Priority-based rate control for service differentiation and congestion control in wireless multimedia sensor networks

Yaghmaee, Mohammad Hossein; Adjeroh, Donald A.

doi:10.1016/j.comnet.2009.02.011

Cited by 119 publications

(82 citation statements)

References 14 publications

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“…In recent years, several congestion control protocols have been proposed for WMSNs [39][40] [41]. These protocols can be divided into four categories depending on how they detect the presence of congestion and how they control congestion.…”

Section: Congestion Control Protocols In Wmsnsmentioning

confidence: 99%

“…PCCP has several known weaknesses as outlined in [41]. The first known weakness of PCCP is the unfairness of the rate adjustment during the different congestion conditions.…”

Section: Priority Aware Protocolsmentioning

confidence: 99%

“…The last weakness of PCCP is that it considers constant service time of packets which cannot be relied on as the wireless transmission media is prone to changes [41].…”

Section: Priority Aware Protocolsmentioning

confidence: 99%

“…A known weakness of CCF is low utilization of the available capacity when certain nodes do not have any data to send or when they become idle for a long period [41]. Its rate adjustment strategy also yields low utilization because it depends on the service time to calculate the new rates.…”

Section: Priority Aware Protocolsmentioning

confidence: 99%

“…Another reason why WRR is preferred to a First In First Out (FIFO) scheduler for example, is that it is designed to better handle traffic classes with different requirements, which is the case for our system design [41]. After packets have been served by the scheduler, they go to the outgoing link where they are sent on to the appropriate node.…”

Section: Figure 32: Wrr Schedulermentioning

confidence: 99%

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A Priority Rate-Based Routing Protocol for Wireless Multimedia Sensor Networks

Tshiningayamwe

Lusilao-Zodi

Dlodlo

2015

Advances in Intelligent Systems and Computing

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The development of affordable hardware has made it possible to transmit multimedia data over a wireless medium using sensor devices. Deployed sensors span larger geographical areas, generating different kinds of traffic that need to be communicated either in real-time or non-realtime mode to the sink. The tiny sized design of sensor nodes has made them even more attractive in various environments as they can be left unattended for longer periods.Since sensor nodes are equipped with limited resources, newer energy-efficient protocols and architectures are required in order to meet requirements within their limited capabilities when dealing with multimedia data. This is because multimedia applications are characterized by strict quality of service requirements that distinctively differentiate them from other data types during transmission. However, the large volume of data produced by the sensor nodes can easily cause traffic congestion making it difficult to meet these requirements. Congestion has negative impacts on the data transmitted as well as the sensor network at large. Failure to control congestion will affect the quality of multimedia data received at the sink and further shorten the system lifetime.Next generation wireless sensor networks are predicted to deploy a different model where service is allocated to multimedia while bearing congestion in mind. Applying traditional wireless sensor routing algorithms to wireless multimedia sensor networks may lead to high delay and poor visual quality for multimedia applications.In this research, a Priority Rate-Based Routing Protocol (PRRP) that assigns priorities to traffic depending on their service requirements is proposed. PRRP detects congestion by using adaptive random early detection (A-RED) and a priority rate-based adjustment technique to control congestion.We study the performance of our proposed multi-path routing algorithm for real-time traffic when mixed with three non real-time traffic each with a different priority: high, medium or low. Simulation results show that the proposed algorithm performs better when compared to two existing algorithms, PCCP and PBRC-SD, in terms of queueing delay, packet loss and throughput.vi

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Section: Congestion Control Protocols In Wmsnsmentioning

confidence: 99%

“…PCCP has several known weaknesses as outlined in [41]. The first known weakness of PCCP is the unfairness of the rate adjustment during the different congestion conditions.…”

Section: Priority Aware Protocolsmentioning

confidence: 99%

“…The last weakness of PCCP is that it considers constant service time of packets which cannot be relied on as the wireless transmission media is prone to changes [41].…”

Section: Priority Aware Protocolsmentioning

confidence: 99%

Section: Priority Aware Protocolsmentioning

confidence: 99%

Section: Figure 32: Wrr Schedulermentioning

confidence: 99%

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A Priority Rate-Based Routing Protocol for Wireless Multimedia Sensor Networks

Tshiningayamwe

Lusilao-Zodi

Dlodlo

2015

Advances in Intelligent Systems and Computing

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A Class of Cross‐Layer Optimization Design for Congestion and Energy Efficiency with Compressed Sensing in Wireless Sensing Networks

Li¹,

Jing²,

Li³

2013

Asian Journal of Control

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In wireless sensor networks (WSNs), the congestion problem not only causes packet loss, but also leads to an increase in delays and energy consumption. The actual performance of wireless sensor networks (WSNs) can be severely influenced by the quality of the communication channel and the bit in transmission. In this paper, the distributed protocols, which attain global optimum control for signals by the compressed sensing technique and achieve fair channel allocation by the scheduling algorithm, are proposed for WSNs. We take into account the congestion problem by robust optimization with congestion ratio for two classic aspects in energy limited WSNs: minimum transmission rate and maximum transmitted information. To achieve the goal, three protocols are developed. In the first protocol, the desired control input is designed based on the compressed sensing technique. A minimal bit of signal is provided to reduce the transmission flow for the congestion model. The second protocol is resource allocation. The resources can be allocated increasingly to the channel in order to avoid more severe congestion. This can also avoid conservative reduction of resource allocation for eliminating congestion. Channel selection abides by the fair resource allocation principle. The above protocols separately are implemented through a congestion ratio at network layer, transport layer, and MAC layer. Simulation results demonstrate that the proposed algorithm effectively relieves congestion, and achieves higher throughput and lower energy consumption.

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Tournament‐based congestion control protocol for multimedia streaming in ubiquitous sensor networks

Lee

Jeong

Lian

2010

Int J Communication

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SUMMARYCongestion in the ubiquitous sensor network occurs when traffic load exceeds available capacity at any point in a network. Congestion causes overall channel quality to degrade and loss rates to rise, leads to buffer drops and increases latencies. Therefore, congestion and latency have effects on energy efficiency, memory size, buffer size, and throughput. This paper proposes a new method, called TCCP (Tournamentbased Congestion Control Protocol), to minimize congestion in the ubiquitous sensor network. In this paper, the winner is the stream with the highest importance level in the competition of ubiquitous sensor network. In general, there are a lot of congestion and delay in the continuous streaming of multimedia streams with lower importance level. The proposed method consists of three parts: tournament decision, best-fit control strategy and service differentiation. The final winner in the tournament controls congestion effectively, minimizes packet loss due to congestion, decreases energy consumption, and improves QoS. The simulation result shows that the proposed method is more effective and has better performance compared with those of CCF (congestion control and fairness), PCCP (priority based congestion control protocol), and CODA (congestion detection and avoidance).

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Priority-based rate control for service differentiation and congestion control in wireless multimedia sensor networks

Cited by 119 publications

References 14 publications

A Priority Rate-Based Routing Protocol for Wireless Multimedia Sensor Networks

A Priority Rate-Based Routing Protocol for Wireless Multimedia Sensor Networks

A Class of Cross‐Layer Optimization Design for Congestion and Energy Efficiency with Compressed Sensing in Wireless Sensing Networks

Tournament‐based congestion control protocol for multimedia streaming in ubiquitous sensor networks

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