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TOSSIM: Accurate and Scalable Simulation of Entire TinyOS Applications
, 2003
"... Accurate and scalable simulation has historically been a key enabling factor for systems research. We present TOSSIM, a simulator for TinyOS wireless sensor networks. By exploiting the sensor network domain and TinyOS’s design, TOSSIM can capture network behavior at a high fidelity while scaling to ..."
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Cited by 784 (19 self)
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Accurate and scalable simulation has historically been a key enabling factor for systems research. We present TOSSIM, a simulator for TinyOS wireless sensor networks. By exploiting the sensor network domain and TinyOS’s design, TOSSIM can capture network behavior at a high fidelity while scaling to thousands of nodes. By using a probabilistic bit error model for the network, TOSSIM remains simple and efficient, but expressive enough to capture a wide range of network interactions. Using TOSSIM, we have discovered several bugs in TinyOS, ranging from network bitlevel MAC interactions to queue overflows in an ad-hoc routing protocol. Through these and other evaluations, we show that detailed, scalable sensor network simulation is possible.
Tinydb: An acquisitional query processing system for sensor networks
- ACM Trans. Database Syst
, 2005
"... We discuss the design of an acquisitional query processor for data collection in sensor networks. Acquisitional issues are those that pertain to where, when, and how often data is physically acquired (sampled) and delivered to query processing operators. By focusing on the locations and costs of acq ..."
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Cited by 626 (8 self)
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We discuss the design of an acquisitional query processor for data collection in sensor networks. Acquisitional issues are those that pertain to where, when, and how often data is physically acquired (sampled) and delivered to query processing operators. By focusing on the locations and costs of acquiring data, we are able to significantly reduce power consumption over traditional passive systems that assume the a priori existence of data. We discuss simple extensions to SQL for controlling data acquisition, and show how acquisitional issues influence query optimization, dissemination, and execution. We evaluate these issues in the context of TinyDB, a distributed query processor for smart sensor devices, and show how acquisitional techniques can provide significant reductions in power consumption on our sensor devices. Categories and Subject Descriptors: H.2.3 [Database Management]: Languages—Query languages; H.2.4 [Database Management]: Systems—Distributed databases; query processing
Establishing Pairwise Keys in Distributed Sensor Networks
, 2003
"... Pairwise key establishment is a fundamental security service in sensor networks; it enables sensor nodes to communicate securely with each other using cryptographic techniques. However, due to the resource constraints on sensors, it is infeasible to use traditional key management techniques such as ..."
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Cited by 543 (29 self)
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Pairwise key establishment is a fundamental security service in sensor networks; it enables sensor nodes to communicate securely with each other using cryptographic techniques. However, due to the resource constraints on sensors, it is infeasible to use traditional key management techniques such as public key cryptography and key distribution center (KDC). To facilitate the study of novel pairwise key predistribution techniques, this paper presents a general framework for establishing pairwise keys between sensors on the basis of a polynomial-based key predistribution protocol [2]. This paper then presents two efficient instantiations of the general framework: a random subset assignment key predistribution scheme and a grid-based key predistribution scheme. The analysis in this paper indicates that these two schemes have a number of nice properties, including high probability (or guarantee) to establish pairwise keys, tolerance of node captures, and low communication overhead. Finally, this paper presents a technique to reduce the computation at sensors required by these schemes.
Tinysec: A link layer security architecture for wireless sensor networks
- in Proc of the 2nd Int’l Conf on Embedded Networked Sensor Systems
"... We introduce TinySec, the first fully-implemented link layer security architecture for wireless sensor networks. In our design, we leverage recent lessons learned from design vulnerabilities in security protocols for other wireless networks such as 802.11b and GSM. Conventional security protocols te ..."
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Cited by 521 (0 self)
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We introduce TinySec, the first fully-implemented link layer security architecture for wireless sensor networks. In our design, we leverage recent lessons learned from design vulnerabilities in security protocols for other wireless networks such as 802.11b and GSM. Conventional security protocols tend to be conservative in their security guarantees, typically adding 16–32 bytes of overhead. With small memories, weak processors, limited energy, and 30 byte packets, sensor networks cannot afford this luxury. TinySec addresses these extreme resource constraints with careful design; we explore the tradeoffs among different cryptographic primitives and use the inherent sensor network limitations to our advantage when choosing parameters to find a sweet spot for security, packet overhead, and resource requirements. TinySec is portable to a variety of hardware and radio platforms. Our experimental results on a 36 node distributed sensor network application clearly demonstrate that software based link layer protocols are feasible and efficient, adding less than 10 % energy, latency, and bandwidth overhead.
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.
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.
A line in the sand: a wireless sensor network for target detection, classification, and tracking
- COMPUTER NETWORKS
, 2004
"... Intrusion detection is a surveillance problem of practical import that is well suited to wireless sensor networks. In this paper, we study the application of sensor networks to the intrusion detection problem and the related problems of classifying and tracking targets. Our approach is based on a de ..."
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Cited by 272 (41 self)
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Intrusion detection is a surveillance problem of practical import that is well suited to wireless sensor networks. In this paper, we study the application of sensor networks to the intrusion detection problem and the related problems of classifying and tracking targets. Our approach is based on a dense, distributed, wireless network of multi-modal resource-poor sensors combined into loosely coherent sensor arrays that perform in situ detection, estimation, compression, and exfiltration. We ground our study in the context of a security scenario called ‘‘A Line in the Sand’ ’ and accordingly define the target, system, environment, and fault models. Based on the performance requirements of the scenario and the sensing, communication, energy, and computation ability of the sensor network, we explore the design space of sensors, signal processing algorithms, communications, networking, and middleware services. We introduce the influence field, which can be estimated from a network of binary sensors, as the basis for a novel classifier. A contribution of our work is that we do not assume a reliable network; on the contrary, we quantitatively analyze the effects of network unreliability on application performance. Our work includes multiple experimental deployments of over 90
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.
Hood: a neighborhood abstraction for sensor networks
- in Proceedings of the 2nd international conference on Mobile
"... This paper proposes a neighborhood programming abstrac-tion for sensor networks, wherein a node can identify a sub-set of nodes around it by a variety of criteria and share state with those nodes. This abstraction allows developers to design distributed algorithms in terms of the neighbor-hood abstr ..."
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Cited by 224 (11 self)
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This paper proposes a neighborhood programming abstrac-tion for sensor networks, wherein a node can identify a sub-set of nodes around it by a variety of criteria and share state with those nodes. This abstraction allows developers to design distributed algorithms in terms of the neighbor-hood abstraction itself, instead of decomposing them into component parts such as messaging protocols, data caches, and neighbor lists. In those applications that are already neighborhood-based, this abstraction is shown to facilitate good application design and to reduce algorithmic complex-ity, inter-component coupling, and total lines of code. The abstraction as defined here has been successfully used to im-plement several complex applications and is shown to cap-ture the essence of many more existing distributed sensor network algorithms.
