Hop-based approach for holes and boundary detection in wireless sensor networks

Khan, Ijaz; Jabeur, Nafaâ; Zeadally, Sherali

doi:10.1049/iet-wss.2012.0076

Cited by 33 publications

(17 citation statements)

References 18 publications

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“…The authors in [27] propose a topological approach for the detection of the boundaries of holes and the external boundary of a sensor network. This approach is based on the identification and checking of the connectivity of the x-hop neighbors surrounding every node and it includes three steps: information collection, path construction and path checking.…”

Section: The Work Of [25] Presents a Theoretical Analysis Methods For mentioning

confidence: 99%

D-LPCN: A distributed least polar-angle connected node algorithm for finding the boundary of a wireless sensor network

et al. 2017

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A boundary of wireless sensor networks (WSNs) can be used in many fields, for example, to monitor a frontier or a secure place of strategic sensitive sites like oil fields or frontiers of a country. This situation is modeled as the problem of finding a polygon hull in a connected Euclidean graph, which represents a minimal set of connected boundary nodes. In this paper we propose a new algorithm called D-LPCN (Distributed Least Polar-angle Connected Node) which represents the distributed version of the LPCN algorithm introduced in [1]. In each iteration, any boundary node, except the first one, chooses its nearest polar angle node among its neighbors with respect to the node found in the previous iteration. The first starting node can be automatically determined using the Minimum Finding algorithm, which has two main advantages. The first one is that the algorithm works with any type of a connected network, given as planar or not. Furthermore, it takes into account any blocking situation and contains the necessary elements to avoid them. The second advantage is that the algorithm can determine all the boundaries of the different connected parts of the network. The proposed algorithm is validated using the CupCarbon, Tossim and Contiki simulators. It has also been implemented using real sensor nodes based on the TelosB and Arduino/XBee platforms. We have estimated the energy consumption of each node and we have found that the consumption of the network depends on the number of the boundary nodes and their neighbors. The simulation results show that the proposed algorithm is less energy consuming than the existing algorithms and its distributed version is less energy consuming than the centralized version.

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Section: The Work Of [25] Presents a Theoretical Analysis Methods For mentioning

confidence: 99%

D-LPCN: A distributed least polar-angle connected node algorithm for finding the boundary of a wireless sensor network

et al. 2017

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“…Khan et al [33] devise a topology based method for hole detection, in which the connectivity between nodes and their x-hop neighbors is used without the location of nodes.…”

Section: Boundary Node Detection In Wireless Sensor Networkmentioning

confidence: 99%

Finding the polygon hull of a network without conditions on the starting vertex

Bounceur

Bezoui

Hammoudeh

et al. 2019

Trans Emerging Tel Tech

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Many real-life problems arising within the fields of wireless communication, image processing, combinatorial optimisation, etc., can be modeled by means of Euclidean graphs. In the case of Wireless Sensor Networks (WSN), the overall topology of the graph is not known, because sensor nodes are often randomly deployed. One of the significant problems in this field is the search for boundary nodes. This problem is important in cases such as the surveillance of an area of interest, image contour reconstruction, graph matching problems, routing or clustering data, etc. In the literature, many algorithms are proposed to solve this problem, a recent one of which is the LPCN algorithm and its distributed version D-LPCN which are both based on the concept of a polar angle visit. An inconvenience of these algorithms is the determination of the starting vertex. In effect, the point with the minimum x-coordinate is a possible starting point but it has to be known at the beginning which considerably increases the algorithms' complexity. In this article, we propose a new method called RRLPCN (Reset and Restart with Least Polar-angle Connected Node) which is based on the LPCN algorithm to find the boundary vertices of a Euclidean graph. The main idea is to start the LPCN algorithm from an arbitrary vertex and, whenever it finds a vertex with an x-coordinate smaller than that of the starting one, LPCN is reset and restarted from this new vertex. The algorithm stops as soon as it visits the

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“…Balancing Energy. Based on the collected data, an agent ASSN should be able to predict and delimit the boundaries of potential energy holes [31]. Preventive actions can then be taken to ultimately balance energy over the SSN.…”

Section: Controlling Service Sensor Network Withmentioning

confidence: 99%

Enabling Cyber Physical Systems with Wireless Sensor Networking Technologies, Multiagent System Paradigm, and Natural Ecosystems

Jabeur

Sahli

Zeadally

2015

Mobile Information Systems

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Wireless sensor networks (WSNs) are key components in the emergent cyber physical systems (CPSs). They may include hundreds of spatially distributed sensors which interact to solve complex tasks going beyond their individual capabilities. Due to the limited capabilities of sensors, sensor actions cannot meet CPS requirements while controlling and coordinating the operations of physical and engineered systems. To overcome these constraints, we explore the ecosystem metaphor for WSNs with the aim of taking advantage of the efficient adaptation behavior and communication mechanisms of living organisms. By mapping these organisms onto sensors and ecosystems onto WSNs, we highlight shortcomings that prevent WSNs from delivering the capabilities of ecosystems at several levels, including structure, topology, goals, communications, and functions. We then propose an agent-based architecture that migrates complex processing tasks outside the physical sensor network while incorporating missing characteristics of autonomy, intelligence, and context awareness to the WSN. Unlike existing works, we use software agents to map WSNs to natural ecosystems and enhance WSN capabilities to take advantage of bioinspired algorithms. We extend our architecture and propose a new intelligent CPS framework where several control levels are embedded in the physical system, thereby allowing agents to support WSNs technologies in enabling CPSs.

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Hop-based approach for holes and boundary detection in wireless sensor networks

Cited by 33 publications

References 18 publications

D-LPCN: A distributed least polar-angle connected node algorithm for finding the boundary of a wireless sensor network

D-LPCN: A distributed least polar-angle connected node algorithm for finding the boundary of a wireless sensor network

Finding the polygon hull of a network without conditions on the starting vertex

Enabling Cyber Physical Systems with Wireless Sensor Networking Technologies, Multiagent System Paradigm, and Natural Ecosystems

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