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In wireless communication environments, backoff is traditionally based on the IEEE binary exponential backoff (BEB). Using BEB results in a high delay in message transmission, collisions, and ultimately wasting the limited available bandwidth. As each node has to obtain medium access before transmitting a message, in dense networks, the collision probability in the medium access control (MAC) layer becomes very high, when a poor backoff algorithm is used. The logarithmic algorithm proposes some improvements to the backoff algorithms that aim to efficiently use the channel and to reduce collisions.
The algorithm under study is based on changing the incremental behavior of the backoff value. The BEB is used by the local area networks (LANs) standards, IEEE 802.11, MAC.
BEB uses a uniform random distribution to choose the backoff value; this often leads to reducing the effect of a window-sized increment. This paper carries out a deeper study and analysis of the logarithmic backoff algorithm that uses logarithmic increments, instead of an exponential extension of the window size to eliminate the degrading effect of random number distribution. Results from simulation experiments reveal that the algorithm subject under study achieves higher throughput and less packet loss, when in a mobile ad hoc environment. Abstract = 'In wireless communication environments, backoff is traditionally based on the IEEE binary exponential backoff (BEB). Using BEB results in a high delay in message transmission, collisions, and ultimately wasting the limited available bandwidth.
As each node has to obtain medium access before transmitting a message, in dense networks, the collision probability in the medium access control (MAC) layer becomes very high, when a poor backoff algorithm is used. The logarithmic algorithm proposes some improvements to the backoff algorithms that aim to efficiently use the channel and to reduce collisions. The algorithm under study is based on changing the incremental behavior of the backoff value. The BEB is used by the local area networks (LANs) standards, IEEE 802.11, MAC. BEB uses a uniform random distribution to choose the backoff value; this often leads to reducing the effect of a window-sized increment.
This paper carries out a deeper study and analysis of the logarithmic backoff algorithm that uses logarithmic increments, instead of an exponential extension of the window size to eliminate the degrading effect of random number distribution. Results from simulation experiments reveal that the algorithm subject under study achieves higher throughput and less packet loss, when in a mobile ad hoc environment.' TY - JOUR T1 - On a Modified Backoff Algorithm for MAC Protocol in MANETs AU - Manaseer, Saher AU - Ould-Khaoua, Mohamed AU - Mackenzie, Lewis PY - 2009 Y1 - 2009 N2 - In wireless communication environments, backoff is traditionally based on the IEEE binary exponential backoff (BEB). Using BEB results in a high delay in message transmission, collisions, and ultimately wasting the limited available bandwidth. As each node has to obtain medium access before transmitting a message, in dense networks, the collision probability in the medium access control (MAC) layer becomes very high, when a poor backoff algorithm is used.
The logarithmic algorithm proposes some improvements to the backoff algorithms that aim to efficiently use the channel and to reduce collisions. The algorithm under study is based on changing the incremental behavior of the backoff value. The BEB is used by the local area networks (LANs) standards, IEEE 802.11, MAC. BEB uses a uniform random distribution to choose the backoff value; this often leads to reducing the effect of a window-sized increment.
This paper carries out a deeper study and analysis of the logarithmic backoff algorithm that uses logarithmic increments, instead of an exponential extension of the window size to eliminate the degrading effect of random number distribution. Results from simulation experiments reveal that the algorithm subject under study achieves higher throughput and less packet loss, when in a mobile ad hoc environment. AB - In wireless communication environments, backoff is traditionally based on the IEEE binary exponential backoff (BEB). Using BEB results in a high delay in message transmission, collisions, and ultimately wasting the limited available bandwidth.
As each node has to obtain medium access before transmitting a message, in dense networks, the collision probability in the medium access control (MAC) layer becomes very high, when a poor backoff algorithm is used. The logarithmic algorithm proposes some improvements to the backoff algorithms that aim to efficiently use the channel and to reduce collisions. The algorithm under study is based on changing the incremental behavior of the backoff value. The BEB is used by the local area networks (LANs) standards, IEEE 802.11, MAC.
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BEB uses a uniform random distribution to choose the backoff value; this often leads to reducing the effect of a window-sized increment. This paper carries out a deeper study and analysis of the logarithmic backoff algorithm that uses logarithmic increments, instead of an exponential extension of the window size to eliminate the degrading effect of random number distribution. Results from simulation experiments reveal that the algorithm subject under study achieves higher throughput and less packet loss, when in a mobile ad hoc environment. KW - Ad Hoc Networks KW - Backoff Algorithm KW - IEEE 802.11 KW - Medium Access Control KW - Throughput UR - UR - U2 - 10.4018/jbdcn. DO - 10.4018/jbdcn. M3 - Article VL - 5 SP - 60 EP - 73 JO - International Journal of Business Data Communications and Networking T2 - International Journal of Business Data Communications and Networking JF - International Journal of Business Data Communications and Networking SN - 1548-0631 IS - 1 ER.
The IEEE 802.15.3 medium access control (MAC) is proposed, especially, for wireless personal area network (WPAN) short and high data rates applications, to coordinate the access to the wireless medium among the competing devices. A concept of a geometrically increasing probability distribution for contention process was brought up in the work of Tay et al. In this paper, we adopt this idea as improved backoff (IB) for contention process of IEEE 802.15.3, where binary exponential backoff (BEB) is originally used. Here, we propose an analytical model for IB and compared both BEB and IB for saturated and nonsaturated traffic conditions. Furthermore, our research results demonstrate that IB provides an edge over BEB in terms of channel efficiency, channel access delay, and energy efficiency. The IEEE standard 802.15.3 MAC or WPAN MAC layer is based on a centralized, connection oriented topology which divides a large network into several smaller ones termed 'piconets.' A piconet consists of a Piconet Network Controller (PNC) and DEVs (DEVices).
One DEV is required to perform the role of PNC (Piconet Coordinator), which provides the basic timing for the piconet as well as other piconet management functions, such as power management, Quality of Service (QoS) scheduling, and security. The standard also allows for the formation of child piconets and neighbor piconets. In IEEE 802.15.3 MAC protocol, the channel time is divided into superframes, where each superframe beginning with a beacon. The superframe is composed of the three major parts: the beacon, the optional contention access period (CAP), and the channel time allocation period (CTAP) or channel time allocation time (CTA). Wireless channel is usually vulnerable to errors. Hence, error control mechanism is an essential part of any MAC protocol design. In accordance with that, IEEE 802.15.3 standard defines three types of acknowledgment mechanisms for CTAs and CAPs: the No-ACK, Imm-ACK, and Dly-ACK mechanisms.
During the CAP time devices request for reservation in CTA and also send data packets if needed. So the time length of CAP is dynamic and it is determined by the PNC. Longer the duration of CAP time is, more the number of devices will send their CTA slot requests and causes less time for CTA slots.
Hence, it is important to improve the performance for both data and request packets transmission within limited time frame of CAP. In our previous work we present the detail performance analysis of WPAN MAC and identified some key issues to improve the MAC performance, especially, for CAP duration. In this paper, we limit our research focus on improving the performance of CAP using IB instead of BEB during the contention process, and hence, overall WPAN MAC performance. During the CAP, MAC protocol performs backoff procedure before transmitting any kind of data or request packets.
This backoff mechanism is similar to CSMA/CA mechanism of IEEE 802.11 with some different parameters. In WAPN MAC, retry count is limited up to 3 counts (0 to 3) with maximum window size of 64 slots (8, 16, 32, and 64). Related Work To the best of our knowledge, there is no work on the performance or channel analysis of IEEE 802.15.3 networks with respect to contention-based scheme during the CAP time. However, a large amount of literature is available on IEEE 802.15.3 MAC scheduling, optimization of superframe size, and various traffic analyses.
Some of the important related works are as follow. In the authors presented the implementation of IEEE 802.15.3 module in ns-2 and discussed various experimental scenario results including various scheduling techniques.
Specially, to investigate the performance of real-time and best-effort traffic with various super frame lengths and different ACK policies. In the authors presented two adaptive Dly-ACK schemes for both TCP and UDP traffic. The first one is to request the Dly-ACK frame adaptively or change the burst size of Dly-ACK according to the transmitter queue status. The second is a retransmission counter to enable the destination DEV to deliver the MAC data frames to upper layer timely and orderly. Similarly, the work presented in also discussed about different acknowledge schemes and optimization of channel capacity. Both papers laid a good foundation in simulation and analytical works of IEEE 802.15.3 MAC protocol. In the authors formulated a throughput optimization problem under error channel condition and derive a closed form solution for the optimal throughput.
Similarly, in the authors presented a detailed performance analysis of WPAN with different designing parameters as well as with different ACK policies and aggregation method. BEB Scheme BEB-based carrier sense multiple access with collision avoidance (CSMA/CA) is the most basic and widely used mechanism for MAC protocol. In WPAN MAC, if the channel is idle for backoff interframe space (BIFS) or short interframe space (SIFS) the DEV starts executing the BEB scheme. At each packet transmission, the backoff counter is uniformly selected from the given range of 0, CW-1 (in rest of the paper we keep using terms 'DEV' and 'node' interchangeably). Here, CW is known as contention window and its value depends on the number of failed transmissions for the packet. At the first transmission attempt, CW is set to minimum value of 8 and if transmission attempt fails then its value gets double, and again set to minimum value on successful transmission.
In WPAN MAC, the maximum contention window value is set to 64 with the maximum retry limit up to 3 counts. After selecting CW node decrement its value by 1 as long as channel is sensed idle and freeze its value when channel is sensed busy. Figure 1 Throughput versus number of active nodes (this result is taken from ). In nutshell, during the CAP, backoff window size and the number of active nodes are the major factors to have impact on the throughput performance. The BEB scheme does not work well when we are interested in the high bandwidth utilization, latency, and energy efficiency.
Academic Conferences: Analytical Study Of Backoff Algorithms For Mac Download
These observations and result lead us to use new medium access scheme for IEEE 802.15.3 MAC. So to improve the channel performance during the CAP time, we use a fixed-size contention window, but a nonuniform, geometrically increasing probability distribution for picking a transmission slot in the contention window interval.
In contrast to BEB scheme, IB scheme uses a small and fixed CW. In IB scheme, nodes choose nonuniform geometrically increasing probability distribution ( P) for picking a transmission slot in the contention window. Nodes which are executing IB scheme pick a slot in the range of (1, CW) with the probability distribution P. Here, CW is contention window and its value is fixed. More information on CW we will be presenting in the later sections of this paper. Figure shows the probability distribution P. The higher slot numbers have higher probability to get selected by nodes compared to lower slot numbers.
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In physical meaning we can explain this as follows. At the start node select a higher slot number for its CW by estimating large population of active nodes ( n) and keep sensing the channel status. If no nodes transmit in the first or starting slots then each node adjusts its estimation of competing nodes by multiplicatively increasing its transmission probability for the next slot selection cycle. Every node keeps repeating the process of estimation of active nodes in every slot selection cycle and allows the competition to happen at geometrically decreasing values of n all within the fixed contention window (CW). Figure 2 Difference between uniform and truncated geometric distributions. In contrast to the probability distribution P, in uniform distribution, as shown in Figure, all the contending nodes have the same probability of transmitting in a randomly chosen time slot. From Figure, in the probability distribution P, we can depict that when the population of competing nodes ( n) is large, most of the nodes will choose medium to higher slot numbers of CW before accessing the channel and a very few nodes will choose low slot numbers, hence, a collision-free transmission will take place in lower slot numbers.
When n is medium, most nodes will choose higher slot numbers and a collision-free transmission will take place in medium slot numbers. Similarly, when n is small, a collision-free transmission will take place in higher slot numbers.
Thus for any value of n, and for any fast change in n, a collision free transmission can take place. These special characteristics of IB give the advantage over the BEB in terms of different performance metrics. If only one node gets the chance to select the contention slot within the fixed CW, it will transmit in that slot.
While other nodes will select new random contention slots for next contention process, to win channel medium, regardless of success or failure of transmission of winner node. (1) where is a distribution parameter.
In this range of increases exponentially with, so the later slots have higher probability. Here, it is worth to note that IB scheme does not use timer suspension like in IEEE 802.11 to save energy and reduce latency in case of a collision. The only problem with the IB is fairness, however, for WPAN MAC, especially, during CAP fairness is not an issue as every node do not have request packet for PNC for every time. For the general wireless communication scenario we need fairness mechanism, which we left to our future research investigation. In this section we present the general frame work to model the backoff algorithms. This frame work basically consists of three steps: finding the attempting probability for a node in backoff, finding the transition probability for a given channel state, and model the stationary probabilities of the channel state for required protocol details. Here we also model channel efficiency, channel access delay, and energy efficiency with these three basic steps (In this paper, we use terms 'algorithm,' 'scheme,' and 'method' interchangeably.
Approach and Assumptions Most of the studies on backoff algorithm (BA) are focused on the stability issue rather than performance analysis of backoff algorithm. In this paper our main focus is to analyze and compare the performance of both IB and BEB with respect to network load in steady-state condition. Here, we define network load in terms of the number of nodes that are contending for the access medium.
Another approach is to consider total arrival packet rate to the network as an offered load. The main purpose of BA is to reduce the effect of contention among the nodes and try to adopt the population of nodes so the number of nodes contending for medium is a more favorable way to define an offered load for analyzing BA.
Here, we assume a fixed number of nodes in saturated and nonsaturated conditions. Saturation conditions mean every node always has a packet to transmit and similarly in nonsaturation case every node receives a packet with probability. More on saturation and nonsaturation will be explained later. The channel is an ideal and introducing no errors to the reception of a packet other than collision.
Also, capture effect is not considered. The BA performed in a time-slotted fashion. A node attempts to attain the access the channel only at the beginning of a slot. Furthermore, all nodes are well synchronized in time slots and propagation delay is negligible compared to the length of an idle slot. BEB and IB Analytical Modeling. In BEB, at first transmission, a packet is transmitted after waiting for the number of slots randomly chosen from the given range of contention window ( ), where is the minimum contention window size. This contention window is used as time unit for a node to detect the transmission of a frame from any other node.
This time unit is defined as 'slot time.' We model the operation of BEB at an individual node using the state diagram shown in Figure.
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This diagram is based on the models presented in including the freezing and retry limit parameters. Abc software packages for mac. Figure 3 Markov Chain Model for IEEE 802.
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As shown in Figure let j denote the backoff stage, where, 1, 2, 3 (assuming immediate acknowledgement for a data/request packet). So, we have,. A delayed-ack scheme for mac. Let be defined as a random process representing the backoff counter of a node with representing random process of the back stage. Is decremented at the start of every idle backoff slot. It is important to note that time scale for does not represent real time but it observes only backoff slots and its suspended for the duration of all transmissions and interframe spaces (i.e., SIFS). And whenever reaches zero the station transmits and regardless of the outcome of the transmission, uniformly chooses a new value for from ( ) (i.e., new backoff counter value).
Here, we define as the conditional collision probability and we also assume that it is independent and constant, regardless the number of retransmissions attempted. Also represents the probability of detecting the channel busy. Thus, the two-dimension process, is a discrete-time Markov Chain.
Therefore, the state of each node is described by, where stands for the backoff stage, and stands for the backoff timer value. In addition to normal state diagram we also add 2 extra states to model the nonsaturation traffic condition. A node may now wait in the idle state for a packet from upper layers before going into backoff procedure.
This corresponds to a delay in the idle state and it is represented by upper left two sates in the Figure. The delay in the idle state is modeled geometric with parameter.
The state transition diagram of the Markov chain model shown in Figure has the following transition probabilities. (2) The first equation in (2) indicates that at the beginning of each slot time, the backoff counter is decremented if the channel is sensed idle. The second equation shows that the backoff counter is frozen if channel is sensed busy. The third and fourth equations, respectively, indicate that following an unsuccessful transmission, the node backoff stage selects a backoff interval uniformly in the range of (0, ) and when the backoff stage reaches, stays constant.
The rest of the equations shows the transition probabilities for two extra sates we added. Here, we take to introduce 2 extra states. These transition probabilities are straightforward to understand, as shown in Figure. Similar to BEB algorithm, Figure shows the state diagram of IB algorithm at an individual node. As we explained in the previous section, IB does not use contention counter suspension and there is only one stage (i.e., fixed backoff window).
In IB, each node selects the contention slot with a geometrically increasing distribution as presented in (1) from ( ). Using similar notation as BEB, j represents the backoff stage (, in IB) and represents the back of timer value (, in IB). Here, and represent the collision probability and the probability of detecting the channel busy, respectively.
Therefore, Figure shows the one-dimension discrete-time Markov Chain for IB at an individual node. In this Markov Chain, the nonnull one step transition probabilities are as follows. (3) The first equation in (3) indicates the backoff counter which is decremented if the channel is sensed idle. The second equation indicates that the node defers the transmission of a new frame and enters stage 0 of the backoff procedure if it detects a successful transmission of its current frame or finds the channel busy or if it detects that a collision occurred to its current not successfully transmitted frame. The third equation indicates that the node selects a backoff interval nonuniformly in the range of (1, CW) following an unsuccessful transmission.
Channel Efficiency Analysis In BEB, let be the stationary distribution of the Markov chain ,. Let be the probability that a node transmits during a generic slot time. A node transmits when its backoff counter reaches zero. Similar to is given.
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