Energy Efficient and Delay Optimized TDMA Scheduling for Clustered Wireless Sensor Networks

Shi, Liqi; Fapojuwo, Abraham O.

doi:10.1109/wcnc.2009.4917709

Cited by 6 publications

(4 citation statements)

References 16 publications

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“…This increases computations and power utilization of nodes. Liqi Shi and Abraham O. Fapojuwo [20] propose Energy Efficient and Delay Optimized TDMA Scheduling for Clustered Wireless Sensor Networks with cross layer optimization model at physical, link and network layer.…”

Section:  Power Management At Application Layer Using Cross Layeringmentioning

confidence: 99%

Evidence-based Power Management in Distributed Sensor Networks

Wesley

Mir²,

Patel³

et al. 2013

Modelling, Identification and Control / 801: Advances in Computer Science

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A novel evidence-based approach to energy management in distributed sensor networks (DSNs) is presented. Current approaches and algorithms to DSN energy management are "bottom up" in that they do not consider aspects of the domain of application and particular geographic and environmental situational dynamics to manage energy usage as efficiently as possible. Results from an evidential approach to DSN energy management in a forest fire monitoring and management application are presented. A body of mathematics called evidential reasoning is used to represent and integrate information about the situational dynamics and forest fire detection and monitoring application to draw inferences about the state of nodes in a distributed network. An 18% improvement in energy efficiency compared to the LEACH-C algorithm was observed when the state of the forest environment and knowledge about the dynamics of forest fires are considered managing the state and activity of the DSN. Simulation results using NS2 suggest that the useful life of DSNs can be extended significantly if the situational dynamics and aspects of the domain of application are taken into account.

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Section:  Power Management At Application Layer Using Cross Layeringmentioning

confidence: 99%

Evidence-based Power Management in Distributed Sensor Networks

Wesley

Mir²,

Patel³

et al. 2013

Modelling, Identification and Control / 801: Advances in Computer Science

View full text Add to dashboard Cite

show abstract

“…This value, for example, can be calculated using the cross-layer optimization models as presented in [13] and [14]. Assume the traffic on all the active links is divided into equally portioned flows, T (in bps, <R), and two flows with rate T belong to the same reuse set only if they are transmitted simultaneously (i.e., assigned the same time slots).…”

Section: System Modelmentioning

confidence: 99%

“…5, in which the distance between two neighboring nodes in the same row or column is 10 meters. The flows on all links in this network are derived based on the least energy consumption model proposed in [14]. Set T =0.2 kbps, we get M=42 according to (7).…”

Section: Assumementioning

confidence: 99%

Energy efficient reuse set formulation with end-to-end packet loss constraint in TDMA based wireless sensor networks

Shi

Fapojuwo

2009

Proceedings of the 2009 International Conference on Wireless Communications and Mobile Computing: Connecting the World Wireless

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In this paper, we propose an algorithm which is capable of forming reuse sets of links in time division multiple access (TDMA) based wireless sensor networks (WSNs) to gain less frame length. For each reuse set, we use linear programming to achieve optimal energy consumption. We further show how to apply this algorithm with endto-end packet loss rate constraint. The major contribution of this paper is twofold. First, the proposed scheme gives an energy efficient way to support quality of service (QoS) requests such as delay (by reduced frame length) and end-to-end packet loss rate. Secondly, the relationships amongst energy consumption, frame length (thus delay) and packet loss rate in WSNs revealed in this paper can be utilized in designing WSNs with delay and packet loss constraints.

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“…Its focus is on the computation of optimal transmission power, routing, and duty-cycle schedule that optimize the energy-efficiency of WSNs. In [4], a TDMA scheduling algorithm for energy efficiency and optimized delay is proposed based on a cross-layer optimization mode for clustered WSNs. The system model combines physical, MAC and network layers for wide energy conservation.…”

mentioning

confidence: 99%

Cross-layer energy efficiency analysis and optimization in WSN

Tang

Sun

Liang

2010

2010 International Conference on Networking, Sensing and Control (ICNSC)

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Energy conversation is a critical problem in wireless sensor networks (WSNs) so that the energy consumption must be minimized while satisfying application requirements. The energy efficiency can be supported across all layers of the protocol stack. In this paper, we propose and analyze a cross-layer energy efficiency model, which takes routing layer, MAC layer, data link layer, hardware circuitry, and battery discharge nonlinearity into account. For successfully delivering all data generated by source nodes to the sink node with minimal network energy consumption, we consider two orthogonal modulation schemes of M-ary pulse position modulation (PPM) and frequency shift keying (FSK), and distribute an appropriate time slot to every link so that the optimal routing can be obtained. Based on the model, we formulate the optimization problem of minimizing network energy consumption and solve it by existed approaches. The numerical results show that, if PPM scheme is adopted, the cross-layer energy efficiency model with optimal routing has up to 99% lower network energy consumption than that with a uniform single-hop routing in general WSN, and the optimal model also exists 93% energy saving if FSK is used. Multi-hop routing is more energy efficiency than single-hop routing in general WSN, while single-hop routing is more preferable in dense WSN. I. INTRODUCTIONn a typical WSN, nodes are powered by non-rechargeable batteries and thus energy is a scarce resource. It is imperative that energy conservation is considered across all layers of the protocol stack in order to minimizing the total network energy consumption and prolong the operational lifetime of the network.WSNs have extensive potential applications. Nodes of a WSN are generally deployed to collect the interested data (temperature, chemicals, etc.) or just sense the presence or the absence of a phenomenon of interest in an information field.

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Energy Efficient and Delay Optimized TDMA Scheduling for Clustered Wireless Sensor Networks

Cited by 6 publications

References 16 publications

Evidence-based Power Management in Distributed Sensor Networks

Evidence-based Power Management in Distributed Sensor Networks

Energy efficient reuse set formulation with end-to-end packet loss constraint in TDMA based wireless sensor networks

Cross-layer energy efficiency analysis and optimization in WSN

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