Wireless Sensor And Actor Networks Research Articles

A preferential attachment model for primate social networks

Wildlife monitoring is an enormous organizational challenge due to the required time and effort for setting and maintaining it. It is particularly difficult when the observed species has a complex social hierarchy and different roles for the members in the social group.In this paper, we introduce an approach to model a primate social network. The primates have complex social behaviors and network structure. As a result, there is a need for realistic computational models to fully understand and analyze the social behavior of such animal groups. We propose a novel spatial cut-off preferential attachment model with a center of mass concept to model the characteristics of the primate groups and a role determination algorithm, which groups the primates into their roles in the society based on the data collected by the wireless sensor and actor networks (WSAN). The performance of the monitoring and role determination algorithms, the applicability of the network formation and the mobility models are evaluated through extensive simulations. The results show that the proposed primate group models deliver networks with properties similar to real-life primate groups in terms of social network characteristics.

A Self-Healing Connectivity Recovery Algorithm in Wireless Sensor-Actor Networks

Wireless sensor and actor networks (WSANs) additionally employ actor nodes within the wireless sensor network (WSN) which can process the sensed data and perform certain actions based on this collected data. In most applications, inter-actor coordination is required to provide the best response. One actor failure may lead to partitioning the inter-actor networks, tolerating the actor failure and restoring the lost connectivity need to be performed while imposing the least overhead on the individual actors autonomously. In this paper, we present a Self-healing Connectivity Recovery Algorithm (SCRA) which is to recover the failure actor. SCRA proactively identifies actors whether is a cut vertex or not to the network connectivity based on the depth-first search algorithm (DFS), and designates a minimal CDS backup nodes. If an actor node suddenly fails, the minimal block backup nodes move and initiate a recovery process until the network is reconnected. Through simulated experiments, the results show that the algorithm is more effective than present algorithms in terms of total travel distance, and total number of messages.

Priority- and Delay-Aware Medium Access for Wireless Sensor Networks in the Smart Grid

Monitoring smart-grid assets in a timely manner is highly desired for emerging smart-grid applications such as transformer monitoring, capacitor bank control, plug-in hybrid-electric-vehicle load management, and power quality assessment. Wireless sensor and actor networks (WSANs) are anticipated to be widely utilized in a wide range of smart-grid applications due to their numerous advantages along with their successful adoption in various critical areas including military and health. For resource-constrained WSANs, transmitting delay-critical data from smart-grid assets calls for data prioritization and delay responsiveness. In this paper, we introduce two medium-access approaches, namely, delay-responsive cross-layer (DRX) data transmission and fair and delay-aware cross-layer (FDRX) data transmission, which aim to address the delay and service requirements of smart grids. DRX is based on delay-estimation and data-prioritization steps that are performed by the application layer, in addition to the MAC layer parameters responding to the delay requirements of the smart-grid application and the network condition. On the other hand, FDRX incorporates fairness into DRX by preventing a few nodes from dominating the communication channel. We provide a comprehensive performance evaluation of those approaches. We show that DRX reduces the end-to-end delay while FDRX has lower collision rate compared with DRX. We outline the tradeoffs regarding these approaches and draw future research directions for robust communication protocols for smart-grid monitoring applications.

Cooperative Localization Algorithm based on Coverage Optimization of Actors for Wireless Sensor and Actor Networks

Different from existing range-free algorithms in wireless sensor networks (WSN), a cooperative localization algorithm based on coverage optimization of actors (CLCOA) for wireless sensor and actor networks (WSAN) is proposed. It uses mobile actors instead of anchors in WSN. Firstly, the area of the unknown node is determined through the movement of positioning actors. Then this area decreases through iteration. When localization accuracy is satisfied, the centroid of this area is calculated and treated as the coordinate of the unknown node. Free actors adjust their positions through virtual force while locating actors work. Accordingly, actors’ coverage is optimized. Via simulation, it is proven that CLCOA has high locating accuracy with RSSI error and GPS error, and the introduction of virtual force improves actors’ coverage and locating speed

Optimal Placement of Actors in WSANs Based on Imposed Delay Constraints

Wireless Sensor and Actor Networks (WSANs) refer to a group of sensors and actors linked by wireless medium to probe environment and perform specific actions. Such certain actions should always be taken before a deadline when an event of interest is detected. In order to provide such services, the whole monitor area is divided into several virtual areas and nodes in the same area form a cluster. Clustering of the WSANs is often pursued to give that each actor acts as a cluster-head. The number of actors is related to the size and the deployment of WSANs cluster. In this paper, we find a method to determine the accurate number of actors which enables them to receive data and take actions in an imposed time-delay. Thek-MinTE and thek-MaxTE clustering algorithm are proposed to form the minimum and maximum size of cluster, respectively. In those clustering algorithms, actors are deployed in such a way that sensors could route data to actors withinkhops. Then, clusters are arranged by the regular hexagon. At last, we evaluate the placement of actors and results show that our approach is effective.

STARR-DCS

This article presents a novel framework for data-centric storage (DCS) in a wireless sensor and actor network (WSAN) that employs a randomly selected set of data replication nodes, which also change over time. This enables reductions in the average network traffic and energy consumption by adapting the number of replicas to applications' traffic, while balancing energy burdens by varying their locations. To that end, we propose and validate a simple model to determine the optimal number of replicas, in terms of minimizing average traffic/energy consumption, based on measurements of applications' production and consumption traffic. Simple mechanisms are proposed to decide when the current set of replication nodes should be changed, to enable new applications and nodes to efficiently bootstrap into a working WSAN, to recover from failing nodes, and to adapt to changing conditions. Extensive simulations demonstrate that our approach can extend a WSAN's lifetime by at least 60%, and up to a factor of 10× depending on the lifetime criterion being considered. The feasibility of the proposed framework has been validated in a prototype with 20 resource-constrained motes, and the results obtained via simulation for large WSANs have been also corroborated in that prototype.

RENDEZVOUS: towards fast event detecting in wireless sensor and actor networks

Fast event detection is important in wireless sensor and actor networks (WSANs) since actors can perform appropriate actions which sensor nodes are not capable to do. While WSANs inherits the typical constrains of WSNs such as energy and computation limitations of sensor nodes. In this paper, we propose a fast event detecting algorithm named RENDEZVOUS to accelerate the actor's event detecting process while keep the energy consumption of sensor nodes as minimum. When design RENDEZVOUS, we first study the mobility control of a actor to help the actor move around close to a event by using Reinforcement Learning techniques with collected sensory data. We then design a scheme to search nearby actors from the event side inspired by a searching behavior of desert ants. By both perform search actions from sensor side and actor side, the proposed algorithm can achieve fast event detecting with neglect-able additional energy cost on sensors side. Extensive simulation results demonstrate the efficiency of RENDEZVOUS.

EMD: Energy-Efficient P2P Message Dissemination in Delay-Tolerant Wireless Sensor and Actor Networks

In this paper, we address the problem of peer-to-peer networking for data dissemination among actors in wireless sensor and actor networks (WSANs), which consist of static sensors, responsible for environment monitoring, and mobile actors, in charge of data collection and task performing. This problem has not been received much attention although peer-to-peer networking has achieved great successes in other networks such as the Internet and mobile ad hoc networks (MANETs). Unlike the Internet and MANETs, WSANs contain static sensors that are energy-constrained and actors that cannot communicate with each other directly. These unique characteristics make the data dissemination problem in WSANs extremely challenging. We present an Energy-Efficient Message Dissemination protocol (EMD) to solve this problem in delay-tolerant WSANs. EMD is grounded on a novel principle of Carry-Disseminate-Store-and-Forward proposed for the first time here. While traveling, a source actor disseminates messages (data) to sensors upon contact, which will store the messages and forward them to other actors when they come into communication range. The actors receiving the messages from sensors work as source actors and help to distribute the messages. We theoretically analyze the data dissemination strategy under which the original source actor can distribute its messages to all other actors at minimum communication cost within a given delay bound. Through extensive simulations we demonstrate the performance of EMD.

Lightweight routing with dynamic interests in wireless sensor and actor networks

Wireless sensor and actor networks (WSANs) have been increasingly popular for environmental monitoring applications in the last decade. While the deployment of sensor nodes enables a fine granularity of data collection, resource-rich actor nodes provide further evaluation of the information and reaction. Quality of service (QoS) and routing solutions for WSANs are challenging compared to traditional networks because of the limited node resources. WSANs also have different QoS requirements than wireless sensor networks (WSNs) since actors and sensor nodes have distinct resource constraints.In this paper, we present, LRP-QS, a lightweight routing protocol with dynamic interests and QoS support for WSANs. LRP-QS provides QoS by differentiating the rates among different types of interests with dynamic packet tagging at sensor nodes and per flow management at actor nodes. The interests, which define the types of events to observe, are distributed in the network. The weights of the interests are determined dynamically by using a nonsensitive ranking algorithm depending on the variation in the observed values of data collected in response to interests. Our simulation studies show that the proposed protocol provides a higher packet delivery ratio and a lower memory consumption than the existing state of the art protocols.

A cooperative pursuit-evasion game in wireless sensor and actor networks

This paper studies the problem of the pursuit-evasion game under the wireless sensor and actor networks (WSANs). In order to plan paths for pursuers to capture an evader in the pursuit-evasion game, a novel multi-step cooperative strategy is presented. Under this strategy, the pursuit-evasion game is studied in two stages. In the first stage we assume that the evader is always static in the workplace, and in the second stage the evader will move once it senses the existence of pursuers. A Daisy-Chain Formation algorithm and a sliding mode-based method are presented to control the pursuit. Based on Lyapunov stability theory, the proposed algorithm is proved to be convergent. At last, simulation results are provided to demonstrate the effectiveness of the proposed method.

2013 Association for Radiologic & Imaging Nursing Convention

Wireless sensor and actor networks (WSANs) have been increasingly popular for environmental monitoring applications in the last decade. While the deployment of sensor nodes enables a fine granularity of data collection, resource-rich actor nodes provide further evaluation of the information and reaction. Quality of service (QoS) and routing solutions for WSANs are challenging compared to traditional networks because of the limited node resources. WSANs also have different QoS requirements than wireless sensor networks (WSNs) since actors and sensor nodes have distinct resource constraints.In this paper, we present, LRP-QS, a lightweight routing protocol with dynamic interests and QoS support for WSANs. LRP-QS provides QoS by differentiating the rates among different types of interests with dynamic packet tagging at sensor nodes and per flow management at actor nodes. The interests, which define the types of events to observe, are distributed in the network. The weights of the interests are determined dynamically by using a nonsensitive ranking algorithm depending on the variation in the observed values of data collected in response to interests. Our simulation studies show that the proposed protocol provides a higher packet delivery ratio and a lower memory consumption than the existing state of the art protocols.

Enhancing real-time performance via controlled actor relocation in wireless sensor and actor networks

Actors’relocation is utilized during the network initialization to enhance real-time performance of wireless sensor and actor networks(WSANs)which is an important issue of WSANs.The actor deployment problem in WSANs is proved NP-Hard whether the amount of actors is redundant or not,but to the best of our knowledge,no effective distributed algorithms in previous research can solve the problem.Thus two actor deployment strategies which need not the boundary control compared with present deployment strategies are proposed to solve this problem approximately based on the Voronoi diagram.Through simulation experiment,the results show that our distributed strategies are more effective than the present deployment strategies in terms of real-time performance,convergence time and energy consumption.

Network Partitioning Recovery Mechanisms in WSANs: a Survey

Wireless sensor and actor networks (WSANs) are more promising and most addressing research field in the area of wireless sensor networks in recent scenario. It composed of possibly a large number of tiny, autonomous sensor devices and resources rich actor nodes equipped with wireless communication and computation capabilities. Actors collect sensors' information and respond collaboratively to achieve an application specific mission. Since actors have to coordinate their operation, a strongly connected inter-actor network would be required at all the time in the network. Actor nodes may fail for many reasons (i.e. due of battery exhaustion or hardware failure due to hash environment etc.) and failures may convert connected network into disjoint networks. This can hinder sometimes not only the performance of network but also degrade the usefulness and effectiveness of the network. Thus, having a partitioning detection and connectivity restoration procedure at the time of failure occurs in the network is crucial for WSANs. In this paper, we review the present network partitioning recovery approaches and provide an overall view of this study by summarizing previous achievements.

Fire Monitoring and Extinguishing Algorithm Using Wireless Sensor and Actor Networks

Buildings may be subjected to natural hazards such as earthquakes, winds and fires during their long -term use. Fire is a very common hazard and could be monitored and prevented using Wireless sensor and actor networks (WSANs). WSANs refer to a group of sen sors and actors linked by wireless medium to perform distributed sensing and actuation tasks. In such a network, sensors gather information about the physical world, while actors take decisions and then perform appropriate actions upon the environment, w hich allows remote, automated interaction with the environment. In this paper , routing algorithm for fire monitoring and extinguishing(FMEA) is proposed that makes use of thethreshold sensing for monitoring and extinguishing fire. Initially when fire is detected sensors raise alarms so that lives could be saved with no waste in time .Once the temperature exceeds a certain threshold then extinguishing takes place. The sensing environment consists of many Monitoring Nodes that sense fire and report the data to the Cluster Head. The Cluster Head directs the Actors to extinguish the fire before sending the data to the Base Station.

Application-Oriented Fault Detection and Recovery Algorithm for Wireless Sensor and Actor Networks

Recent years have witnessed a growing interest in applications of wireless sensor and actor networks (WSANs). In WSANs, maintaining interactor connectivity is of vital concern in order to reach application level. Failure of a critical actor may partition the inter-actor network into disjoint segments. This paper proposed an application-oriented fault detection and recovery algorithm (AFDR), a novel distributed algorithm to reestablish connectivity. AFDR identifies critical actors and designates backups for them. A backup actor detects the critical node failure and initiates a recovery process via moving to the optimal position. The purpose of AFDR is to satisfy application requirements, reduce recovery overhead, and limit the impact of critical node failure on coverage and connectivity to the utmost. The effectiveness of AFDR is validated through simulation experiments.

Formal Specification and Validation of a Hybrid Connectivity Restoration Algorithm for Wireless Sensor and Actor Networks

Maintaining inter-actor connectivity is extremely crucial in mission-critical applications of Wireless Sensor and Actor Networks (WSANs), as actors have to quickly plan optimal coordinated responses to detected events. Failure of a critical actor partitions the inter-actor network into disjoint segments besides leaving a coverage hole, and thus hinders the network operation. This paper presents a Partitioning detection and Connectivity Restoration (PCR) algorithm to tolerate critical actor failure. As part of pre-failure planning, PCR determines critical/non-critical actors based on localized information and designates each critical node with an appropriate backup (preferably non-critical). The pre-designated backup detects the failure of its primary actor and initiates a post-failure recovery process that may involve coordinated multi-actor relocation. To prove the correctness, we construct a formal specification of PCR using Z notation. We model WSAN topology as a dynamic graph and transform PCR to corresponding formal specification using Z notation. Formal specification is analyzed and validated using the Z Eves tool. Moreover, we simulate the specification to quantitatively analyze the efficiency of PCR. Simulation results confirm the effectiveness of PCR and the results shown that it outperforms contemporary schemes found in the literature.

Bio-Inspired Cross-Layer Communication and Coordination in Sensor and Vehicular Actor Networks

In this paper, based on the prey model in foraging theory, the BIO-inspired Cross-layer (BIOX) communication and coordination protocol is introduced for wireless sensor and actor networks (WSANs). BIOX permits each sensor node to autonomously determine its next-hop selection and channel access strategy using bio-inspired next-hop selection and channel access profitability measures. Based on these profitability measures, BIOX provides optimal performance in energy-efficient and reliable sensor-actor communication. Furthermore, using task allocation profitability measure, BIOX also guarantees stable allocation of available tasks in a way that each task is accomplished by an actor node within a bounded time delay. Performance evaluations reveal that BIOX significantly prolongs the network lifetime while providing highly reliable sensor-actor communication and effective task allocation for actor nodes.

NeuralSens: A neural network based framework to allow dynamic adaptation in wireless sensor and actor networks

Wireless Sensor and Actor Networks (WSANs) constitute a new way of distributed computing and are steadily gaining importance due to the wide variety of applications that can be implemented with them. As a result they are increasingly present everywhere (industry, farm use, buildings, etc.). However, there are still many important areas in which the WSANs can be improved. One of the most important aspects is to give the sensor networks the capability of being wirelessly reprogrammed so that developers do not have to physically interact with the sensor nodes. Many proposals that deal with this issue have been proposed, but most of them are hardly dependent on the operating system and demand a high energy consumption, even if only a small change has been made in the code. In this work, we propose a new way of wirelessly reprogramming based on the concept of neural networks. Unlike most of the existing approaches, our proposal is independent of the operating system and allows small pieces of code to be reprogrammed with a low energy consumption. The architecture developed to achieve that is described and case studies are presented that show the use of our proposal by means of practical examples.

ORACLE: Mobility control in wireless sensor and actor networks

Mobile actor is a promising tool for wireless sensor and actor networks (WSANs) provisioning energy and time efficient data collection. In this paper, we study actors’ mobility control in WSANs for efficient events detecting in terms of time and energy consumption. We introduce an innovative approach ORACLE, to make actors predict events before sensors detection and migrate to the areas where the event may occur. In specific, we propose an event prediction scheme to predict an event from collected sensory data by utilizing the maximum likelihood estimation. Based on the perception, we design a control policy of actor’s mobility pattern with Markov decision process. ORACLE not only enables minimal motion of actors which conserves time and energy to reach the event areas but also is energy-efficiency for sensors to reduce the forwarding range for event detection message. We evaluate the effectiveness of our proposed scheme through extensive experimental analysis.

Modelling data-aggregation in multi-replication data centric storage systems for wireless sensor and actor networks

This paper studies data-centric storage (DCS) as a suitable system to perform data aggregation on wireless sensor and actor networks (WSANs), in which sensor and actor nodes collaborate together in a fully distributed way without any central base station that manages the network or provides connectivity to the outside world. The authors compare different multi-replication DCS proposals and choose the best one to be applied when studying data aggregation. In addition, the authors provide mathematical models for the production, consumption and overall network traffic for different application profiles. Those application profiles are based on the ability of a particular application to perform data aggregation and on what type of traffic is dominant, either the consumption or the production one. Furthermore, the authors provide closed formulas for each application profile that defines the optimal number of replicas that minimise the overall network traffic. Finally, the authors validate the proposed models via simulation.