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196
Contiki - a Lightweight and Flexible Operating System for Tiny Networked Sensors
, 2004
"... of tiny networked devices that communicate untethered. For large scale networks it is important to be able to dynamically download code into the network. In this paper we present Contiki, a lightweight operating system with support for dynamic loading and replacement of individual programs and servi ..."
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Cited by 516 (45 self)
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of tiny networked devices that communicate untethered. For large scale networks it is important to be able to dynamically download code into the network. In this paper we present Contiki, a lightweight operating system with support for dynamic loading and replacement of individual programs and services. Contiki is built around an event-driven kernel but provides optional preemptive multithreading that can be applied to individual processes. We show that dynamic loading and unloading is feasible in a resource constrained environment, while keeping the base system lightweight and compact.
ASCENT: Adaptive self-configuring sensor networks topologies
, 2004
"... Advances in microsensor and radio technology will enable small but smart sensors to be deployed for a wide range of environmental monitoring applications. The low per-node cost will allow these wireless networks of sensors and actuators to be densely distributed. The nodes in these dense networks w ..."
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Cited by 449 (15 self)
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Advances in microsensor and radio technology will enable small but smart sensors to be deployed for a wide range of environmental monitoring applications. The low per-node cost will allow these wireless networks of sensors and actuators to be densely distributed. The nodes in these dense networks will coordinate to perform the distributed sensing and actuation tasks. Moreover, as described in this paper, the nodes can also coordinate to exploit the redundancy provided by high density so as to extend overall system lifetime. The large number of nodes deployed in these systems will preclude manual configuration, and the environmental dynamics will preclude design-time preconfiguration. Therefore, nodes will have to self-configure to establish a topology that provides communication under stringent energy constraints. ASCENT builds on the notion that, as density increases, only a subset of the nodes are necessary to establish a routing forwarding backbone. In ASCENT, each node assesses its connectivity and adapts its participation in the multihop network topology based on the measured operating region. This paper motivates and describes the ASCENT algorithm and presents analysis, simulation, and experimental measurements. We show that the system achieves linear increase in energy savings as a function of the density and the convergence time required in case of node failures while still providing adequate connectivity.
Simulating the power consumption of large-scale sensor network applications
- In Sensys
, 2004
"... Developing sensor network applications demands a new set of tools to aid programmers. A number of simulation environments have been developed that provide varying degrees of scalability, realism, and detail for understanding the behavior of sensor networks. To date, however, none of these tools have ..."
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Cited by 327 (4 self)
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Developing sensor network applications demands a new set of tools to aid programmers. A number of simulation environments have been developed that provide varying degrees of scalability, realism, and detail for understanding the behavior of sensor networks. To date, however, none of these tools have addressed one of the most important aspects of sensor application design: that of power consumption. While simple approximations of overall power usage can be derived from estimates of node duty cycle and communication rates, these techniques often fail to capture the detailed, low-level energy requirements of the CPU, radio, sensors, and other peripherals. In this paper, we present PowerTOSSIM, a scalable simulation environment for wireless sensor networks that provides an accurate, per-node estimate of power consumption. PowerTOSSIM is an extension to TOSSIM, an event-driven simulation environment for TinyOS applications. In PowerTOSSIM, TinyOS components corresponding to specific hardware peripherals (such as the radio, EEPROM, LEDs, and so forth) are instrumented to obtain a trace of each device’s activity during the simulation run. PowerTOSSIM employs a novel code-transformation technique to estimate the number of CPU cycles executed by each node, eliminating the need for expensive instruction-level simulation of sensor nodes. PowerTOSSIM includes a detailed model of hardware energy consumption based on the Mica2 sensor node platform. Through instrumentation of actual sensor nodes, we demonstrate that PowerTOSSIM provides accurate estimation of power consumption for a range of applications and scales to support very large simulations.
Avrora: Scalable Sensor Network Simulation With Precise Timing
- IN PROC. OF THE 4TH INTL. CONF. ON INFORMATION PROCESSING IN SENSOR NETWORKS (IPSN
, 2005
"... Simulation can be an important step in the development of software for wireless sensor networks and has been the subject of intense research in the past decade. While most previous efforts in simulating wireless sensor networks have focused on protocol-level issues utilizing models of the software i ..."
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Cited by 270 (5 self)
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Simulation can be an important step in the development of software for wireless sensor networks and has been the subject of intense research in the past decade. While most previous efforts in simulating wireless sensor networks have focused on protocol-level issues utilizing models of the software implementation, a significant challenge remains in precisely measuring time-dependent properties such as radio channel utilization. One promising approach, first demonstrated by ATEMU, is to simulate the behavior of sensor network programs at the machine code level with cycle-accuracy, but poor performance has so far limited its scalability. In this paper we present Avrora, a cycle-accurate instructionlevel sensor network simulator which scales to networks of up to 10,000 nodes and performs as much as 20 times faster than previous simulators with equivalent accuracy, handling as many as 25 nodes in real-time. We show how an event queue can enable efficient instruction-level simulation of microcontroller programs and allow the hidden parallelism in finegrained sensor network simulations to be extracted, once two core synchronization problems are identified and solved. Avrora's ability to measure detailed time-critical phenomena can shed new light on design issues for large-scale sensor networks.
Sympathy for the sensor network debugger
- In SenSys
, 2005
"... Being embedded in the physical world, sensor networks present a wide range of bugs and misbehavior qualitatively different from those in most distributed systems. Unfortunately, due to resource constraints, programmers must investigate these bugs with only limited visibility into the application. Th ..."
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Cited by 141 (3 self)
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Being embedded in the physical world, sensor networks present a wide range of bugs and misbehavior qualitatively different from those in most distributed systems. Unfortunately, due to resource constraints, programmers must investigate these bugs with only limited visibility into the application. This paper presents the design and evaluation of Sympathy, a tool for detecting and debugging failures in sensor networks. Sympathy has selected metrics that enable efficient failure detection, and includes an algorithm that root-causes failures and localizes their sources in order to reduce overall failure notifications and point the user to a small number of probable causes. We describe Sympathy and evaluate its performance through fault injection and by debugging an active application, ESS, in simulation and deployment. We show that for a broad class of data gathering applications, it is possible to detect and diagnose failures by collecting and analyzing a minimal set of metrics at a centralized sink. We have found that there is a tradeoff between notification latency and detection accuracy; that additional metrics traffic does not always improve notification latency; and that Sympathy’s process of failure localization reduces primary failure notifications by at least 50 % in most cases.
The platforms enabling wireless sensor networks.
- Communications of the ACM
, 2004
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Mantis os: An embedded multithreaded operating system for wireless micro sensor platforms
- ACM/Kluwer Mobile Networks & Applications (MONET), Special Issue on Wireless Sensor Networks
, 2005
"... The MANTIS MultimodAl system for NeTworks of In-situ wireless Sensors provides a new multithreaded cross-platform embedded operating system for wireless sensor networks. As sensor networks accommodate increasingly complex tasks such as compression, aggregation and signal processing, preemptive multi ..."
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Cited by 104 (5 self)
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The MANTIS MultimodAl system for NeTworks of In-situ wireless Sensors provides a new multithreaded cross-platform embedded operating system for wireless sensor networks. As sensor networks accommodate increasingly complex tasks such as compression, aggregation and signal processing, preemptive multithreading in the MANTIS sensor OS (MOS) enables micro sensor nodes to natively interleave complex tasks with time-sensitive tasks, thereby mitigating the bounded buffer producer-consumer problem. To achieve memory efficiency, MOS is implemented in a lightweight RAM footprint that fits in less than 500 bytes of memory, including kernel, scheduler, and network stack. To achieve energy efficiency, the MOS power-efficient scheduler sleeps the microcontroller after all active threads have called the MOS sleep() function, reducing current consumption to the µA range. A key MOS design feature is flexibility in the form of cross-platform support and testing across PCs, PDAs, and different micro sensor platforms. Another key MOS design feature is support for remote management of in-situ sensors via dynamic reprogramming and remote login.
Temporal Properties of Low Power Wireless Links: Modeling and Implications on Multi-Hop Routing
"... Recently, several studies have analyzed the statistical properties of low power wireless links in real environments, clearly demonstrating the differences between experimentally observed communication properties and widely used simulation models. However, most of these studies have not performed in ..."
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Cited by 102 (4 self)
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Recently, several studies have analyzed the statistical properties of low power wireless links in real environments, clearly demonstrating the differences between experimentally observed communication properties and widely used simulation models. However, most of these studies have not performed in depth analysis of the temporal properties of wireless links. These properties have high impact on the performance of routing algorithms. Our first goal is to study the statistical temporal properties of links in low power wireless communications. We study short term temporal issues, like lagged autocorrelation of individual links, lagged correlation of reverse links, and consecutive same path links. We also study long term temporal aspects, gaining insight on the length of time the channel needs to be measured and how often we should update our models. Our second objective is to explore how statistical temporal properties impact routing protocols. We studied one-to-one routing schemes and developed new routing algorithms that consider autocorrelation, and reverse link and consecutive same path link lagged correlations. We have developed two new routing algorithms for the cost link model: (i) a generalized Dijkstra algorithm with centralized execution, and (ii)a localized distributed probabilistic algorithm.
Statistical model of lossy links in wireless sensor networks
- In IPSN
, 2005
"... Abstract—Recently, several landmark wireless sensor network deployment studies clearly demonstrated a large discrepancy between experimentally observed communication properties and properties produced by widely used simulation models. Our first goal is to provide sound foundations for conclusions dr ..."
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Cited by 98 (8 self)
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Abstract—Recently, several landmark wireless sensor network deployment studies clearly demonstrated a large discrepancy between experimentally observed communication properties and properties produced by widely used simulation models. Our first goal is to provide sound foundations for conclusions drawn from these studies by extracting the relationship between pairs of location (e.g distance) and communication properties (e.g. reception rate) using non-parametric statistical techniques and by calculating intervals of confidence for all claims. The objective is to determine not only the most likely value of one feature for an alternate given feature value, but also to establish a complete characterization of the relationship by providing a probability density function (PDF). The PDF provides the likelihood that any particular value of one feature is associated with a given value of another feature. Furthermore, we study not only individual link properties, but also their correlation with respect to common transmitters and receivers and their geometrical location. The second objective is to develop a series of wireless network simulation environments that produce networks of an arbitrary size and under arbitrary deployment rules with realistic communication properties. For this task we use an iterative improvement-based optimization procedure to generate instances of the network that are statistically similar to empirically observed networks. We evaluate the accuracy of the conclusions drawn using the proposed model and therefore comprehensiveness of the considered properties on a set of standard communication tasks, such as connectivity maintenance and routing. Index terms: sensor networks, wireless channel modeling, simulations, network measurements, experimentation with real networks/testbeds, statistics. I.
A system for simulation, emulation, and deployment of heterogeneous sensor networks
- In Proceedings of the Second ACM Conference on Embedded Networked Sensor Systems
, 2004
"... Recently deployed Wireless Sensor Network systems (WSNs) are increasingly following heterogeneous designs, incorporating a mixture of elements with widely varying capabilities. The development and deployment of WSNs rides heavily on the availability of simulation, emulation, visualization and analys ..."
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Cited by 91 (2 self)
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Recently deployed Wireless Sensor Network systems (WSNs) are increasingly following heterogeneous designs, incorporating a mixture of elements with widely varying capabilities. The development and deployment of WSNs rides heavily on the availability of simulation, emulation, visualization and analysis support. In this work, we develop tools specifically to support heterogeneous systems, as well as to support the measurement and visualization of operational systems that is critical to addressing the inevitable problems that crop up in deployment. Our system differs from related systems in three key ways: in its ability to simulate and emulate heterogeneous systems in their entirety, in its extensive support for integration and interoperability between Motes and Microservers, and in its unified
