On “Movement-Assisted Connectivity Restoration in Wireless Sensor and Actor Networks”

Wang, ShiGuang; Mao, Xufei; Tang, Shaojie; Li, Xiangyang; Zhao, Jizhong; Dai, Guojun

doi:10.1109/tpds.2010.102

Cited by 38 publications

(4 citation statements)

References 17 publications

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“…The aim of k-connectivity restoration is to preserve the k-connectivity of the WSN after losing some motes. Deploying new motes [47][48][49][50][51][52], extending the transmission ranges [53] and moving the available motes [54][55][56][57][58][59] are significant approaches to connectivity restoration. Most of the proposed approaches restore 1-connectivity after failure in a cut vertex [54,55,[57][58][59][60].…”

Section: Related Workmentioning

confidence: 99%

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

Akram

Dagdeviren

Dağdeviren

et al. 2021

Sensors

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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.

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Section: Related Workmentioning

confidence: 99%

“…To restore the k-connectivity of a given WSN, an algorithm named MCCR has been proposed in [56]. This algorithm uses maximum weighted matching and k-connectivity test algorithms to output optimal movements.…”

Section: Related Workmentioning

confidence: 99%

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

Akram

Dagdeviren

Dağdeviren

et al. 2021

Sensors

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“…KDFA provides a strong resilience to protect the key exposure at intermediate compromised nodes. Interactor connectivity is the mandatory part for this communication; therefore, connectivity restoration [24–26] should also be considered to achieve sustainable communication and coordination [27] in different regions using actor nodes.…”

Section: Related Workmentioning

confidence: 99%

Secure Key Distribution Using Fragmentation and Assimilation in Wireless Sensor and Actor Networks

Ullah

Sher

Imran

et al. 2015

International Journal of Distributed Sensor Networks

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Secure key distribution is one of the most important building blocks to ensure confidentiality in wireless sensor and actor networks (WSANs). However, the key distribution becomes a challenging task when keys have to be relayed by compromised nodes in order to establish secure communication between distant nodes. To deal with this issue, we propose in this paper a key distribution scheme, named key distribution using fragmentation and assimilation (KDFA). In this scheme, the sender node splits the actual key into fragments and sends them through intermediate actor nodes towards the receiver node. The latter assimilates these key fragments using XOR operation to reconstruct the actual key. In this case, attacker cannot retrieve the actual key and only gets the key fragment. KDFA is composed of two parts: (a) key distribution protocol (KDP) to distribute the key using intra-actor and interactor communication scenarios and (b) key fragmentation algorithm (KFA) to slice the key using binary calculations. KDFA execution has been specified and formally verified using Rubin logic. Moreover, the performance and the resilience of the proposed protocol are further analyzed through extensive simulations using ns-2.35. Results show that KDFA is resilient against actor node compromise and key exposure.

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“…Bridge detection is an important research area for different types of networks [4–9]. After bridges are detected, various solutions can be applied [10] in order to neutralize bridges.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Bridge Detection Algorithms for Wireless Sensor Networks

Dağdeviren

Akram

2013

International Journal of Distributed Sensor Networks

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A bridge is a critical edge whose fault disables the data delivery of a WSN component. Because of this, it is important to detect bridges and take preventions before they are corrupted. Since WSNs are battery powered, protocols running on WSN should be energy efficient. In this paper, we propose two distributed energy-efficient bridge detection algorithms for WSNs. The first algorithm is the improved version of Pritchard's algorithm where two phases are merged into a single phase and radio broadcast communication is used instead of unicast in order to remove a downcast operation and remove extra message headers. The second algorithm runs proposed rules on 2-hop neighborhoods of each node and tries to detect all bridges in a breadth-first search (BFS) execution session using O( ) messages with O(Δ(log 2 ( ))) bits where is the node count and Δ is the maximum node degree. Since BFS is a natural routing algorithm for WSNs, the second algorithm achieves both routing and bridge detections. If the second proposed algorithm is not able to to classify all edges within the BFS phase, improved version of Turau's algorithm is executed as the second phase. We show the operation of the algorithms, analyze them, and provide extensive simulation results on TOSSIM environment. We compare our proposed algorithms with the other bridge detection algorithms and show that our proposed algorithms provide less resource consumption. The energy saving of our algorithms is up to 4.3 times, while it takes less time in most of the situations.

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On “Movement-Assisted Connectivity Restoration in Wireless Sensor and Actor Networks”

Cited by 38 publications

References 17 publications

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

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

Secure Key Distribution Using Fragmentation and Assimilation in Wireless Sensor and Actor Networks

Energy-Efficient Bridge Detection Algorithms for Wireless Sensor Networks

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