An approach for congestion control in sensor network using priority based application

In wireless sensor networks congestion occurs in intermediate nodes while data packets travel from source to sink. Congestion causes packet loss which in turn drastically decreases network performance and throughput As sensors are energy constraint so it is a decisive task to detect the congestion and congested regions in a network to perform congestion control. In addition to that different application i.e. real time and non-real time data in sensor network have different QoS (delay, link utilization, and packet loss) guarantee requirement In this paper we proposed a new QoS adaptive cross-layer approach to control the congestion and support QoS guarantee for different application data in sensor network. This approach maintains two congestion control algorithm to control namely short-term and long-term congestion. To ensure real time and non-real time data flow, hop-by-hop QoS aware scheduling and QoS distributed MAC Manager are considered. The experimental outputs of this work are able to show that proposed scheme gives guaranteed QoS for different application data and gives a noticeable performance in terms of energy analysis and lifetime of the network.

Congestion control is an important factor for performance improvement in wireless sensor networks (WSNs). Congestion occurs due to various reasons including a variation in the data rate between incoming and outgoing links, buffer size, flooding attacks and multiple inputs and minimum output capability. Various outcomes of congestion in sensor networks include immense packet loss or packet drop, fast energy depletion, unfairness across the network, reduced node performance and increased delay in packet delivery. Hence, there is an extreme need to check channel congestion in order to enhance the performance with better congestion management. The job of choosing a suitable congestion control technique is a challenging task for the network designer. In this article, the authors traverse through the underlying conceptual ideas on congestion control schemes which come under six unique models. This article highlights a survey on the existing works done so far on congestion control domains in sensor networks. A comparative analysis based on Quality of Service parameters has been discussed.

Congestion in Wireless Multimedia Sensor Networks (WMSN) may cause packet loss, buffer overflow and increases queueing delay, which has a significant negative impact on the network performance and reliability. This problem imposes more resource constraints that involve energy consumption and buffer size to meet additional requirements such as desired buffer size and limited amount of packet loss. One of the fundamental issues of congestion problem in such networks is the queue management. In fact, handling congestion without considering flexible buffer management and queueing methods, stay insignificant against dropping rate and packet loss. Consequently, a novel congestion control approach is needed to overcome these problems. In this paper, a new queue management mechanism called: Priority Queue Management based Explicit Congestion Control (PQMECC) is proposed and modeled using Stochastic Automata Networks, which are appropriate for modeling and analyzing complex systems with interacting components and complex synchronization. The congestion control technique used in PQMECC is based on priority, load repartition mechanism and explicit congestion notification which is generated only if the congestion reaches the threshold value.

In wireless multimedia sensor networks (WMSNs) a sensor node may have different types of sensor which gather different kinds of data. To support quality of service (QoS) requirements for multimedia applications having a reliable and fair transport protocol is necessary. One of the main objectives of the transport layer in WMSNs is congestion control. We observe that the information provided may have different levels of importance and argue that sensor networks should be willing to spend more resources in disseminating packets carrying more important information. In WMSN event-driven applications, it is critical to report the detected events in the area, resulting in sudden bursts of traffic due to occurrence of spatially-correlated or multiple events, causing loss of data. Also, nodes have very limited power due to hardware constraints. Packet losses and retransmissions resulting from congestion, cost precious energy and shorten the lifetime of sensor nodes. Till now, in WMSNs, Congestion control techniques are based on detection of congestion and recovery, but they cannot eliminate or prevent the occurrence of congestion. Collision is a symptom of congestion in the wireless channel and can result in a time-variant channel capacity. The main intention of this protocol is to be used as a mechanism for reducing congestion in the network by free resources to set accurate rates and priority data needs. If two nodes send their packets in the shortest path to the parent node in a crowded place, a source node must prioritize the data and uses data that have lower priorities of a suitable detour nodes consisting of low or non- active consciously. Proposed algorithm is applied to the nodes near the base station (which convey more traffic) after the congestion detection mechanism detected the congestion. The results obtained from simulation test done by NS-2 simulator indicate that the proposed model is more innovative and presents better performance in compare with CCF, PCCP and DCCP protocols.

Sink-to-sensors congestion control

The main essence of this proposed method for the control of congestion in VANET is exploiting the already existing resources of the network and at the same time preventing the unnecessary overheads of nodes as well as links of a network. The control of congestion in the networks such as vehicular ad hoc suffers through a special kind of challenges. These challenges are the consequences of the environmental specificities such as frequently changing of the topology, large amount of variations in the nodes density, nature of the communication in broadcasting and the configurational characteristics of the neighbor etc. Keeping above described point into mind, we proposed a technique for the control of unnecessary congestion by reducing the number of transmitting messages in VANET. It supports discarding of similar types of messages. Here each node consists of a neighbor table for comparing the incoming messages with the previous messages. The information from the message is extracted and the values are compared with the values of neighbor table using a database query. If a match is found then the corresponding message field in the table is updated else a new entry is added in the table and the message is transferred to control queue (CQ) or the service queue (SQ).After being processed the entry is deleted from the queue as well as table. The working efficiency of this developed method is determined on the ground of the average delay of these three main types of messages v/s its mean message size.

In the Wireless Multimedia Sensor Networks (WM-SNs) field, real-time multimedia flow increases the probability of collision and congestion in sensor network which degrade the performance of Quality of Service (QoS). How to meet the high QoS requirement of WMSNs applications under the condition of energy constraint is a crucial issue. In this paper, we propose a predicted available bandwidth estimation based dynamic multi-channel allocation mechanism, non-overlapping channels is dynamically deployed according to the channel allocated admission algorithm for the different application loads. Further, energy consumption model called energy per successfully transmitted bits (ESTB) based on CSMA-CA procedure of IEEE 802.15.4 standard is introduced to offer more objective analysis on the estimation of energy consumption. Simulation result shows the dynamic multi-channel allocation approach perform better than benchmark on the metrics of reliability and latency, achieves the trade-off between energy efficiency and QoS requirement.

In this paper we propose a distributed congestion control algorithm for tree based communications in wireless sensor networks, that seeks to adaptively assign a fair and efficient transmission rate to each node. In our algorithm, each node monitors its aggregate output and input traffic rates. Based on the difference of the two, a node then decides either to increase or decrease the bandwidth allocable to a flow originating from itself and to those being routed through it. Since the application requirements in sensor network follows no common trait, our design abstracts the notion of fairness, allowing for the development of a generic utility controlling module. Such separation of the utility and fairness controlling modules enables each one to use a separate control law, thereby portraying a more flexible design. The working of our congestion control is independent of the underlying routing algorithm and is designed to adapt to changes in the underlying routing topology. We evaluate the performance of the algorithm via extensive simulations using an event-driven packet level simulator. The results suggest that the proposed protocol acquires a significantly high goodput of around 95% of the actual transmission rate, converges quickly to the optimal rate, and attains the desired fairness.

The Internet has always done a remarkable job at surprising people. Technology oscillates, and some envisioned architectures of the future fail while others thrive. From the origination of peer-to-peer computing, it became easier task for communication and information transfer. But there exists still few hysterical issues like congestion, and security. Congestion occurs when one part of subnet becomes overloaded. The means of moderating the traffic in the networks is referred as congestion control. This paper critically analyses various issues behind congestion in various networks and various techniques to avoid and prevent from congestion and to efficiently control the congestion in the networks. This paper essentially focuses on the future networks posing various challenges and exposed issues regarding congestion control.

Congestion control in Cluster Wireless Sensor Networks (CWSNs) has drawn widespread attention and research interests. The increasing number of nodes and scale of networks cause more complex congestion control and management. Active Queue Management (AQM) is one of the major congestion control approaches in CWSNs, and Random Early Detection (RED) algorithm is commonly used to achieve high utilization in AQM. However, traditional RED algorithm depends exclusively on source-side control, which is insufficient to maintain efficiency and state stability. Specifically, when congestion occurs, deficiency of feedback will hinder the instability of the system. In this paper, we adopt the Additive-Increase Multiplicative-Decrease (AIMD) adjustment scheme and propose an improved RED algorithm by using neighbor feedback and scheduling scheme. The congestion control model is presented, which is a linear system with a non-linear feedback, and modeled by Lur’e type system. In the context of delayed Lur’e dynamical network, we adopt the concept of cluster synchronization and show that the congestion controlled system is able to achieve cluster synchronization. Sufficient conditions are derived by applying Lyapunov-Krasovskii functionals. Numerical examples are investigated to validate the effectiveness of the congestion control algorithm and the stability of the network.

Information-centric networking (ICN) is expected to be a candidate for future internet architecture, and it supports features such as multicast that improves bandwidth utilization and transmission efficiency. However, multicast itself does not provide congestion control. When multiple multicast groups coexist, multicast traffic may exhaust all network resources, and cause network congestion and packet loss. Additionally, traditional IP multicast congestion control mechanisms cannot be directly applied to ICN architecture. Therefore, it is necessary to consider an effective congestion control mechanism for ICN multicast. This paper proposes a single-rate multicast congestion control mechanism, called SRMCC. It supports router-assisted awareness of the network congestion state and congestion control message aggregation. Moreover, the fair shared rate estimation method is innovatively proposed to achieve protocol fairness. Most importantly, it adjusts the rate according to different congestion states indicated by the queue occupancy ratio. By introducing a rate selection factor, it can achieve a balance between packet loss rate and throughput. Experimental results show that our proposal outperforms other mechanisms in throughput, packet loss rate, total bandwidth utilization, and overhead, and achieves protocol fairness and better TCP friendliness.

Due to the relatively high node density and source-to-sink communication pattern, wireless sensor networks (WSNs) are subject to congestion and packet losses. Further, the availability of low-cost hardware, such as Cyclops cameras, is promoting wireless multimedia sensing to support, for example, visual surveillance. As a result, congestion control is becoming more critical in WSNs. In this paper, we present a lightweight distributed congestion control method in WSNs. We develop new metrics to detect congestion in each node by considering the queue lengths and channel conditions observed in the one-hop neighborhood. Based on the estimated level of congestion, each node dynamically adapts its packet transmission rate and balance the load among the one-hop neighbors to avoid creating congestion and bottleneck nodes. In a simulation study performed in OMNeT++, our approach significantly enhances the end-to-end (e2e) packet delivery ratio and reduces the e2e delay without increasing the total energy consumption compared to the tested baseline approach.

Normally sensor nodes are located at unattended environment which has low battery power. The wireless hypermedia sensor based networks have huge capacity and continuous flow of data from source to sink. Congestion arises at the time of incoming data is greater than available resources. The congestion causes packet loss, buffer over flow, energy wastage and increases end to end delay. The proposed method Dynamic Alternate Buffer switching and Congestion Control is used to manage congestion in an efficient manner. In which congestion is detected based on remaining buffer, remaining energy and trust level of the sensor nodes. This approach is based on cost evaluation method which decides primary and spare buffers at run time. This method is used to enable dynamic buffer switching and optimize the effect of congestion. The performance of BETCC compared with various existing protocol like TCEER and TFCC in terms of energy consumption and data loss ratio.

Congestion control in wireless sensor networks based on bird flocking behavior

High-speed networks with large delays present a unique environment where TCP may have a problem utilizing the full bandwidth. Several congestion control proposals have been suggested to remedy this problem. The existing protocols consider mainly two properties: TCP friendliness and bandwidth scalability. That is, a protocol should not take away too much bandwidth from standard TCP flows while utilizing the full bandwidth of high-speed networks. This work presents another important constraint, namely, RTT (round trip time) unfairness where competing flows with different RTTs may consume vastly unfair bandwidth shares. Existing schemes have a severe RTT unfairness problem because the congestion window increase rate gets larger as the window grows ironically the very reason that makes them more scalable. RTT unfairness for high-speed networks occurs distinctly with drop tail routers for flows with large congestion windows where packet loss can be highly synchronized. After identifying the RTT unfairness problem of existing protocols, This work presents a new congestion control scheme that alleviates RTT unfairness while supporting TCP friendliness and bandwidth scalability. The proposed congestion control algorithm uses two window size control policies called additive increase and binary search increase. When the congestion window is large, additive increase with a large increment ensures square RTT unfairness as well as good scalability. Under small congestion windows, binary search increase supports TCP friendliness. The simulation results confirm these properties of the protocol.