On the Optimality of Generic Rate-Based AIMD and AIAD Congestion Control Schemes in Cognitive Radio Sensor Networks

Esmaeelzadeh, Vahid; Berangi, Reza

doi:10.1155/2015/614643

Cited by 6 publications

(17 citation statements)

References 17 publications

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“…These values are indicative for simulation purposes and can be set to any other positive real numbers. The PU states .r d ; r a / D .1; 5/ and (1,3) are considered as high-activity states, and the states .r d ; r a / D .1; 1/, (3,3) and (5,5), PUs are considered as medium-activity states in the channel. Also, the PU states .r d ; r a / D .3; 1/ and (5,1) are considered as low activity in the channel.…”

Section: Packet Loss Probabilitymentioning

confidence: 99%

“…(4) According to information theory definitions, the joint entropy of data issued by two sensors (H.S 1 ; S 2 /) are calculated. (5) The joint entropy of data issued by multiple sensors (H.S 1 ; : : : ; S N /) is estimated by a proposed heuristics algorithm.…”

Section: Weighting Process Of Multimedia Flowsmentioning

confidence: 99%

“…Therefore, an appropriate admission control mechanism is needed to decide whether a new connection should be accepted or rejected considering the PUs activity in CR channels and other network constraints. In general, connection admission control (CAC) is a proactive type of congestion control mechanism [4,5] to prevent congestion. This mechanism reduces packet end-to-end delay and packet loss probability and hence improves real-time performance [6].…”

Section: Introductionmentioning

confidence: 99%

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A correlation‐based and spectrum‐aware admission control mechanism for multimedia streaming in cognitive radio sensor networks

Hosseini

Esmaeelzadeh

Berangi

et al. 2015

Int J Communication

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SUMMARYBandwidth management and traffic control are critical issues to guarantee the quality of service in cognitive radio networks. This paper exploits a network load refinement approach to achieve the efficient resource utilization and provide the required quality of service. A connection admission control approach is introduced in cognitive radio multimedia sensor networks to provide the data transmission reliability and decrease jitter and packet end-to-end delay. In this approach, the admission of multimedia flows is controlled based on multimedia sensors' correlation information and traffic characteristics. We propose a problem, connection admission control optimization problem, to optimize the connection admission control operation. Furthermore, using a proposed weighting scheme according to the correlation of flows issued by multimedia sensors enables us to convert the connection admission control optimization problem to a binary integerprogramming problem. This problem is a kind of a Knapsack problem that is solved by a branch and bound method. Simulation results verify the proposed admission control method's effectiveness and demonstrate the benefits of admission control and traffic management in cognitive radio multimedia sensor networks.

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Section: Packet Loss Probabilitymentioning

confidence: 99%

Section: Weighting Process Of Multimedia Flowsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A correlation‐based and spectrum‐aware admission control mechanism for multimedia streaming in cognitive radio sensor networks

Hosseini

Esmaeelzadeh

Berangi

et al. 2015

Int J Communication

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“…Cognitive radio technology 12 can be used in wireless sensor networks (WSNs) to over- 13 come spectrum shortage problem and reserve the limited 14 resources of sensors in WSNs [3]. Wireless sensor networks 15 with CR-equipped sensor nodes are called cognitive radio 16 sensor networks (CRSNs) [3]. With regard to the applica-17 tion, opportunistic spectrum access (OSA) feature of sensor 18 nodes in CRSNs can decrease the collision and retransmission 19 probabilities in the environments with bursty traffic which 20 is common in sensor networks.…”

Section: Introductionmentioning

confidence: 99%

“…Au-104 thors in [5] investigate the challenges of real-time transport 105 over CRSNs in the different spectrum environments of smart 106 grid. In [15], the optimality of simple rate adjustment tech-107 niques is investigated in CRSNs. In [16], the stochastic back-108 log and delay bounds of generic AIMD congestion control 109 schemes in CRSNs are modeled based on stochastic network 110 calculus (SNC) [17].…”

Section: Introductionmentioning

confidence: 99%

Modeling of rate-based congestion control schemes in cognitive radio sensor networks

et al. 2016

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a b s t r a c tPerformance evaluation of transport layer protocols in cognitive radio sensor networks (CRSNs) is useful to provide quality-of-service for real-time reliable applications. This paper develops an analytical framework to model the steady-state sending rate of collecting cognitive radio (CR) sensors in rate-based generic additive-increase multiplicative-decrease (AIMD) and additive-increase additive-decrease (AIAD) congestion control schemes. Evolution process of sending rate is modeled by a discrete time Markov chain (DTMC) in the terms of queue length. We model the queue length distribution of a CR node by a semi-Markov chain (SMC) with assuming general probability density functions (PDFs) of input rate and attainable sending rate of the node. These PDFs are derived based on the parameters of MAC and physical layers and CRSN configuration. The proposed models are verified through various simulations.

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Delay sensitive and power-aware SMDP-based connection admission control mechanism in cognitive radio sensor networks

Hosseini

Esmaeelzadeh

Berangi

et al. 2017

Computer Communications

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Due to the opportunistically resource usage of users in cognitive radio sensor networks (CRSNs), the availability of network resources is highly variable. Therefore, admission control is an essential mechanism to manage the traffic of cognitive radio users in order to satisfy the quality of service (QoS) requirements of applications. In this study, a connection admission control (CAC) mechanism is introduced to satisfy the requirements of delay sensitivity and power consumption awareness. This proposed mechanism is modeled through a semi Markov decision process (SMDP) and a linear programming problem is derived with the aim of obtaining the optimal policy to control the traffic of CRSNs and achieving maximum reward. The number of required channels at each network state is estimated through a graph coloring approach. An end to end delay constraint is defined for the optimization problem which is inspired from Kleinrock independence approximation. Furthermore, a power-aware weighting method is proposed for this mechanism. We conduct different simulation-based scenarios to investigate the performance of the proposed mechanism. The experimental results demonstrate the efficiency of this SMDP-based mechanism in comparison to the last CAC mechanism in CRSNs.

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On the Optimality of Generic Rate-Based AIMD and AIAD Congestion Control Schemes in Cognitive Radio Sensor Networks

Cited by 6 publications

References 17 publications

A correlation‐based and spectrum‐aware admission control mechanism for multimedia streaming in cognitive radio sensor networks

A correlation‐based and spectrum‐aware admission control mechanism for multimedia streaming in cognitive radio sensor networks

Modeling of rate-based congestion control schemes in cognitive radio sensor networks

Delay sensitive and power-aware SMDP-based connection admission control mechanism in cognitive radio sensor networks

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