Showing papers on "Sensor node published in 2004"

Medium access control with coordinated adaptive sleeping for wireless sensor networks

Abstract: This paper proposes S-MAC, a medium access control (MAC) protocol designed for wireless sensor networks. Wireless sensor networks use battery-operated computing and sensing devices. A network of these devices will collaborate for a common application such as environmental monitoring. We expect sensor networks to be deployed in an ad hoc fashion, with nodes remaining largely inactive for long time, but becoming suddenly active when something is detected. These characteristics of sensor networks and applications motivate a MAC that is different from traditional wireless MACs such as IEEE 802.11 in several ways: energy conservation and self-configuration are primary goals, while per-node fairness and latency are less important. S-MAC uses a few novel techniques to reduce energy consumption and support self-configuration. It enables low-duty-cycle operation in a multihop network. Nodes form virtual clusters based on common sleep schedules to reduce control overhead and enable traffic-adaptive wake-up. S-MAC uses in-channel signaling to avoid overhearing unnecessary traffic. Finally, S-MAC applies message passing to reduce contention latency for applications that require in-network data processing. The paper presents measurement results of S-MAC performance on a sample sensor node, the UC Berkeley Mote, and reveals fundamental tradeoffs on energy, latency and throughput. Results show that S-MAC obtains significant energy savings compared with an 802.11-like MAC without sleeping.

Wireless Sensor Networks

Abstract: Sensor networks consist of a set of sensor nodes, each equipped with one or more sensors, communication subsystems, storage and processing resources, and in some cases actuators. The sensors in a node observe phenomena such as thermal, optic, acoustic, seismic, and acceleration events, while the processing and other components analyze the raw data and formulate answers to specific user requests. Recent advances in technology have paved the way for the design and implementation of new generations of sensor network nodes, packaged in very small and inexpensive form factors with sophisticated computation and wireless communication abilities. Although still at infancy, these new classes of sensor networks, generally referred to as wireless sensor networks (WSN), show great promise and potential with applications ranging in areas that have already been addressed, to domains never before imagined. In this article we provide an overview of this new and exciting field and a brief discussion on the factors pushing the recent flurry of sensor network related research and commercial undertakings. We also provide overview discussions on architectural design characteristics of such networks including physical components, software layers, and higher level services. At each step, we highlight special characteristics of WSNs and discuss why existing approaches and results from wireless communication networks are not necessarily suitable in WSN domains. We conclude by briefly summarizing the state of the art and the future research directions.

Simulating the power consumption of large-scale sensor network applications

Abstract: 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, 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 runPowerTOSSIM 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.

An analysis of a large scale habitat monitoring application

Abstract: Habitat and environmental monitoring is a driving application for wireless sensor networks. We present an analysis of data from a second generation sensor networks deployed during the summer and autumn of 2003. During a 4 month deployment, these networks, consisting of 150 devices, produced unique datasets for both systems and biological analysis. This paper focuses on nodal and network performance, with an emphasis on lifetime, reliability, and the the static and dynamic aspects of single and multi-hop networks. We compare the results collected to expectations set during the design phase: we were able to accurately predict lifetime of the single-hop network, but we underestimated the impact of multi-hop traffic overhearing and the nuances of power source selection. While initial packet loss data was commensurate with lab experiments, over the duration of the deployment, reliability of the backend infrastructure and the transit network had a dominant impact on overall network performance. Finally, we evaluate the physical design of the sensor node based on deployment experience and a post mortem analysis. The results shed light on a number of design issues from network deployment, through selection of power sources to optimizations of routing decisions.

Localization of wireless sensor networks with a mobile beacon

Abstract: Wireless sensor networks have the potential to become the pervasive sensing (and actuating) technology of the future For many applications, a large number of inexpensive sensors is preferable to a few expensive ones The large number of sensors in a sensor network and most application scenarios preclude hand placement of the sensors Determining the physical location of the sensors after they have been deployed is known as the problem of localization We present a localization technique based on a single mobile beacon aware of its position (eg by being equipped with a GPS receiver) Sensor nodes receiving beacon packets infer proximity constraints to the mobile beacon and use them to construct and maintain position estimates The proposed scheme is radio-frequency based, and thus no extra hardware is necessary The accuracy (on the order of a few meters in most cases) is sufficient for most applications An implementation is used to evaluate the performance of the proposed approach

Radio frequency identification (RFID) based sensor networks

Abstract: An RF addressable sensor network architecture is provided. The RF addressable sensor network includes one or more RF addressable sensors, one or more wireless sensor readers coupled to a communications network, and one or more end user devices coupled to the communications network. The RF addressable sensor network may also include a sensor network processor. An RF addressable sensor includes one or more sensor elements, one or more antennas for communicating with the wireless sensor reader, an RF power and communications interface, and RFID control module, and a sensor interface. The wireless sensor reader includes one or more antennas, a user interface, a controller, a network communications module, and an RF addressable sensor logic module.

WiseMAC: An Ultra Low Power MAC Protocol for Multi-hop Wireless Sensor Networks

Abstract: WiseMAC is a medium access control protocol designed for wireless sensor networks. This protocol is based on non-persistent CSMA and uses the preamble sampling technique to minimize the power consumed when listening to an idle medium. The novelty in this protocol consists in exploiting the knowledge of the sampling schedule of one’s direct neighbors to use a wake-up preamble of minimized size. This scheme allows not only to reduce the transmit and the receive power consumption, but also brings a drastic reduction of the energy wasted due to overhearing. WiseMAC requires no set-up signalling, no network-wide synchronization and is adaptive to the traffic load. It presents an ultra-low power consumption in low traffic conditions and a high energy efficiency in high traffic conditions. The performance of the WiseMAC protocol is evaluated using simulations and mathematical analysis, and compared with S-MAC, T-MAC, CSMA/CA and an ideal protocol.

Energy-efficient area monitoring for sensor networks

Abstract: The nodes in sensor networks must self-organize to monitor the target area as long as possible. Researchers at the Fundamental Computer Science Laboratory of Lille are developing strategies for selecting and updating an energy-efficient connected active sensor set that extends the network lifetime. We report on their work to optimize energy consumption in three separate problems: area coverage, request spreading, and data aggregation.

ACE: An Emergent Algorithm for Highly Uniform Cluster Formation

Abstract: The efficient subdivision of a sensor network into uniform, mostly non-overlapping clusters of physically close nodes is an important building block in the design of efficient upper layer network functions such as routing, broadcast, data aggregation, and query processing.

WiseNET: an ultralow-power wireless sensor network solution

Abstract: A wireless sensor network consists of many energy-autonomous microsensors distributed throughout an area of interest. Each node monitors its local environment, locally processing and storing the collected data so that other nodes can use it. To optimize power consumption, the Swiss Center for Electronics and Microtechnology has developed WiseNET, an ultralow-power platform for the implementation of wireless sensor networks that achieves low-power operation through a careful codesign approach. The WiseNET platform uses a codesign approach that combines a dedicated duty-cycled radio with WiseMAC, a low-power media access control protocol, and a complex system-on-chip sensor node to exploit the intimate relationship between MAC-layer performance and radio transceiver parameters. The WiseNET solution consumes about 100 times less power than comparable solutions.

Power Sources for Wireless Sensor Networks

Abstract: Wireless sensor networks are poised to become a very significant enabling technology in many sectors. Already a few very low power wireless sensor platforms have entered the marketplace. Almost all of these platforms are designed to run on batteries that have a very limited lifetime. In order for wireless sensor networks to become a ubiquitous part of our environment, alternative power sources must be employed. This paper reviews many potential power sources for wireless sensor nodes. Well established power sources, such as batteries, are reviewed along with emerging technologies and currently untapped sources. Power sources are classified as energy reservoirs, power distribution methods, or power scavenging methods, which enable wireless nodes to be completely self-sustaining. Several sources capable of providing power on the order of 100 μW/cm3 for very long lifetimes are feasible. It is the authors’ opinion that no single power source will suffice for all applications, and that the choice of a power source needs to be considered on an application-by-application basis.

Energy-latency tradeoffs for data gathering in wireless sensor networks

Abstract: We study the problem of scheduling packet transmissions for data gathering in wireless sensor networks. The focus is to explore the energy-latency tradeoffs in wireless communication using techniques such as modulation scaling. The data aggregation tree - a multiple-source single-sink communication paradigm - is employed for abstracting the packet flow. We consider a real-time scenario where the data gathering must be performed within a specified latency constraint. We present algorithms to minimize the overall energy dissipation of the sensor nodes in the aggregation tree subject to the latency constraint. For the off-line problem, we propose (a) a numerical algorithm for the optimal solution, and (h) a pseudo-polynomial time approximation algorithm based on dynamic programming. We also discuss techniques for handling interference among the sensor nodes. Simulations have been conducted for both long-range communication and short-range communication. The simulation results show that compared with the classic shutdown technique, between 20% to 90% energy savings can be achieved by our techniques, under different settings of several key system parameters. We also develop an on-line distributed protocol that relies only on the local information available at each sensor node within the aggregation tree. Simulation results show that between 15% to 90% energy conservation can be achieved by the on-line protocol. The adaptability of the protocol with respect to variations in the packet size and latency constraint is also demonstrated through several run-time scenarios.

MNP: multihop network reprogramming service for sensor networks

Abstract: Reprogramming of sensor networks is an important and challenging problem as it is often necessary to reprogram the sensors in place. In this paper, we propose a multihop reprogramming service designed for Mica-2/XSM motes. One of the problems in reprogramming is the issue of message collision. To reduce the problem of collision and hidden terminal problem, we propose a sender selection algorithm that attempts to guarantee that in a neighborhood there is at most one source transmitting the program at a time. Further, our sender selection is greedy in that it tries to select the sender that is expected to have the most impact. We also use pipelining to enable fast data propagation. MNP is energy efficient because it reduces the active radio time of a sensor node by putting the node into "sleep" state when its neighbors are transmitting a segment that is not of interest. Finally, we argue that it is possible to tune our service according to the remaining battery level of a sensor, i.e., it can be tuned so that the probability that a sensor is given the responsibility of transmitting the code is proportional to its remaining battery life

ATEMU: a fine-grained sensor network simulator

Abstract: In this paper we describe the design and implementation of ATEMU, a fine grained sensor network simulator. ATEMU is intended to bridge the gap between actual sensor network deployments and sensor network simulations. We adopt a hybrid strategy, where the operation of individual sensor nodes is emulated in an instruction by instruction manner, and their interactions with each other via wireless transmissions are simulated in a realistic manner. A unique feature of ATEMU is its ability to simulate a heterogeneous sensor network. Using ATEMU it is possible to not only accurately simulate the operation of different application on the MICA2 platform but also a complete sensor network where the sensor nodes themselves maybe based on different hardware platforms. In addition we also describe our implementation of XATDB, our front-end debugger/GUI for ATEMU. XATDB provides an excellent educational tool for people to start learning about the operation of sensor nodes and sensor networks, without requiring the purchase of actual sensor node hardware. The accuracy and emulation capabilities provided by ATEMU ensure that when and if actual hardware is used, the software will already have undergone rigorous testing and debugging on an accurate platform. This would provide the sensor network deployment community with a much more accurate estimate of the performance of various algorithms and protocols in realistic scenarios and platforms.

Public key cryptography in sensor networks—revisited

Abstract: The common perception of public key cryptography is that it is complex, slow and power hungry, and as such not at all suitable for use in ultra-low power environments like wireless sensor networks. It is therefore common practice to emulate the asymmetry of traditional public key based cryptographic services through a set of protocols [1] using symmetric key based message authentication codes (MACs). Although the low computational complexity of MACs is advantageous, the protocol layer requires time synchronization between devices on the network and a significant amount of overhead for communication and temporary storage. The requirement for a general purpose CPU to implement these protocols as well as their complexity makes them prone to vulnerabilities and practically eliminates all the advantages of using symmetric key techniques in the first place. In this paper we challenge the basic assumptions about public key cryptography in sensor networks which are based on a traditional software based approach. We propose a custom hardware assisted approach for which we claim that it makes public key cryptography feasible in such environments, provided we use the right selection of algorithms and associated parameters, careful optimization, and low-power design techniques. In order to validate our claim we present proof of concept implementations of two different algorithms—Rabin’s Scheme and NtruEncrypt—and analyze their architecture and performance according to various established metrics like power consumption, area, delay, throughput, level of security and energy per bit. Our implementation of NtruEncrypt in ASIC standard cell logic uses no more than 3,000 gates with an average power consumption of less than 20 μW. We envision that our public key core would be embedded into a light-weight sensor node architecture.

Asymptotic results for decentralized detection in power constrained wireless sensor networks

Abstract: In this paper, we study a binary decentralized detection problem in which a set of sensor nodes provides partial information about the state of nature to a fusion center. Sensor nodes have access to conditionally independent and identically distributed observations, given the state of nature, and transmit their data over a wireless channel. Upon reception of the information, the fusion center attempts to accurately reconstruct the state of nature. Specifically, we extend existing asymptotic results about large sensor networks to the case where the network is subject to a joint power constraint, and where the communication channel from each sensor node to the fusion center is corrupted by additive noise. Large deviation theory is used to show that having identical sensor nodes, i.e., each node using the same transmission scheme, is asymptotically optimal. Furthermore, a performance metric by which sensor node candidates can be compared is established. We supplement the theory with examples to illustrate how the results derived in this paper apply to the design of practical sensing systems.

Multiple sink network design problem in large scale wireless sensor networks

Abstract: The battery resource of the sensor nodes should be managed efficiently, in order to prolong network lifetime in wireless sensor networks. Moreover, in large-scale networks with a large number of sensor nodes, multiple sink nodes should be deployed, not only to increase the manageability of the network, but also to reduce the energy-dissipation at each node. In this paper, we focus on the multiple sink location problems in large-scale wireless sensor networks. Different problems depending on the design criteria are presented. We consider locating sink nodes to the sensor environment, where we are given a time constraint that states the minimum required operational time for the sensor network. We use simulation techniques to evaluate the quality of our solution.

Event Detection Services Using Data Service Middleware in Distributed Sensor Networks

Abstract: This paper presents the real-time event detection service using Data Service Middleware (DSWare). DSWare provides data-centric and group-based services for sensor networks. The real-time event service handles unreliability of individual sensor reports, correlation among different sensor observations, and inherent real-time characteristics of events. The event service supports confidence functions which are designed based on data semantics, including relative importance of sub-events and historical patterns. When the failure rate is high, the event service enables partial detection of critical events to be reported in a timely manner. It can also be applied to differentiate between the occurrences of events and false alarms.

Performance measurements of motes sensor networks

Abstract: In this paper we investigate the performance of mica2 and mica2dot Berkeley motes by means of an extensive experimental analysis. This study is aimed at analyzing the main elements that characterize the performance of a sensor network, e.g., power consumption in different operating conditions, impact of weather conditions, interference between neighboring nodes, etc. Even if the analysis is related to a specific technology it provides some general useful information. Specifically, we found that the transmission range of mote sensor nodes decreases significantly in the presence of fog or rain. We also investigated the interference between neighboring nodes and, based on the experimental results, we propose a channel model for mote sensor nodes. This model is very similar to the channel model of IEEE 802.11 networks.

Location-aware key management scheme for wireless sensor networks

Abstract: Sensor networks are composed of a large number of low power sensor devices. For secure communication among sensors, secret keys must be established between them. Recently, several pairwise key schemes have been proposed for large distributed sensor networks. These schemes randomly select a set of keys from a key pool and install the keys in the memory of each sensor. After deployment, the sensors can set up keys by using the preinstalled keys. Due to lack of tamper-resistant hardware, the sensor networks are vulnerable to node capture attacks. The information gained from captured nodes can be used to compromise communication among uncompromised sensors. Du et al. [1], Liu and Ning [2] proposed to use the known deployment information to reduce the memory requirements and mitigate the consequences of node capture attack. Our analysis shows that the assumption of random capture of sensors is too weak. An intelligent attacker can selectively capture sensors to get more information with less efforts. In addition to selective node capture attack, all recent proposals are vulnerable to node fabrication attack, in which an attacker can fabricate new sensors by manipulating the compromised secret keys and then deploy the fabricated sensors into the sensor system. To counter these attacks, we propose a grid-group scheme which uses known deployment information. Unlike the pairwise key scheme using deployment information proposed by Du et al., we uniformly deploy sensors in a large area; instead of randomly distributing keys from a large key pool to each sensor, we systematically distribute secret keys to each sensor from a structured key pool. Our performance analysis shows that our scheme requires less number of keys preinstalled for each sensor and is resilient to selective node capture attack and node fabrication attack.

Multipurpose sensor port

Abstract: A sensor port is adapted to connect to either a sensor or a data source. A reader is configured to identify which of the sensor and the data source is connected to the sensor port. A data path is configured to communicate an analog signal associated with the sensor and digital data associated with the data source to a signal processor according to the identification made by the reader.

Traffic Measurement and Vehicle Classification with a Single Magnetic Sensor

Abstract: Wireless magnetic sensor networks offer a very attractive, low-cost alternative to inductive loops for traffic measurement in freeways and at intersections. In addition to vehicle count, occupancy and speed, the sensors yield traffic information (such as vehicle classification) that cannot be obtained from loop data. Because such networks can be deployed in a very short time, they can also be used (and reused) for temporary traffic measurement. This paper reports the detection capabilities of magnetic sensors, based on two field experiments. The first experiment collected a two-hour trace of measurements on Hearst Avenue in Berkeley. The vehicle detection rate is better than 99 percent (100 percent for vehicles other than motorcycles); and estimates of vehicle length and speed appear to be better than 90 percent. Moreover, the measurements also give inter-vehicle spacing or headways, which reveal such interesting phenomena as platoon formation downstream of a traffic signal. Results of the second experiment are preliminary. Sensor data from 37 passing vehicles at the same site are processed and classified into 6 types. Sixty percent of the vehicles are classified correctly, when length is not used as a feature. The classification algorithm can be implemented in real time by the sensor node itself, in contrast to other methods based on high scan-rate inductive loop signals, which require extensive offline computation. We believe that when length is used as a feature, 80-90 percent of vehicles will be correctly classified.

Cross-layer scheduling for power efficiency in wireless sensor networks

Abstract: Wireless sensor networks are considered the sensing technology of the future. Large numbers of untethered sensor nodes can be used for tracking small animals and targets, environmental monitoring, enforcing security perimeters, etc. A major problem for many sensor network applications is determining the most efficient way of conserving the energy of the power source. Some networks use batteries, while others suggest different methods of gathering energy (e.g., solar cells). Regardless of the powering method, energy conservation is of prime importance for sensor networks. The best way to conserve energy is to turn the sensor nodes off; however, since an inactive sensor node is no longer part of the network, the network can become disconnected. This creates a fundamental trade-off. In this paper, we propose a deterministic, schedule-based energy conservation scheme. In the proposed approach, time-synchronized sensors form on-off schedules that enable the sensors to be awake only when necessary. The schedule establishment is fully distributed and thus appropriate for large sensor networks. The performance of the proposed approach is evaluated through the use of simulations

On the Computational Complexity of Sensor Network Localization

Abstract: Determining the positions of the sensor nodes in a network is essential to many network functionalities such as routing, coverage and tracking, and event detection. The localization problem for sensor networks is to reconstruct the positions of all of the sensors in a network, given the distances between all pairs of sensors that are within some radius r of each other. In the past few years, many algorithms for solving the localization problem were proposed, without knowing the computational complexity of the problem. In this paper, we show that no polynomial-time algorithm can solve this problem in the worst case, even for sets of distance pairs for which a unique solution exists, unless RP = NP. We also discuss the consequences of our result and present open problems.

Incremental network programming for wireless sensors

Abstract: We present an incremental network programming mechanism which re programs wireless sensors quickly by transmitting the incremental changes for the new program version. Using the Rsync algorithm we generate the difference of the two program images, which allows us to distribute just the key changes of the program. Unlike previous approaches, our design does not assume any prior knowledge of the program code structure and can be applied to any hardware platform. To meet the resource constraints of wireless sensors we tuned the Rsync algorithm which was originally made for updating binary files among computationally powerful machines. In our design, the sensor node processes the delivery and the decoding of the difference script in separate steps. This makes it easy to extend for multi-hop network programming. We are able to achieve the speedup of 9.1 for changing a constant and 2.1 to 2.5 for changing a few lines in the source code over the non-incremental delivery.

Revisiting random key pre-distribution schemes for wireless sensor networks

Abstract: Key management is one of the fundamental building blocks of security services. In a network with resource constrained nodes like sensor networks, traditional key management techniques, such as public key cryptography or key distribution center (e.g., Kerberos), are often not effective. To solve this problem, several key pre-distribution schemes have been proposed for sensor networks based on random graph theory. In these schemes, a set of randomly chosen keys or secret information is pre-distributed to each sensor node and a network is securely formed based on this information. Most of the schemes assumed that the underlying physical network is dense enough, that is, the degree of each node is hig.In this paper, we revisit the random graph theory and use giant component theory by Erdos and Renyi to show that even if the node degree is small, most of the nodes in the network can be connected. Further, we use this fact to analyze the Eschenhauer et. al's, Du et. al's, and Chan et. al's key pre-distribution schemes and evaluate the relation between connectivity, memory size, and security. We show that we can reduce the amount of memory required or improve security by trading-off a very small number of isolated nodes. Our simulation results show that the communication overhead does not increase significantly even after reducing the node degree. In addition, we present an approach by which nodes can dynamically adjust their transmission power to establish secure links with the targeted networked neighbors. Finally, we propose an effcient path-key identification algorithm and compare it with the existing scheme.

Modeling the performance of wireless sensor networks

Abstract: A critical issue in wireless sensor networks is represented by the limited availability of energy within network nodes; therefore making good use of energy is a must. A widely employed energy-saving technique is to place nodes in sleep mode, corresponding to a low-power consumption as well as to reduced operational capabilities. In this work, we develop a Markov model of a sensor network whose nodes may enter a sleep mode, and we use this model to investigate the system performance in terms of energy consumption, network capacity, and data deliver delay. Furthermore, the proposed model enables us to investigate the trade-offs existing between these performance metrics and the sensor dynamics in sleep/active mode. Analytical results present an excellent matching with simulation results for a large variety of system scenarios showing the accuracy of our approach.

Ad Hoc wireless node and network

Abstract: A node is suitable for a wireless network. A wireless network comprises one or more sensor nodes and/or one or more control nodes. In the wireless network, the sensor node transmits in response to a sensed event and/or a request from a control node. A transmission/routing of data between a sensor node and/or a control node may be subject to a policy constraint and a resource constraint.

Glacsweb: a sensor network for hostile environments

Abstract: A sensor network is described which obtains data from nodes on and inside glaciers. Power management through scheduling and selective control is used to allow a lifetime of at least one year on batteries. Radio links in the glacier and across 2.5 km distances are used for data and commands. The prototype system was installed in Norway in 2003 and this paper describes details of the full design for 2004 through discussion of the lessons learnt.