Backoff Algorithm Research Articles

The Performance Evaluation of an IEEE 802.11 Network Containing Misbehavior Nodes under Different Backoff Algorithms

Security of any wireless network is always an important issue due to its serious impacts on network performance. Practically, the IEEE 802.11 medium access control can be violated by several native or smart attacks that result in downgrading network performance. In recent years, there are several studies using analytical model to analyze medium access control (MAC) layer misbehavior issue to explore this problem but they have focused on binary exponential backoff only. Moreover, a practical condition such as the freezing backoff issue is not included in the previous models. Hence, this paper presents a novel analytical model of the IEEE 802.11 MAC to thoroughly understand impacts of misbehaving node on network throughput and delay parameters. Particularly, the model can express detailed backoff algorithms so that the evaluation of the network performance under some typical attacks through numerical simulation results would be easy.

Performance Improvement of Multi-User Multiple-Input Multiple-Output Protocol for WLAN

The increase in the number of devices with a massive revolution in mobile technology leads to increase the capacity of the wireless communications net-works. Multi-user Multiple-Input Multiple-Output is an advanced procedure of Multiple-Input Multiple-Output, which improves the performance of Wireless Local Area Networks. Moreover, Multi-user Multiple-Input Multiple-Output leads the Wireless Local Area Networks toward covering more areas. Due to the growth of the number of clients and requirements, researchers try to improve the performance of the Medium Access Control protocol of Multi-user Multiple-Input Multiple-Output technology to serve the user better, by supporting different data sizes, and reducing the waiting time to be able to transmit data quickly. In this paper, we propose a Clustering Multi-user Multiple-Input Multiple-Output protocol, which is an improved Medium Access Control protocol for Multi-user Multiple-Input Multiple-Out-put based on MIMOMate clustering technique and Padovan Backoff Algorithm. Utilizing MIMOMMate focuses on the signal power which only serves the user in that cluster, minimizes the energy consumption and increases the capacity. The implementation of Clustering Multi-user Multiple-Input Multiple-Output performs on the Network Simulator (NS2.34) platform. The results show that Clustering Multi-user Multiple-Input Multiple-Output protocol improves the throughput by 89.8%, and reduces the latency of wireless communication by 43.9% in scenarios with contention. As a result, the overall performances of the network are improved.

A Study on IEEE 802.11 MAC Layer Misbehavior under Different Back-off Algorithms

Security of any wireless network is an important issue. The IEEE 802.11 medium access control can be violated by several native or smart attacks that result to downgrade network performance. In recent years, there are several studies using analytical model to analyze MAC layer misbehavior issue to explore this problem but focused on binary exponential back-off only. Moreover, a practical condition such as freezing back-off issue is not included in the previous models. Hence, this paper presents a novel analytical model of the IEEE 802.11 MAC to thoroughly understand impacts of misbehaving node on network throughput and delay parameters. Especially, the model can express detailed back-off algorithms so that comforts to evaluate the network performance under some typical attacks by numerical simulation method.

Performance analysis of binary exponential backoff MAC protocol for cognitive radio in the IEEE 802.16e/m network

We propose a distributed MAC protocol for cognitive radio when primary network is IEEE 802.16e/m WiMAX. Our proposed MAC protocol is the Truncated Binary Exponential Backoff Algorithm where the backoff window size of algorithm is doubled at each collision, and the backoff counter is operated by frame basis in IEEE 802.16e/m and is freezed at a frame with no idle slots. We model our proposed MAC protocol as a 3-dimensional discrete-time Markov chain and obtain steady state probability of the Markov chain by using a censored Markov chain method. Based on this steady state probability, we obtain the throughput, packet loss probability and packet delay distribution of secondary users. Our numerical examples show that the initial contention window size can be determined according to the number of secondary users in order to obtain higher throughput for secondary users, and the maximum backoff window has a large impact on the secondary user's packet loss probability. Secondary users' packet delay distribution is much influenced by the initial contention window size and the number of secondary users.

A self-adaptive back-off optimization scheme based on beacons probability prediction for vehicle Ad-Hoc networks

In order to improve the broadcast reception rates of beacon messages in vehicle ad-hoc networks, a conclusion that the relationship between collision probability and minimum contention window size and the relationship between expiration probability and minimum window size was reached by building a Markov model. According to this conclusion, a back-off algorithm based on adjusting the size of minimum contention window called CEB is proposed, and this algorithm is on the basis of the differential size between the number of expiration beacons and preset threshold. Simulations were done to compare the performance of CEB with that of RBEB and BEB, and the results show that the performance of the new proposed algorithm is better than that of RBEB and BEB.

Minimizing contention collision probability and guaranteeing packet delay for cloud big data transmissions in 4G LTE-A packet random access

For transmitting Explosive Bursts Big Data of Mobile Cloud Computing applications, the 4G LTE/LTE-A standards are specified to provide extreme high data rate and low access delay for various real-time-demanded cloud services. In the uplink, data packet transmissions of different classes of traffic of various UEs need randomly contend for the limited number of preambles through the Uplink RACH channel time slots. Clearly, the extremely explosive data contentions certainly yield serious collisions, and then significantly increase access delay and packet dropping rate. That is, the quality of service (QoS) of the delay-sensitive-based real-time traffic and the loss-sensitive-based non-real-time traffic cannot be guaranteed satisfyingly. For overcoming the critical random access issue in cloud services over 4G LTE-A, 3GPP specifies the Uniform Distribution Backoff Procedure and Access Class Barring (ACB) as the random access mechanism. The Random Access CHannel (RACH) for random contentions in 3GPP LTE-A neglects some key factors: 1) different classes of traffic requiring different delay bounds, 2) how to reducing collision probability, 3) intensive congestion traffic and 4) differentiating the collision domains. This paper thus proposes an adaptive random contention approach (ARC) that consists of three phases: 1) Sigmoid-based Access Class Barring algorithm, 2) Dynamic Preamble Selection Range (DPSR) algorithm, and 3) Dynamic Initial Backoff (DIB) algorithm. The main contribution of ARC is based on the adaptive Sigmoid feature analysis of Cumulative Distribution Function of Normal Distribution according to the successful contention probability and the RACH congestion state. Numerical results demonstrate that the proposed approach outperforms the compared approaches in collision probability, goodput and access delay. Furthermore, the mathematical analytical model for the proposed approach is analyzed. The analysis result is very close the simulation result. It justifies the correctness and efficiency of the proposed approach.

Efficient medium access protocol for Internet of things applications

SummaryThe recent progresses made in microelectronics and sensor networks led to the emergence of a new family of networks called Internet of things (IoT). Several factors may degrade seriously IoT applications performance and prevent the connected objects to accomplish out their services. One factor is the inability of medium access control (MAC) protocol, namely, DCF 802.11 function, to distinguish between different sources of frame losses. To address this problem, we propose in this article an improvement called MAC protocol with distinction between data losses (MAC‐DL), which consists mainly to consider the different sources of frame losses in the functioning of the backoff algorithm. After the evaluation of MAC‐DL performance, the results showed a better performance compared with MAC protocol with the original DCF 802.11 function and to 2 other protocols proposed in the literature. Our solution improved significantly the quality of service and the energy efficient for typical IoT scenarios.

Performance evaluation of X-MAC/BEB protocol for wireless sensor networks

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.

Fair Channel Access in Uplink WLANs Supporting Multi-Packet Reception With Multi-User MIMO

In uplink wireless local area networks (WLANs) with multi-packet reception (MPR) which can be implementable with multi-user multiple-input multiple-output techniques, partial successes among simultaneous transmissions may frequently occur due to frame errors. This causes an increase in the contention window size only for the failed stations (STAs) under the binary exponential backoff algorithm, and a severe unfairness problem in terms of channel access opportunity may occur among the STAs with different frame error rates. In this letter, we propose a novel medium access control (MAC) protocol to support fair channel access in uplink WLANs with MPR. Analysis and simulation results show that our proposed MAC protocol can significantly improve the fairness in terms of both channel access opportunity and throughput.

Wake-up timer and binary exponential backoff for ZigBee-based wireless sensor network for flexible movement control system of a self-lifting scaffold

Synchronous movement of attached self-lifting scaffolds is traditionally monitored with wired sensors in high-rise building construction, which limits their flexibility of movements. A ZigBee-based wireless sensor system has been suggested in this article to prove the effectiveness of wireless sensor networks in actual implementation. Two optoelectronic sensors are integrated into a ZigBee node for measuring the displacement of attached self-lifting scaffolds. The proposed wireless sensor network combines an end device and a coordinator to allow easy replacement of sensors as compared to a wired network. A wake-up timer algorithm is proposed to reduce the transmitting power during continuous wireless data communication in the wireless sensor network. Furthermore, a variant binary exponential backoff transmission algorithm for data loss avoidance is proposed. The variant binary exponential backoff algorithm reduces packet collisions during simultaneous access by increasing the randomizing moments at nodes attempting to access the wireless channels. The performance of three of the proposed modules—a cable sensor, a 315-MHz sensor, and a ZigBee sensor—is evaluated in terms of packet delivery ratio and the end-to-end delay of a ZigBee-based wireless sensor network. The experimental results show that the proposed variant binary exponential backoff transmission algorithm achieves a higher packet delivery ratio at the cost of higher delays. The average cost of the developed ZigBee-based wireless sensor network decreased by 24% compared with the cable sensor. The power consumption of ZigBee is approximately 53.75% of the 315-MHz sensor. The average current consumption is reduced by approximately 1.5 mA with the wake-up timer algorithm at the same sampling rate.

Performance Evaluation of a State-Aware Backoff Algorithm in Congested Wireless Local Area Networks

Performance Evaluation of a State-Aware Backoff Algorithm in Congested Wireless Local Area Networks

Performance of Energy-Efficient Cooperative MAC Protocol with Power Backoff in MANETs

This paper presents an energy-efficient cooperative MAC (EECO-MAC) protocol using power control in mobile ad hoc networks. Cooperative communications improve network performance by taking full advantage of the broadcast nature of wireless channels. The power control technique improves the network lifetime by adjusting the transmission power dynamically. We propose the best partnership selection algorithm, which takes energy consumption into consideration for selection of the optimal cooperative helper to join in the transmission. Through exchanging control packets, the optimal transmission power is allocated for senders to transmit data packets to receivers. In order to enhance energy saving, space---time backoff and time---space backoff algorithms are proposed. Simulation results show that EECO-MAC consumes less energy and prolongs the network lifetime compared to IEEE 802.11 DCF and CoopMAC at the cost of delay. Performance improvement offered by our proposed protocol is apparent in congested networks where nodes have low and limited energy.

Game-Theoretic Queue-Stabilizing Backoff Algorithm in S-ALOHA and CSMA Systems

This letter investigates a queue-stabilizing backoff algorithm for slotted ALOHA and carrier-sense multiple access systems from game-theoretic perspective. Since queue stability of each user could be achieved when user’s throughput is greater than its mean packet arrival rate, every user tries to achieve its throughput up to a certain target level, by playing a non-cooperative game of determining a (re)transmission probability. We characterize Nash equilibrium points (NEPs) of this game and the convergence of a distributed backoff algorithm for users to employ to reach the NEPs.

Back-Off Time Calculation Algorithms in WSN

In a Mobile Wireless Sensor Mesh Network (MWSMN), based on the IEEE 802.15.4 standard, low power consumption is vitally important since the network devices are mostly battery driven. This is especially true for devices dependent on small form factors, such as those used in wireless sensor network. This paper proposes four new approaches to reduce the Back-Off Time in ZigBee standard in order to minimize the collisions caused by transmission between neighbouring nodes within the mesh network. The four alternate algorithms for the Back-Off Time calculation are compared to the ZigBee standard Back-Off Time algorithm regarding their energy needs using the simulation suite OPNET Modeler. To study the behaviour of the parameters of all algorithms in all scenarios, the statistical Analysis of Variance (ANOVA) has been used and it shows that the null hypotheses are rejected except for one case. The results show that the two passive algorithms Tabu Search and Simulated Annealing search techniques are suitable for battery-driven, energy-sensible networks. The Ant Colony Optimization (ACO) approaches increase throughput and reduce the packet loss but cost more in terms of energy due to the implementation of additional control packets. To the best of the authors’ knowledge, this is the first approach for MWSMN that uses the Swarm Intelligence technique and the search solution algorithm for the Back-Off Time optimization.

Weighted proportional fairness and pricing based resource allocation for uplink offloading using IP flow mobility

Mobile data offloading has been proposed as a solution for the network congestion problem that is continuously aggravating due to the increase in mobile data demand. However, the majority of the state-of-the-art is focused on the downlink offloading, while the change of mobile user habits, like mobile content creation and uploading, makes uplink offloading a rising issue. In this work we focus on the uplink offloading using IP Flow Mobility (IFOM). IFOM allows a LTE mobile User Equipment (UE) to maintain two concurrent data streams, one through LTE and the other through WiFi access technology, that presents uplink limitations due to the inherent fairness design of IEEE 802.11 DCF by employing the CSMA/CA scheme with a binary exponential backoff algorithm. In this paper, we propose a weighted proportionally fair bandwidth allocation algorithm for the data volume that is being offloaded through WiFi, in conjunction with a pricing-based rate allocation for the rest of the data volume needs of the UEs that are transmitted through the LTE uplink. We aim to improve the energy efficiency of the UEs and to increase the offloaded data volume under the concurrent use of access technologies that IFOM allows. In the weighted proportionally fair WiFi bandwidth allocation, we consider both the different upload data needs of the UEs, along with their LTE spectrum efficiency and propose an access mechanism that improves the use of WiFi access in uplink offloading. In the LTE part, we propose a two-stage pricing-based rate allocation under both linear and exponential pricing approaches, aiming to satisfy all offloading UEs regarding their LTE uplink access. We theoretically analyse the proposed algorithms and evaluate their performance through simulations. We compare their performance with the 802.11 DCF access scheme and with a state-of-the-art access algorithm under different number of offloading UEs and for both linear and exponential pricing-based rate allocation for the LTE uplink. Through the evaluation of energy efficiency, offloading capabilities and throughput performance, we provide an improved uplink access scheme for UEs that operate with IFOM for uplink offloading.

DBR-MAC: A Depth-Based Routing Aware MAC Protocol for Data Collection in Underwater Acoustic Sensor Networks

Due to long propagation delays, routing discovery is very expensive in underwater acoustic sensor networks. Therefore, depth-based routing (DBR) protocols are usually preferred whose routing discovery cost is almost zero. However, DBR protocols working with broadcast medium access control (MAC) bring severe collisions especially in the data collection network. Moreover, in DBR, all the packets are forwarded from deep to shallow nodes along the direction toward the sink node. The directional packet transmissions may lead to load imbalance, where some nodes undertake most loads and we call these nodes key nodes. However, the majority of existing MAC protocols cannot provide the key nodes priority of accessing channel in the collision domain. It is necessary to design a MAC protocol coupling with DBR. In this paper, we adopt a cross-layer approach to propose a DBR aware MAC protocol called DBR-MAC, which smoothly integrates a handshaking-based MAC and a DBR protocol. It improves the throughput, energy, and time efficiency at the cost of fairness. A depth-based transmission scheduling scheme is introduced based on the depth information, angle information, and overheard one-hop neighboring nodes' transmissions to make key nodes have higher priority to access the channel than other nodes. DBR-MAC is a cross-layer scheme and its directional forwarding tries best to forward packets from source to the floating sink node by the least hops. Moreover, an adaptive depth-based backoff algorithm cuts down the backoff time for the nodes and prevents the congestions at key nodes. Extensive simulations show that the throughput, energy, and time efficiency of DBR-MAC outperform existing MAC protocols when applied in the data collection network.

Performance analysis of contending customer equipment in wireless networks

Initial ranging is the primary and important process in wireless networks for the customer premise equipments (CPEs) to access the network and establish their connections with the base station. Contention may occur during the initial ranging process. To avoid contention, the mandatory solution defined in the standards is based on a truncated binary exponential random backoff (TBERB) algorithm with a fixed initial contention window size. However, the TBERB algorithm does not take into account the possibility that the number of contended CPEs may change dynamically over time, leading to a dynamically changing collision probability. To the best of our knowledge, this is the first attempt to address this issue. There are three major contributions presented in this paper. First, a comprehensive analysis of initial ranging mechanisms in wireless networks is provided and initial ranging request success probability is derived based on number of contending CPEs and the initial contention window size. Second, the average ranging success delay is derived for the maximum backoff stages. It is found that the collision probability is highly dependent on the size of the initial contention window and the number of contending CPEs. To achieve the higher success probability or to reduce the collision probability among CPEs, the BS needs to adjust the initial contention window size. To keep the collision probability at a specific value for the particular number of contending CPEs, it is necessary for the BS to schedule the required size of the initial contention window to facilitate the maximum number of CPEs to establish their connections with reasonable delay. In our third contribution, the initial window size is optimized to provide the least upper bound that meets the collision probability constraint for a particular number of contending CPEs. The numerical results validate our analysis.

D2D: Delay-Aware Distributed Dynamic Adaptation of Contention Window in Wireless Networks

The IEEE 802.11e enhanced distributed channel access (EDCA) protocol follows class-based service differentiation for providing differentiated quality-of-service (QoS). However, its collision avoidance mechanism using backoff algorithm can be inefficient for providing improved performance with respect to throughput and channel access delay, especially in a high network configuration (i.e. number of stations) with imperfect wireless channel. The existing and emerging works have devoted considerable attention on tuning the backoff parameters for achieving optimal throughput only. The prior works do not consider the channel access delay and throughput metrics altogether for performance improvement. Additionally, in most of the cases, the optimal configuration of backoff parameters are performed by a centralized controller. In this paper, we propose a delay-aware distributed dynamic adaptation of contention window scheme, namely D2D , for the cumulative improvement of both the throughput and the channel access delay at runtime. The D2D scheme requires two ad-hoc, distributed, and easy-to-obtain estimates— delay deviation ratio and channel busyness ratio —of the present delay level and channel congestion status of the network, respectively. A key advantage of the D2D scheme is that it is compliant with the IEEE 802.11 standard, and, thus, can be seamlessly integrable with the existing wireless card. We show the integrated model of the medium access control protocol, namely D2D Channel Access ( D2DCA ), for the IEEE 802.11e networks. We further propose a two-dimensional Markov chain model of the D2DCA protocol for analyzing its theoretical performance in saturated networks with imperfect wireless channel. Theoretical comparison with the benchmark protocols establishes the effectiveness of the D2DCA protocol.

A backoff algorithm based on self-adaptive contention window update factor for IEEE 802.11 DCF

The binary exponential backoff (BEB) mechanism is applied to the packet retransmission in lots of wireless network protocols including IEEE 802.11 and 802.15.4. In distributed dynamic network environments, the fixed contention window (CW) updating factor of BEB mechanism can't adapt to the variety of network size properly, resulting in serious collisions. To solve this problem, this paper proposes a backoff algorithm based on self-adaptive contention window update factor for IEEE 802.11 DCF. In WLANs, this proposed backoff algorithm can greatly enhance the throughput by setting the optimal CW updating factor according to the theoretical analysis. When the number of active nodes varies, an intelligent scheme can adaptively adjust the CW updating factor to achieve the maximal throughput during run time. As a result, it effectively reduces the number of collisions, improves the channel utilization and retains the advantages of the binary exponential back-off algorithm, such as simplicity and zero cost. In IEEE 802.11 distributed coordination function (DCF) protocol, the numerical analysis of physical layer parameters show that the new backoff algorithm performance is much better than BEB, MIMD and MMS algorithm.

History-Based Backoff Algorithms for Mobile Ad Hoc Networks

Mobile Ad hoc Network (MANET) is a wireless network consisting of mobile devices (laptops, smart phones, etc.) that move and communicate with each other without the use of any existing network infrastructure or centralized server to avoid collisions which have negative effects on the performance of the network. Access to the shared media is controlled by a Backoff algorithm that is a part of the Media Access Protocol. In this paper, we improve the History Based Probabilistic Backoff (HPPB) algorithm by modifying the increment/decrement behavior of the Contention Window to introduce History Based Increment Backoff (HBIB) algorithm which outperforms HBPB in terms of throughput and end-to-end delay with various numbers of nodes and different traffic loads.