Towards offering more useful data reliably to mobile cloudfrom wireless sensor network

The integration of ubiquitous wireless sensor network (WSN) and powerful mobile cloud computing (MCC) is a research topic that is attracting growing interest in both academia and industry. In this new paradigm, WSN provides data to the cloud, and mobile users request data from the cloud. To support applications involving WSN-MCC integration, which need to reliably offer data that are more useful to the mobile users from WSN to cloud, this paper first identifies the critical issues that affect the usefulness of sensory data and the reliability of WSN, then proposes a novel WSN-MCC integration scheme named TPSS, which consists of two main parts: 1) TPSDT (Time and Priority based Selective Data Transmission) for WSN gateway to selectively transmit sensory data that are more useful to the cloud, considering the time and priority features of the data requested by the mobile user; 2) PSS (Priority-based Sleep Scheduling) algorithm for WSN to save energy consumption so that it can gather and transmit data in a more reliable way. Analytical and experimental results demonstrate the effectiveness of TPSS in improving usefulness of sensory data and reliability of WSN for WSN-MCC integration

Accurate angle-of-arrival measurement using particle swarm optimization

As one of the major methods for location positioning, angle-of-arrival (AOA) estimation is a significant technology in radar, sonar, radio astronomy, and mobile communications. AOA measurements can be exploited to locate mobile units, enhance communication efficiency and network capacity, and support location-aided routing, dynamic network management, and many location-based services. In this paper, we propose an algorithm for AOA estimation in colored noise fields and harsh application scenarios. By modeling the unknown noise covariance as a linear combination of known weighting matrices, a maximum likelihood (ML) criterion is established, and a particle swarm optimization (PSO) paradigm is designed to optimize the cost function. Simulation results demonstrate that the paired estimator PSO-ML significantly outperforms other popular techniques and produces superior AOA estimates

Inconsistency of the Wolf sunspot number series around 1848

Aims. Sunspot number is a benchmark series in many studies, but may still contain inhomogeneities and inconsistencies. In particular, an essential discrepancy exists between the two main sunspot number series, Wolf (WSN) and group (GSN) sunspot numbers, before 1848. The source of this discrepancy has so far remained unresolved. However, the recently digitized series of solar observations in 1825-1867 by Samuel Heinrich Schwabe, who was the primary observer of the WSN before 1848, makes such an assessment possible. Methods. We construct sunspot series, similar to WSN and GSN, but using only Schwabe's data. These series, called WSN-S and GSN-S, respectively, were compared with the original WSN and GSN series for the period 1835-1867 to look for possible inhomogeneities. Results. We show that: (1) The GSN series is homogeneous and consistent with the Schwabe data throughout the entire studied period; (2) The WSN series decreases by roughly ~20% around 1848 caused by the change of the primary observer from Schwabe to Wolf and an inappropriate individual correction factor used for Schwabe in the WSN; (3) This implies a major inhomogeneity in the WSN, which needs to be corrected by reducing its values by 20% before 1848; (4) The corrected WSN series is in good agreement with the GSN series. This study supports the earlier conclusions that the GSN series is more consistent and homogeneous in the earlier part than the WSN series.Comment: Published as: Leussu, R., I.G. Usoskin, R. Arlt and K. Mursula, Inconsistency of the Wolf sunspot number series around 1848, Astron. Astrophys., 559, A28, 201

Simulation Platform for Wireless Sensor Networks Based on Impulse Radio Ultra Wide Band

Impulse Radio Ultra Wide Band (IR-UWB) is a promising technology to address Wireless Sensor Network (WSN) constraints. However, existing network simulation tools do not provide a complete WSN simulation architecture, with the IR-UWB specificities at the PHYsical (PHY) and the Medium Access Control (MAC) layers. In this paper, we propose a WSN simulation architecture based on the IR-UWB technique. At the PHY layer, we take into account the pulse collision by dealing with the pulse propagation delay. We also modelled MAC protocols specific to IRUWB, for WSN applications. To completely fit the WSN simulation requirements, we propose a generic and reusable sensor and sensing channel model. Most of the WSN application performances can be evaluated thanks to the proposed simulation architecture. The proposed models are implemented on a scalable and well known network simulator: Global Mobile Information System Simulator (GloMoSim). However, they can be reused for all other packet based simulation platforms

Process-Based Design and Integration of Wireless Sensor Network Applications

Abstract Wireless Sensor and Actuator Networks (WSNs) are distributed sensor and actuator networks that monitor and control real-world phenomena, enabling the integration of the physical with the virtual world. They are used in domains like building automation, control systems, remote healthcare, etc., which are all highly process-driven. Today, tools and insights of Business Process Modeling (BPM) are not used to model WSN logic, as BPM focuses mostly on the coordination of people and IT systems and neglects the integration of embedded IT. WSN development still requires significant special-purpose, low-level, and manual coding of process logic. By exploiting similarities between WSN applications and business processes, this work aims to create a holistic system enabling the modeling and execution of executable processes that integrate, coordinate, and control WSNs. Concretely, we present a WSNspecific extension for Business Process Modeling Notation (BPMN) and a compiler that transforms the extended BPMN models into WSN-specific code to distribute process execution over both a WSN and a standard business process engine. The developed tool-chain allows modeling of an independent control loop for the WSN.

EMEEDP: Enhanced Multi-hop Energy Efficient Distributed Protocol for Heterogeneous Wireless Sensor Network

In WSN (Wireless Sensor Network) every sensor node sensed the data and transmit it to the CH (Cluster head) or BS (Base Station). Sensors are randomly deployed in unreachable areas, where battery replacement or battery charge is not possible. For this reason, Energy conservation is the important design goal while developing a routing and distributed protocol to increase the lifetime of WSN. In this paper, an enhanced energy efficient distributed protocol for heterogeneous WSN have been reported. EMEEDP is proposed for heterogeneous WSN to increase the lifetime of the network. An efficient algorithm is proposed in the form of flowchart and based on various clustering equation proved that the proposed work accomplishes longer lifetime with improved QOS parameters parallel to MEEP. A WSN implemented and tested using Raspberry Pi devices as a base station, temperature sensors as a node and xively.com as a cloud. Users use data for decision purpose or business purposes from xively.com using internet.Comment: 6 pages, 4 figures. arXiv admin note: substantial text overlap with arXiv:1409.1412 by other author