• 제목/요약/키워드: exponential backoff algorithm

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IEEE 802.11e MAC 성능향상을 위한 PFA (Persistence Factor Adaptive) 백오프 알고리즘 (PFA (Persistence Factor Adaptive) Backoff Algorithm for performance improvement of IEEE 802.11e MAC)

  • 유동관
    • 한국컴퓨터정보학회논문지
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    • 제14권5호
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    • pp.77-83
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    • 2009
  • 본 논문은 IEEE 802.11 무선 LAN에서 DCF나 EDCF 방식이 사용하는 기존의 이진 지수함수 백오프 알고리즘이 네트워크의 트래픽 양이 증가할 경우 잠재적 충돌 가능성이 높아지고 트래픽별 차별화 서비스에 대한 단점이 있어 이를 보완하고자 한다. 이를 위해 일정 계수에 PF를 곱한 값을 적용시켜 성능을 개선시킨 다음에 이것의 성능을 기존의 BEB 알고리즘의 성능과 비교 분석하여 보았다. 개선된 백오프 알고리즘의 성능 분석은 채널이용률, 충돌율, Goodput 관점에서 이루어졌으며 이것을 기존의 알고리즘과 비교한 결과 일정 계수에 PF를 곱한 값을 적용시켜 성능을 개선시킨 PFA 백오프 알고리즘이 기존의 백오프 방식보다 스테이션 수 n값이 40과 같은 큰 값일 경우 채널이용률, Goodput 성능 등이 10%이상 더 향상됨을 볼 수 있었다.

IEEE 802.16 망을 위한 랜덤 액세스 기법 (Random Access Method for the IEEE 802.16 Networks)

  • 김명환;국광호;이강원;김영일
    • 한국시뮬레이션학회논문지
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    • 제17권4호
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    • pp.11-19
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    • 2008
  • IEEE 802.16 광대역 무선 액세스 망의 성능을 향상시키기 위해서는 하향 링크와 상향 링크의 효율을 향상시키는 것이 필요한데, 상향 링크의 효율을 향상시키기 위해서는 효율적으로 대역폭을 요청할 수 있는 random access 기법의 연구가 필요하다. 본 논문은 프레임 당 전송되고자 하는 메시지 수에 기초한 random access 기법인 RA_NBRM 기법과 conflict resolution 기법에 기초한 random access 기법인 RA_CRA 기법을 제안하고 시뮬레이션을 통하여 이들의 성능이 현재 IEEE 802.16 시스템에서 적용하고 있는 binary exponential backoff 기법보다 우수함을 보였다.

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A Reactive Cross Collision Exclusionary Backoff Algorithm in IEEE 802.11 Network

  • Pudasaini, Subodh;Chang, Yu-Sun;Shin, Seok-Joo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제4권6호
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    • pp.1098-1115
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    • 2010
  • An inseparable challenge associated with every random access network is the design of an efficient Collision Resolution Algorithm (CRA), since collisions cannot be completely avoided in such network. To maximize the collision resolution efficiency of a popular CRA, namely Binary Exponential Backoff (BEB), we propose a reactive backoff algorithm. The proposed backoff algorithm is reactive in the sense that it updates the contention window based on the previously selected backoff value in the failed contention stage to avoid a typical type of collision, referred as cross-collision. Cross-collision would occur if the contention slot pointed by the currently selected backoff value appeared to be present in the overlapped portion of the adjacent (the previous and the current) windows. The proposed reactive algorithm contributes to significant performance improvements in the network since it offers a supplementary feature of Cross Collision Exclusion (XCE) and also retains the legacy collision mitigation features. We formulate a Markovian model to emulate the characteristics of the proposed algorithm. Based on the solution of the model, we then estimate the throughput and delay performances of WLAN following the signaling mechanisms of the Distributed Coordination Function (DCF) considering IEEE 802.11b system parameters. We validate the accuracy of the analytical performance estimation framework by comparing the analytically obtained results with the results that we obtain from the simulation experiments performed in ns-2. Through the rigorous analysis, based on the validated model, we show that the proposed reactive cross collision exclusionary backoff algorithm significantly enhances the throughput and reduces the average packet delay in the network.

단일 경쟁 매체에서의 새로운 로드 기반 동적 매체 접속 제어 백오프 알고리즘 (Load-based Dynamic Backoff Algorithm in Contention-based Wireless Shared Medium)

  • 서창근;왕위동;유상조
    • 한국통신학회논문지
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    • 제30권6B호
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    • pp.406-415
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    • 2005
  • IEEE 802.11 무선 랜과 같이 단일 매체를 사용하는 무선망의 단말들은 경쟁을 통하여 매체를 점유하게 되며, 매체의 충돌이 발생하게 될 때 백오프 알고리즘을 사용하게 된다. 백오프 알고리즘은 매체의 충돌 확률을 줄임으로써 매체의 이용률을 높이고 효율적인 매체의 운영을 가능하게 하는 매체 접속 제어 방법의 중요한 요소이다. 본 논문에서는 QoS를 제공하기 위한 표준인 IEEE 802.11e를 기본으로 하여 네트워크의 매체 부하 및 혼잡 상태에 따라 능동적으로 경쟁 윈도우의 크기를 변화시키는 새로운 방법인 로드 기반 동적 매체 접속 제어 백오프 알고리즘을 제안한다. 제안된 부하 및 혼잡 상태의 예측과 우선순위에 따른 가중치의 차별화를 통한 동적 경쟁 윈도우 변경 방법이 기존의 IEEE 802.11e에서 사용하는 BEB 방법보다 매체의 이용률을 높이고 효율적으로 데이터의 충돌을 줄일 수 있음을 보인다.

A Study on CSMA/CA for IEEE 802.11 WLAN Environment

  • Moon Il-Young;Cho Sung-Joon
    • Journal of information and communication convergence engineering
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    • 제4권2호
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    • pp.71-74
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    • 2006
  • A basic access method about IEEE 802.11 MAC layer protocol using IEEE 802.11 wireless LANs is the DCF thatis based on the CSMA/CA. But, cause of IEEE 802.11 MAC layer uses original backoff algorithm (exponential backoff method), when collision occurred, the size of contention windows increases the double size Also, a time of packet transmission delay increases and efficienty is decreased by original backoff scheme. In this paper, we have analyzed TCP packet transmission time of IEEE 802.11 MAC DCF protocol for wireless LANs a proposed enhanced backoff algorithm. It is considered the transmission time of transmission control protocol (TCP) packet on the orthogonal frequency division multiplexing (OFDM) in additive white gaussian noise (A WGN) and Rician fading channel. From the results, a proposed enhanced backoff algorithm produces a better performance improvement than an original backoff in wireless LAN environment. Also, in OFDM/quadrature phase shift keying channel (QPSK), we can achieve that the transmission time in wireless channel decreases as the TCP packet size increases and based on the data collected, we can infer the correlation between packet size and the transmission time, allowing for an inference of the optimal packet size in the TCP layer.

A Study on CSMA/CA for WLAN Environment

  • Moon Il-Young;Cho Sung-Joon
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2006년도 춘계종합학술대회
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    • pp.530-533
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    • 2006
  • Recently, a basic access method about IEEE 802.11 MAC layer protocol using IEEE 802.11 wireless LANs is the DCF thatis based on the CSMA/CA. But, cause of IEEE 802.11 MAC layer uses original backoff algorithm (exponential backoff method), when collision occurred, the size of contention windows increases the double size. Also, a time of packet transmission delay increases and efficiency is decreased by original backoff scheme. In this paper, we have analyzed TCP packet transmission time of IEEE 802.11 MAC DCF protocol for wireless LANs a proposed enhanced backoff algorithm. It is considered the transmission time of transmission control protocol (TCP) packet on the orthogonal frequency division multiplexing (OFDM) in additive white gaussian noise (AWGN) and Rician fading channel. From the results, a proposed enhanced backoff algorithm produces a better performance improvement than an original backoff in wireless LAN environment. Also, in OFDM/quadrature phase shift keying channel (QPSK), we can achieve that the transmission time in wireless channel decreases as the TCP packet size increases and based on the data collected, we can infer the correlation between packet size and the transmission time, allowing for an inference of the optimal packet size in the TCP layer.

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Performance Evaluation of X-MAC/BEB Protocol for Wireless Sensor Networks

  • Ullah, Ayaz;Ahn, Jong-Suk
    • Journal of Communications and Networks
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    • 제18권5호
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    • pp.857-869
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    • 2016
  • This paper proposes an X-MAC/BEB protocol that runs a binary exponential backoff (BEB) algorithm on top of an X-MAC protocol to save more energy by reducing collision, especially in densely populated wireless sensor networks (WSNs). X-MAC, a lightweight asynchronous duty cycle medium access control (MAC) protocol, was introduced for spending less energy than its predecessor, B-MAC. One of X-MAC 's conspicuous technique is a mechanism to allow senders to promptly send their data when their receivers wake up. X-MAC, however, has no mechanism to deal with sudden traffic fluctuations that often occur whenever closely located nodes simultaneously diffuse their sense data. To precisely evaluate the impact of the BEB algorithm on X-MAC, this paper builds an analytical model of X-MAC/BEB that integrates the BEB model with the X-MAC model. The analytical and simulation results confirmed that X-MAC/BEB outperformed X-MAC in terms of throughput, delay, and energy consumption, especially in congested WSNs.

A New IEEE 802.11 DCF Utilizing Freezing Experiences in Backoff Interval and Its Saturation Throughput

  • Sakakibara, Katsumi;Taketsugu, Jumpei
    • Journal of Communications and Networks
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    • 제12권1호
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    • pp.43-51
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    • 2010
  • IEEE 802.11 defines distributed coordination function (DCF), which is characterized by CSMA/CA and binary exponential backoff (BEB) algorithm. Most modifications on DCF so far have focused on updating of the contention window (CW) size depending on the outcome of own frame transmission without considering freezing periods experienced in the backoff interval. We propose two simple but novel schemes which effectively utilize the number of freezing periods sensed during the current backoff interval. The proposed schemes can be applied to DCF and its family, such as double increment double decrement (DIDD). Saturation throughput of the proposed schemes is analyzed by means of Bianchi's Markovian model. Computer simulation validates the accuracy of the analysis. Numerical results based on IEEE 802.11b show that up to about 20% improvement of saturation throughput can be achieved by combining the proposed scheme with conventional schemes when applied to the basic access procedure.

Applying Deep Reinforcement Learning to Improve Throughput and Reduce Collision Rate in IEEE 802.11 Networks

  • Ke, Chih-Heng;Astuti, Lia
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권1호
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    • pp.334-349
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    • 2022
  • The effectiveness of Wi-Fi networks is greatly influenced by the optimization of contention window (CW) parameters. Unfortunately, the conventional approach employed by IEEE 802.11 wireless networks is not scalable enough to sustain consistent performance for the increasing number of stations. Yet, it is still the default when accessing channels for single-users of 802.11 transmissions. Recently, there has been a spike in attempts to enhance network performance using a machine learning (ML) technique known as reinforcement learning (RL). Its advantage is interacting with the surrounding environment and making decisions based on its own experience. Deep RL (DRL) uses deep neural networks (DNN) to deal with more complex environments (such as continuous state spaces or actions spaces) and to get optimum rewards. As a result, we present a new approach of CW control mechanism, which is termed as contention window threshold (CWThreshold). It uses the DRL principle to define the threshold value and learn optimal settings under various network scenarios. We demonstrate our proposed method, known as a smart exponential-threshold-linear backoff algorithm with a deep Q-learning network (SETL-DQN). The simulation results show that our proposed SETL-DQN algorithm can effectively improve the throughput and reduce the collision rates.