40,800 research outputs found
Over-the-air software updates in the internet of things : an overview of key principles
Due to the fast pace at which IoT is evolving, there is an increasing need to support over-theair software updates for security updates, bug fixes, and software extensions. To this end, multiple over-the-air techniques have been proposed, each covering a specific aspect of the update process, such as (partial) code updates, data dissemination, and security. However, each technique introduces overhead, especially in terms of energy consumption, thereby impacting the operational lifetime of the battery constrained devices. Until now, a comprehensive overview describing the different update steps and quantifying the impact of each step is missing in the scientific literature, making it hard to assess the overall feasibility of an over-the-air update. To remedy this, our article analyzes which parts of an IoT operating system are most updated after device deployment, proposes a step-by-step approach to integrate software updates in IoT solutions, and quantifies the energy cost of each of the involved steps. The results show that besides the obvious dissemination cost, other phases such as security also introduce a significant overhead. For instance, a typical firmware update requires 135.026 mJ, of which the main portions are data dissemination (63.11 percent) and encryption (5.29 percent). However, when modular updates are used instead, the energy cost (e.g., for a MAC update) is reduced to 26.743 mJ (48.69 percent for data dissemination and 26.47 percent for encryption)
Architectures for Wireless Sensor Networks
Various architectures have been developed for wireless sensor networks. Many of them leave to the programmer important concepts as the way in which the inter-task communication and dynamic reconfigurations are addressed. In this paper we describe the characteristics of a new architecture we proposed - the data-centric architecture. This architecture offers an easy way of structuring the applications designed for wireless sensor nodes that confers them superior performances
GCP: Gossip-based Code Propagation for Large-scale Mobile Wireless Sensor Networks
Wireless sensor networks (WSN) have recently received an increasing interest.
They are now expected to be deployed for long periods of time, thus requiring
software updates. Updating the software code automatically on a huge number of
sensors is a tremendous task, as ''by hand'' updates can obviously not be
considered, especially when all participating sensors are embedded on mobile
entities. In this paper, we investigate an approach to automatically update
software in mobile sensor-based application when no localization mechanism is
available. We leverage the peer-to-peer cooperation paradigm to achieve a good
trade-off between reliability and scalability of code propagation. More
specifically, we present the design and evaluation of GCP ({\emph Gossip-based
Code Propagation}), a distributed software update algorithm for mobile wireless
sensor networks. GCP relies on two different mechanisms (piggy-backing and
forwarding control) to improve significantly the load balance without
sacrificing on the propagation speed. We compare GCP against traditional
dissemination approaches. Simulation results based on both synthetic and
realistic workloads show that GCP achieves a good convergence speed while
balancing the load evenly between sensors
Whisper: Fast Flooding for Low-Power Wireless Networks
This paper presents Whisper, a fast and reliable protocol to flood small
amounts of data into a multi-hop network. Whisper relies on three main
cornerstones. First, it embeds the message to be flooded into a signaling
packet that is composed of multiple packlets. A packlet is a portion of the
message payload that mimics the structure of an actual packet. A node must
intercept only one of the packlets to know that there is an ongoing
transmission. Second, Whisper exploits the structure of the signaling packet to
reduce idle listening and, thus, to reduce the radio-on time of the nodes.
Third, it relies on synchronous transmissions to quickly flood the signaling
packet through the network. Our evaluation on the Flocklab testbed shows that
Whisper achieves comparable reliability but significantly lower radio-on time
than Glossy -- a state-of-the-art flooding algorithm. Specifically, Whisper can
disseminate data in FlockLab twice as fast as Glossy with no loss in
reliability. Further, Whisper spends 30% less time in channel sampling compared
to Glossy when no data traffic must be disseminated
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A Low-Overhead Script Language for Tiny Networked Embedded Systems
With sensor networks starting to get mainstream acceptance, programmability is of increasing importance.
Customers and field engineers will need to reprogram existing deployments and software developers
will need to test and debug software in network testbeds. Script languages, which are a popular
mechanism for reprogramming in general-purpose computing, have not been considered for wireless sensor
networks because of the perceived overhead of interpreting a script language on tiny sensor nodes.
In this paper we show that a structured script language is both feasible and efficient for programming
tiny sensor nodes. We present a structured script language, SCript, and develop an interpreter for the
language. To reduce program distribution energy the SCript interpreter stores a tokenized representation
of the scripts which is distributed through the wireless network. The ROM and RAM footprint of the
interpreter is similar to that of existing virtual machines for sensor networks. We show that the interpretation
overhead of our language is on par with that of existing virtual machines. Thus script languages,
previously considered as too expensive for tiny sensor nodes, are a viable alternative to virtual machines
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