An energy-efficient multi-sensor scheduling mechanism with QoS support for WBANs

Omidvar, Hamed; Ashtiani, Farid; Javidi, Tara; Nasiri-Kenari, Masoumeh; Vahdat, Bijan Vosoughi

doi:10.1109/wcnc.2014.6952486

Cited by 3 publications

(9 citation statements)

References 17 publications

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“…Therefore, the state of the channels could be modelled by a discrete time Markov chain. An important characteristic of the channels in a WBAN is their correlation [6]. As a result, for a network including K sensors, the vector denoting the state of the channels in the nth superframe is a vector including K elements given by s n ∈ S n where…”

Section: Modelling the Nodes' Channel Statesmentioning

confidence: 99%

“…Moreover, because of the importance of the packet transmission before a deadline, the influence of the discarded packets shall be considered in the cost function. According to these points, the cost function considered in [6] is as follows:…”

Section: Cost Functionmentioning

confidence: 99%

“…Thus, for determining the transmission policy, the coordinator could use only a probability distribution vector (belief vector) over different channel states (partial CSIT) that leads to an observable MDP (POMDP) model. In [6] this problem has been studied assuming partially informed coordinator using POMDP algorithm. The results show that the power consumption will decrease up to 31% using POMDP algorithm in comparison with ARQ algorithm, for different packet lengths.…”

Section: Introductionmentioning

confidence: 99%

“…The main focus of our proposed algorithm is to consider the influence of decisions at each superframe on only a limited number of subsequent superframes. In this respect, we modify the structure of the cost function in POMDP formulation [6], in a way that decision making at each superframe is performed by considering the overall effects of all possible decisions on only a limited number of upcoming superframes. This modification is considered separately for deterministic and random packet arrivals.…”

Section: Introductionmentioning

confidence: 99%

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Semi‐myopic algorithm for resource allocation in wireless body area networks

Karimzadeh-Farshbafan

Ashtiani

2018

IET wirel. sens. syst.

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The key features of wireless body area networks are limited energy resources of the sensor nodes and the need for highly reliable packet transmission. Therefore, designing a suitable algorithm that schedules transmission of the nodes is very important. Although an optimal algorithm has been previously reported based on a partially observable Markov decision process (POMDP), its complexity is high. In this study, the authors propose a suboptimal algorithm for scheduling the transmissions, i.e. a semi-myopic algorithm, with a performance close to the optimal, albeit with much lower complexity. To this end, they modify the structure of the cost function of the optimal algorithm such that the scheduling decision at each superframe is made regarding its effect on only a few upcoming superframes. The authors' proposed algorithm is considered in two different incoming packet scenarios, deterministic and random arrivals. Simulation results show that for both types of arrivals, there is a negligible difference between their proposed algorithm and the optimal one, i.e. POMDP, in terms of energy consumption and reliability.

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Section: Modelling the Nodes' Channel Statesmentioning

confidence: 99%

Section: Cost Functionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Semi‐myopic algorithm for resource allocation in wireless body area networks

Karimzadeh-Farshbafan

Ashtiani

2018

IET wirel. sens. syst.

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“…Moreover, the coexistence of WBANs and wireless local area networks (WLANs) has been investigated in medical environments in terms of the packet error rate [ 18 ]. In [ 19 ], the set of the channel states of sensor nodes to the coordinator is defined as the collective channel state which is used as a factor in designing a scheduling algorithm. In addition, the scheduling algorithm also selects the collective buffer state, and the time index to determine the transmission of the next superframe by sensor nodes to ensure QoS in medical environments.…”

Section: Related Workmentioning

confidence: 99%

Link Scheduling Algorithm with Interference Prediction for Multiple Mobile WBANs

Moh

2017

Sensors

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As wireless body area networks (WBANs) become a key element in electronic healthcare (e-healthcare) systems, the coexistence of multiple mobile WBANs is becoming an issue. The network performance is negatively affected by the unpredictable movement of the human body. In such an environment, inter-WBAN interference can be caused by the overlapping transmission range of nearby WBANs. We propose a link scheduling algorithm with interference prediction (LSIP) for multiple mobile WBANs, which allows multiple mobile WBANs to transmit at the same time without causing inter-WBAN interference. In the LSIP, a superframe includes the contention access phase using carrier sense multiple access with collision avoidance (CSMA/CA) and the scheduled phase using time division multiple access (TDMA) for non-interfering nodes and interfering nodes, respectively. For interference prediction, we define a parameter called interference duration as the duration during which disparate WBANs interfere with each other. The Bayesian model is used to estimate and classify the interference using a signal to interference plus noise ratio (SINR) and the number of neighboring WBANs. The simulation results show that the proposed LSIP algorithm improves the packet delivery ratio and throughput significantly with acceptable delay.

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