An adaptive rate control for congestion avoidance in wireless body area networks

Baek, Youngmi; Lee, Byunghwa; Li, Jilong; Shu, Qin; Han, Jing; Han, Kijun

doi:10.1109/cyberc.2009.5342200

Cited by 9 publications

(5 citation statements)

References 7 publications

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“…Baek et al [26] proposed an adaptive rate control method for congestion avoidance in WBANs. The network model applies tree topology.…”

Section: Related Workmentioning

confidence: 99%

“…Like in our proposed model, the multi-hop network and utility optimization are used in a centralized manner, but the optimum data rate is searched for in a continuous domain. The models in [26][27][28] also use multi-hop network topology but throughput is maximized instead of utility. Furthermore, they follow a distributed approach in rate adaptation.…”

Section: Related Workmentioning

confidence: 99%

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Discrete Data Rate Adaptation for Wireless Body Area Networks

Szkaliczki

2023

Applied Sciences

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eHealth services require continuous data streaming and a stable level of quality of service. However, wireless network connections can be characterized by variable bandwidths. This requires continuous adaptation of systems, including adapting the bit rates of data streamed by sensors. Assigning appropriate rates to the data represents a main task in congestion control. Most of the current methods look for proper sensor data rates within continuous domains. We examine the case when sensors can generate data streams with several different qualities (e.g., sampling rates, sampling accuracies, etc.). For this reason, the domain of the data rate values can be restricted to the discrete values representing the data rates of the possible quality variations. This paper examines the optimization of the utility of the delivered data under resource constraints by selecting an appropriate variation of the provided data from a discrete set. We provide a formal model for delivering data streams in WBANs and recommend an optimization algorithm to solve the problem. Our recommended solutions are related to the multiple-choice multidimensional knapsack problem. By comparing the proposed algorithms, we found that the greedy method closely approximates the optimum in a short running time.

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“…Baek et al [26] proposed an adaptive rate control method for congestion avoidance in WBANs. The network model applies tree topology.…”

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Discrete Data Rate Adaptation for Wireless Body Area Networks

Szkaliczki

2023

Applied Sciences

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“…Several congestion control algorithms have been applied to BANs. Baek et al in [13] proposed an adaptive rate control scheme named ARCS for congestion avoidance in WBAN. In order to avoid congestion in the network.…”

Section: Related Workmentioning

confidence: 99%

CAMP: Congestion Avoidance and Mitigation Protocol for Wireless Body Area Networks

Anwar¹,

Abdullah²,

Saedudin

et al. 2018

IJIE

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Word population of old age people is growing very fast. This is a leading threat to current health care systems which trends to lesser the health facilities in proportional to the population. As reported by US Bureau of Census, the number of aged population is expected to be twice in 2025 from 380 (in 1990) [1]. The aged people mostly fall to different chronic health issues which require steady healthcare. These people needs to stick with hospitals, if not, they may experience the life risk [2]. Researchers affirm that most diseases can be overcome if they could caught earlier [3]. So, there an intense requirement of an intelligent health system which serve the purpose of timely diagnosis of the diseases'. To cope with these issues, scientists and technologists introduced Body Sensor Networks (BSNs) for health care systems [4]. BSN system can be deployed within a hospital or at the patient's home. These networks are made up of minimized bio-medical sensors (BMS) and capable of gathering information such as blood pressure, temperate, ECG from the human body and sending the information to the medical server[5]. Fig. 1 illustrate the types of BMS which can be used in BSN. Typically, medical server is placed at the healthcare facility which stores and analyze the information received form these BMS'. The server then generates alerts to the concerned health care experts and immediate caretakers if the found any abnormality. The system architecture of BSN is illustrated in Fig. 2. The BSN directly related to human body is known as intra-WBAN in which BMS are implanted under the human skin or wearable over the human skin or on clothes. These BMS' are controlled by Body Coordinator (BC) which collects and forward data to the outside BSN. BC has high computational, storage and power resources as compared to BMSs[6].

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“…In the first phase, the demands of the sink are broadcasted and in the second phase, congestion is controlled. Baek et al (2009) proposed an adaptive rate control for wireless body sensor networks. In this scheme, congestion is controlled by a prediction mechanism using a rate function.…”

Section: Introductionmentioning

confidence: 99%

“…HOCA has two phases. In the first phase, the demands of the sink are broadcasted and in the second phase, congestion is controlled Baek et al (2009). proposed an adaptive rate control for wireless body sensor networks.…”

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confidence: 99%

A Traffic Redirection Based Congestion Control Scheme in Body Area Networks

Ayatollahitafti¹,

Ngadi²,

Sharif³

2014

RJASET

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Growing data traffic generated by several sources in a Body Area Network (BAN) leads to congestion. One of the major challenges in BANs is congestion alleviation. Congestion causes packet drops which leads to lower network performance and higher delay due to packet retransmission. In this study, a novel traffic redirection based congestion control scheme is proposed in BANs. In the proposed scheme, when a sensor node is congested, its neighboring nodes select new next hop node. New next hop node selection is based on the queue size and hop counts to the sink of the neighboring nodes. Simulation results show that our protocol provides significant improvement in packet delivery ratio and end-to-end delay compared with the existing protocol.

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An adaptive rate control for congestion avoidance in wireless body area networks

Cited by 9 publications

References 7 publications

Discrete Data Rate Adaptation for Wireless Body Area Networks

Discrete Data Rate Adaptation for Wireless Body Area Networks

CAMP: Congestion Avoidance and Mitigation Protocol for Wireless Body Area Networks

A Traffic Redirection Based Congestion Control Scheme in Body Area Networks

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