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

Mobile, Secure, and Programmable Networking

Bezoui

Lagadec

et al. 2019

Self Cite

A leader node in Ad hoc networks and especially in WSNs and IoT networks is needed in many cases, for example to generate keys for encryption/decryption, to find a node with minimum energy or situated in an extreme part of the network. In our work, we need as a leader the node situated on the extreme left of the network to start the process of finding its boundary nodes. These nodes will be used to monitor any sensitive, dangerous or non-accessible site. For this kind of applications, algorithms must be robust and fault-tolerant since it is difficult and even impossible to intervene if a node fails. Such a situation can be catastrophic in case that this node is the leader. In this paper, we present a new algorithm called DoTRo, which is based on a tree routing protocol. It starts from local leaders which will start the process of flooding to determine a spanning tree. During this process their value will be routed. If two spanning trees meet each other then the tree routing the best value will continue its process while the other tree will stop it. The remaining tree is the dominating one and its root will be the leader. This algorithm turns out to be low energy consuming with reduction rates that can exceed 85%. It is efficient and fault-tolerant since it works in the case where any node can fail and in the case where the network is disconnected.

Section: Cupcarbon Simulator and Senscriptmentioning

confidence: 99%

“…in the literature. A recent algorithm, called D-LPCN [1], can be used for this purpose. This algorithm starts from the node which is on the extreme left of the network, that we suppose to be embedded in the plane with nodes being identified by their coordinates.…”

Section: Introduction and Related Workmentioning

confidence: 99%

DoTRo: A New Dominating Tree Routing Algorithm for Efficient and Fault-Tolerant Leader Election in WSNs and IoT Networks

Mobile, Secure, and Programmable Networking

Bezoui

Lagadec

et al. 2019

Self Cite

“…Saoudi et al [51] have presented a distributed version of the LPCN (Least Polar-angle Connected Node) algorithm introduced in [36]. In each iteration, the current boundary node chooses the nearest polar angle given by the previously chosen node and its neighbors, and the first node has to be a boundary node.…”

Section: Boundary Node Detection In Wireless Sensor Networkmentioning

confidence: 99%

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

Trans Emerging Tel Tech

Bezoui

Hammoudeh

et al. 2019

Self Cite

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

“…In the case of routing, it can be the highest level or the lowest level of energy. In case of the D-LPCN [8,12], it is the node that starts the algorithm, which is the node having the minimum x-coordinate. Houses can also be equipped with sensors and applications used to adapt the temperature and the brightness automatically depending on the outside weather.…”

Section: Introduction and Related Workmentioning

confidence: 99%

A New Leader Election Algorithm based on the WBS Algorithm Dedicated to Smart-cities

Kadjouh

Proceedings of the 3rd International Conference on Future Networks and Distributed Systems

Tari

et al. 2019

Self Cite

One of the interesting techniques for leader election is used in the WBS (Wait Before Starting) algorithm, in which each node in the network will wait for a time corresponding to its value before starting to send the first message to neighbours. This means that the node with the smallest value becomes the leader and it also starts first. This approach is impracticable in the case of real values (case of GPS-coordinates). Also, if the values are very large, the waiting time becomes too long. In this paper, we propose a fast, fault-tolerant and low energy leader election algorithm dedicated to smart-cities, which is based on the technique of waiting before starting, with minimum complexity and in which every node sends one and only one message. Here, the leader is the node with the smallest x-coordinate and the total of sent and received messages is used to represent the global consumption in the network. We give a detailed description of the algorithm, prove its accuracy, discuss its complexity in terms of exchanged messages and evaluate its performance using the CupCarbon simulator. We show that our algorithm is well balanced in terms of energy consumption, it is efficient and adapts well to the increase of the nodes number in the network.