Showing papers on "Wireless sensor network published in 2001"
16 Jul 2001
TL;DR: A novel approach to the localization of sensors in an ad-hoc network that enables sensor nodes to discover their locations using a set distributed iterative algorithms is described.
Abstract: The recent advances in radio and em beddedsystem technologies have enabled the proliferation of wireless microsensor networks. Such wirelessly connected sensors are released in many diverse environments to perform various monitoring tasks. In many such tasks, location awareness is inherently one of the most essential system parameters. It is not only needed to report the origins of events, but also to assist group querying of sensors, routing, and to answer questions on the network coverage. In this paper we present a novel approach to the localization of sensors in an ad-hoc network. We describe a system called AHLoS (Ad-Hoc Localization System) that enables sensor nodes to discover their locations using a set distributed iterative algorithms. The operation of AHLoS is demonstrated with an accuracy of a few centimeters using our prototype testbed while scalability and performance are studied through simulation.
2,931 citations
16 Jul 2001
TL;DR: A suite of security building blocks optimized for resource-constrained environments and wireless communication, and shows that they are practical even on minimal hardware: the performance of the protocol suite easily matches the data rate of the network.
Abstract: As sensor networks edge closer towards wide-spread deployment, security issues become a central concern. So far, much research has focused on making sensor networks feasible and useful, and has not concentrated on security.We present a suite of security building blocks optimized for resource-constrained environments and wireless communication. SPINS has two secure building blocks: SNEP and mTESLA SNEP provides the following important baseline security primitives: Data confidentiality, two-party data authentication, and data freshness. A particularly hard problem is to provide efficient broadcast authentication, which is an important mechanism for sensor networks. mTESLA is a new protocol which provides authenticated broadcast for severely resource-constrained environments. We implemented the above protocols, and show that they are practical even on minimal hardware: the performance of the protocol suite easily matches the data rate of our network. Additionally, we demonstrate that the suite can be used for building higher level protocols.
2,703 citations
23 Apr 2001
TL;DR: This paper proposes a formal classification of sensor networks, based on their mode of functioning, as proactive and reactive networks, and introduces a new energy efficient protocol, TEEN (Threshold sensitive Energy Efficient sensor Network protocol) for reactive networks.
Abstract: Wireless sensor networks are expected to find wide applicability and increasing deployment in the near future. In this paper, we propose a formal classification of sensor networks, based on their mode of functioning, as proactive and reactive networks. Reactive networks, as opposed to passive data collecting proactive networks, respond immediately to changes in the relevant parameters of interest. We also introduce a new energy efficient protocol, TEEN (Threshold sensitive Energy Efficient sensor Network protocol) for reactive networks. We evaluate the performance of our protocol for a simple temperature sensing application. In terms of energy efficiency, our protocol has been observed to outperform existing conventional sensor network protocols.
2,423 citations
01 Dec 2001
TL;DR: This work is proposing APS - a distributed, hop by hop positioning algorithm, that works as an extension of both distance vector routing and GPS positioning in order to provide approximate location for all nodes in a network where only a limited fraction of nodes have self location capability.
Abstract: Many ad hoc network protocols and applications assume the knowledge of geographic location of nodes. The absolute location of each networked node is an assumed fact by most sensor networks which can then present the sensed information on a geographical map. Finding location without the aid of GPS in each node of an ad hoc network is important in cases where GPS is either not accessible, or not practical to use due to power, form factor or line of sight conditions. Location would also enable routing in sufficiently isotropic large networks, without the use of large routing tables. We are proposing APS - a distributed, hop by hop positioning algorithm, that works as an extension of both distance vector routing and GPS positioning in order to provide approximate location for all nodes in a network where only a limited fraction of nodes have self location capability.
1,887 citations
22 Apr 2001
TL;DR: This work establishes the main highlight of the paper-optimal polynomial time worst and average case algorithm for coverage calculation, which answers the questions about quality of service (surveillance) that can be provided by a particular sensor network.
Abstract: Wireless ad-hoc sensor networks have recently emerged as a premier research topic. They have great long-term economic potential, ability to transform our lives, and pose many new system-building challenges. Sensor networks also pose a number of new conceptual and optimization problems. Some, such as location, deployment, and tracking, are fundamental issues, in that many applications rely on them for needed information. We address one of the fundamental problems, namely coverage. Coverage in general, answers the questions about quality of service (surveillance) that can be provided by a particular sensor network. We first define the coverage problem from several points of view including deterministic, statistical, worst and best case, and present examples in each domain. By combining the computational geometry and graph theoretic techniques, specifically the Voronoi diagram and graph search algorithms, we establish the main highlight of the paper-optimal polynomial time worst and average case algorithm for coverage calculation. We also present comprehensive experimental results and discuss future research directions related to coverage in sensor networks.
1,837 citations
22 Apr 2001
TL;DR: A method for estimating unknown node positions in a sensor network based exclusively on connectivity-induced constraints is described, and a method for placing rectangular bounds around the possible positions for all unknown nodes in the network is given.
Abstract: A method for estimating unknown node positions in a sensor network based exclusively on connectivity-induced constraints is described. Known peer-to-peer communication in the network is modeled as a set of geometric constraints on the node positions. The global solution of a feasibility problem for these constraints yields estimates for the unknown positions of the nodes in the network. Providing that the constraints are tight enough, simulation illustrates that this estimate becomes close to the actual node positions. Additionally, a method for placing rectangular bounds around the possible positions for all unknown nodes in the network is given. The area of the bounding rectangles decreases as additional or tighter constraints are included in the problem. Specific models are suggested and simulated for isotropic and directional communication, representative of broadcast-based and optical transmission respectively, though the methods presented are not limited to these simple cases.
1,733 citations
TL;DR: In this article, a novel braided multipath scheme was proposed to enable energy efficient recovery from failure of the shortest path between source and sink, which results in several partially disjoint multipath schemes.
Abstract: Previously proposed sensor network data dissemination schemes require periodic low-rate flooding of data in order to allow recovery from failure. We consider constructing two kinds of multipaths to enable energy efficient recovery from failure of the shortest path between source and sink. Disjoint multipath has been studied in the literature. We propose a novel braided multipath scheme, which results in several partially disjoint multipath schemes. We find that braided multipaths are a viable alternative for energy-efficient recovery from isolated and patterned failures.
1,379 citations
07 May 2001
TL;DR: This work identifies opportunities and challenges for distributed signal processing in networks of these sensing elements and investigates some of the architectural challenges posed by systems that are massively distributed, physically-coupled, wirelessly networked, and energy limited.
Abstract: Pervasive micro-sensing and actuation may revolutionize the way in which we understand and manage complex physical systems: from airplane wings to complex ecosystems. The capabilities for detailed physical monitoring and manipulation offer enormous opportunities for almost every scientific discipline, and it will alter the feasible granularity of engineering. We identify opportunities and challenges for distributed signal processing in networks of these sensing elements and investigate some of the architectural challenges posed by systems that are massively distributed, physically-coupled, wirelessly networked, and energy limited.
1,258 citations
11 Jun 2001
TL;DR: The experimental results demonstrate that by using only a subset of sensor nodes at each moment, the system achieves a significant energy savings while fully preserving coverage.
Abstract: Wireless sensor networks have emerged recently as an effective way of monitoring remote or inhospitable physical environments. One of the major challenges in devising such networks lies in the constrained energy and computational resources available to sensor nodes. These constraints must be taken into account at all levels of the system hierarchy. The deployment of sensor nodes is the first step in establishing a sensor network. Since sensor networks contain a large number of sensor nodes, the nodes must be deployed in clusters, where the location of each particular node cannot be fully guaranteed a priori. Therefore, the number of nodes that must be deployed in order to completely cover the whole monitored area is often higher than if a deterministic procedure were used. In networks with stochastically placed nodes, activating only the necessary number of sensor nodes at any particular moment can save energy. We introduce a heuristic that selects mutually exclusive sets of sensor nodes, where the members of each of those sets together completely cover the monitored area. The intervals of activity are the same for all sets, and only one of the sets is active at any time. The experimental results demonstrate that by using only a subset of sensor nodes at each moment, we achieve a significant energy savings while fully preserving coverage.
1,074 citations
16 Jul 2001
TL;DR: This work proposes an adaptive rate control mechanism aiming to support media access control in sensor networks and finds that such a scheme is most effective in achieving the authors' fairness goal while being energy efficient for both low and high duty cycle of network traffic.
Abstract: We study the problem of media access control in the novel regime of sensor networks, where unique application behavior and tight constraints in computation power, storage, energy resources, and radio technology have shaped this design space to be very different from that found in traditional mobile computing regime. Media access control in sensor networks must not only be energy efficient but should also allow fair bandwidth allocation to the infrastructure for all nodes in a multihop network. We propose an adaptive rate control mechanism aiming to support these two goals and find that such a scheme is most effective in achieving our fairness goal while being energy efficient for both low and high duty cycle of network traffic.
1,068 citations
16 Jul 2001
TL;DR: This work proposes a physical layer driven approach to designing protocols and algorithms for wireless microsensor networks that have extremely long lifetimes and shows how to reduce energy consumption of non-ideal hardware through physical layer aware algorithms and protocols.
Abstract: The potential for collaborative, robust networks of microsensors has attracted a great deal of research attention. For the most part, this is due to the compelling applications that will be enabled once wireless microsensor networks are in place; location-sensing, environmental sensing, medical monitoring and similar applications are all gaining interest. However, wireless microsensor networks pose numerous design challenges. For applications requiring long-term, robust sensing, such as military reconnaissance, one important challenge is to design sensor networks that have long system lifetimes. This challenge is especially difficult due to the energy-constrained nature of the devices. In order to design networks that have extremely long lifetimes, we propose a physical layer driven approach to designing protocols and algorithms. We first present a hardware model for our wireless sensor node and then introduce the design of physical layer aware protocols, algorithms, and applications that minimize energy consumption of the system. Our approach prescribes methods that can be used at all levels of the hierarchy to take advantage of the underlying hardware. We also show how to reduce energy consumption of non-ideal hardware through physical layer aware algorithms and protocols.
01 Apr 2001
TL;DR: This work proposes a tiered system architecture in which data collected at numerous, inexpensive sensor nodes is filtered by local processing on its way through to larger, more capable and more expensive nodes.
Abstract: As new fabrication and integration technologies reduce the cost and size of micro-sensors and wireless interfaces, it becomes feasible to deploy densely distributed wireless networks of sensors and actuators These systems promise to revolutionize biological, earth, and environmental monitoring applications, providing data at granularities unrealizable by other means In addition to the challenges of miniaturization, new system architectures and new network algorithms must be developed to transform the vast quantity of raw sensor data into a manageable stream of high-level data To address this, we propose a tiered system architecture in which data collected at numerous, inexpensive sensor nodes is filtered by local processing on its way through to larger, more capable and more expensive nodesWe briefly describe Habitat monitoring as our motivating application and introduce initial system building blocks designed to support this application The remainder of the paper presents details of our experimental platform
TL;DR: A comprehensive summary of recent work addressing energy efficient and low-power design within all layers of the wireless network protocol stack of wireless networks is presented.
Abstract: Wireless networking has witnessed an explosion of interest from consumers in recent years for its applications in mobile and personal communications. As wireless networks become an integral component of the modern communication infrastructure, energy efficiency will be an important design consideration due to the limited battery life of mobile terminals. Power conservation techniques are commonly used in the hardware design of such systems. Since the network interface is a significant consumer of power, considerable research has been devoted to low-power design of the entire network protocol stack of wireless networks in an effort to enhance energy efficiency. This paper presents a comprehensive summary of recent work addressing energy efficient and low-power design within all layers of the wireless network protocol stack.
Journal Article•
TL;DR: In this article, the authors define the concept of sensor databases mixing stored data and sensor data represented as time series and describe the design and implementation of the COUGAR sensor database system.
Abstract: Sensor networks are being widely deployed for measurement, detection and surveillance applications. In these new applications, users issue long-running queries over a combination of stored data and sensor data. Most existing applications rely on a centralized system for collecting sensor data. These systems lack flexibility because data is extracted in a predefined way; also, they do not scale to a large number of devices because large volumes of raw data are transferred regardless of the queries that are submitted. In our new concept of sensor database system, queries dictate which data is extracted from the sensors. In this paper, we define the concept of sensor databases mixing stored data represented as relations and sensor data represented as time series. Each long-running query formulated over a sensor database defines a persistent view, which is maintained during a given time interval. We also describe the design and implementation of the COUGAR sensor database system.
08 Jan 2001
TL;DR: This paper defines the concept of sensor databases mixing stored data represented as relations and sensorData represented as time series, and describes the design and implementation of the COUGAR sensor database system.
Abstract: Sensor networks are being widely deployed for measurement, detection and surveillance applications. In these new applications, users issue long-running queries over a combination of stored data and sensor data. Most existing applications rely on a centralized system for collecting sensor data. These systems lack flexibility because data is extracted in a predefined way; also, they do not scale to a large number of devices because large volumes of raw data are transferred regardless of the queries that are submitted. In our new concept of sensor database system, queries dictate which data is extracted from the sensors. In this paper, we define the concept of sensor databases mixing stored data represented as relations and sensor data represented as time series. Each long-running query formulated over a sensor database defines a persistent view, which is maintained during a given time interval. We also describe the design and implementation of the COUGAR sensor database system.
TL;DR: It is argued that power-aware methodology uses an embedded microoperating system to reduce node energy consumption by exploiting both sleep state and active power management.
Abstract: We propose an OS-directed power management technique to improve the energy efficiency of sensor nodes. Dynamic power management (DPM) is an effective tool in reducing system power consumption without significantly degrading performance. The basic idea is to shut down devices when not needed and wake them up when necessary. DPM, in general, is not a trivial problem. If the energy and performance overheads in sleep-state transition were negligible, then a simple greedy algorithm that makes the system enter the deepest sleep state when idling would be perfect. However, in reality, sleep-state transitioning has the overhead of storing processor state and turning off power. Waking up also takes a finite amount of time. Therefore, implementing the correct policy for sleep-state transitioning is critical for DPM success. It is argued that power-aware methodology uses an embedded microoperating system to reduce node energy consumption by exploiting both sleep state and active power management.
07 May 2001
TL;DR: The algorithms presented herein rely on range measurements between pairs of nodes and the a priori coordinates of sparsely located anchor nodes to establish confident position estimates through assumptions, checks, and iterative refinements.
Abstract: Evolving networks of ad-hoc wireless sensing nodes rely heavily on the ability to establish position information. The algorithms presented herein rely on range measurements between pairs of nodes and the a priori coordinates of sparsely located anchor nodes. Clusters of nodes surrounding anchor nodes cooperatively establish confident position estimates through assumptions, checks, and iterative refinements. Once established, these positions are propagated to more distant nodes, allowing the entire network to create an accurate map of itself. Major obstacles include overcoming inaccuracies in range measurements as great as /spl plusmn/50%, as well as the development of initial guesses for node locations in clusters with few or no anchor nodes. Solutions to these problems are presented and discussed, using position error as the primary metric. Algorithms are compared according to position error, scalability, and communication and computational requirements. Early simulations yield average position errors of 5% in the presence of both range and initial position inaccuracies.
16 Jul 2001
TL;DR: This work has developed an efficient and effective algorithm for exposure calculation in sensor networks, specifically for finding minimal exposure paths and provides an unbounded level of accuracy as a function of run time and storage.
Abstract: Wireless ad-hoc sensor networks will provide one of the missing connections between the Internet and the physical world One of the fundamental problems in sensor networks is the calculation of coverage Exposure is directly related to coverage in that it is a measure of how well an object, moving on an arbitrary path, can be observed by the sensor network over a period of timeIn addition to the informal definition, we formally define exposure and study its properties We have developed an efficient and effective algorithm for exposure calculation in sensor networks, specifically for finding minimal exposure paths The minimal exposure path provides valuable information about the worst case exposure-based coverage in sensor networks The algorithm works for any given distribution of sensors, sensor and intensity models, and characteristics of the network It provides an unbounded level of accuracy as a function of run time and storage We provide an extensive collection of experimental results and study the scaling behavior of exposure and the proposed algorithm for its calculation
11 Jun 2001
TL;DR: It is shown that in all data gathering scenarios presented, there exist networks which achieve lifetimes equal to or >95% of the derived bounds, depending on the scenario, and bounds are either tight or near-tight.
Abstract: We ask a fundamental question concerning the limits of energy efficiency of sensor networks-what is the upper bound on the lifetime of a sensor network that collects data from a specified region using a certain number of energy-constrained nodes? The answer to this question is valuable for two main reasons. First, it allows calibration of real world data-gathering protocols and an understanding of factors that prevent these protocols from approaching fundamental limits. Secondly, the dependence of lifetime on factors like the region of observation, the source behavior within that region, basestation location, number of nodes, radio path loss characteristics, efficiency of node electronics and the energy available on a node, is exposed. This allows architects of sensor networks to focus on factors that have the greatest potential impact on network lifetime. By employing a combination of theory and extensive simulations of constructed networks, we show that in all data gathering scenarios presented, there exist networks which achieve lifetimes equal to or >95% of the derived bounds. Hence, depending on the scenario, our bounds are either tight or near-tight.
21 Oct 2001
TL;DR: This paper is the first description of the software architecture that supports named data and in- network processing in an operational, multi-application sensor-network and shows that approaches such as in-network aggregation and nested queries can significantly affect network traffic.
Abstract: In most distributed systems, naming of nodes for low-level communication leverages topological location (such as node addresses) and is independent of any application. In this paper, we investigate an emerging class of distributed systems where low-level communication does not rely on network topological location. Rather, low-level communication is based on attributes that are external to the network topology and relevant to the application. When combined with dense deployment of nodes, this kind of named data enables in-network processing for data aggregation, collaborative signal processing, and similar problems. These approaches are essential for emerging applications such as sensor networks where resources such as bandwidth and energy are limited. This paper is the first description of the software architecture that supports named data and in-network processing in an operational, multi-application sensor-network. We show that approaches such as in-network aggregation and nested queries can significantly affect network traffic. In one experiment aggregation reduces traffic by up to 42% and nested queries reduce loss rates by 30%. Although aggregation has been previously studied in simulation, this paper demonstrates nested queries as another form of in-network processing, and it presents the first evaluation of these approaches over an operational testbed.
01 Jan 2001
TL;DR: This paper presents a clustering scheme to create a hierarchical control structure for multi-hop wireless networks and presents an efficient distributed implementation of the clustering algorithm for a set of wireless nodes to create the set of desired clusters.
Abstract: In this paper we present a clustering scheme to create a hierarchical control structure for multi-hop wireless networks. A cluster is defined as a subset of vertices, whose induced graph is connected. In addition, a cluster is required to obey certain constraints that are useful for management and scalability of the hierarchy. All these constraints cannot be met simultaneously for general graphs, but we show how such a clustering can be obtained for wireless network topologies. Finally, we present an efficient distributed implementation of our clustering algorithm for a set of wireless nodes to create the set of desired clusters.
TL;DR: A sensor information networking architecture, called SINA, that facilitates querying, monitoring, and tasking of sensor networks and provides mechanisms to create associations and coordinate activities among sensor nodes.
Abstract: This article introduces a sensor information networking architecture, called SINA, that facilitates querying, monitoring, and tasking of sensor networks. SINA serves the role of middleware that abstracts a network of sensor nodes as a collection of massively distributed objects. SINA's execution environment provides a set of configuration and communication primitives that enable scalable and energy-efficient organization of and interactions among sensor objects. On top the execution environment is a programmable substrate that provides mechanisms to create associations and coordinate activities among sensor nodes. Users then access information within a sensor network using declarative queries, or perform tasks using programming script.
23 Apr 2001
TL;DR: A new service model for time synchronization is proposed that provides a much more natural expression of these techniques: explicit timestamp conversions, and the implementation and characterization of several synchronization methods that exemplify the design principles are described.
Abstract: Time synchronization is a critical piece of infrastructure for any distributed system. Distributed, wireless sensor networks make extensive use of synchronized time, but often have unique requirements in the scope, lifetime, and precision of the synchronization achieved, as well as the time and energy required to achieve it. Existing time synchronization methods need to be extended to meet these new needs. We outline the synchronization requirements of future sensor networks and present an implementation of our own lowpower synchronization scheme, post-facto synchronization. We also describe an experiment that characterizes its performance for creating short-lived and localized but highprecision synchronization using very little energy.
15 Oct 2001
TL;DR: This work presents a novel backoff-based cost field setup algorithm that finds the optimal costs of all nodes to the sink with one single message overhead at each node in a large sensor network.
Abstract: Wireless sensor networks offer a wide range of challenges to networking research, including unconstrained network scale, limited computing, memory and energy resources, and wireless channel errors. We study the problem of delivering messages from any sensor to an interested client user along the minimum-cost path in a large sensor network. We propose a new cost field based approach to minimum cost forwarding. In the design, we present a novel backoff-based cost field setup algorithm that finds the optimal costs of all nodes to the sink with one single message overhead at each node. Once the field is established, the message, carrying dynamic cost information, flows along the minimum cost path in the cost field. Each intermediate node forwards the message only if it finds itself to be on the optimal path, based on dynamic cost states. Our design does not require an intermediate node to maintain explicit "forwarding path" states. It requires a few simple operations and scales to any network size. We show the correctness and effectiveness of the design by both simulations and analysis.
23 Apr 2001
TL;DR: This paper considers the problem of data collection from a sensor web consisting of N nodes, where nodes have packets of data in each round of communication that need to be gathered and fused with other nodes’ packets into one packet and transmitted to a distant base station.
Abstract: In this paper we consider the problem of data collection from a sensor web consisting of N nodes, where nodes have packets of data in each round of communication that need to be gathered and fused with other nodes’ packets into one packet and transmitted to a distant base station. Nodes have power control in their wireless communications and can transmit directly to any node in the network or to the base station. With unit delay cost for each packet transmission, if all nodes transmit data directly to the base station, then both high energy and high delay per round will occur. In our prior work [6], we developed an algorithm to minimize the energy cost per round, where a linear chain of all the nodes are formed to gather data, and nodes took turns to transmit to the base station. If the goal is to minimize the delay cost, then a binary combining scheme can be used to accomplish this task in about log N units of delay with parallel communications and incurring a slight increase in energy cost. The goal is to find data gathering schemes that balance the energy and delay cost, as measured by energy*delay. We conducted extensive simulation experiments with a number of schemes for this problem with 100 nodes in playing fields of 50m x 50m and 100m x 100m and the base station located at least 100 meters and 200 meters, respectively, from any node. With CDMA capable sensor nodes, a chain-based binary scheme performs best in terms of energy*delay. If the sensor nodes are not CDMA capable, then parallel communications are possible only among spatially separated nodes, and a chain-based 3 level hierarchy scheme performs well. These schemes perform 60 to 100 times better than direct scheme and also outperform a cluster based scheme, called LEACH [3].
03 Jan 2001
TL;DR: An overview of the key technologies required for low-energy distributed microsensors include power aware computation/communication component technology, low- energy signaling and networking, system partitioning based on computation and communication tradeoffs, and a power aware software infrastructure is presented.
Abstract: Wireless distributed microsensor systems will enable fault tolerant monitoring and control of a variety of applications. Due to the large number of microsensor nodes that may be deployed and the need for long system lifetimes, replacing the battery is not an option. Sensor systems must utilize the minimal possible energy while operating over a wide range of operating scenarios. This paper presents an overview of the key technologies required for low-energy distributed microsensors. These include power aware computation/communication component technology, low-energy signaling and networking, system partitioning based on computation and communication tradeoffs, and a power aware software infrastructure.
11 Nov 2001
TL;DR: Recursive hierarchy provides a framework for extending position estimation throughout a sensor network that can use and enhance a variety of technologies and protocols to produce fine-grained position estimates.
Abstract: Recursive hierarchy provides a framework for extending position estimation throughout a sensor network Given imprecise ranging and inter-node communication, nodes scattered throughout a large volume can estimate their physical locations from a small set of reference nodes using only local information System coverage increases iteratively, as nodes with newly estimated positions join the reference set, capitalizing on the massive scale of sensor networks The system frames position estimation as a geometric problem solvable through common nonlinear regression techniques and develops methods for gauging the reliability of position estimates This provides a flexible framework that can use and enhance a variety of technologies and protocols to produce fine-grained position estimates A specific model provides a simulation environment showing that over 90% of position estimates are correct to within 3% of the ranging distance with only 5% of the system in the initial reference set
11 Jun 2001
TL;DR: A protocol that, given a communication network, computes a subnetwork such that, for every pair of nodes connected in the original network, there is a a minimum-energy path between u and /spl upsi/ in the subnetwork (where aMinimumEnergy path is one that allows messages to be transmitted with a minimum use of energy).
Abstract: We propose a protocol that, given a communication network, computes a subnetwork such that, for every pair (u, /spl upsi/) of nodes connected in the original network, there is a a minimum-energy path between u and /spl upsi/ in the subnetwork (where a minimum-energy path is one that allows messages to be transmitted with a minimum use of energy). The network computed by our protocol is in general a subnetwork of the one computed by the protocol given by Rodoplu and Meng (see IEEE J. Selected Areas in Communications, vol.17, no.8, p.1333-44, 1999). Moreover, our protocol is computationally simpler. We demonstrate the performance improvements obtained by using the subnetwork computed by our protocol through simulation.
11 Nov 2001
TL;DR: It is shown through simulation that PARO is capable of outperforming traditional broadcast-based routing protocols (e.g., MANET routing protocols) due to its power conserving point-to-point on-demand design.
Abstract: This paper introduces PARO, a power-aware routing optimization that helps to minimize the transmission power needed to forward packets between wireless devices in ad hoc networks. Using PARO, one or more intermediate nodes called "redirectors" elects to forward packets on behalf of source-destination pairs thus reducing the aggregate transmission power consumed by wireless devices. PARO is applicable to a number of networking environments including sensor networks, home networks and mobile ad hoc networks. In this paper, we present the detailed design of PARO and evaluate the protocol using simulation and experimentation. We show through simulation that PARO is capable of outperforming traditional broadcast-based routing protocols (e.g., MANET routing protocols) due to its power conserving point-to-point on-demand design. We discuss some initial experiences from an early implementation of the protocol in an experimental wireless testbed using off-the-shelf radio technology.
Journal Article•
TL;DR: This work explores three themes in the design of self-configuring sensor networks: tuning density to trade operational quality against lifetime; using multiple sensor modalities to obtain robust measurements; and exploiting fixed environmental characteristics.
Abstract: Pervasive networks of micro-sensors and actuators offer to revolutionize the ways in which we understand and construct complex physical systems. Sensor networks must be scalable, long-lived and robust systems, overcoming energy limitations and a lack of pre-installed infrastructure. We explore three themes in the design of self-configuring sensor networks: tuning density to trade operational quality against lifetime; using multiple sensor modalities to obtain robust measurements; and exploiting fixed environmental characteristics. We illustrate these themes through the problem of localization, which is a key building block for sensor systems that itself requires coordination.