Fair congestion control method for terminal groups with wireless random access in M2M network

Ogawa, Teiichiro; Kotabe, Satoshi; Nishizawa, Hideki; Hidefumi, Nakamura; Shibata, Takashi

doi:10.1109/iscit.2012.6380851

Cited by 8 publications

(10 citation statements)

References 3 publications

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“…Cluster based access control [39] K-means and coordinator selection scheme [42] Bulk signal handling scheme [2] Signalling message compression scheme [43] Group based packet rates adjustment method [44] Figure 3.4: Congestion control mechanisms applied to core network. subgroup of MTC UEs receives this information, so that collision among themselves is manageable.…”

Section: Congestion Control Methods Applied To Cnmentioning

confidence: 99%

Dynamic access class barring and relay assisted radio resource allocation methods for cellular M2M networks

Ferdouse¹

2021

Preprint

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Cellular based M2M systems generate massive number of access requests which create congestion in the cellular network. The contention-based random access procedures are designed for cellular networks which cannot accommodate a large number of M2M traffic. Moreover, M2M systems share same radio resources with cellular users. Resource allocation problem becomes a challenging issue in cellular M2M systems. In this thesis, we address these two problems by analyzing a contention-based slotted Aloha random access procedure for M2M networks using different performance metrics. The impact of massive M2M traffic over cellular traffic is studied based on different arrival rate, random access opportunity and throughput. An analytical model of selecting a base station (eNB) along with load balancing is developed. Finally, two methods have been presented and evaluated with M2M traffic. First one is dynamic access class barring method which controls RAN level congestion by selecting an appropriate eNB and applying load balancing method. Second one is relay-assisted radio resource allocation method which maximizes the sum throughput of the system by utilizing the available radio resource blocks and relay nodes to the MTC systems. Numerical results show that frame transmission rate influences the selection probability of the base stations. Moreover, the dynamic access class barring parameter along with frame transmission rate improve the overall throughput and access success probability among base stations as well as avoid overload situation in a particular base station.

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Section: Congestion Control Methods Applied To Cnmentioning

confidence: 99%

Dynamic access class barring and relay assisted radio resource allocation methods for cellular M2M networks

Ferdouse¹

2021

Preprint

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“…In , authors show the profile ID creation mechanism by reducing message size, which helps to reduce processing overhead at the system interfaces and node, respectively. Group‐based packet rates adjustment method: Two major problems will be generated by massive access: firstly, the minimum call rate that can not be assured in groups because of the RA collision and secondly, the wastage of bandwidth. The authors in proposed to change time slots, calculate and define three different packet rate: Offered Packet Rate (OPR), Available Packet Rate (APR) and Minimum Packet Rate. APR of a group is calculated by the sum of all packet rate received by BS.…”

Section: Congestion In Machine‐type Communication Over Third Generatimentioning

confidence: 99%

Congestion and overload control techniques in massive M2M systems: a survey

Ferdouse

Anpalagan

Misra

2015

Trans. Emerging Tel. Tech.

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Smart applications, Internet of things, cloud computing technologies are becoming connected together by autonomous and intelligent devices. Communication among those devices, called machine‐type communication (MTC) can be done through cellular networks. A cellular network typically handles both voice and data traffic. Cellular based machine‐to‐machine (M2M) communication utilises cellular infrastructure to convey their information among MTC devices. Although MTC devices generate small amount of data traffic, massive amount of MTC devices create overload problem which hugely impacts the radio access and core networks of the cellular system. This article discusses M2M systems, its various applications, architectural requirements, functionalities, services and features from congestion and overload control point of view. In particular, a survey of congestion control problem in M2M systems and its various solutions are discussed in this article. Copyright © 2015 John Wiley & Sons, Ltd.

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“…Traffic overload and PRACH overload control [25], ACB and extended ACB are the best congestion control learning-based eNB selection [37], choices for congestion control prioritised RA [66], fair congestion control and PRACH overload situations. [70], code expanded random access [64], composite ACB and EAB [69] Resource management Randomness of small data In [77], resources are assigned according [77], partial time frequency allocation [75] to data types whilst in [75] small portion of radio resources of each cellular user is consumed by MTC device thus reducing the interference.…”

Section: Channel Statementioning

confidence: 99%

“…Delay constraint scheduling [43] Does not consider Opportunistic hard priority [26] Does not consider Utility-based scheduling [48] Does not consider Resource sharing optimisation [49] Explicit energy efficiency objective Self-adaptive persistent scheduling [50] Implicit energy efficiency Ubiquitous massive access [13] Implicit energy efficiency Periodic scheduling with queue awareness [28] Does not consider QoS-aware fair scheduling [46] Implicit energy efficiency Channel awareness, unawareness [39] Implicit energy efficiency Dynamic access control [59] Does not consider Cooperative extended ACB [60] Does not consider MU-MIMIO detection [55] Does not consider Low or no mobility [51] Explicit energy efficiency objective Group based [38] Explicit energy efficient objective Client relay [87] Explicit energy efficiency objective RFSA [36] Explicit energy efficiency objective Cooperative sleep wake [81] Explicit energy efficiency objective EC minimisation [90] Explicit energy efficiency objective DRAC [91] Explicit energy efficiency objective Call admission [92] Implicit energy efficiency PRACH overload control [25] Does not consider Learning-based eNB selection [37] Implicit energy efficiency Prioritised RA [66] Does not consider Fair congestion control [70] Does not consider Code-expanded random access [64] Does not consider Composite ACB and EAB [69] Does not consider Randomness of small data [77] Does not consider Partial time frequency allocation [75] Implicit energy efficiency keep the communication system on (for listening to the medium and for control packets) is the dominant component of energy consumption, which can be controlled to extend the network lifetime. Periodic, asynchronous, on-demand sleep wake scheduling are the most common ways to minimise energy consumption.…”

Section: Access Techniques Energy Efficiency Considerationmentioning

confidence: 99%

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Medium access control techniques in M2M communication: survey and critical review

Hussain

Anpalagan

Vannithamby

2014

Trans. Emerging Tel. Tech.

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Machine-to-machine (M2M) communication has received increasing attention in recent year. An M2M network exhibits some salient features such as large number of machines/devices, low data rates, delay tolerant/sensitive, small packets, energy constrained and low or no mobility. A large number of M2M terminals may exist in a small area with many trying to simultaneously and randomly access for channel resources, which will result in overload and access problem. This increased signalling overhead and diverse requirements of machine-type communication (MTC) devices call for the development of flexible and efficient scheduling and random access techniques. In an M2M scenario, where the network is operating at high offered load with a large number of contending transmitters, distributed random access techniques are more appropriate than centralised scheduling techniques because of less control messages and better channel utilisation. There is a need for comparison of various medium access methods that can be used in the development of an efficient hybrid M2M and human to human network. In this article, we review and compare various scheduling and random access techniques in cellular networks, particularly in Long-Term Evolution. We also discuss how successful they are to fulfill the unique requirements of M2M communication and networking. Resource management in M2M networks with a large number of MTC devices is also discussed from the access point of view. Energy efficiency, being one of the main challenges of quality-of-service-constrained M2M communication, is also discussed. Minimisation of the energy consumption is tightly bound to channel access and hence considered in the comparison of various medium access control protocols. Finally, some potential research directions related to access control and resource allocation are presented for future work.

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Fair congestion control method for terminal groups with wireless random access in M2M network

Cited by 8 publications

References 3 publications

Dynamic access class barring and relay assisted radio resource allocation methods for cellular M2M networks

Dynamic access class barring and relay assisted radio resource allocation methods for cellular M2M networks

Congestion and overload control techniques in massive M2M systems: a survey

Medium access control techniques in M2M communication: survey and critical review

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