Sensor node

About: Sensor node is a research topic. Over the lifetime, 20765 publications have been published within this topic receiving 317733 citations.

Energy-efficient target coverage in wireless sensor networks

Abstract: A critical aspect of applications with wireless sensor networks is network lifetime. Power-constrained wireless sensor networks are usable as long as they can communicate sensed data to a processing node. Sensing and communications consume energy, therefore judicious power management and sensor scheduling can effectively extend network lifetime. To cover a set of targets with known locations when ground access in the remote area is prohibited, one solution is to deploy the sensors remotely, from an aircraft. The lack of precise sensor placement is compensated by a large sensor population deployed in the drop zone, that would improve the probability of target coverage. The data collected from the sensors is sent to a central node (e.g. cluster head) for processing. In this paper we propose un efficient method to extend the sensor network life time by organizing the sensors into a maximal number of set covers that are activated successively. Only the sensors from the current active set are responsible for monitoring all targets and for transmitting the collected data, while all other nodes are in a low-energy sleep mode. By allowing sensors to participate in multiple sets, our problem formulation increases the network lifetime compared with related work [M. Cardei et al], that has the additional requirements of sensor sets being disjoint and operating equal time intervals. In this paper we model the solution as the maximum set covers problem and design two heuristics that efficiently compute the sets, using linear programming and a greedy approach. Simulation results are presented to verify our approaches.

Cross-Level Sensor Network Simulation with COOJA

Abstract: Simulators for wireless sensor networks are a valuable tool for system development. However, current simulators can only simulate a single level of a system at once. This makes system development and evolution difficult since developers cannot use the same simulator for both high-level algorithm development and low-level development such as device-driver implementations. We propose cross-level simulation, a novel type of wireless sensor network simulation that enables holistic simultaneous simulation at different levels. We present an implementation of such a simulator, COOJA, a simulator for the Contiki sensor node operating system. COOJA allows for simultaneous simulation at the network level, the operating system level, and the machine code instruction set level. With COOJA, we show the feasibility of the cross-level simulation approach.

LEAP+: Efficient security mechanisms for large-scale distributed sensor networks

Abstract: We describe LEAPp (Localized Encryption and Authentication Protocol), a key management protocol for sensor networks that is designed to support in-network processing, while at the same time restricting the security impact of a node compromise to the immediate network neighborhood of the compromised node. The design of the protocol is motivated by the observation that different types of messages exchanged between sensor nodes have different security requirements, and that a single keying mechanism is not suitable for meeting these different security requirements. LEAPp supports the establishment of four types of keys for each sensor node: an individual key shared with the base station, a pairwise key shared with another sensor node, a cluster key shared with multiple neighboring nodes, and a global key shared by all the nodes in the network. LEAPp also supports (weak) local source authentication without precluding in-network processing. Our performance analysis shows that LEAPp is very efficient in terms of computational, communication, and storage costs. We analyze the security of LEAPp under various attack models and show that LEAPp is very effective in defending against many sophisticated attacks, such as HELLO flood attacks, node cloning attacks, and wormhole attacks. A prototype implementation of LEAPp on a sensor network testbed is also described.

Improving wireless sensor network lifetime through power aware organization

Abstract: A critical aspect of applications with wireless sensor networks is network lifetime. Battery-powered sensors are usable as long as they can communicate captured data to a processing node. Sensing and communications consume energy, therefore judicious power management and scheduling can effectively extend operational time. To monitor a set of targets with known locations when ground access in the monitored area is prohibited, one solution is to deploy the sensors remotely, from an aircraft. The loss of precise sensor placement would then be compensated by a large sensor population density in the drop zone, that would improve the probability of target coverage. The data collected from the sensors is sent to a central node for processing. In this paper we propose an efficient method to extend the sensor network operational time by organizing the sensors into a maximal number of disjoint set covers that are activated successively. Only the sensors from the current active set are responsible for monitoring all targets and for transmitting the collected data, while nodes from all other sets are in a low-energy sleep mode. In this paper we address the maximum disjoint set covers problem and we design a heuristic that computes the sets. Theoretical analysis and performance evaluation results are presented to verify our approach.

Reputation-based framework for high integrity sensor networks

Abstract: Sensor network technology promises a vast increase in automatic data collection capabilities through efficient deployment of tiny sensing devices. The technology will allow users to measure phenomena of interest at unprecedented spatial and temporal densities. However, as with almost every data-driven technology, the many benefits come with a significant challenge in data reliability. If wireless sensor networks are really going to provide data for the scientific community, citizen-driven activism, or organizations which test that companies are upholding environmental laws, then an important question arises: How can a user trust the accuracy of information provided by the sensor networkq Data integrity is vulnerable to both node and system failures. In data collection systems, faults are indicators that sensor nodes are not providing useful information. In data fusion systems the consequences are more dire; the final outcome is easily affected by corrupted sensor measurements, and the problems are no longer visibly obvious.In this article, we investigate a generalized and unified approach for providing information about the data accuracy in sensor networks. Our approach is to allow the sensor nodes to develop a community of trust. We propose a framework where each sensor node maintains reputation metrics which both represent past behavior of other nodes and are used as an inherent aspect in predicting their future behavior. We employ a Bayesian formulation, specifically a beta reputation system, for the algorithm steps of reputation representation, updates, integration and trust evolution. This framework is available as a middleware service on motes and has been ported to two sensor network operating systems, TinyOS and SOS. We evaluate the efficacy of this framework using multiple contexts: (1) a lab-scale test bed of Mica2 motes, (2) Avrora simulations, and (3) real data sets collected from sensor network deployments in James Reserve.