composes models of the relevant pieces to appropriately select and size the components. The approach is demonstrated through the design of the HydroWatch weather node, micro-solar subsystem and network, in the context of a microclimate monitoring project in a deep forest setting (paper, talk).

Interestingly, they have found the speckled nature of the illumination in the forest environment dramatically affects the solar current in the panel which wouldn’t be improved by its larger size, but instead, by the arrangement of more and smaller cells connected in parallel. Also, the useful range of voltages from these panels is very limited and therefore proper coupling  of the electronics to profit on these constrains is as relevant as other optimizations.

Enjoy your readings.

As new fabrication and integration technologies reduce the cost and size of wireless sensors, the observation and control of our physical world will expand dramatically using the temporally and spatially dense monitoring afforded by wireless sensor networks technology. Several applications such as habitat monitoring, counter-sniper system, environment sampling, and structure monitoring, have been launched, showing the promising future of wide range of applications of networked sensor systems.

Their success is nonetheless determined by whether the sensor networks can provide a high quality stream of data over a long period. The inherent feature of unattended and untethered deployment of networked sensors in a malicious environment, however, imposes challenges to the underlying systems. These challenges are further complicated by the fact that sensor systems are usually seriously energy-constrained. Most previous efforts focus on devising techniques to save the sensor node energy and thus extend the lifetime of the whole sensor network. However, with more deployments of real sensor systems, in which the main function is to collect interesting data and to share with peers, data quality has been becoming a more important issue in the design of sensor systems. Consistency, accuracy, reliability, and survivability concerns have to be addressed in sensor data collection, storage, and processing.

The goal of the special issue is to publish the most recent results in the data quality management aspects of wireless sensor networks research. Researchers and practitioners working in this area are expected to take this opportunity to discuss and express their views on the current trends, challenges, and state of the art solutions addressing various issues in sensor networks.

The full call for papers is here.

From 7.5th floor:

Data management in the worldwide sensor web draws the big picture in mentioning that now too much attention has been placed on the networking issues of distributed sensing and too little on tools to manage, analyze and understand the data. The authors ask the question weather we can design sensor networks with data quality in mind? They ask a very crucial question, but as often in location-aware computing, it is very unclear on who can claim what quality in location information is or in other words who can answer “how good is good enough?”. Of course it is important to manage temporal and spatial data and handle their inherent uncertainty (e.g. via probabilistic theory) or mask it (e.g. via interpolation) or play with it (seamful design). It seems clear now that my thesis is about acknowledging that situation (uncertainty in the location information, fluctuant quality in the data), but instead of aiming to produce “perfect data”, I plan to provide an understanding and solutions from a human and urban perspective. It comes, at the first place, with the observation of people experiencing location-aware systems in CatchBob!, and making use of location information, in my taxi driver (co-evolution, context and granularity). This observations help me accumulating evidences on the contextual factors influencing the granularity (≈human expectation of quality) of the location information used.

Balazinska, M., Deshpande, A., Franklin, M. J., Gibbons, P. B., Gray, J., Hansen, M., Liebhold, M., Nath, S., Szalay, A., and Tao, V. (2007). Data management in the worldwide sensor web. IEEE Pervasive Computing, 6(2):30–40.

A common scenario for WSN often feature masters or base stations in charge of coordinating the application functionality. Although this centralized approach is appropriate for some applications, there are other situations in which distributed control and processing is necessary to implement more complex control loops. The generalized Wireless Sensor and Actuator Network (WSAN) is the scope researchers are now exploring to come up with more decentralized architectures that encompass multiple sinks and heterogeneous nodes. In such settings, new programming abstractions are required to manage complexity and heterogeneity without sacrificing efficiency.

Logical Neighborhoods (LN) is a novel programming abstraction for WSNs. A logical neighborhood includes nodes whose dependable roles in the network are specified declaratively, along with requirements about the cost of the communication involved, and regardless of the physical neighbors related to the node’s radio range. This enable the programmer to slice the network according to the application needs, effectively replacing the physical neighborhood with a higher-level, application-defined notion of proximity.

Late last year, at the flagship conference on wireless sensor networks: ACM SenSys 07 held in Sydney, Australia, Luca Mottola and G.P. Picco received the Best Demo Award for the demo “Programming WSN with Logical Neighborhoods: A Road Tunnel Use Case”.
The original LN papers can be found here and here.

Further info is available on the dedicated Web site.

This is the tittle of an interesting paper on WSN to be presented in HotNets-VI, a 2 days ACM supported workshop to be held this week in Atlanta, Georgia, USA.

Please be aware this is strictly related to WSN. As far as we know, no research has yet supported extending the concept to humans!

The paper can be downloaded here

All you need is a couple of Tmote Sky boards, cygwin and Java you can start doing software-based energy profiling in Contiki. If you are at SenSys’07 in Sydney – watch out for the demo of `software based energy estimation’ by SICS Sweden on 7th Nov, otherwise get more information here.

Accenture Technology Labs is taking interest in sensornets. The emerging trend of Sensor Telemetry combines data—historical and current—with two-way wireless communications to offer unprecedented visibility into and management of equipment, products and interactions. It promises organizations more detailed, real-time views, not just of individual business transactions, but of physical state and operations, and human conditions. Sensor Telemetry will also enable organizations to respond faster and even predict incidents before they occur.

(more…)

Considering a wireless sensor network whose nodes are distributed randomly over a given area, a probability model for the network lifetime is provided. Using this model and assuming that packet generation follows a Poisson distribution, an analytical expression for the complementary cumulative density function (CCDF) of the lifetime is obtained. Using this CCDF, one can accurately find the probability that the network achieves a given lifetime. It is also shown that when the number of sensors, N, is large, with an error exponentially decaying with N, one can predict whether or not a certain lifetime can be achieved. The results of this work are obtained for both multi-hop and single-hop wireless sensor networks and are verified with computer simulation. The approaches of this paper are shown to be applicable to other packet generation models and the effect of the area shape is also investigated.

By M. Noori et al.

More info here.