Congestion Control Protocol

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An Energy Efficient and Cooperative Congestion Control Protocol in MANET

An Energy Efficient and Cooperative Congestion Control Protocol in MANET

Here, the proposed energy efficient and cooperative congestion control protocol builds a cooperative multicast tree rooted at the source towards the receivers. The distance i.e. the geographical location of the nodes is assumed. Their residual energy is measured. The nodes are sorted based on its location from the source and arranged in a sequence order. A distance threshold value Q is set and the nodes which are less than Q(n < Q) are multicast from the source and the nodes which are greater than Q(n > Q) are multicast by the relay node where n is the nodes. In case of multicasting the node which has the maximum residual energy per corresponding receiver is set as the relay node. The relay node then forwards the packets from the source to the corresponding receivers. But, since MANET topology is dynamic i.e. its nodes have the random motion hence if relay nodes fails to forward the packets to the receiver then the nodes having the second most highest residual energy must be chosen as a relay node for the multicasting purposes.
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A Multievent Congestion Control Protocol for Wireless Sensor Networks

A Multievent Congestion Control Protocol for Wireless Sensor Networks

Congestion detection and avoidance (CODA) in sensor networks [3] uses open-loop and closed-loop mechanisms to handle congestion which is detected on the basis of channel sampling and buffer occupancy. Once congestion is detected, the open-loop mechanism broadcasts back pressure message to their neighboring nodes which further propagate these messages to upstream source nodes, depending on their local bu ff er occupancy. SenTCP [6] uses hop-by-hop, open- loop congestion control mechanism that detects congestion using both bu ff er occupancy and packet interarrival time. In SenTCP, nodes avoid congestion by issuing periodic feedback signals to adjust the reporting rate of their upstream nodes depending on local buffer status. Priority-based congestion control protocol (PCCP) [10] uses packet interarrival time and packet service time to detect congestion level at a node and employs weighted fairness to allow nodes to receive priority-dependent throughput. If all nodes have the same priority, then PCCP can give same per-node throughput. With different priorities, PCCP can provide throughput based on the priority of the node.
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An Efficient Congestion Control Protocol for Wired/Wireless Networks

An Efficient Congestion Control Protocol for Wired/Wireless Networks

[4]. In [5], a congestion control mechanism, called TCP NewReno, is developed by refining the fast recovery algorithm of TCP Reno to recover multiple packet losses from a window of data. In [6], an extension of Reno, called TCP SACK (TCP with Selective Acknowledgement), is developed by modifying the fast recovery algorithm of Reno keeping the other algorithms unchanged. Similar to NewReno, TCP SACK handles multiple packet losses from the same window but it has a better estimation capability for the number of outstanding packets. Additional mechanisms include Forward Acknowledgment (FACK) [7], Selective Acknowledgment (SACK) [6], dynamic recovery [8], an Extension to the SACK Option (D–SACK) [9], TCP with Faster Recovery (FR–TCP) [10], Reordering–Robust TCP (RR–TCP) [11], Duplicate Acknowledgment Counting (DAC) [12], TCP SACK+ [13], TCP Vegas [14,15]. Other proposals, such as TCP Westwood [16] and TCP WestwoodNew [17] are developed to overcome congestion in wireless networks. A survey of TCP Reno, NewReno and SACK over mobile ad-hoc network is investigated in [18]. Comparative studies between the different proposals for TCP congestion control are presented in [19-21].
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State-of-the-Art Congestion Control Protocols in WSN: A Survey

State-of-the-Art Congestion Control Protocols in WSN: A Survey

Wireless multimedia congestion control protocol (WCCP) is a multi-layered protocol architecture proposed for alleviating congestion in multimedia WSNs. WCCP is a combination of two protocols, i-e., Source Congestion Avoidance Protocol (SCAP) and Receiver Congestion Control Protocol (RCCP). WCCP considers the features of frames within the multimedia packets at transport layer, also known as group of picture (GOP), at the application layer. GOP contains three different types of frames with varying combinations, i.e., one I frame and multiple P and B-frames. Furthermore, these varying types of frames have a varying effect on the overall quality of the received video. I-frames are the key frames in terms of quality and are highly important than the remaining two frames. As a result, loss of I-frames adversely effects the underlying multimedia applications. During feature selection of WCCP protocol, I Frames is prioritized over P and B frames. Once congestion is detected, SCAP protocol at the source node is informed. WCCP keeps I-frames at the base station, while ignores P and B frames during congestion. This improves the performance of the network and quality of the video received at the base
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Vol 7, No 2 (2015)

Vol 7, No 2 (2015)

Abstract: Wireless Sensor Networks (WSNs) have been a current trend in the research field and has many issues when there are multiple mobile sinks. Data dissemination gets critical as their locations have to be repeatedly updated and results in huge consumption of the restricted battery supply in sensor nodes. In this paper, we propose GCCP – NS, a grid based congestion control protocol with N -sinks that solves the data dissemination problem leading to congestion. We construct a dual level grid structure to trail the locations of all the source nodes that reports the information to the mobile sinks by monitoring the network in a hierarchical manner. As an added advantage, it aids in data dissemination based on query flooding from the mobile sinks using quorum based method within each cell in the grid and avoids congestion in an effective manner. Simulation results show that our proposed protocol outperforms the other schemes in terms of packet delivery ratio, energy expenditure and throughput.
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Congestion Detection & Minimization in Wireless Sensor Network By Using Multipath Rate Organization Technique

Congestion Detection & Minimization in Wireless Sensor Network By Using Multipath Rate Organization Technique

It uses mechanisms likes Receiver based congestion detection, open loop hop-by hop backpressure, closed loop multi source regulation. Congestion Control and Fairness (CCF)[6] is a congestion control protocol to ensure fairness. It uses two schemes: probabilistic selection and epoch based proportional selection. It ensures absolute fairness among every node. Siphon detects congestion using queue length. It uses traffic redirection to mitigate congestion. It doesn’t use any rate adjustment technique.

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CONGESTION AVOIDANCE AND CONTROL IN WIRELESS SENSOR NETWORKS A SURVEY

CONGESTION AVOIDANCE AND CONTROL IN WIRELESS SENSOR NETWORKS A SURVEY

389 | P a g e The flocking behaviour of birds aids in the implementation of a robust, scalable and self-adaptive congestion control protocol in WSNs [5]. This approach takes on a swarm intelligence paradigm enthused by the collective behaviour of bird flocks. The major concept here is to „guide‟ packets (birds) to form flocks and travel on the way to the sink (global attractor), while attempting to prevent congestion regions (obstacles). The direction of motion of a packet flock is determined by the repelling and attracting forces between the packets, and the field of view and the artificial magnetic field in the direction of the artificial magnetic pole (sink). The implementation of the proposed approach is easier at the individual nodes, with reduced exchange of information. Flock-based Congestion Control (Flock-CC) method balances the load by efficiently utilizing the allotted network resources and transferring the data packets to the sink. Also, the proposed method attains the potential in opposition to failing nodes, scalability in different network sizes and performs well than usual techniques. The performance in terms of power and including the power in the desirability function is a difficult task in this work.
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Congestion Free Routing in MANET based on Node Reliability Supported AODV

Congestion Free Routing in MANET based on Node Reliability Supported AODV

To find out non contestant route, the intermediate adjacent node broadcasts RREQ to all neighbors except the sender node which is likely to be congested. Route reply is generated by the receiver node if it is already having a valid route to the destination. The proposed protocol RREP is modified by including the PDR value of a node in addition to the information contained in RREP. After reading RREP, node unicasts it to sender intermediate node. On receiving RREP from the neighbor nodes, the sender node compares the PDR value with the set threshold of the protocol is 70%. That trust value is calculated from the total number of data forwarded out of a total number of packet receives multiply by hundred that is the packet delivery ratio of the node (PDR). The RREP containing PDR less than 70%, forward route entry for the destination node is created. It uses the node from which reliable RREP is received as the next hop toward the destination. The hop count is incremented by one. This forward route entry for the destination will be utilized if the source selects this congestion free path for transmission to the destination. Trust value is calculated for each node during routing and is checked against the threshold value. In our case, the threshold value is 70% PDR which is calculated as the average of trust values of the nodes that take part in the routing after calculating and observing PDR at every node in simulation for 100 times. If trust value is above the threshold then the node is treated as trustworthy and reliable whereas lesser than threshold value indicates the possibility for the node to drop packets for the current transmission and will not be considered suitable for routing and an alternate path is selected for routing[10]. However, this node may be the best node for some other transmission between some other source and destination in the same network at a different time interval. To select the next reliable hop, the trust value of all neighboring nodes from the current intermediate node is calculated and finally, a node with the highest trust value than the threshold is selected as the next hop node for the current routing.
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Title: Modified AODV for Congestion Control in MANET

Title: Modified AODV for Congestion Control in MANET

In our work we have not considered the energy concept at nodes, but in actual the congestion detection is done at node which takes energy of node in processing, decreasing the alive time of node. In future work, energy can be considered as a constraint in the algorithm as it may happen as with our case, after 50n seconds congestion detection, energy residual are not enough to send an alarm to source node about congestion in the path. That will increase the packet drop ratio. Our work is lacking with the effective new path searched after congestion. It‟s a path with many hopes. These should be decreased so that energy of packets doesn‟t reduce much.
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A FUZZY BASED BUFFER SPLIT ALGORITHM FOR BUFFER ATTACK DETECTION IN INTERNET OF 
THINGS

A FUZZY BASED BUFFER SPLIT ALGORITHM FOR BUFFER ATTACK DETECTION IN INTERNET OF THINGS

A schedule based on the fly has been constructed according to the change in nodes demand and obtain a slot-based “step-by-step” energy consumption model of the TSCH schedule mechanism [14]. It has been applied to different scenarios for bringing out the potential effects of network congestion. The reliable, efficient, fair and interference aware congestion control (REFIACC) has been sought to prevent the interferences and ensure a high fairness of bandwidth utilization among sensor nodes by scheduling the communications [15]. The congestion and interference in inter and intra hot spots have been mitigated taking into account the dissimilarity between the links capacities in the scheduling process.
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Routing based Congestion Control Metric: RFR

Routing based Congestion Control Metric: RFR

Mobile adhoc network is a collection of mobile nodes which are self organize able and configure itself on the fly. These networks for their infrastructure less, quick to deploy environment provide applications in diverse domains. Since their inception they have been deployed in military areas, emergency and rescue operations, business applications and many more just because they are economical. In these networks, a mobile terminal has dual functions of a node and routing. Routes are generally broken due to node movements, load on the network, insufficient bandwidth, power insufficiency, etc. Also wireless links are unreliable and error prone. All these factors lead to congestion in the networks which jams the network and poorly affects its performance. Routing algorithms should adapt to such dynamic environment and provide quality of service and error free delivery. Congestion and load balancing are challenging tasks due to unpredictable nature of these networks.
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Congestion Control for Content Centric Networking Based on Protocol Oblivious Forwarding

Congestion Control for Content Centric Networking Based on Protocol Oblivious Forwarding

In CCN, we set flag in the interest packet instead of the returned data. When the congestion is detected, the feedback will immediately been brought back to the receivers. In addition, we also detect congestion in intermediate nodes. A simple router model is illustrated in Figure 2. A router has lots of interfaces, and each interface corresponds to a transmission buffer. We only consider the flow in one direction. The number of interest packets from router R1 to R2 indicate the number of data packets to be returned to R1. So we calculate the queue length of interest packets in router R1 to judge the degree of congestion. The average queue length avgQ is expressed as follows, where Q is the actual queue length that is expressed as the average queue length using exponentially weighted moving average model (EWMA). WQ is the weight. Symbol description of the algorithm is shown in Table 1.
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Load Balancing in Mobile Ad Hoc Networks: A Survey

Load Balancing in Mobile Ad Hoc Networks: A Survey

Pham and Perreau conducted a performance analysis [15]. The authors of [15] provided some insight into choosing the right trade-off between increased overheads and better performance. A novel end-to-end approach for achieving the dual goal of enhanced reliability under path failures, and multi-path load balancing in mobile ad hoc networks (MANETs) is proposed by Argyriou and Madisetti in [16]. The authors of [16] achieved their objective by fully exploiting the presence of multiple paths in mobile ad hoc networks in order to jointly attack the problems of frequent route failures and load balancing. In [17] Chakrabarti and Kulkarni modified the way to construct alternate routes that are maintained and used in DSR. In routing protocol proposed in [17] load balancing is done among the number of alternate routes. The approach in [17] also enabled to provide QoS guarantees by ensuring the appropriate bandwidth which is available for a flow even when nodes are under mobility. Souinli et.al [18] proposed load-balancing mechanisms that push the traffic further from the center of the network. They provided a novel routing metrics that take into account nodes degree of centrality, for both proactive and reactive routing protocols.
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Improved Transport Layer Protocol for Congestion Control in Wireless Sensor Networks

Improved Transport Layer Protocol for Congestion Control in Wireless Sensor Networks

This congestion control mechanism also introduces delay in the network as no node can send packets to the nodes which have sent STOP messages. Also, the use of explicit messages to notify congestion consumes network energy so we need a congestion control mechanism which does not use explicit control messages instead uses rate control to optimal values. To calculate new data rate in case of congestion, the proposed solution makes use of the time interval between the generation of consecutive packets. When the node’s buffer size goes below the threshold, the node piggybacks it new state in the ACK packet so that the neighboring nodes can adjust their data transmission rates towards that node. This new method of congestion mitigation is better than the old method used by CTCP because CTCP reduces the transmission rate to zero whenever a node sends STOP message instead the transmission rate should be calculated using the exact buffer occupancy. The new method uses the exact buffer occupancy to calculate the transmission rate. This new transmission rate gives better results in terms of average delivery ratio than the zero transmission rate of the old congestion control method of CTCP.
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Vitality Rooted Modern Trends in Delay Tolerant Networks

Vitality Rooted Modern Trends in Delay Tolerant Networks

Vehicular Ad-hoc Network (VANET) is gotten from the Mobile Ad-hoc Network (MANET). Enlarged DTN based Energy Efficient Routing Protocol for Vehicular Ad hoc Networks (ADTNEER) [26] is a mix of different systems, for example, store stay splash, association lifetime and connection state data. It uses those various methodologies to give preferred execution over the VANET. It additionally utilizes the rakish locale system for choosing the best reasonable next bounce. VANET essentially comprise of two elements: vehicle and Road-side Infrastructure Units (PSU). The vehicle is the moving substance and PSU is the fixed elements which are associated with the web. VANET hub can speak with different vehicles legitimately. Due the versatility of hubs, it is challengeable to perform start to finish correspondence.
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Router congestion control

Router congestion control

Our protocol is inspired both by network packet queuing theory and by auction theory. From the network packet queuing theory perspective our protocol is similar to CHOKe. In case of congestion, CHOKe penalize all the sources in proportion to their arrival rate. We instead penalize only the highest rate senders. This ensures that the best thing for a sender in case of congestion is to not be the highest rate flow. So all the senders compete not to be the highest rate flow; this process eliminates the congestion. If we consider CHOKe and our protocol in the setting of the auction of a single item, the winner, in the case of CHOKe, is picked randomly with probabilities proportional to the bids; whereas in our protocol the winner is the highest bidder. Since nobody wants to “win” the penalty, the senders in our protocol compete to not be the winner, until the total bids are low enough that the auction is cancelled.
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Title: TCP Window Based End-to-End Mechanisms

Title: TCP Window Based End-to-End Mechanisms

TCP-Peach [3] is primarily targeted at satellite networks and avoids problems such as the long duration of the slow start phase caused by the long satellite propagation delays, the low rate imposed on the sender due to the long RTT, and the high error rate of the wireless environment [11]. TCP-Peach uses a sudden start mechanism instead of slow start. In sudden start, a number of dummy segments are sent during each RTT (in addition to data segments) and the congestion window grows with returning ACKs for these dummy segments as well as data [8]. These dummy segments have lower priority than data and therefore intermediate routers can drop them in times of congestion. TCP-Peach also proposes a rapid recovery algorithm for handling packet losses that are not due to congestion [14]. This algorithm is executed after the execution of the fast recovery algorithm when DUPACKs are received [4]. In the rapid recovery phase, a number of dummy segments are sent to probe the availability of network resources. According to the number of received ACKs for the dummy segments, the sender can determine whether the loss was due to congestion or channel errors [18].
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A Deployment of Congestion Control

A Deployment of Congestion Control

designing. Since PESANE controls large-scale archetypes, without exploring neural networks, coding the codebase of 16 Fortran files was rel-atively straightforward. Analysts have com-plete control over the hacked operating system, which of course is necessary so that forward-error correction and superblocks are entirely in-compatible[1],[ 3],[5]. Systems engineers have complete control over the server daemon, which of course is necessary so that the seminal client-server al-gorithm for the refinement of semaphores by David Johnson is recursively enumerable. Next, since our approach learns simulated annealing, without storing context-free grammar, imple-menting the client-side library was relatively straightforward. Overall, our application adds only modest overhead and complexity to prior relational frameworks
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Design and Improve AODV Protocol for Congestion Control in MANET using Cryptography Technique

Design and Improve AODV Protocol for Congestion Control in MANET using Cryptography Technique

Gurveen Vaseer, Garima Ghai and Pushpinder Singh Patheja. “A Novel Intrusion Detection Algorithm: An AODV Routing Protocol” developed Mobile ad-hoc network (MANET) is a collection of movable nodes capable of self-routing, constraining energy and decentralized handling of nodes. It faces many challenges due to uncertainty of network topology i.e. security and congestion. In this paper we propose a novel algorithm for intrusion detection gainst attacks such as probing, Denial-of-service (DoS), vampire and User-To-Root (U2R) in a MANET environment. The attack detection has been carried out using a profile (behaviour) analysis and a confusion matrix (True positives, True negatives, False positives, False negatives). The performance of a standard Adhoc On-Demand Distance Vector (AODV) routing protocol has been reported for all 4 types of attack in a network simulator-2(ns-2) environment. To the best of authors’ knowledge, this is the first paper reporting a novel intrusion detection algorithm using behaviour analysis for an AODV protocol in a MANET environment [1].
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Traffic Congestion Control

Traffic Congestion Control

Reader and Database. RFID is a wireless technology that uses radiofrequency electromagnetic energy to carry information between the RFID tag and RFID reader. Some RFID systems will only work within the range inches or centimeters while others may work for 100 meters (300 feet) or more. Various types of tags are available but we can mainly divide them into two categories:Passive tags and active tags. The passive tags don’tcontain any internal power source. The active tags contain a battery as an internal power source used to operate microchip’s circuitry and to broadcast theinformation to the reader. The range and cost of these tags is more as compare to passive tags. A GSM modem is a specialized type of modem, which accepts a SIM card and operates over a subscription to a mobile operator, just like a mobile phone. GPS is also used along with the RFID in order to locate the position of vehicle whenever theft occurs.PIC 16F877A is used here to control all the processes that are involved and Fire Brigade are also stuck in traffic and waste their valuable time. The proposed system provides quality of service to Emergency vehicles and improves the accuracy of Automatic Traffic Light Violation Detection system as well as helps to trace out the stolen vehicles using RFID The traffic light control plays a vital role in any intelligent traffic management system. The green light sequence and green light duration are the two key aspects to be considered in traffic light control. In many countries, most traffic lights feature fixed sequences and light length duration. Fixed control methods are however only suitable for stable and regular traffic, but not for dynamic traffic situations. Looking at the present state of practice, the green light sequence is determined without taking the possible presence of emergency vehicles into account. Therefore, emergency vehicles such as ambulances, police cars, fire engines, etc. must wait in traffic at an intersection as depicted which delays their arrival at their destination causing loss of lives and property. In Ireland, an average of
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