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2021 ◽  
Author(s):  
Unchitta Kan ◽  
Michelle Feng ◽  
Mason A. Porter

Individuals who interact with each other in social networks often exchange ideas and influence each other's opinions. A popular approach to studying the dynamics of opinion spread on networks is by examining bounded-confidence (BC) models, in which the nodes of a network have continuous-valued states that encode their opinions and are receptive to other opinions if they lie within some confidence bound of their own opinion. We extend the Deffuant--Weisbuch (DW) model, which is a well-known BC model, by studying opinion dynamics that coevolve with network structure. We propose an adaptive variant of the DW model in which the nodes of a network can (1) alter their opinion when they interact with a neighboring node and (2) break a connection with a neighbor based on an opinion tolerance threshold and then form a new connection to a node following the principle of homophily. This opinion tolerance threshold acts as a threshold to determine if the opinions of adjacent nodes are sufficiently different to be viewed as discordant. We find that our adaptive BC model requires a larger confidence bound than the standard DW model for the nodes of a network to achieve a consensus. Interestingly, our model includes regions with `pseudo-consensus' steady states, in which there exist two subclusters within an opinion-consensus group that deviate from each other by a small amount. We conduct extensive numerical simulations of our adaptive BC model and examine the importance of early-time dynamics and nodes with initial moderate opinions for achieving consensus. We also examine the effects of coevolution on the convergence time of the dynamics.


Author(s):  
Hamed Amini ◽  
Andreea Minca ◽  
Agnès Sulem

We introduce threshold growth in the classical threshold contagion model, or equivalently a network of Cramér-Lundberg processes in which nodes have downward jumps when there is a failure of a neighboring node. Choosing the configuration model as underlying graph, we prove fluid limits for the baseline model, as well as extensions to the directed case, state-dependent interarrival times and the case of growth driven by upward jumps. We obtain explicit ruin probabilities for the nodes according to their characteristics: initial threshold and in- (and out-) degree. We then allow nodes to choose their connectivity by trading off link benefits and contagion risk. We define a rational equilibrium concept in which nodes choose their connectivity according to an expected failure probability of any given link and then impose condition that the expected failure probability coincides with the actual failure probability under the optimal connectivity. We show existence of an asymptotic equilibrium and convergence of the sequence of equilibria on the finite networks. In particular, our results show that systems with higher overall growth may have higher failure probability in equilibrium.


Webology ◽  
2021 ◽  
Vol 18 (Special Issue 04) ◽  
pp. 752-764
Author(s):  
R. Deeptha

Routing is portrayed as one of the most important prevailing challenges in research with reference to multi-hop networks in a wireless environment. Opportunistic routing (OR) protocol is an emerging area related to research, due to the improvement in communication reliability, compared to the traditional routing models. The major perception related to OR is to determine a group of neighboring node candidates, named as a candidate set using the advantages of broadcast capability of the wireless medium thereby to collaboratively transmit data packets towards the destination using the coordination of the forwarded candidate set. The design and performance of OR protocols over multi-hop wireless networks mainly depend on the processes of forwarding selection of candidates and assignment of priorities. Therefore, the researchers have designed and developed several different algorithms for those OR processes. In this paper, following a short outline on traditional routing and OR protocols, metrics involved in the design of existing OR protocols, classification of OR based protocols, and hurdles in the design of OR protocols over multi-hop wireless networks are examined. More precisely, the OR protocols are divided into two categories, based on the forwarding candidate set selection and forwarding candidate coordination methods. Furthermore, the most significant challenges of OR protocol design, such as prioritization of forwarding candidates, utilizing the cross-layer approach for candidate coordination, and achieving the quality of service also investigated.


2021 ◽  
Author(s):  
Gayathri VM ◽  
Supraja p ◽  
Razia Sulthana A ◽  
Mukunthan P

Abstract Security plays a vital role in communication networks. Since the nodes are mobile in Mobile Ad-hoc Networks (MANET), they are vulnerable to different types of attacks. Because of its mobility nature any node can enter the network at any time based on the coverage of the network. No centralized mechanism is found to verify or authenticate the nodes that are arriving/leaving the network. An algorithm is proposed for secure communication between source and destination based on the QoS parameters is called Modified Device Key Generation Algorithm (MDKGA). This algorithm elects an agent node based on the QoS parameters. Agent node is responsible for secure key generation and distribution of keys among the nodes. The neighboring node selection is based on trust value which acts as a heuristic function to select the node using A* algorithm.Various performance metrics are also analyzed. Comparison study has been carried out between the protocols of MANET.


2020 ◽  
Author(s):  
Costas Michaelides ◽  
Foteini-Niovi Pavlidou

A large number of wireless sensor nodes in a certain area results in high contention. Inevitably, the transmissions of any possible critical data packets may fail due to collisions. In this article, we introduce an aspect of human intelligence in wireless sensor networks, influenced by cooperative networking, which enhances the timely delivery of critical data. Mutual aid among sensors (MAAS), is an emergency out-of-the-box medium access control (MAC) function for IEEE 802.15.4-2020. Specifically, the network coordinator detects critical data packets and sets an emergency flag to its next beacon, to inform the nodes that they may overhear data packets. When a node overhears a critical data packet from a neighboring node it switches to sleep mode and stays idle until the end of the superframe. Thus, interference is mitigated locally and temporarily. Simulation results, using the CC2650 radio parameters in OMNeT++, show that interference is reduced significantly, in favor of the timely delivery of critical data packets.


2020 ◽  
Author(s):  
Costas Michaelides ◽  
Foteini-Niovi Pavlidou

A large number of wireless sensor nodes in a certain area results in high contention. Inevitably, the transmissions of any possible critical data packets may fail due to collisions. In this article, we introduce an aspect of human intelligence in wireless sensor networks, influenced by cooperative networking, which enhances the timely delivery of critical data. Mutual aid among sensors (MAAS), is an emergency out-of-the-box medium access control (MAC) function for IEEE 802.15.4-2020. Specifically, the network coordinator detects critical data packets and sets an emergency flag to its next beacon, to inform the nodes that they may overhear data packets. When a node overhears a critical data packet from a neighboring node it switches to sleep mode and stays idle until the end of the superframe. Thus, interference is mitigated locally and temporarily. Simulation results, using the CC2650 radio parameters in OMNeT++, show that interference is reduced significantly, in favor of the timely delivery of critical data packets.


Author(s):  
Ranjit Singh ◽  
Rakesh Poonia

Earlier the work has analyzed and implemented through IPV4 based traffic. The researchers have address the source IPv4 based routing in MRMC method. The router configures with a standard IPV4 based network extracts the source IPV4 address from the packet Header. This paper has been defined the network topology which was work on IPV6 protocol and it may also support IPV4 protocol. This paper implements the equalization that takes observation of channel state. The stations collect channel state information to their neighboring node, later on it was transfer to Gateway. The collected information was only possible through equalization method. In general, the equalization divided into two ways, per symbol and Sequence based which are according to receiver Theory. We are using sequence based theory under equalization that take data from maximum likelihood neighbors. We were used proposed Hybrid that take the existing method and combine with dynamic channel method. The proposed model avoids the multipath propagation problem and that problem only arise when we changes the channel from one wavelength to another wavelength. This paper showed proposed results that would be analysis the position of the packets in cluster head (CH). The router is taking as the cluster head which is being deployed on the number of nodes and these nodes randomly moves from one location to another. The MATLAB Simulator has been used in this research paper that helps to solve the complex mathematical equation. Network Simulator (NS2) has used to implement the Network Model.


Author(s):  
Jyoti Neeli ◽  
N. K. Cauvery

Offering a secure communication in wireless adhoc network is yet an open-end problem irrespective of archives of existing literatures towards security enhancement. Inclination towards solving specific forms of attack in adhoc network is majorly seen as an existing trend which lowers the applicability of existing security solution while application environment or attack scenario is changed. Therefore, the proposed system implements an analytical secure routing modeling which performs consistent monitoring of the malicious behaviour of its neighboring node and formulates decision towards secure routing by the source nodes. Harnessing the potential ofconceptual probabilistic modeling, the proposed system is capable as well as applicable for resisting maximum number / types of threats in wireless network. The study outcome show proposed scheme offer better performance in contrast to existing secure routing scheme.


2019 ◽  
Vol 2019 ◽  
pp. 1-19
Author(s):  
Hyeonsang Cho ◽  
Jungmin So

In this paper, we propose a data dissemination protocol for asynchronous duty-cycling wireless sensor networks. In an asynchronous duty-cycling network, each node independently selects its wake-up time. In this environment, data dissemination becomes energy consuming, because broadcasting a packet does reach all neighbors but only the neighbors that are awake at the time. A node can forward its packet to all neighbors by continuously transmitting the packet for a whole wake-up interval, but it leads to high energy consumption and high dissemination delay. The idea proposed in this paper is to use opportunistic forwarding, where each node forwards the packet to a neighbor that wakes up early and receives the packet. Each node forwards the packet, as long as there is a neighboring node that has not received the packet yet. The main benefit of this opportunistic forwarding-based dissemination is that every time a packet is disseminated, it may take a different path to reach the nodes. At the beginning of dissemination, a sender needs to transmit for a very short duration of time because there are plenty of neighboring nodes to receive the packet. As more nodes receive the packet, the transmit duration of the sender becomes longer, thus consuming more energy. Since the order of dissemination is different every time, energy consumption is naturally balanced among the nodes, without explicit measures. Through extensive simulations, we show that the proposed protocol achieves longer network lifetime and shorter dissemination delay compared to other dissemination protocols in various network environments.


2019 ◽  
Vol 16 (11) ◽  
pp. 107-119 ◽  
Author(s):  
Wei Chang ◽  
Yihong Hu ◽  
Guochu Shou ◽  
Yaqiong Liu ◽  
Zhigang Guo

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