Congestion control mechanisms in wireless sensor networks: A survey

Ghaffari, Ali

doi:10.1016/j.jnca.2015.03.002

Cited by 208 publications

(119 citation statements)

References 58 publications

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“…Manzoor et al [1] propose quadrature-LEACH for homogenous networks which enhances stability period, network life-time and throughput quiet significantly. Yu et al [2] proposed a cluster based routing protocol for wireless sensor networks with nonuniform node distribution, the routing algorithm increases forwarding tasks of the nodes in scarcely covered areas by forcing cluster heads to choose nodes with higher energy and fewer member nodes as their next hops and finally, achieves load balance among cluster heads.…”

Section: Related Workmentioning

confidence: 99%

Topology Tree Construction and Congestion Avoidance Scheme for Diversified WSN Environment

2017

IJMTER

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Abstract-Disaster information gathering systems are constructed with diverse sensor devices. The flooding situations of the rivers/canals are monitored with the general purpose sensor devices. Congestion and unbalanced energy consumption problems are raised in the WSN due to the many to one communication requirements. Congestion Control and Energy-balanced scheme based on the hierarchy (CcEbH) is applied to manage traffic conditions. The hierarchical topology is build with three types of neighbor nodes. The same hierarchy nodes, upstream nodes and downstream nodes are assigned in the topology construction process. The congestion is detected with the queue length information of the downstream nodes. The congestion avoidance scheme reroutes the data forwarding process to other downstream nodes with energy details. The diversified sensor data collection system is build with topology tree construction and congestion avoidance scheme. Single and multiple sink based data forwarding mechanism is applied in the disaster management process. Integrated index model is used to manage the congestion and energy levels. Data aggregation and event detection tasks are combined in the system.

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Section: Related Workmentioning

confidence: 99%

Topology Tree Construction and Congestion Avoidance Scheme for Diversified WSN Environment

2017

IJMTER

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“…Congestion control is another research issue which directly affects Quality of Service (QoS) parameters such as packet delivery ratio (PDR), end to end delay and energy consumption [10]. Congestion in WSN can be at two levels: node level & link level congestion.…”

Section: Congestion Control In Wsnmentioning

confidence: 99%

“…Congestion control [10] in WSN is done in three steps: congestion detection, congestion notification & congestion control.…”

Section: Congestion Control In Wsnmentioning

confidence: 99%

Wireless Sensor Network- Challenges and Possibilities

Rathee¹,

Singh²,

Nandini³

2016

IJCA

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Wireless Sensor Network (WSN) is the current research field in computer science & has growing use in day to day life. As a new technology, it has several research challenges and vast opportunities for the researchers. This paper highlights WSN, its architecture, challenges, applications and classification of various protocols concerning it. It also classifies various security protocols to make WSN a secure network.

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“…selection of an alternate non-congested path (resource control) to forward packets to destination nodes [5], [6]. In traffic control, the sending rate of the source node is reduced to a specific value such that the number of injected packets into the network is reduced and therefore; congestion is alleviated.…”

Section: Introductionmentioning

confidence: 99%

Optimization Based Hybrid Congestion Alleviation for 6LoWPAN Networks

Al-Kashoash

Amer

Mihaylova

et al. 2017

IEEE Internet Things J.

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Abstract-The IPv6 over Low-Power Wireless Personal Area Network (6LoWPAN) protocol stack is a key part of the Internet of Things (IoT) where the 6LoWPAN motes will account for the majority of the IoT 'things'. In 6LoWPAN networks, heavy network traffic causes congestion which significantly effects the network performance and the quality of service (QoS) metrics. Generally, two main strategies are used to control and alleviate congestion in 6LoWPAN networks: resource control and traffic control. All the existing work of congestion control in 6LoWPAN networks use one of these. In this paper, we propose a novel congestion control algorithm called optimization based hybrid congestion alleviation (OHCA) which combines both strategies into a hybrid solution. OHCA utilizes the positive aspects of each strategy and efficiently uses the network resources. The proposed algorithm uses a multi-attribute optimization methodology called grey relational analysis for resource control by combining three routing metrics (buffer occupancy, expected transmission count and queuing delay) and forwarding packets through noncongested parents. Also, OHCA uses optimization theory and Network Utility Maximization (NUM) framework to achieve traffic control when the non-congested parent is not available where the optimal nodes' sending rate are computed by using Lagrange multipliers and KKT conditions. The proposed algorithm is aware of node priorities and application priorities to support the IoT application requirements where the applications' sending rate allocation is modelled as a constrained optimization problem. OHCA has been tested and evaluated through simulation by using Contiki OS and compared with comparative algorithms. Simulation results show that OHCA improves performance in the presence of congestion by an overall average of 28.36%, 28.02%, 48.07%, 31.97% and 90.35% in terms of throughput, weighted fairness index, end-to-end delay, energy consumption and buffer dropped packets as compared to DCCC6 and QU-RPL.

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Congestion control mechanisms in wireless sensor networks: A survey

Cited by 208 publications

References 58 publications

Topology Tree Construction and Congestion Avoidance Scheme for Diversified WSN Environment

Topology Tree Construction and Congestion Avoidance Scheme for Diversified WSN Environment

Wireless Sensor Network- Challenges and Possibilities

Optimization Based Hybrid Congestion Alleviation for 6LoWPAN Networks

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