Research on Wireless Sensor Actuator Distribution Algorithm Meeting Maximum Request Expectation

Coordination in wireless sensor–actuator networks: A survey

In a wireless sensor-actuator network (WSAN), sensor nodes deliver messages with sensed values to only nearby nodes due to weak radio. Messages are forwarded by sensor nodes to an actuator node by a routing protocol like a flooding protocol. In the redundant data transmission (RT) protocol, a sensor node sends a message with not only its sensed value but also sensed values received from other sensor nodes. Each message carries so many number of sensed values that the message loss ratio is not increased. Even if a message with a sensed value v is lost, an actuator node can receive the value v from a message sent by another sensor node. Thus, each sensed value is redundantly carried in multiple messages. The redundancy of a sensed value is in nature increased by broadcasting the value. In order to reduce the redundancy, we take a strategy that the farther sensor nodes from an actuator node forward the fewer number of sensed values. We evaluate the RT protocol in terms of loss ratio, redundancy, and delay time of sensed values. We show that about 80% of sensed values can be delivered to an actuator node even if 95% of messages are lost due to noise and collision.

An energy efficient and QoS aware routing protocol for wireless sensor and actuator networks

A new framework is proposed to cope with the uncertain time delay of networked control system. Event-clock-driven controller nodes, together with clock-driven sensor nodes and actuator nodes are required in this framework. Queuing Strategy is introduced both in controller nodes and actuator nodes while the time delay between controller node and actuator node is compensated by multi-step control increment given by the algorithm of General Predictive Control. An output error prediction model is built using BP neural network to deal with the time delay between sensor node and controller node. The principle of this model is to revise the predictive output of general predictive control model using predictive error signal; if the value of time delay exceeds the upper limit, controller nodes will immediately produce the control strategies adopting the revised predictive output, and thus the compensation for time delay between sensor nodes and controller nodes would be accomplished. Simulation experiments are practiced over Ethernet network which embraces both kinds of time delay. It is proved that the scheme of complete compensation remains a good control performance.

Wireless sensor/actuator networks (WSANs) are emerging as a new generation of sensor networks. Serving as the backbone of control applications, WSANs will enable an unprecedented degree of distributed and mobile control. However, the unreliability of wireless communications and the real-time requirements of control applications raise great challenges for WSAN design. With emphasis on the reliability issue, this paper presents an application-level design methodology for WSANs in mobile control applications. The solution is generic in that it is independent of the underlying platforms, environment, control system models, and controller design. To capture the link quality characteristics in terms of packet loss rate, experiments are conducted on a real WSAN system. From the experimental observations, a simple yet efficient method is proposed to deal with unpredictable packet loss on actuator nodes. Trace-based simulations give promising results, which demonstrate the effectiveness of the proposed approach.

A large number of potential applications for Wireless Sensor and Actuator Networks (WSAN) have yet to be embraced by industry despite high interest amongst academic researchers. This is due to various factors such as unpredictable costs related to development, deployment and maintenance of WSAN, especially when integration with existing IT infrastructure and legacy systems is needed. Service-Oriented Architecture (SOA) is seen as a promising technique to bridge the gap between sensor nodes and enterprise applications such as factory monitoring, control, and tracking systems where sensor data is used. To date, research efforts have focused on middleware software systems located in gateway devices that implement standard service technology, such as Devices Profile for Web Services (DPWS), for interacting with the sensor network. This paper takes a different approach-deploying interoperable Simple Object Access Protocol (SOAP)-based web services directly on the nodes and not using gateways. This strategy provides for easy integration with legacy IT systems and supports heterogeneity at the lowest level. Twofold analysis of the related overhead, which is the main challenge of this solution, is performed; Quantification of resource consumption as well as techniques to mitigate it are presented, along with latency measurements showing the impact of different parts of the system on system performance. A proof-of-concept application using Mulle-a resource-constrained sensor platform-is also presented.

In the Web of Things (WoT), special communication networks composed of sensor nodes, actuator nodes and service nodes form the basis for new types of web application systems, which are directly connected to the real world via sensors and actuators. We propose a conceptual framework for simulating WoT systems as multi-agent systems where both sensor nodes, actuator nodes and service nodes, as well as other systems in their environment interacting with them (such as other web applications, web services and human users), are modeled and simulated as agents. Our conceptual framework includes an ontology of WoT systems as sensor/actuator systems, and a meta-model for defining an agent-based WoT system simulation language.

T–S fuzzy-model-based piecewise [formula omitted] output feedback controller design for networked nonlinear systems with medium access constraint

In conventional sensor networks, information sensed by distributed sensor nodes is collected to a sink node, and applications are executed based on this information. However, when actuator nodes in a field execute the applications, the sink node does not have to collect all the sensing information, but each actuator node collects the information required for its application. We aim to collect the required information to each actuator node, and generate a group whose members are source sensor nodes involved by each actuator node. We propose a protocol to efficiently collect sensing information of grouped source nodes. Furthermore, we experimentally demonstrate that actuator nodes can collect the information and that the proposed protocol can decrease the number of packets transmitted in the network.

Intelligent building refers to a residence that is automated through a network of electronic devices which cooperate transparently to provide protection and comfort to the residents and minimize the energy consumption drastically. In this paper, a novel approach is made to design an intelligent building control solution using wireless sensor actuator networks (WSAN) in hardware domain. The intelligent building control solution provides automation to most household operations such as intrusion alarm, environment monitoring and controlling, asset tracking, etc. Real-time sensing is established with the help of sensor modules whereas real-time tracking is achieved with the deployment of active radio frequency identification (RFID) module. The WSAN greatly consists of gateway, routers, and end devices. The main controlling unit of WSAN is AVR microcontroller which manages the transceiver section and processes the received data accordingly. This paper focuses on remote monitoring and management system for a partly automated building equipped with sensors and actuators. Here, we also explore the prospects of wireless mesh networks and design a framework for developing an intelligent and smart environment.

Wireless sensor actuator network (WSAN) emerges as a potential technology with the capacities of self-organizing communication and feedback control. In this paper, we present a novel collaborative optimization algorithm of plant control and system cost toward WSANs taking time delay into account. First, the WSAN model is formulated as a linear system with multipath network structure. In order to provide effective control and reduce the usage of system resource, the quadratic cost function is introduced as the collaborative optimization problem in discrete-time domain. Then, a two-phase design is proposed to derive the design of optimal control for each given path in terms of a backward recursion. In addition, the best transmission path selection is obtained depending on minimal system power consumption. Finally, numerical simulations are utilized to show the effectiveness of the proposed algorithm in both traditional control system and load frequency control in the power grid application.

This paper presents the design and implementation of a wireless monitoring system for building smart room architectures in home environments. The proposed system consists of wireless sensor nodes and actuator nodes which are organized into a monitoring network by ZigBee protocols. A base station and some general wireless nodes have been developed to form a prototype system. Various sensor and actuator modules have also been implemented to enable some typical indoor monitoring applications such as resident tracking, energy-efficient home appliance control and home security. The proposed system provides a flexible solution for us to make our living spaces more intelligent.

Background: Metastasis to the axillary lymph nodes is a key indicator of prognosis in breast cancer. Lymph node ratio (LNR) is reported to be superior to the absolute number of nodes involved (pN stage) in classifying patients at high versus low risk of death following breast cancer. Aim of the study: This prospective study investigated the predictive value of the lymph node ratio (LNR) compared with the number of positive lymph nodes (pN), serum C-reactive protein (CRP) levels, hormones status and other prognostic factors in Syrian -breast cancer patients. Patients and methods: 60 breast cancer patients aged between 32 to 77 years old, admitted in National hospital of Jableh (Lattakia-Syria) were selected from December 2015 until December 2016. LNR calculated as the ratio of the number of positive nodes to the total number of nodes excised, LNR had been categorized as low: (0 -0.2), intermediate: (>0.2 - 0.65), and high risk: (>0.65 – 1). Blood samples were collected for CRP levels on admission and measured by immunoturbidimetric determination, levels >5mg/l were considered positive. Estrogen-Receptor (ER), Progesterone Receptor (PR) and human epidermal growth factor receptor 2 (Her-2) expression were assessed. Results: Strong relationship was found between LNR-classification system and increased number of positive lymph nodes in breast cancer patients (P 4 were at high risk (100%) in comparison with patients with pN=4, and this difference was statistically important (P 0.05). Mean level of CRP was 5.38 ±2.94mg/l at low LNR, 7.29±5.21mg/l at intermediate LNR and 7.68±4.55mg/l at high LNR, but the differences were not statically significant (P=0.27). Patients at high risk according to LNR-classification were positive for ER-receptor (n=4, 100%, P=0.248), PR-receptors(n=3, 75%, (P=0.028) and for Her-2 receptor (n=3, 75%, P=0.963). Conclusion: Patients with number of positive lymph nodes more than 4 lymph nodes were at high risk according to LNR-classification system in comparison with patients with 4 lymph nodes or less as a predictive number of lymph nodes. LNR- classification was more interesting than pNstaging in comparison with level of serum CRP, but similar to other classic risk factor such as Grade, Stage, tumor size and age. LNR-classification system was interesting in positive PR-receptor expression patients as an added value of LNR for predicting future response to hormone therapy.

In the Web of Things (WoT), special communication networks composed of sensor nodes, actuator nodes and service nodes form the basis for new types of web application systems, which are directly connected to the real world via sensors and actuators. The simulation of a WoT system allows evaluating different design options. It may require supporting "hardware in the loop", "software in the loop" and "humans in the loop". We propose several elements of a conceptual framework for simulating WoT systems at the application level, focusing on the simulation of three simple types of sensors. Our conceptual framework includes an ontology of WoT systems as sensor/actuator systems, and a meta-model for defining a WoT simulation language.

We propose and demonstrate a design methodology for embedded systems satisfying low power requirements suitable for self-powered sensor and actuator nodes. This design methodology focuses on 1. smart energy management at runtime and 2. application-specific System-On- Chip (SoC) design at design time, contributing to low-power systems on both algorithmic and technology level. Smart energy management is performed spatially at runtime by a behaviour-based or state-action-driven selection from a set of different (implemented) algorithms classified by their demand of computation power, and temporally by varying data processing rates. It can be shown that power/energy consumption of an application-specific SoC design depends strongly on computation complexity. Signal and control processing is modelled on abstract level using signal flow diagrams. These signal flow graphs are mapped to Petri Nets to enable direct high-level synthesis of digital SoC circuits using a multi-process architecture with the Communicating-Sequential-Process model on execution level. Power analysis using simulation techniques on gatelevel provides input for the algorithmic selection during runtime of the system, leading to a closed-loop design flow. Additionally, the signal-flow approach enables power management by varying the signal flow and data processing rates depending on actual energy consumption, estimated energy deposit, and required Quality-of-Service.