An Autonomous Connectivity Restoration Algorithm Based on Finite State Machine for Wireless Sensor-Actor Networks

Zhang, Ying; Wang, Jim; Guan, Hao

doi:10.3390/s18010153

Cited by 31 publications

(17 citation statements)

References 31 publications

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“…The first subcategory methods restore connectivity by moving surviving node to the location of the damaged cut-vertex node. The connectivity restoration methods proposed in [10]- [13] have similar idea, which can be summarized as finding out the cut-vertex nodes in the network first, then if the cut-vertex node is detected to be unavailable, restoring connectivity by cascaded movement of the related nodes. However, the cascaded movement causes lots of communication overhead because every moving node broadcasts a message to its neighbor before relocation.…”

Section: ) Repositioning Surviving Nodesmentioning

confidence: 99%

SIDR: A Swarm Intelligence-Based Damage-Resilient Mechanism for UAV Swarm Networks

et al. 2020

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Unmanned Aerial Vehicle (UAV) swarm networks have been presented as a promising paradigm for conducting monitoring, and interconnecting tasks in unattended or even hostile environments. However, harsh deployment scenario may make the UAVs susceptible to large-scale damage, and thus degrades the connectivity and performance of the network. None of existing technologies can effectively reorganize the surviving UAVs in a severely damaged UAV swarm into a unified UAV Swarm Network (USNET), this paper presents and analyzes the damage-resilience problem of USNETs for the first time, and put forwards a Swarm Intelligence-based Damage-Resilient (SIDR) mechanism. First, a damage model of USNETs and several metrics are defined before the problem is formally formulated. Second, the SIDR mechanism is detailed based on comprehensively utilizing the storage, communication, positioning, and maneuvering capabilities of UAVs. Third, a potential-field-based solution to the proposed SIDR mechanism is presented, aiming to recover a USNET rapidly and elastically. At last, an evaluation environment is built on the OMNeT++ platform, and the proposed SIDR mechanism is implemented. Extensive simulations are conducted in both dynamic and static scenarios. Simulation results demonstrate that SIDR outperforms the existing algorithms in terms of resilience capability, convergence time and communication overhead. Even if a USNET is divided into multiple disjoint subnets with arbitrary shape, SIDR can aggregate the surviving nodes into a connected network while the network is still flying along the flight path during the recovery process.

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Section: ) Repositioning Surviving Nodesmentioning

confidence: 99%

SIDR: A Swarm Intelligence-Based Damage-Resilient Mechanism for UAV Swarm Networks

et al. 2020

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“…They include the innovative multicast repair (M-REP) mechanism [ 36 ] and its enhanced version EM-REP [ 38 ]. The M-REP FRR mechanism uses the multicast [ 39 , 40 , 41 ] routing protocol—protocol independent multicast—dense mode (PIM DM) to flood traffic around failed element and create alternative FRR path. Enhanced version EM-REP adds support for the repair of multiple failures and link-state routing protocol such as OSPF or IS-IS.…”

Section: Related Workmentioning

confidence: 99%

A New Bit Repair Fast Reroute Mechanism for Smart Sensors IoT Network Infrastructure

Papán

Segeč

Yeremenko

et al. 2020

Sensors

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Today’s IP networks are experiencing a high increase in used and connected Internet of Things (IoT) devices and related deployed critical services. This puts increased demands on the reliability of underlayer transport networks. Therefore, modern networks must meet specific qualitative and quantitative parameters to satisfy customer service demands in line with the most common requirements of network fault tolerance and minimal packet loss. After a router or link failure within the transport network, the network convergence process begins. This process can take an unpredictable amount of time, usually depending on the size, the design of the network and the routing protocol used. Several solutions have been developed to address these issues, where one of which is the group of so-called Fast ReRoute (FRR) mechanisms. A general feature of these mechanisms is the fact that the resilience to network connectivity failures is addressed by calculating a pre-prepared alternative path. The path serves as a backup in the event of a network failure. This paper presents a new Bit Repair (B-REP) FRR mechanism that uses a special BIER header field (Bit-String) to explicitly indicate an alternative path used to route the packet. B-REP calculates an alternative path in advance as a majority of existing FRR solutions. The advantage of B-REP is the ability to define an alternative hop-by-hop path with full repair coverage throughout the network, where, unlike other solutions, we propose the use of a standardized solution for this purpose. The area of the B-REP application is communication networks working on the principle of packet switching, which use some link-state routing protocol. Therefore, B-REP can be successfully used in the IoT solutions especially in the field of ensuring communication from sensors in order to guarantee a minimum packet loss during data transmission.

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“…One of the researches in scattered failures is the distributed autonomous connectivity restoration method based on finite state machine (DCRMF) that employs a regional restoration [24]. Finite state machine identifies whether a node is a critical or noncritical.…”

Section: Related Workmentioning

confidence: 99%

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

Mohammadi

Farahani

2020

J Wireless Com Network

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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.

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An Autonomous Connectivity Restoration Algorithm Based on Finite State Machine for Wireless Sensor-Actor Networks

Cited by 31 publications

References 31 publications

SIDR: A Swarm Intelligence-Based Damage-Resilient Mechanism for UAV Swarm Networks

SIDR: A Swarm Intelligence-Based Damage-Resilient Mechanism for UAV Swarm Networks

A New Bit Repair Fast Reroute Mechanism for Smart Sensors IoT Network Infrastructure

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

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