4,494 research outputs found
A Trust Based Fuzzy Algorithm for Congestion Control in Wireless Multimedia Sensor Networks (TFCC)
Network congestion has become a critical issue for resource constrained
Wireless Sensor Networks (WSNs), especially for Wireless Multimedia Sensor
Networks (WMSNs)where large volume of multimedia data is transmitted through
the network. If the traffic load is greater than the available capacity of the
sensor network, congestion occurs and it causes buffer overflow, packet drop,
deterioration of network throughput and quality of service (QoS). Again, the
faulty nodes of the network also aggravate congestion by diffusing useless
packets or retransmitting the same packet several times. This results in the
wastage of energy and decrease in network lifetime. To address this challenge,
a new congestion control algorithm is proposed in which the faulty nodes are
identified and blocked from data communication by using the concept of trust.
The trust metric of all the nodes in the WMSN is derived by using a two-stage
Fuzzy inferencing scheme. The traffic flow from source to sink is optimized by
implementing the Link State Routing Protocol. The congestion of the sensor
nodes is controlled by regulating the rate of traffic flow on the basis of the
priority of the traffic. Finally we compare our protocol with other existing
congestion control protocols to show the merit of the work.Comment: 6 pages, 5 figures, conference pape
Fuzzy based load and energy aware multipath routing for mobile ad hoc networks
Routing is a challenging task in Mobile Ad hoc Networks (MANET) due to their dynamic topology and lack of central administration. As a consequence of un-predictable topology changes of such networks, routing protocols employed need to accurately capture the delay, load, available bandwidth and residual node energy at various locations of the network for effective energy and load balancing. This paper presents a fuzzy logic based scheme that ensures delay, load and energy aware routing to avoid congestion and minimise end-to-end delay in MANETs. In the proposed approach, forwarding delay, average load, available bandwidth and residual battery energy at a mobile node are given as inputs to a fuzzy inference engine to determine the traffic distribution possibility from that node based on the given fuzzy rules. Based on the output from the fuzzy system, traffic is distributed over fail-safe multiple routes to reduce the load at a congested node. Through simulation results, we show that our approach reduces end-to-end delay, packet drop and average energy consumption and increases packet delivery ratio for constant bit rate (CBR) traffic when compared with the popular Ad hoc On-demand Multipath Distance Vector (AOMDV) routing protocol
A Trust Based Congestion Aware Hybrid Ant Colony Optimization Algorithm for Energy Efficient Routing in Wireless Sensor Networks (TC-ACO)
Congestion is a problem of paramount importance in resource constrained
Wireless Sensor Networks, especially for large networks, where the traffic
loads exceed the available capacity of the resources. Sensor nodes are prone to
failure and the misbehavior of these faulty nodes creates further congestion.
The resulting effect is a degradation in network performance, additional
computation and increased energy consumption, which in turn decreases network
lifetime. Hence, the data packet routing algorithm should consider congestion
as one of the parameters, in addition to the role of the faulty nodes and not
merely energy efficient protocols. Unfortunately most of the researchers have
tried to make the routing schemes energy efficient without considering
congestion factor and the effect of the faulty nodes. In this paper we have
proposed a congestion aware, energy efficient, routing approach that utilizes
Ant Colony Optimization algorithm, in which faulty nodes are isolated by means
of the concept of trust. The merits of the proposed scheme are verified through
simulations where they are compared with other protocols.Comment: 6 pages, 5 figures and 2 tables (Conference Paper
A fuzzy-based reliaility for JXTA-overlay P2P platform considering data download speed, peer congestion situation, number of interaction and packet loss parameters
(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.In this paper, we propose and evaluate a new fuzzy-based reliability system for Peer-to-Peer (P2P) communications in JXTA-Overlay platform considering as a new parameter the peer congestion situation. In our system, we considered four input parameters: Data Download Speed (DDS), Peer Congestion Situation (PCS), Number of Interactions (NI) and Packet Loss (PL) to decide the Peer Reliability (PR). We evaluate the proposed system by computer simulations. The simulation results have shown that the proposed system has a good performance and can choose reliable peers to connect in JXTA-Overlay platform.Peer ReviewedPostprint (author's final draft
A genetic algorithm for the design of a fuzzy controller for active queue management
Active queue management (AQM) policies are those
policies of router queue management that allow for the detection of network congestion, the notification of such occurrences to the
hosts on the network borders, and the adoption of a suitable control
policy. This paper proposes the adoption of a fuzzy proportional
integral (FPI) controller as an active queue manager for Internet
routers. The analytical design of the proposed FPI controller is
carried out in analogy with a proportional integral (PI) controller,
which recently has been proposed for AQM. A genetic algorithm is
proposed for tuning of the FPI controller parameters with respect
to optimal disturbance rejection. In the paper the FPI controller
design metodology is described and the results of the comparison
with random early detection (RED), tail drop, and PI controller
are presented
A Rate based Congestion Control Mechanism Using Fuzzy Controller in MANETs
The traditional congestion control mechanism TCP, performs very poorly in MANETs Because there are a number of new challenges such as wireless link error, medium contention and frequent route failures in this kind of networks. In this paper, we propose a fuzzy adhoc rate-based congestion control (FARCC) to enhance the efficiency of network in MANETs. In FARCC, we use a rate-based transmission scheme using two fuzzy controller of zero order Takagi Sugeno Kang (TSK) model to congestion detection and congestion control. The FARCC sender adjusts data rate by receiving a feedback packet from FARCC destination. NS2-based simulation results show that FARCC outperforms ITP and ATP to achieve, in terms of throughput and fair resource allocation in AdHoc networks under random topology
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