A novel OoS-aware Routing for ad hoc networks

Su, Tung-Shih; Lin, C.R.; Hsieh, Wen-Shyong

doi:10.2991/jcis.2006.117

Cited by 9 publications

(5 citation statements)

References 18 publications

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“…An adaptive multi-constraint multipath routing protocol which minimizes loss rate, energy consumption and delay between clusters, based on a weighted cost function and on such parameters as loss rate, residual energy and delay, is presented in [18]. An approach to calculate approximately probabilistic timeliness guarantees end-to-end communication delivery delays in WSNs and is used at run-time to build a metric which estimates the probability density function of the end-to-end latency of a path [22]. In fuzzy stochastic multipath routing (FSMR), multiple metrics are used to determine hop count, battery power, signal strength and fuzzy logic is used to offer multiple optimal paths [23].…”

Section: Related Workmentioning

confidence: 99%

Fuzzy Clustering with Multi-Constraint QoS Service Routing in Wireless Sensor Networks

Agarkhed¹,

Kadrolli²,

Patil³

2019

JTIT

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This paper presents a fuzzy logic-based, service differentiated, QoS aware routing protocol (FMSR) offering multipath routing for WSNs, with the purpose of providing a service differentiated path meant for communication between nodes, based on actual requirements. The proposed protocol initially forms a cluster by fuzzy c-means. Next, the building of a routing follows, so as to establish multiple paths between nodes through the modified QoS k-nearest neighborhood, based on different QoS constraints and on optimum shortest paths. If one node in the path fails due to lack of residual energy, bandwidth, packet loss, delay, an alternate path leading through another neighborhood node is selected for communication. Simulation results show that the proposed protocol performs better in terms of packet delivery ratio, delay, packet drop ratio and throughput compared to other existing routing protocols.

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Section: Related Workmentioning

confidence: 99%

Fuzzy Clustering with Multi-Constraint QoS Service Routing in Wireless Sensor Networks

Agarkhed¹,

Kadrolli²,

Patil³

2019

JTIT

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“…Let be the initial node energy [11]. The energy consumed by the node over a given period of time is estimated as (3) Where and are the number of packets transmitted and received by the node, respectively, over a time period t and ε and δ are constants in the range 0,1 .…”

Section: ) Energy Modelmentioning

confidence: 99%

“…Where is the previous trust of node n for node n prior to the inclusion of the current S ij , and is a constant representing the confidence level for the trust of n for n .If there is no link between n and n then is reduced using a constant β instead of α is normalized using equation (11). (11) Where, is the maximum observed over time period t. The indirect reputation (IDR is estimated from the aggregation of the trust reports received and processed n for n which is shown below:…”

Section: ) Reputation Indexmentioning

confidence: 99%

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Fuzzy logic-based stable multipath routing protocol for mobile ad hoc networks

Mallapur¹,

Patil²

2014

2014 Annual IEEE India Conference (INDICON)

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This paper presents a fuzzy logic stable-backbonebased multipath routing protocol (FLSBMRP) for MANET that provides a high-quality path for communication between nodes. The proposed protocol has two main phases. The first phase is the selection of candidate nodes using a fuzzy logic technique. The second phase is the construction of a routing backbone that establishes multiple paths between nodes through the candidate nodes, thus forming a routing backbone. If any candidate node in the path fails due to a lack of bandwidth, residual energy or link quality, an alternate path through another candidate node is selected for communication before the route breaks, because a candidate node failure may lead to a broken link between the nodes. Simulation results demonstrate that the proposed protocol performs better in terms of the packet delivery ratio, overhead, delay and packet drop ratio than the major existing ad hoc routing protocols.

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“…As bandwidth is shared among neighboring nodes, the node pays attention to the channel and estimates local bandwidth (BWd. It depends on the ratio of idle and busy time period for a predefined interval [19].…”

Section: A Overview Ojsbmrpmentioning

confidence: 99%

Stable Backbone Based Multipath Routing Protocol for Mobile Ad-Hoc Networks

Mallapur¹,

Patil

2013

2013 International Conference on Circuits, Power and Computing Technologies (ICCPCT)

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Mobile A d-Hoc Networks (M A NETs) consists of wireless mobile nodes communicating without the need of services provided by a centralized administration or established infrastructure. They can be setup anywhere and any time because they require neither infrastructure nor centralized administration. Because of mobile nodes in MANET, high node mobility causes complexities in route discovery, route stability etc. in which stability is the main reason for data failure. In most of the existing stability based routing protocol link quality and residual energy of each node is estimated during the routing process, result increased delay and overhead. In order to overcome these issues, in this paper, we construct a Stable Backbone Based Multi-Path Routing Protocol for Mobile Ad-Hoc Network (SBMRP). Initially, the nodes with high residual bandwidth, residual power, link quality and low mobility nodes are designated as candidate nodes. Then multiple paths are established between source and destination through these candidate nodes, thus forming a routing backbone. If any candidate node in the path tend to fail due to lack of bandwidth, residual energy or link quality, alternate path through another candidate node is established. By simulation results, we show that proposed technique minimizes the overhead, packet drop, energy and increases the packet delivery rate.

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A novel OoS-aware Routing for ad hoc networks

Cited by 9 publications

References 18 publications

Fuzzy Clustering with Multi-Constraint QoS Service Routing in Wireless Sensor Networks

Fuzzy Clustering with Multi-Constraint QoS Service Routing in Wireless Sensor Networks

Fuzzy logic-based stable multipath routing protocol for mobile ad hoc networks

Stable Backbone Based Multipath Routing Protocol for Mobile Ad-Hoc Networks

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