QoS in Wireless Multimedia Sensor Networks: A Layered and Cross-Layered Approach

Hamid, Zara; Hussain, Faisal

doi:10.1007/s11277-013-1389-0

Cited by 41 publications

(30 citation statements)

References 53 publications

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“…Cross-layer protocols improve the communication performance by merging the information of different layers jointly; for example, the network layer can decide how to route by incorporating the congestion information from the transport layer and the link quality value from the MAC layer. This incorporation of different layers improves the Wireless Communications and Mobile Computing 3 communication quality and maximizes the network lifetime [13][14][15]. Data prediction technique builds the prediction model which describes the data evolution of the sensed phenomenon within certain error bounds.…”

Section: Related Workmentioning

confidence: 99%

“…Data compression [2][3][4], data aggregation [5,6], topology control [7,8], energy-aware 2 Wireless Communications and Mobile Computing protocol [9][10][11][12][13][14][15], data prediction [16], and sink mobility [17,18] were commonly applied to conserve the energy, while delay-aware routing [10,19] and delay-aware MAC [20,21] were widely used to optimize the response delay. These past works improved the energy and delay performance of the WMSN significantly.…”

Section: Introductionmentioning

confidence: 99%

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Energy and Delay Optimization of Heterogeneous Multicore Wireless Multimedia Sensor Nodes by Adaptive Genetic‐Simulated Annealing Algorithm

Liu

Zhou

Xiang

et al. 2018

Wireless Communications and Mobile Computing

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Energy efficiency and delay optimization are significant for the proliferation of wireless multimedia sensor network (WMSN). In this article, an energy-efficient, delay-efficient, hardware and software cooptimization platform is researched to minimize the energy cost while guaranteeing the deadline of the real-time WMSN tasks. First, a multicore reconfigurable WMSN hardware platform is designed and implemented. This platform uses both the heterogeneous multicore architecture and the dynamic voltage and frequency scaling (DVFS) technique. By this means, the nodes can adjust the hardware characteristics dynamically in terms of the software run-time contexts. Consequently, the software can be executed more efficiently with less energy cost and shorter execution time. Then, based on this hardware platform, an energy and delay multiobjective optimization algorithm and a DVFS adaption algorithm are investigated. These algorithms aim to search out the global energy optimization solution within the acceptable calculation time and strip the time redundancy in the task executing process. Thus, the energy efficiency of the WMSN node can be improved significantly even under strict constraint of the execution time. Simulation and real-world experiments proved that the proposed approaches can decrease the energy cost by more than 29% compared to the traditional single-core WMSN node. Moreover, the node can react quickly to the time-sensitive events.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Energy and Delay Optimization of Heterogeneous Multicore Wireless Multimedia Sensor Nodes by Adaptive Genetic‐Simulated Annealing Algorithm

Liu

Zhou

Xiang

et al. 2018

Wireless Communications and Mobile Computing

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“…While, NRT has lower QoS requirements on latency and high packet delivery, which is used to transmit text, pictures, etc. SQ-MAC can achieve QoS-aware function through realizing service differentiation of two traffic classes [12,13].…”

Section: Sq-mac Designmentioning

confidence: 99%

Untitled

2017

IJCSI

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Considering traditional MAC protocols for Wireless Sensor Networks cannot provide service differentiation for different traffic classes, we propose a Self-adaption QoS-aware MAC protocol (SQ-MAC). The protocol can provide collision-free time slots for nodes, and take different contention window size for different traffic classes. It can also introduce virtual multiqueue and relatively fair scheduling mechanism for data packets. Simulation results show that, compared with the low priority traffic, the transmission quality of high priority traffic is effectively improved, in terms of packet delivery ratio, latency and so on. Additionally, compared with S-MAC and DQ-MAC, SQ-MAC also maintains a good network performance.

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“…In order to achieve high gains in the overall performance of WSN, cross-layer interaction is used in the design of proposed protocol. The concept of cross-layer design is about sharing of information among two or more layers for adaptation purposes and to increase the inter-layer interactions [19][20][21]. The proposed system uses interaction between physical layer, Mac layer and network layer in order to select the next optimal forwarding node.…”

Section: Cross-layer Design In the Proposed Protocolmentioning

confidence: 99%

CARPM: Cross Layer Ant Based Routing Protocol for Wireless Multimedia Sensor Network

Abazeed

Saleem

Zubair

et al. 2015

Ad-Hoc Networks and Wireless

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Abstract. Applying multimedia to Wireless Sensor Network (WSN) adds more challenges due to WSN resource constraints and the strict Quality of Service (QoS) requirements for multimedia transmission. Different multimedia applications may have different QoS requirements, so routing protocols designed for Wireless Multimedia Sensor Network (WMSN) should be conversant of these requirements and challenges in order to ensure the efficient use of resources to transfer multimedia packets in an utmost manner. The majority of solutions proposed for WMSN depends on traditional layered based mechanisms which are inefficient for multimedia transmission. In this paper we propose a crosslayer Ant based Routing Protocol for WMSN (CARPM) by using modified ant colony optimization (ACO) technique to enhance the routing efficiency. The proposed protocol uses an improved ACO to search for the best path that are satisfied with the multimedia traffic requirements. While making best decision the weightage is given to energy consumption, and queuing delay. The proposed cross layer scheme works between the routing, MAC, and physical layers. Since, the remaining power and timestamp metrics are exchanged from physical layer to network layer. Dynamics duty cycle assignment is proposed at MAC layer which changes according to traffic rate. The presented algorithm is simulated using NS2 and is proven to satisfy its goals through a series of simulations.

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QoS in Wireless Multimedia Sensor Networks: A Layered and Cross-Layered Approach

Cited by 41 publications

References 53 publications

Energy and Delay Optimization of Heterogeneous Multicore Wireless Multimedia Sensor Nodes by Adaptive Genetic‐Simulated Annealing Algorithm

Energy and Delay Optimization of Heterogeneous Multicore Wireless Multimedia Sensor Nodes by Adaptive Genetic‐Simulated Annealing Algorithm

Untitled

CARPM: Cross Layer Ant Based Routing Protocol for Wireless Multimedia Sensor Network

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