Collaborative two-level task scheduling for wireless sensor nodes with multiple sensing units

Sanli, H. Ozgur; Poornachandran, R.; Çam, Hasan

doi:10.1109/sahcn.2005.1557089

Cited by 16 publications

(19 citation statements)

References 17 publications

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“…To our best knowledge, there is no work which investigates the target coverage problem for WHSNs with multiple sensing units. Even though Sanli et al (2005) thought of the situation of multiple sensing units and processed the tasks after detecting events, but did not study the coverage problem.…”

Section: Related Workmentioning

confidence: 99%

“…A wireless heterogeneous sensor network (WHSN) is a kind of WSNs but each sensor may have different capability, such as various transmission capability, different number of sensing units, and so on (Sanli et al, 2005;Shih et al, 2006). In the paper, the WHSN with multiple sensing units means that each sensor in the WHSN may be equipped with more than one sensing unit and the attribute that each sensing unit can sense may be different as well.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, if all sensing units are equipped in a sensor, the sensor will run out of energy soon. Therefore, a WHSN with multiple sensing units is a promising way to be deployed if multiple attributes are required to be sensed in the sensing field (Sanli et al, 2005;Shih et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

On target coverage in wireless heterogeneous sensor networks with multiple sensing units

Shih

Chen

Chou

et al. 2009

Journal of Network and Computer Applications

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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On target coverage in wireless heterogeneous sensor networks with multiple sensing units

Shih

Chen

Chou

et al. 2009

Journal of Network and Computer Applications

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“…Deploying sensor nodes at a large scale has been a challenge that obstructs the acceptance by the community. Task scheduling was studied to minimize the energy consumption by allocating tasks over the sensor network and scheduling the execution with respect to energy modes or sensory data of individual sensor nodes [8], [9]. Different from these studies, divisible load scheduling theory obtains an optimal distribution of the workload on a number of processors as closed-form solutions, allowing a tractable means of performance analysis [5], [6], [7], [10].…”

Section: Related Workmentioning

confidence: 99%

Sensing Workload Scheduling in Sensor Networks Using Divisible Load Theory

Liu

Kang

2007

IEEE GLOBECOM 2007-2007 IEEE Global Telecommunications Conference

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This paper presents scheduling strategies for sensing workload in wireless sensor networks using Divisible Load Theory (DLT), which offers a tractable model and realistic approach to investigate optimal scheduling issues in distributed systems. Due to the limited energy resource it is desirable that a sensor network can complete tasks as fast as possible. Sensor nodes are coordinated to perform measuring, transmitting, and processing data. Two closely related network models are presented to illustrate how the workload is scheduled among sensor nodes so that the finish time is minimized. Closed-form solutions are derived to achieve the optimization if the source node satisfies certain utility rate, which is used to evaluate the informative ratio of sensory data. Furthermore, we present the energy model for sensor nodes in the multi-hop multi-source network topology. Finally, simulation results are presented to demonstrate the effects of different parameters such as the number of sensor nodes, measurement, communication, and processing speed on the finish time and energy consumption.

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“…It allows a tractable means of performance analysis [6,9], compared to other task scheduling methods currently proposed in WSNs [10,11].…”

Section: Related Workmentioning

confidence: 99%

Coordinated Workload Scheduling in Hierarchical Sensor Networks for Data Fusion Applications

Kang

Cao

2007

2007 IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems

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We consider a sensing task scheduling problem in two-level hierarchical sensor networks. To minimize the execution time of a given task, we propose efficient scheduling strategies following the divisible load scheduling paradigm. The proposed scheduling strategies minimize the finish time by eliminating transmission collisions and idle gaps between two successive data transmissions. In-network data aggregation for sensor data is further considered at data fusion nodes. Fused data are produced by some fusion functions on original data from local clusters. The scheduling strategies consist of two phases: intra-cluster scheduling and inter-cluster scheduling. Intra-cluster scheduling deals with assigning different fractions of a sensing workload among source nodes in each cluster; inter-cluster scheduling involves the distribution of fused data among all fusion nodes. Closed-form solutions to the problem of task scheduling are derived. Energy model is described for each kind of sensor nodes, considering data acquisition, communication, and processing. Finally, simulation results are presented to demonstrate the impacts of different system parameters such as the number of sensor nodes, measurement, communication, and processing speed, on the finish time and energy consumption.

show abstract

Collaborative two-level task scheduling for wireless sensor nodes with multiple sensing units

Cited by 16 publications

References 17 publications

On target coverage in wireless heterogeneous sensor networks with multiple sensing units

On target coverage in wireless heterogeneous sensor networks with multiple sensing units

Sensing Workload Scheduling in Sensor Networks Using Divisible Load Theory

Coordinated Workload Scheduling in Hierarchical Sensor Networks for Data Fusion Applications

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