RACE: A Real-Time Scheduling Policy and Communication Architecture for Large-Scale Wireless Sensor Networks

Mizanian, Kambiz; Hajisheykhi, Reza; Baharloo, Mohammad; Jahangir, Amir Hossein

doi:10.1109/cnsr.2009.84

Cited by 15 publications

(9 citation statements)

References 4 publications

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“…For solving the existing problem in [8,9], the contribution [10] introduced an improving scheduling strategy, EF-RM (emergency task first rate monotonic), which is the preemptive scheduling for both periodical and nonperiodical tasks to ensure the implementation of the important task of priority in TinyOS. The contribution [11] proposed the IS-EDF (idle sleep-earliest deadline first) scheduling strategy, which adjusts the priority of tasks dynamically to ensure that the important task is realtime processed. In this paper, through further research on the relevant contributions mentioned above, we propose the priority queue-based data processing model for multitask network and deduce the theoretical formulas of the QoS of network with the proposed model, including average queue length, delay, and delay jitter.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Multitask Scheduling Model for Wireless Sensor Networks

Yin

et al. 2014

Journal of Applied Mathematics

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The sensor nodes of multitask wireless network are constrained in performance-driven computation. Theoretical studies on the data processing model of wireless sensor nodes suggest satisfying the requirements of high qualities of service (QoS) of multiple application networks, thus improving the efficiency of network. In this paper, we present the priority based data processing model for multitask sensor nodes in the architecture of multitask wireless sensor network. The proposed model is deduced with the M/M/1 queuing model based on the queuing theory where the average delay of data packets passing by sensor nodes is estimated. The model is validated with the real data from the Huoerxinhe Coal Mine. By applying the proposed priority based data processing model in the multitask wireless sensor network, the average delay of data packets in a sensor nodes is reduced nearly to 50%. The simulation results show that the proposed model can improve the throughput of network efficiently.

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Section: Introductionmentioning

confidence: 99%

An Efficient Multitask Scheduling Model for Wireless Sensor Networks

Yin

et al. 2014

Journal of Applied Mathematics

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“…Mizanian et al [28] arranged RACE, bundle programming approach and directing algorithmic system for period enormous scale detecting component organizes that uses a circle free Bellman-Ford algorithmic project to search out routes with the base movement load and postpone in the middle of supply and destination. RACE utilizes the Earliest point as a part of time starting (EDF) programming thought to send parcels with soonest point in time.…”

Section: Deadlinementioning

confidence: 99%

Packet Scheduling for Wireless Sensor Network

Reddy¹

2014

IJWD

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“…Q-MAC [9] can balance the tradeoff between energy consumption and the sleeping delay in query-based sensor networks by predicting nodes' wake-up time using query commands. The authors of [10] presented and evaluated a packet scheduling policy and routing algorithm called RACE that inherently accounts for time constraints. However, both Q-MAC and the sleep scheduling in [10] only aimed to minimize but not guarantee the end-to-end delay.…”

Section: Related Workmentioning

confidence: 99%

“…The authors of [10] presented and evaluated a packet scheduling policy and routing algorithm called RACE that inherently accounts for time constraints. However, both Q-MAC and the sleep scheduling in [10] only aimed to minimize but not guarantee the end-to-end delay. The authors of [11] proposed a methodology to provide a time-division cluster scheduling (TDCS) mechanism.…”

Section: Related Workmentioning

confidence: 99%

Adaptive Scheduling and Routing Scheme for Delay Guarantee in Wireless Sensor Networks

Sun

Chen

Luo

2013

International Journal of Distributed Sensor Networks

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In wireless sensor networks (WSNs), periodical sleeping scheme on sensor nodes is an effective way to save energy. However, it will hinder the capability of the network to provide real-time data reporting due to relay node being sleep. Motivated by this, we propose an adaptive scheduling and routing scheme for guaranteeing dynamic end-to-end delay requirement while minimizing the energy consumption. First of all, we utilize an optimal wake-up scheduling algorithm to achieve the initial wake-up schedules and routes and design an adaptive adjustment algorithm. When the end-to-end delay requirement of a region changes, our proposed adaptive adjustment algorithm can locally adjust the wake-up schedules or the routing tables of the nodes which are the nearest ones to the source node, so as to minimize energy consumption and the impact on other regions while guaranteeing the new end-to-end delay requirement of the region. Through experiments in a real wireless sensor network and extensive simulations, we can get that the proposed scheme can conserve at least 20% energy consumption comparing to other existing adjustment algorithms, and its performance approaches that of the optimal solution.

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RACE: A Real-Time Scheduling Policy and Communication Architecture for Large-Scale Wireless Sensor Networks

Cited by 15 publications

References 4 publications

An Efficient Multitask Scheduling Model for Wireless Sensor Networks

An Efficient Multitask Scheduling Model for Wireless Sensor Networks

Packet Scheduling for Wireless Sensor Network

Adaptive Scheduling and Routing Scheme for Delay Guarantee in Wireless Sensor Networks

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