930 resultados para Sensor network


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A wireless sensor network (WSN) is a group of sensors that are geographically distributed and interconnected by wireless networks. Sensors gather information about the state of physical world. Then, after processing forward them to the main destination. To be able to provide this service, there are many aspects of communication techniques that need to be explored. Supporting quality of service (QoS) will be of critical importance for pervasive WSNs that serve as the network infrastructure of diverse applications. To illustrate new research and development interests in this field, this paper examines and discusses the requirements, critical challenges, and open research issues on QoS management in WSNs. A brief overview of recent progress is given.

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Two main problems prevent the deployment of content delivery in a wireless sensor network: the address, which is widely used in the Internet as the identifier, is meaningless in wireless network, and the routing efficiency is a big concern in wireless sensor network. This paper presents an embedded multi-level ring (MVR) structure to address those two problems. The MVR uses names rather than addresses to identify sensor nodes. The MVR routes packets on the name identifiers without being aware the location. Some sensor nodes are selected as the backbone nodes and are placed on the different levels of the virtual rings. MVR hashes nodes and contents identifiers, and stores them at the backbone nodes. MVR takes the cross-level routing to improve the routing efficiency. Further, MVR is constructed decentralized and runs on the mobile nodes themselves, requiring no central control. Experiments using ns2 simulator for up to 200 nodes show that the storage and bandwidth requirements of MVR grow slowly with the size of the network. Furthermore, MVR has demonstrated as self-administrating, fault-tolerant, and resilient under the different workloads. We also discuss alternative implementation options, and future work.

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To build the service-oriented applications in a wireless sensor network (WSN), the workflow can be utilized to compose a set of atomic services and execute the corresponding pre-designed processes. In general, WSN applications rely closely on the sensor data which are usually inaccurate or even incomplete in the resource-constrained WSN. Then, the erroneous sensor data will affect the execution of atomic services and furthermore the workflows, which form an important part in the bottom-to-up dynamics of WSN applications. In order to alleviate this issue, it is necessary to manage the workflow hierarchically. However, the hierarchical workflow management remains an open and challenging problem. In this paper, by adopting the Bloom filter as an effective connection between the sensor node layer and the upper application layer, a hierarchical workflow management approach is proposed to ensure the QoS of workflow-based WSN application . The case study and experimental evaluations demonstrate the capability of the proposed approach.

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Wireless sensor networks (WSNs) are used in health monitoring, tracking and security applications. Such networks transfer data from specific areas to a nominated destination. In the network, each sensor node acts as a routing element for other sensor nodes during the transmission of data. This can increase energy consumption of the sensor node. In this paper, we propose a routing protocol for improving network lifetime and performance. The proposed protocol uses type-2 fuzzy logic to minimize the effects of uncertainty produced by the environmental noise. Simulation results show that the proposed protocol performs better than a recently developed routing protocol in terms of extending network lifetime and saving energy and also reducing data packet lost.

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As a significant milestone in the data dissemination of wireless sensor networks (WSNs), the comb-needle (CN) model was developed to dynamically balance the sensor data pushing and pulling during hybrid data dissemination. Unfortunately, the hybrid push-pull data dissemination strategy may overload some sensor nodes and form the hotspots that consume energy significantly. This usually leads to the collapse of the network at a very early stage. In the past decade, although many energy-aware dynamic data dissemination methods have been proposed to alleviate the hotspots issue, the block characteristic of sensor nodes has been overlooked and how to offload traffic from hot blocks with low energy through long-distance hybrid dissemination remains an open problem. In this paper, we developed a block-aware data dissemination model to balance the inter-block energy and eliminate the spreading of intra-block hotspots. Through the clustering mechanism based on geography and energy, "similar" large-scale sensor nodes can be efficiently grouped into specific blocks to form the global block information (GBI). Based on GBI, the long-distance block-cross hybrid algorithms are further developed by effectively aggregating inter-block and intra-block data disseminations. Extensive experimental results demonstrate the capability and the efficiency of the proposed approach. © 2014 Elsevier Ltd.

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Nowadays, there is an increasing interest in wireless sensor networks (WSN) for environmental monitoring systems because it can be used to improve the quality of life and living conditions are becoming a major concern to people. This paper describes the design and development of a real time monitoring system based on ZigBee WSN characterized by a lower energy consumption, low cost, reduced dimensions and fast adaptation to the network tree topology. The developed system encompasses an optimized sensing process about environmental parameters, low rate transmission from sensor nodes to the gateway, packet parsing and data storing in a remote database and real time visualization through a web server.

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Our society uses a large diversity of co-existing wired and wireless networks in order to satisfy its communication needs. A cooper- ation between these networks can benefit performance, service availabil- ity and deployment ease, and leads to the emergence of hybrid networks. This position paper focuses on a hybrid mobile-sensor network identify- ing potential advantages and challenges of its use and defining feasible applications. The main value of the paper, however, is in the proposed analysis approach to evaluate the performance at the mobile network side given the mixed mobile-sensor traffic. The approach combines packet- level analysis with modelling of flow-level behaviour and can be applied for the study of various application scenarios. In this paper we consider two applications with distinct traffic models namely multimedia traffic and best-effort traffic.

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With research on Wireless Sensor Networks (WSNs) becoming more and more mature in the past five years, researchers from universities all over the world have set up testbeds of wireless sensor networks, in most cases to test and evaluate the real-world behavior of developed WSN protocol mechanisms. Although these testbeds differ heavily in the employed sensor node types and the general architectural set up, they all have similar requirements with respect to management and scheduling functionalities: as every shared resource, a testbed requires a notion of users, resource reservation features, support for reprogramming and reconfiguration of the nodes, provisions to debug and remotely reset sensor nodes in case of node failures, as well as a solution for collecting and storing experimental data. The TARWIS management architecture presented in this paper targets at providing these functionalities independent from node type and node operating system. TARWIS has been designed as a re-usable management solution for research and/or educational oriented research testbeds of wireless sensor networks, relieving researchers intending to deploy a testbed from the burden to implement their own scheduling and testbed management solutions from scratch.

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A body sensor network solution for personal healthcare under an indoor environment is developed. The system is capable of logging the physiological signals of human beings, tracking the orientations of human body, and monitoring the environmental attributes, which covers all necessary information for the personal healthcare in an indoor environment. The major three chapters of this dissertation contain three subsystems in this work, each corresponding to one subsystem: BioLogger, PAMS and CosNet. Each chapter covers the background and motivation of the subsystem, the related theory, the hardware/software design, and the evaluation of the prototype’s performance.