Cooperation Mechanism Taxonomy for Wireless Sensor and Actor Networks

Ruiz-Ibarra, Erica; Villaseñor-González, Luis

doi:10.1007/978-0-387-09441-0_6

Cited by 8 publications

(8 citation statements)

References 18 publications

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“…Maximum distance is important to avoid misleading conclusions from solely average distance measurements caused in cases where a few maximum measurements exist, with emphatic deviation from the average distance, thus comprising potentially important bottlenecks (iii) Deviation in average distance: the deviation of each selection technique from the reference technique ("None") is calculated for all the Voronoi types (Euclidean, AWV, and MWV). The deviation of the average distance is extracted according to (6). It shows the average percentile difference (error) of the Voronoi splitting algorithm following a selection technique from the native consideration ("None").…”

Section: Simulation Frameworkmentioning

confidence: 99%

“…Therefore, this kind of hybrid network (also denoted as cyber physical system [5]) extends typical WSNs goals of environment observation, event data processing, and decision-making by aiming at performing appropriate actions interacting with the environment [6]. In this context, the collaborative operation of sensors enables the distributed sensing of a physical phenomenon.…”

Section: Introductionmentioning

confidence: 99%

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Resource Aware Sensor-to-Actor Allocation Framework for WSANs Based on Voronoi Cells Theory

2017

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Wireless sensor and actor networks (WSANs) have emerged as a promising research field and have been applied in a wide variety of application domains due to their capability of environment monitoring, event data processing, and decision-making by aiming at performing appropriate actions interacting with the environment. Coordination mechanisms among nodes and actors are a critical research challenge pertaining to the optimum allocation of sensors to a particular actor. Although efforts related to the node-to-actor coordination problem have been presented in the current literature, there is a significant oversight regarding critical characteristics such as the heterogeneous capabilities of the actors as well as the network's heterogeneous density. In this paper, aiming to address such shortcomings, we introduce the term Actor Service Capacity, which indicates the ability of an actor to serve a particular number of nodes. We also propose a novel node-to-actor coordination algorithm, based on the Voronoi tessellation, aiming to guarantee that the number of nodes, allocated to each actor, will not exceed its capabilities. Furthermore, a set of selection techniques are proposed so as to be applied on the coordination framework. Respective evaluation analysis offers useful conclusions and highlights the importance and the advantages of the proposed algorithm.

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Section: Simulation Frameworkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Resource Aware Sensor-to-Actor Allocation Framework for WSANs Based on Voronoi Cells Theory

2017

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“…Unlike wireless sensors networks (WSNs), where a single base-station is responsible for the network operation and management, in WSANs sensor-sensor, sensor-actuator, and actuator-actuator coordination is required to achieve the overall application objective [2]. In particular, the sensoractuator coordination ensures the transmission of data reports from sensors that detect an event to an actor(s).…”

Section: Introductionmentioning

confidence: 99%

Effective handling of spreading events using wireless sensor and actuator networks

Lalouani¹,

Younis

Bagaa

et al. 2014

2014 International Wireless Communications and Mobile Computing Conference (IWCMC)

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Wireless sensors and actors networks (WSANs) have the capacity for not only monitoring some phenomena through sensor nodes but also performing appropriate actions. Most of the contemporary WSAN management solutions focus on defining communication path among sensors and actors and on tasking appropriate actors to handle the detected events. In this paper we classify events based on how they evolve over time into continuous and discrete and categorize the WSAN management strategies accordingly. Unlike discrete events, a continuous event spreads quickly and becomes more serious as time passes. Such a characteristic introduces more challenges and motivates a nonconventional management strategies. This paper presents an approach for Sensor-Actuator Coordination for Handling Spreading events (SACHS). SACHS opts to enable the network to respond quickly in order to avoid the event from growing in scope, e.g., prevent a fire from spreading, while reducing the energy overhead due to the coordination messages and due to actor's relocation to the event region. SACHS limits sensor-actor and actor-actor interactions and exploits local sensor-sensor communication to determine the scope of the event, define spots for actors to position at, and schedule the actors' response. The simulation results confirm the performance advantage of SACHS compared to competing schemes.

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“…WSANs can be applied in many areas, such as fire detection in forest, home automation and precision agriculture (Stankovic, 2008). Due to the coexistence of sensors and actuators, coordination is demanded at different levels of WSANs, which can be categorized into Sensor-Sensor (S-S), Sensor-Actuator (S-A) and Actuator-Actuator (A-A) coordinations (Ruiz-Ibarra and Villasenor-Gonzalez, 2008). Extensive studies have been carried out to address the S-S coordination in collaborative sensing, cooperative transmission, sensor scheduling, etc., in the context of wireless sensor networks (WSNs) (Akyildiz et al, 2002;Yuan et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Collaborative Estimation and Actuation for Wireless Sensor and Actuator Networks

Cao

Chen

et al. 2014

IFAC Proceedings Volumes

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Wireless sensor and actuator networks (WSANs) facilitate close interactions between human and the environment. Efficient coordination among the sensors and actuators plays a vital role in carrying out sensing and acting in WSANs. In this paper, we develop a collaborative estimation and actuation mechanism, which consists of a sensor-actuator coordination phase and an actuator-actuator coordination phase. The first phase is based on distributed Kalman filter in federated configuration, which is able to provide reliable and precise sensing data. On this basis, the second phase allocates proper tasks based on system requirements and coordinates actuators to accomplish the tasks. Particularly, the actuator-actuator coordination is formulated as an optimization problem and an effective method is proposed to search the solution based on sequential unconstrained minimization technique. Simulation results demonstrate the effectiveness of our proposed mechanism.

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Cooperation Mechanism Taxonomy for Wireless Sensor and Actor Networks

Cited by 8 publications

References 18 publications

Resource Aware Sensor-to-Actor Allocation Framework for WSANs Based on Voronoi Cells Theory

Resource Aware Sensor-to-Actor Allocation Framework for WSANs Based on Voronoi Cells Theory

Effective handling of spreading events using wireless sensor and actuator networks

Collaborative Estimation and Actuation for Wireless Sensor and Actuator Networks

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