Probabilistic Bandwidth Assignment in Wireless Sensor Networks

Khan, Dawood Ashraf; Nefzi, Bilel; Santinelli, Luca; Song, Ye-Qiong

doi:10.1007/978-3-642-31869-6_55

Cited by 6 publications

(3 citation statements)

References 24 publications

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“…All these congestion control schemes do not consider traffic priorities, and require the transmission of control packets (which may be done by piggybacking). In [12] the authors propose a probabilistic approach to control the bandwidth assignment in WSNs based on the IEEE 802.15.4 standard in a tree-structured WSN. The protocol aims at obtaining the fairness among the nodes rather than among the traffic types.…”

Section: Related Workmentioning

confidence: 99%

Priority-based bandwidth allocation in wireless sensor networks

Marin

Rossi

2016

Proceedings of the 9th EAI International Conference on Performance Evaluation Methodologies and Tools

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In Wireless Sensor Networks (WSN) a set of motes monitors the environment by measuring some physical phenomena such as humidity, light, temperature, vibrations. The coexistence of different data types arises the problem of assigning the network resources in a fair way by taking into account possible different priorities among the traffic streams. In this paper we propose an allocation control scheme which is easy to implement, meets the limited resources of sensor nodes, and does not require extra control traffic in the WSN. Our scheme is based on the idea that the motes maintain a window with the classes of the latest transmissions. We propose an analytical model and provide an algorithm to study the performance of this allocation scheme with respect to the throughput and the fairness achieved. The model is a continuous time Markov chain which is proved to be dynamically reversible (although not reversible) and admits a product-form equilibrium distribution

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Section: Related Workmentioning

confidence: 99%

Priority-based bandwidth allocation in wireless sensor networks

Marin

Rossi

2016

Proceedings of the 9th EAI International Conference on Performance Evaluation Methodologies and Tools

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show abstract

“…In addition, some researchers make use of stochastic network calculus (e.g., [22][23][24][25][26]) to analyze the performance. But in this paper we only focus on the deterministic network calculus.…”

Section: The Analysis Of Networkmentioning

confidence: 99%

Analyzing Multimode Wireless Sensor Networks Using the Network Calculus

et al. 2015

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The network calculus is a powerful tool to analyze the performance of wireless sensor networks. But the original network calculus can only model the single-mode wireless sensor network. In this paper, we combine the original network calculus with the multimode model to analyze the maximum delay bound of the flow of interest in the multimode wireless sensor network. There are two combined methods A-MM and N-MM. The method A-MM models the whole network as a multimode component, and the method N-MM models each node as a multimode component. We prove that the maximum delay bound computed by the method A-MM is tighter than or equal to that computed by the method N-MM. Experiments show that our proposed methods can significantly decrease the analytical delay bound comparing with the separate flow analysis method. For the large-scale wireless sensor network with 32 thousands of sensor nodes, our proposed methods can decrease about 70% of the analytical delay bound.

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“…These are special nodes that collect the data harvested by the motes' sensors and may govern the actuators (e.g., they may raise a fire alarm in case some motes communicate a sudden rise in the temperature). In this setting, the wireless channel represents a shared resource among the motes whose access must be carefully governed to avoid the congestion collapse of the WSN (see, e.g., Akyildiz and Kasimoglu (2004), Sankarasubramabiam et al (2003), Cherian and Nair (2014), Chitnis et al (2009), and Khan et al (2012)). In this view, we can say that large WSNs represent an example of Collective Adaptive System (CAS) (Frescha 2015;Feng et al 2016), since they share a decentralised control, an autonomous behaviour of the motes, and a competition of the bandwidth resource.…”

Section: Introductionmentioning

confidence: 99%

A Product-Form Model for the Performance Evaluation of a Bandwidth Allocation Strategy in WSNs

Marin

Rossi

Burato

et al. 2018

ACM Trans. Model. Comput. Simul.

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Wireless Sensor Networks (WSNs) are important examples of Collective Adaptive System, which consist of a set of motes that are spatially distributed in an indoor or outdoor space. Each mote monitors its surrounding conditions, such as humidity, intensity of light, temperature, and vibrations, but also collects complex information, such as images or small videos, and cooperates with the whole set of motes forming the WSN to allow the routing process. The traffic in the WSN consists of packets that contain the data harvested by the motes and can be classified according to the type of information that they carry. One pivotal problem in WSNs is the bandwidth allocation among the motes. The problem is known to be challenging due to the reduced computational capacity of the motes, their energy consumption constraints, and the fully decentralised network architecture. In this article, we study a novel algorithm to allocate the WSN bandwidth among the motes by taking into account the type of traffic they aim to send. Under the assumption of a mesh network and Poisson distributed harvested packets, we propose an analytical model for its performance evaluation that allows a designer to study the optimal configuration parameters. Although the Markov chain underlying the model is not reversible, we show it to be ρ-reversible under a certain renaming of states. By an extensive set of simulations, we show that the analytical model accurately approximates the performance of networks that do not satisfy the assumptions. The algorithm is studied with respect to the achieved throughput and fairness. We show that it provides a good approximation of the max-min fairness requirements.

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Probabilistic Bandwidth Assignment in Wireless Sensor Networks

Cited by 6 publications

References 24 publications

Priority-based bandwidth allocation in wireless sensor networks

Priority-based bandwidth allocation in wireless sensor networks

Analyzing Multimode Wireless Sensor Networks Using the Network Calculus

A Product-Form Model for the Performance Evaluation of a Bandwidth Allocation Strategy in WSNs

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