scholarly journals A Novel Hybrid Optimization Scheme on Connectivity Restoration Processes for Large Scale Industrial Wireless Sensor and Actuator Networks

Processes ◽  
2019 ◽  
Vol 7 (12) ◽  
pp. 939 ◽  
Author(s):  
Ying Zhang ◽  
Zheming Zhang ◽  
Bin Zhang
Keyword(s):  
Large Scale ◽  
Industrial Process ◽  
Network Connectivity ◽  
Decisive Role ◽  
Wireless Sensor ◽  
Coverage Area ◽  
Critical Node ◽  
Connectivity Restoration ◽  
Restoration Algorithm ◽  
Backup Node

In the wireless sensor and actuator networks (WSANs) of industrial field monitoring, maintaining network connectivity with coverage perception plays a decisive role in many industrial process scenarios. The mobile actuator node is responsible for collecting data from the sensing nodes and performing diverse specific collaborative operation tasks. However, the failure of the nodes usually causes coverage vulnerability and partition of the network. Urgent and time-sensitive applications expect a minimum coverage loss to complete an instant connectivity restoration. This paper presents a hybrid coverage perception-based connectivity restoration algorithm, which is designed to restore network connectivity with minimal coverage area loss. The algorithm uses a backup node, which is selected nearby the critical node, to ensure a timely restoration when the critical node encounters failure. In the process of backup node migration, the optimal destination will be reselected to maintain the best network coverage after network connectivity recovery. The effectiveness of the proposed algorithm was verified by some simulation experiments.

scholarly journals Intelligent On-Demand Connectivity Restoration for Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Khalid Mahmood ◽  
Muhammad Amir Khan ◽  
Mahmood ul Hassan ◽  
Ansar Munir Shah ◽  
Shahzad Ali ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Connectivity ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
On Demand ◽  
Connectivity Restoration ◽  
Restoration Technique ◽  
Near Future

Wireless sensor networks are envisioned to play a very important role in the Internet of Things in near future and therefore the challenges associated with wireless sensor networks have attracted researchers from all around the globe. A common issue which is well studied is how to restore network connectivity in case of failure of single or multiple nodes. Energy being a scarce resource in sensor networks drives all the proposed solutions to connectivity restoration to be energy efficient. In this paper we introduce an intelligent on-demand connectivity restoration technique for wireless sensor networks to address the connectivity restoration problem, where nodes utilize their transmission range to ensure the connectivity and the replacement of failed nodes with their redundant nodes. The proposed technique helps us to keep track of system topology and can respond to node failures effectively. Thus our system can better handle the issue of node failure by introducing less overhead on sensor node, more efficient energy utilization, better coverage, and connectivity without moving the sensor nodes.

Distributed Scheduling Protocols for Energy Efficient Large-Scale Wireless Sensor Networks

2011 ◽  
pp. 233-248
Author(s):  
Cheng Fu ◽  
Bang Wang
Keyword(s):  
Large Scale ◽  
Distributed Scheduling ◽  
Wireless Sensor ◽  
Surveillance Systems ◽  
Sensor Scheduling ◽  
Application Development ◽  
Coverage Area ◽  
Power Conservation ◽  
Coverage Ratio ◽  
Scheduling Protocols

A major design challenge in wireless sensor network application development is to provide appropriate middleware service protocols to control the energy consumption according to specific application scenarios. In common application scenarios such as in monitoring or surveillance systems, it is usually necessary to extend the system monitoring area as large as possible to cover the maximal area. The two issues of power conservation and maximizing the coverage area have to be considered together with both the sensors’ communication connectivity and their power management strategy. In this chapter,the authors proposed novel enhanced sensor scheduling protocols to address the application scenario of typical surveillance systems. Their protocols take into consideration of both power conservation and coverage ratio to search for the balance between the different requirements. They proposed both centralized and de-centralized sensor scheduling versions, and compared the performance of different algorithms using several metrics. The results provide evidence of the advantages of our proposed protocols comparing with existing sensor scheduling protocols.

scholarly journals TAPU: Test and pick up-based k-connectivity restoration algorithm for wireless sensor networks

2019 ◽  
pp. 985-997 ◽  
Author(s):  
VAHİD KHALİLPOUR AKRAM ◽  
ORHAN DAĞDEVİREN
Keyword(s):  
Lower Cost ◽  
Greedy Algorithms ◽  
Wireless Sensor ◽  
Previous Approach ◽  
K Value ◽  
Shortest Path Tree ◽  
Connectivity Restoration ◽  
Restoration Algorithm ◽  
Optimal Movement ◽  
Failed Node

A k-connected wireless sensor network remains connected if any k-1 arbitrary nodes stop working. The aim of movement-assisted k -connectivity restoration is to preserve the k -connectivity of a network by moving the nodes to the necessary positions after possible failures in nodes. This paper proposes an algorithm named TAPU for k-connectivity restoration that guarantees the optimal movement cost. Our algorithm improves the time and space complexities of the previous approach (MCCR) in both best and worst cases. In the proposed algorithm, the nodes are classified into safe and unsafe groups. Failures of safe nodes do not change the k value of the network while failures of unsafe nodes reduce the k value. After an unsafe node’s failure, the shortest path tree of the failed node is generated. Each node moves to its parent location in the tree starting from a safe node with the minimum moving cost to the root. TAPU has been implemented on simulation and testbed environments including Kobuki robots and Iris nodes. The measurements show that TAPU finds the optimum movement up to 79.5% faster with 50% lower memory usage than MCCR and with up to 59% lower cost than the greedy algorithms.

Combining Power Adjustment and Node’s Movement for Connectivity Restoration in Sensor Networks

2014 ◽  
Vol 644-650 ◽  
pp. 2736-2739 ◽  
Author(s):  
Chun Hui Wu ◽  
Hong Sheng Chen
Keyword(s):  
Sensor Networks ◽  
Large Scale ◽  
Network Connectivity ◽  
Mobile Nodes ◽  
Negative Effects ◽  
Boundary Node ◽  
Connectivity Restoration ◽  
Power Adjustment ◽  
Novel Method ◽  
Entire Network

Mobile sensor networks (MSNs) have many applications in recent years, especially in some harsh environment, such as battlefield reconnaissance. MSNs may suffer from a large-scale damage which causes many nodes to fail and the network to get partitioned into isolate islands. So in order to avoid negative effects on the application, restoring network connectivity is crucial in such case. In this paper, we propose a novel method, CPANMCR, which combines power adjustment and node’s movement to restore the network connectivity. In CPANMCR mainly include three phases: firstly detecting the boundary nodes of every isolate island, then adjusting the power of boundary node to restore the connection, and finally moving mobile nodes to the appropriate location to restore the connectivity of the entire network. Extensive simulation experiments demonstrate that the proposed method can guarantee network connectivity and reduce the total travel distance.

scholarly journals PINC: Pickup Non-Critical Node Based k-Connectivity Restoration in Wireless Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6418
Author(s):  
Vahid Khalilpour Akram ◽  
Zuleyha Akusta Dagdeviren ◽  
Orhan Dagdeviren ◽  
Moharram Challenger
Keyword(s):  
Data Transmission ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Critical Groups ◽  
Critical Node ◽  
Connectivity Restoration ◽  
Critical Nodes ◽  
Communication Path ◽  
Complicated Task ◽  
Node Failures

A Wireless Sensor Network (WSN) is connected if a communication path exists among each pair of sensor nodes (motes). Maintaining reliable connectivity in WSNs is a complicated task, since any failure in the nodes can cause the data transmission paths to break. In a k-connected WSN, the connectivity survives after failure in any k-1 nodes; hence, preserving the k-connectivity ensures that the WSN can permit k-1 node failures without wasting the connectivity. Higher k values will increase the reliability of a WSN against node failures. We propose a simple and efficient algorithm (PINC) to accomplish movement-based k-connectivity restoration that divides the nodes into the critical, which are the nodes whose failure reduces k, and non-critical groups. The PINC algorithm pickups and moves the non-critical nodes when a critical node stops working. This algorithm moves a non-critical node with minimum movement cost to the position of the failed mote. The measurements obtained from the testbed of real IRIS motes and Kobuki robots, along with extensive simulations, revealed that the PINC restores the k-connectivity by generating optimum movements faster than its competitors.

scholarly journals Towards Improved Clustering and Routing Protocol for Wireless Sensor Networks

2020 ◽  
Author(s):  
Mohammad Alharbi ◽  
Mario Kolberg ◽  
Muhammad Zeeshan
Keyword(s):  
Large Scale ◽  
Network Connectivity ◽  
Network Capacity ◽  
Wireless Sensor ◽  
Transmission Range ◽  
Hop Count ◽  
Iot Applications ◽  
Battery Capacity ◽  
Alternate Routing ◽  
Network Backbone

Abstract Wireless sensor network (WSN)-based Internet of Things (IoT) applications suffer from issues including limited battery capacity, frequent disconnections due to multihop communication and a shorter transmission range. Researchers propose different but isolated clustering and routing solutions that are inefficient in terms of energy efficiency and network connectivity in IoT-based WSNs. In this work, we emphasize the importance of considering the context of IoT applications that have further requirements for dedicated data collection per node. We address two interlinked issues, clustering and routing, in a large-scale IoT-based WSN. We propose an improved clustering and routing (ICR) protocol to jointly solve both of these issues. Improved clustering and routing provide area-based clustering derived from the transmission range of network nodes. This clustering also develops a strong network backbone that provides fail-over-proof routing. An efficient routing path is achieved by finding the minimal hop count with the availability of alternate routing paths. The results are compared with state-of-the-art benchmark protocols, Joint Clustering and Routing (JCR), Low Energy Adaptive Hierarchical Clustering (LEACH) and other recent protocols. Theoretical and simulation results demonstrate reliable network topology, improved network lifetime, efficient node density management and improved overall network capacity.

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