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

2012 ◽  
Vol 8 (10) ◽  
pp. 273792 ◽  
Author(s):  
Jinglin Du ◽  
Li Xie ◽  
Xiaoyan Sun ◽  
Ruoqin Zheng
Keyword(s):  
Fault Detection ◽  
Recovery Process ◽  
Wireless Sensor ◽  
Node Failure ◽  
Optimal Position ◽  
Recovery Algorithm ◽  
Critical Node ◽  
Actor Networks ◽  
Application Requirements ◽  
The Impact

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.

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

2014 ◽  
Vol 668-669 ◽  
pp. 1219-1222
Author(s):  
Lei Yao ◽  
Dong Dong Xu ◽  
Jie Zhou ◽  
Jing Lin Du
Keyword(s):  
Search Algorithm ◽  
Network Connectivity ◽  
Recovery Process ◽  
Wireless Sensor ◽  
Self Healing ◽  
Recovery Algorithm ◽  
Best Response ◽  
Actor Networks ◽  
The Individual ◽  
Minimal Block

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.

Fault Tolerance Model for Efficient Actor Recovery Paradigm in WSAN

2021 ◽  
pp. 486-503
Author(s):  
Reem Khalid Mahjoub ◽  
Khaled Elleithy
Keyword(s):  
Fault Tolerance ◽  
Network Performance ◽  
Wireless Sensor ◽  
Network Integration ◽  
Node Failure ◽  
Failure Avoidance ◽  
Tolerance Model ◽  
Actor Networks ◽  
Selection Algorithms ◽  
Critical Node Detection

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.

scholarly journals Node Failure Handling Through Localized Relocation over Wireless Sensor Network

2019 ◽  
Vol 8 (10) ◽  
pp. 2688-2695
Keyword(s):  
Energy Consumption ◽  
Routing Protocols ◽  
Network Performance ◽  
Wireless Sensor ◽  
Security Threats ◽  
Failure Condition ◽  
Node Failure ◽  
Hardware Failure ◽  
Failure Handling ◽  
The Impact

Communication over WSN under environmental hazards is a major issue. These constraints may have an impact over the behavior of the sensors/routing protocols and resource consumption; thus, may lead to the node failure condition i.e. software/hardware failure, security threats, excessive energy consumption, etc. It is necessary to analyze the impact of failure over network performance. In this paper, a node failure management solution is proposed, and its performance is analyzed using different protocols i.e. LEACH, AODV, and DSDV.

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

2021 ◽  
Vol 48 (4) ◽  
Author(s):  
Aditi Zear ◽  
◽  
Virender Ranga ◽  
Keyword(s):  
Network Performance ◽  
Optimal Solution ◽  
Network Connectivity ◽  
Recovery Process ◽  
Wireless Sensor ◽  
Sink Node ◽  
Real Time Control ◽  
Network Nodes ◽  
Actor Networks ◽  
Message Overhead

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.

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

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Solmaz Mohammadi ◽  
Gholamreza Farahani
Keyword(s):  
Computational Intelligence ◽  
Search Space ◽  
Physical Layer ◽  
Wireless Sensor ◽  
Grey Wolf Optimizer ◽  
Single Node ◽  
Node Failure ◽  
Network Failure ◽  
Connectivity Restoration ◽  
Actor Networks

Abstract 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.

Recovering From a Node Failure in Wireless Sensor-Actor Networks With Minimal Topology Changes

2013 ◽  
Vol 62 (1) ◽  
pp. 256-271 ◽  
Author(s):  
Ameer A. Abbasi ◽  
Mohamed F. Younis ◽  
Uthman A. Baroudi
Keyword(s):  
Wireless Sensor ◽  
Node Failure ◽  
Topology Changes ◽  
Actor Networks
Sign in / Sign up

Export Citation Format

Share Document