1,721,200 research outputs found
Programming Storage-centric Sensor Networks with Squirrel
No full textWe present SQUIRREL, a stream-oriented programming framework for storage-centric sensor networks. The storage- centric paradigm—where storage operations prevail over communication activity—applies to scenarios such as batch data collection, delay-tolerant mobile applications, and disconnected operations in static networks. SQUIRREL simplifies developing such applications by decoupling data processing from storage, and by transparently handling the latter. We achieve this through: i) a modular programming abstraction, and ii) a lightweight run-time layer that efficiently allocates data to different storage areas, based on size vs. energy trade- offs. We demonstrate SQUIRREL’s effectiveness based on three real-world applications, each representing a different storage-centric scenario. The results show that—while relieving programmers from a significant burden—SQUIRREL achieves efficient utilization of storage areas, enabling energy savings independently of the storage technology
The FlyZone Testbed Architecture for Aerial Drone Applications
Full text linkAerial drones represent a new breed of mobile computing. Compared to mobile phones and connected cars that only opportunistically sense or communicate, aerial drones offer direct control over their movements. They can thus implement functionality that were previously beyond reach, such as collecting high-resolution imagery, exploring near-inaccessible areas, or inspecting remote areas to gather fine-grain environmental data.This research was partially supported by the EU commission with H2020 project 5G-DIVE (grant agreement 85988), by the Italian Ministry of Education, University, and Research through the cluster project “ICT Solutions to Support Logistics and Transport Processes (ITS)”, and by the Swedish Innovation Agency through project “DePILOT”, “DePILOT Reloaded”, and “DepDrone”
Fundamental concepts of reactive control for autonomous drones
Full text linkAutonomous drones represent a new breed of mobile computing system. Compared to smartphones and connected cars that only opportunistically sense or communicate, drones allow motion control to become part of the application logic. The efficiency of their movements is largely dictated by the low-level control enabling their autonomous operation based on high-level inputs. Existing implementations of such low-level control operate in a timetriggered fashion. In contrast, we conceive a notion of reactive control that allows drones to execute the low-level control logic only upon recognizing the need to, based on the influence of the environment onto the drone operation. As a result, reactive control can dynamically adapt the control rate. This brings fundamental benefits, including more accurate motion control, extended lifetime, and better quality of service in end-user applications. Based on 260+ hours of real-world experiments using three aerial drones, three different control logic, and three hardware platforms, we demonstrate, for example, up to 41% improvements in motion accuracy and up to 22% improvements in flight time
Efficient State Retention for Transiently-powered Embedded Sensing
Full text linkWe present state retention techniques to support embedded sensing applications on 32-bit microcontrollers whose energy provisioning is assisted through ambient harvesting or wireless energy transfer. As energy availability is likely erratic in these settings, applications may be unpredictably interrupted. To behave dependably, applications should resume from where they left as soon as energy is newly available. We investigate the fundamental building block necessary to this end, and conceive three mechanisms to checkpoint and restore a device's state on stable storage quickly and in an energy-efficient manner. The problem is unique in many regards; for example, because of the distinctive performance vs. energy trade-offs of modern 32-bit microcontrollers and the peculiar characteristics of current flash chips. Our results, obtained from real experiments using two different platforms, crucially indicate that there is no ``one-size-fits-all'' solution. The performance depends on factors such as the amount of data to handle, how in memory the data is laid out, as well as an application's read/write patterns
Enabling Location-aware Operation in Decentralized IoT Communications
Full text linkWe present an efficient design to enable location-aware operation
in decentralized IoT communications. Large-scale IoT systems rep-
resent the backbone of a smart city functioning, allowing pervasive
environmental sensing across devices and networks. However, ex-
isting IoT communication systems are largely driven by data types
and miss out on embracing data location, which is fundamental in
environment sensing. To address this issue, we demonstrate it is
possible to efficiently embed a notion of location within the Zenoh
protocol. We make it possible to steer message routing based on
both data type and location, yet without altering the existing rout-
ing core and message forwarding, unlike most existing solutions.
We also present three encoding techniques for location data, each of
them representing a different trade-off between expressiveness and
performance overhead. Our evaluation uses a virtualized environ-
ment and real-world packet traces of heterogeneous networks. We
show, for example, that our design decreases the average message
latency by more than 50% when routing data also based on location,
while increasing throughput, compared to two different baselines
Programming Wireless Sensor Networks with Logical Neighborhoods: A Road Tunnel Use Case
Full text linkWireless sensor networks (WSNs) involving actuation are increasingly envisioned in a range of fields [1]. Among these, there is considerable interest in leveraging off WSNs to improve safety in road tunnels [4]. Researchers are envi- sioning tunnels equipped with WSN nodes that gather physi- cal readings such as temperature and light, monitor the struc- tural integrity of the tunnel, and sense the presence of vehi- cles to detect a possible traffic congestion. Based on sensed data, the system operates a variety of devices, such as ven- tilation fans inside the tunnel, and traffic lights at the en- trances. For instance, when a sensor detects the presence of a fire in a sector, the fans in the same sector are activated, and the traffic lights are turned red to prevent further vehicles from entering the tunnel
Neighborhood view consistency in wireless sensor networks
Full text linkWireless sensor networks (WSNs) are characterized by localized interactions, that is, protocols are often based on message exchanges within a node’s direct radio range. We recognize that for these protocols to work effectively, nodes must have consistent information about their shared neighborhoods. Different types of faults, however, can affect this information, severely impacting a protocol’s performance. We factor this problem out of existing WSN protocols and argue that a notion of neighborhood view consistency (NVC) can be embedded within existing designs to improve their performance. To this end, we study the problem from both a theoretical and a system perspective. We prove that the problem cannot be solved in an asynchronous system using any of Chandra and Toueg’s failure detectors. Because of this, we introduce a new software device called pseudocrash failure detector (PCD), study its properties, and identify necessary and sufficient conditions for solving NVC with PCDs. We prove that, in the presence of transient faults, NVC is impossible to solve with any PCDs, and thus define two weaker specifications of the problem. We develop a global algorithm that satisfies both specifications in the presence of unidirectional links, and a localized algorithm that solves the weakest specification in networks of bidirectional links. We implement the latter atop two different WSN operating systems, integrate our implementations with four different WSN protocols, and run extensive micro-benchmarks and full-stack experiments on a real 90-node WSN testbed. Our results show that the performance significantly improves for NVC-equipped protocols; for example, the Collection Tree Protocol (CTP) halves energy consumption with higher data delivery
Virtual Resources for the Internet of Things
Full text linkWe present Virtual Resources: a software architecture to resolve the tension between effective development and efficient operation of Internet of Things (IoT) applications. Emerging IoT architectures exhibit recurring traits: resource-limited sensors and actuators with RESTful interfaces at one end; full-fledged Cloud-hosted applications at the opposite end. The application logic resides entirely at the latter, creating performance issues such as excessive energy consumption and high latencies. To ameliorate these, Virtual Resources allows developers to push a slice of the application logic to intermediate IoT devices, creating a continuum between physical resources and Cloud-hosted applications. With Virtual Resources, for example, developers can push processing of sensed data to IoT devices close to the physical sensors, reducing the data to transmit and thus saving energy. We describe the key concepts of Virtual Resources and their realization in a CoAP prototype atop resource-constrained devices. Experimental results from cycle-accurate emulation indicate that Virtual Resources enable better performance than Cloud-centric architectures, while retaining the RESTful interaction pattern. For example, energy consumption in representative scenarios improves up to 40% and control loop latencies reduce up to 60%
Building Software for the Internet of Things
No full textThe guest editors present a special issue on building software for the Internet of Things (IoT).</p
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