Wireless Sensor And Actor Networks Research Articles

An Intelligent Path Planning Mechanism for Firefighting in Wireless Sensor and Actor Networks

Forests have an important role in environmental preservation and maintenance. The primary threat is forest fires, which have disastrous repercussions. As a result, it is critical to identify and extinguish a fire before it spreads and destroys resources. To that end, we propose a forest fire detection and fighting mechanism using Wireless Sensor and Actor Networks (WSANs). Temperature sensors are utilized to detect fires, and actors (robots) are employed to extinguish them. Sensors and robots are distributed at random throughout the forest, forming clusters. Clustering, sleep/active scheduling for the sensors, and energy harvesting (EH)/moving modes for the robots, are used to extend and maximize the sensors/robots lifetime in the WSAN. In such a network, robots should move to the fire site as quickly as possible. To do this, we further propose a robot routing mechanism that focuses on determining the shortest path for each firefighting robot. In particular, each firefighting robot equipped with on-board processing uses a fuzzy Q-learning (FQL)-based trajectory mechanism to learn the shortest path to the fire zone in the least amount of time. Simulations are conducted to demonstrate the benefits of employing the proposed framework for a rapid and effective fire response. When compared to the traditional QL, the total approaching rate (a measure of how quickly the firefighting robots can reach the fire) to the fire spot is greater when utilizing the proposed FQL-based strategy.

Coordinated network partition detection and bi-connected inter-partition topology creation in damaged sensor networks using multiple UAVs

Reliable connectivity restoration mechanism is essential for retaining the prolonged network functioning of Wireless Sensor and Actor Networks (WSANs). WSANs operate in harsh or inhospitable environments and are susceptible to multiple node failures that may fragment the fully connected network into disparate fragments. The well-known network recovery techniques deploy new relay nodes for recovery and introduce more cut vertices in the network that generates the resulting network topology vulnerable to further partitioning. Therefore, it is advantageous to identify the network partitions in less time and establish a fault-tolerant topology during the network restoration. This paper provides a new coordinated network partition detection and Bi-connected Inter-partition Topology creation solution in damaged sensor networks using multiple UAVs (UAV-BITS) that operates in different phases. UAV-BITS employs multiple UAVs to identify the network partitions and engages network nodes to self-identify their partitions by creating Connected Component Sets (CCSs) iteratively. During the network recovery process, UAV-BITS creates two-vertex disjoint paths between the network partitions to make the recovered network topology fault-tolerant. UAV-BITS is assessed according to various parameters like the number of deployed relay nodes, the number of messages transmitted during detection and recovery phases, network partition detection and recovery time, and distance traveled by UAVs. The performance of CCS based partition detection mechanism is also compared with a similar UAVs-assisted partition detection approach. The working of existing bi-connected topology creation algorithms that employ representative nodes is also analyzed and compared with the proposed recovery algorithm. The simulation results illustrate that UAV-BITS provides a better fault-tolerant network topology than already proposed solutions. The algorithm also reduces the travel distance of UAVs and detection time.

Partition detection and recovery by UAVs in damaged WSANs using N‐angle clustering

SummaryConnectivity is essential in wireless sensor and actor networks (WSANs) deployed for data collection and monitoring applications. WSANs serving in inhospitable environments are prone to damage, and sometimes, the concurrent multiple node failures in the same area may cause network partitioning. The autonomous network recovery in harsh environments is challenging because the nodes in different partitions cannot determine the scope of the damage. This paper proposes an approach called partition detection and recovery by unmanned aerial vehicles (UAVs) in damaged WSANs using N‐angle clustering (N‐anglePDRU), which consists of all the phases required to accumulate information about the network partitions and reconnect them successfully. The algorithm is evaluated for different randomly generated network topologies according to various state‐of‐the‐art parameters such as detection and recovery time, messages transmitted, relay node count, and distance traveled by UAVs. The proposed approach is also compared with the existing algorithms, and the obtained results demonstrate that N‐anglePDRU recovers the partitioned network in less recovery time with minimum relay nodes and distance traveled.

Distributed Connectivity Restoration Algorithm with Optimal Repair Path in Wireless Sensor and Actor Networks

The actor nodes in wireless sensor and actor network (WSAN) are responsible for receiving the perceived data, processing and collaborating with each other. In most scenarios, maintaining the connectivity of the interactor network is necessary to plan the optimal coordinated response. However, actors are vulnerable to damage due to their limited energy and harsh environment. At worst, such failure can split the interactor network, which is affecting network performance. To restore the network connectivity, the existing methods replace the failed node by selecting a redundant node in the network. Multiple nodes may be involved in moving from the redundant node to the failed node, thus forming a repair path. However, the repair paths generated by such methods are often not optimal. In this paper, we use the gradient generation and diffusion mechanism to restore the connectivity of the interactor network and propose a gradient-based distributed connectivity recovery (GDCR) algorithm. GDCR selects an optimal repair path from the global network based on the generated gradient distribution under fully distributed and localized conditions. GDCR can timely respond to the repair and minimize the recovery range and movement overhead. Simulation results verify the performance of the proposed algorithm.

Distributed partition detection and recovery using UAV in wireless sensor and actor networks

Wireless Sensor and Actor Networks (WSANs) have been extensively employed in various domains ranging from elementary data collection to real-time control and monitoring for critical applications. Network connectivity is a vital robustness measure for overall network performance. Different network functions such as routing, scheduling, and QoS provisioning depends on network connectivity. The failure of articulation points in the network disassociates the network into disjoint segments. We proposed Distributed Partition Detection and Recovery using Unmanned Aerial Vehicle (UAV) (DPDRU) algorithm, as an optimal solution to recover the partitioned network. It consists of three steps: Initialization, Operational and Detection, and Recovery. In the Initialization phase sink node collects all the information about the network. In the Operational and Detection phase, network nodes communicate regularly by exchanging HEARTBEATS, detects failure if some nodes do not get a message from the neighbor node and send failure reports, and sink node identifies network partition. In the recovery phase, the sink node sends UAV at the positional coordinates of the failed node and examines network recovery after UAV reaches the desired location. Our approach primarily focuses on reducing message overhead by sending few update messages to sink node and energy consumption by engaging network nodes only for communication. The requirements of the recovery process (physical movement and communication) are fulfilled by UAV. The algorithm is tested according to the following parameters: Detection Time, Recovery Time, message overhead, and distance traveled by UAV. Simulation results validate the efficacy of the proposed algorithm based on these parameters to provide reliable results. The minimum and the maximum number of messages transmitted are 11 for 10 nodes and 24 for 100 nodes respectively. Hence these results demonstrate that the message overhead in our proposed solution is less as compared to other techniques when the number of nodes increases.

Efficient Solution for Connectivity Restoration (ESCR) in Wireless Sensor and Actor-Networks

Wireless Sensor and actor-network (WSAN) is the utmost significant research area in wireless communication technology. Actor nodes play a vital role during the processing and transmission of valuable data to the base station. WSAN performs its operations in a harsh environment and, therefore, prone to network failure. Moreover, an actor node’s failure causes the network into disjoint segments. Thus, the connectivity restoration of actor nodes is significant. This paper presents a novel technique, namely an efficient solution for connectivity restoration (ESCR), to detect the failure and ensure the connectivity among actor nodes. ESCR comprises two algorithms, i.e., assigning backup nodes and connectivity restoration process. The main objective of the proposed technique is to restore the network with efficient utilization of residual energy and minimum nodes movement. The effectiveness and performance of the ESCR technique are validated through extensive simulations and comparison with baseline approaches. The results show that the ESCR outperforms baseline approaches in terms of the number of nodes moved, total moved distance, reduction in the coverage area, and recovery time.

Computational intelligence-based connectivity restoration in wireless sensor and actor networks

Network failure is categorized into the two types of software and hardware (physical layer) failure. This paper focuses on the physical layer failure in the wireless sensor and actor networks (WSANs). Actors play an important role in data processing, decision-making, and performing appropriate reactions. Single or multiple nodes failure of actors due to the explosion, energy depletion, or harsh environments, can cause multiple disjoint partitions. This paper has proposed a new computational intelligence-based connectivity restoration (CICR) method. It uses a combination of advanced computational intelligence methods to solve restoration problem. The proposed algorithm applies the novel enhanced Lagrangian relaxation with a novel metaheuristic sequential improved grey wolf optimizer (SIGWO) search space algorithm in simultaneous selection of k sponsor and p pathway nodes. The reactive proposed method aims to reduce the travel distance or moving cost and communication cost. As a result, the restored network has minimum of topology change and energy consumption. In terms of total traveled distance, CICR has 37.19%, 71.47%, and 44.71% improvement in the single-node failure averagely in comparison with HCR, HCARE, and CMH, respectively. Also, it has an average of 61.54%, 40.1%, and 57.76% improvement in comparison with DCR, PRACAR, and RTN in multiple partitions resulted from multiple nodes failure, respectively. The reliability of CICR method has improved averagely by 35.85%, 38.46%, 22.03% over HCR, CMH, and HCARE in single-node failure. In multiple nodes failure, reliability of CICR has averagely 61.54% and 20% over DCR and PRACAR, respectively.

A fuzzy-based approach for event evaluation and actor selection in WSANs

Wireless Sensor and Actor Networks (WSANs) are capable to probe the environment through sensor nodes, detect events and than engage actors to take action. Management solutions focus on how to decide which actors will respond to events based on the collected data from the sensors. In this work, we evaluate and categorize events based on their hazardous levels, in order to select an appropriate actor per event. This paper presents two systems for evaluating events called Event Evaluation System (EES) and another one for selecting the actor called Actor Evaluation System (AES). Due to the problems being NP-Hard, we use fuzzy logic for both systems. The output parameter of EES is Event Hazardous Level (EHL), which assesses the event and for the AES is Actor Suitability (AS), which selects the actor based on the hazardous level of the event. From the simulation results, we can see that our systems can evaluate the event based on hazardous levels and have an immediate response from the actors.

Application of Fuzzy Logic for Selection of Actor Nodes in WSANs -Implementation of Two Fuzzy-Based Systems and a Testbed.

The development of sensor networks and the importance of smart devices in the physical world has brought attention to Wireless Sensor and Actor Networks (WSANs). They consist of a large number of static sensors and also a few other smart devices, such as different types of robots. Sensor nodes have responsibility for sensing and sending information towards an actor node any time there is an event that needs immediate intervention such as natural disasters or malicious attacks in the network. The actor node is responsible for processing and taking prompt action accordingly. But in order to select an appropriate actor to do one task, we need to consider different parameters, which make the problem NP-hard. For this reason, we consider Fuzzy Logic and propose two Fuzzy Based Simulation Systems (FBSS). FBSS1 has three input parameters such as Number of Sensors per Actor (NSA), Remaining Energy (RE) and Distance to Event (DE). On the other hand, FBSS2 has one new parameter—Transmission Range (TR)—and for this reason it is more complex. We will explain in detail the differences between these two systems. We also implement a testbed and compare simulation results with experimental results.

Delay-Aware MAC Protocol for Wireless Sensor and Actor Networks in Smart Grid

The conventional electric grid is converting in to the new emerging smart grid by utilizing information and communication technologies. The smart grid allows both the utilities and consumers to monitor and manage energy consumption effectively with the help of wireless sensor and actor networks (WSANs). WSANs have large number of low-power, low-cost, and multi-functional wireless sensor and actor nodes. The wireless sensor nodes collect the data from the physical condition of environment, while actor nodes perform different tasks according to the application requirements. For the monitoring and controlling of smart grid assets, WSANs can be considered as potential tools having the capability of low cost, high latency, and flexibility. In smart grid environment, WSANs have the problem of delay in channel access due to packet collisions. In this research work, we compare the performance results of various medium access control protocols in order to analyze which one among them is the best with respect to better throughput and minimum delay for WSANs in the smart grid environment.

A scalable and energy‐efficient MAC protocol for sensor and actor networks

SummaryA scalable energy‐efficient MAC protocol is proposed for wireless sensor and actor networks (WSAN) to improve the network performance. Actor's placement has computed using midpoint K‐mean technique. These actors perform as the cluster heads and collect the information from its members. Cluster head computes the shortest path to all of its cluster members. Further, it divides the cluster into multiple subtrees and assigns a noninterference channel to every subtree. A token is assigned to each subtree for intracluster communication. Token handling and token processing mechanisms are proposed to transfer token from one node to next eligible node. Finally, a throughput‐based channel selection mechanism has proposed for actor‐actor communication. The proposed protocol is simulated in NS2 and compared with its competitive MAC protocols. The results describe that the existing protocols are out beaten by the proposed mechanism.

Markov decision process and network coding for reliable data transmission in wireless sensor and actor networks

In delay sensitive applications of Wireless Sensor and Actor Networks (WSANs), achieving reliable data collection in the presence of a faulty region is a challenging issue. Sensed data may not be relayed to an actor due to fluctuations of wireless links in faulty regions. In this paper, a reliable data transmission mechanism using opportunistic encoding has been proposed for a WSAN with faulty nodes. A network coding approach has been designed by considering link loss rates and appropriate level of redundancy to achieve reliable data delivery. Further, a Markov Decision Process (MDP) has been proposed for opportunistic network coding decisions. The proposed mechanism determines the level of packet redundancy adaptively in the network coding process to improve reliable data collection and to reduce the number of data transmissions. Moreover, the state of a link changes with dynamic adverse environmental conditions, such as rainfall, fog and high temperature. The proposed mechanism analyzes the quality of link states and determines the applicability of network coding to improve the data transmission reliability and to reduce the number of data transmissions. Further, efficacy of the proposed mechanism has been shown through simulation results by considering number of data transmissions, average delivery delay, energy consumptions and network lifetime.

Distributed task allocation algorithm based on connected dominating set for WSANs

Proper allocation of tasks between actors is one of the critical issues for Wireless Sensor and Actor Networks (WSANs), which can improve the execution efficiency of the network, prolong the network life and so on. Traditional task allocation algorithms assume that the underlying network of the wireless systems are always connected, thus the only thing they should consider is how to improve the performance of task allocation. However, due to the movements of the actors, the assumption is hard to come into existence in WSANs. To solve this problem, we proposed a task allocation algorithm named MIA-TA in this paper. This approach consists of two stages. We apply the improved connected dominating set (CDS) formation algorithm MIA to construct the backbone of the network firstly. Tasks are assigned on the basic of CDS in the second stage. By considering the network conditions of executor’s leave and arrive positions, we can ensure the entire network’s connectivity. Simulation results confirm that MIA-TA algorithm can be used to solve both task allocation and connectivity maintenance problems with reasonable movements and messages generated in the whole process.

Fault Tolerance Model for Efficient Actor Recovery Paradigm in WSAN

Wireless sensor and actor networks (WSAN) is an area where sensors and actors collaborate to sense, handle and perform tasks in real-time. Thus, reliability is an important factor. Due to the natural of WSAN, actor nodes are open to failure. Failure of actor nodes degrades the network performance and may lead to network disjoint. Thus, fault tolerance techniques should be applied to insure the efficiency of the network. In an earlier work, the authors proposed an efficient actor recovery paradigm (EAR) for WSAN which handles the critical actor node failure and recovery while maintaining QoS. EAR is supported with node monitoring and critical node detection (NMCND), network integration and message forwarding (NIMF), priority-based routing for node failure avoidance (PRNFA) and backup selection algorithms. In this article, the authors extend the work by adding a fault tolerance mathematical model. By evaluating the model, EAR shows to manage fault tolerance in deferent levels. To evaluate the effectiveness, the EAR fault tolerance is evaluated by simulation using OMNET++ Simulation. In addition, EAR reliability is measured and compared with RNF, DPCRA, ACR, and ACRA.

Performance analysis of wireless sensor networks and priority queueing systems

Recently, wireless sensor and actor networks (WSANs) technology has been also applied for monitoring critical infrastructure protection (CIP). These new applications make more demanding requirements of WSANs and therefore it is necessary to develop algorithms that can manage the communications and route the information from each sensor node to the sink nodes while providing quality-of-service (QoS) requirements. In order to assess the current state of WSANs in terms of performance and QoS support, this article empirically studies the performance of a network with different workloads in terms of reliability, delay and queue occupation with common network topologies. The results reveal the intrinsic lack of reliability and low throughput that this technology currently exhibits, the importance of matching network level capabilities to data link layer capabilities and different behaviour of a PQS in terms of reliability and delay depending on the congestion of the network.

Open Issues and Security Challenges of Data Communication Channels in Distributed Internet of Things (IoT): A Survey

The concept of the Internet of Things (IoT) has evolved over time. The introduction of the Internet of Things and Services into the manufacturing environment has ushered in a fourth industrial revolution: Industry 4.0. It is no doubt that the world is undergoing constant transformations that somehow change the trajectory and history of humanity. We can illustrate this with the first and second industrial revolutions and the information revolution. IoT is a paradigm based on the internet that comprises many interconnected technologies like RFID (Radio Frequency Identification) and WSAN (Wireless Sensor and Actor Networks) to exchange information. The current needs for better control, monitoring and management in many areas, and the ongoing research in this field, have originated the appearance and creation of multiple systems like smart-home, smart-city and smart-grid. The IoT services can have centralized or distributed architecture. The centralized approach provides is where central entities acquire, process, and provide information while the distributed architectures, is where entities at the edge of the network exchange information and collaborate with each other in a dynamic way. To understand the two approaches, it is necessary to know its advantages and disadvantages especially in terms of security and privacy issues. This paper shows that the distributed approach has various challenges that need to be solved. But also, various interesting properties and strengths. In this paper we present the main research challenges and the existing solutions in the field of IoT security, identifying open issues, the industrial revolution and suggesting some hints for future research.

Implementation and performance evaluation of an intelligent fuzzy-based testbed for WSANs: a case study for object tracking

Wireless sensor and actor networks (WSANs) have emerged as a variation of wireless sensor networks. WSANs are capable of monitoring physical phenomenons, processing sensed data, making decisions based on the sensed data and completing appropriate tasks when needed. In this paper, we propose an intelligent fuzzy-based testbed that based on data provided by sensors and actors selects an appropriate actor node. From the evaluation results, the system selects the actors in order to have low latency and proper task assignment considering multi actors for different job types.

Connectivity Resotration Techniques for Wireless Sensor and Actor Network (WSAN), A Review

Wireless Sensor and actor networks (WSANs) are the most promising research area in the field of wireless communication. It consists of large number of small independent sensor and powerful actor nodes equipped with communication and computation capabilities. Actors gather sensor’s data and react collaboratively to attain application particular assignments. A powerful connected inter-actor network is required to coordinate its operations. Actor node may fail due to the battery depletion or any hardware failure and this failure may divide the network into disjoint segments. This problem can degrade the network performance but also reduce the efficiency and effectiveness of the network. To restore the network into its original state, the researchers have proposed many connectivity restoration techniques during last few years. This paper provides a brief review of the existing connectivity restoration techniques for WSANs with their advantages and limitations.

Implementation and performance evaluation of an intelligent fuzzy-based testbed for WSANs: a case study for object tracking

Wireless sensor and actor networks (WSANs) have emerged as a variation of wireless sensor networks. WSANs are capable of monitoring physical phenomenons, processing sensed data, making decisions based on the sensed data and completing appropriate tasks when needed. In this paper, we propose an intelligent fuzzy-based testbed that based on data provided by sensors and actors selects an appropriate actor node. From the evaluation results, the system selects the actors in order to have low latency and proper task assignment considering multi actors for different job types.

Adaptive buffering using Markov Decision Process in tree-based Wireless Sensor and Actor Networks

In a tree-based Wireless Sensor and Actor Network (WSAN), data acquisition can be done through a mobile actor to reduce the traffic congestion. However, packet dropping at the resource-limited (such as, buffer space and energy) intermediate nodes leads to poor data delivery and energy efficiency. In this paper, a Markov Decision Process (MDP) based buffer management mechanism has been proposed in tree-based WSAN to reduce the data delivery delay and to improve the energy efficiency. A mathematical model for a mobile actor has been presented to analyze buffer occupancy and energy consumption with real-time traffic. The state of a node is represented based on buffer levels which may change with dynamic traffic. The buffer states are analyzed at which packets will be dropped to minimize the average delivery delay and energy consumption. Extensive simulations have been performed to show the efficacy of proposed mechanism in terms of average end-to-end delay and energy consumption.