Leaky bucket

The leaky bucket is an algorithm based on an analogy of how a bucket with a leak will overflow if either the average rate at which water is poured in exceeds the rate at which the bucket leaks or if more water than the capacity of the bucket is poured in all at once, and how the water leaks from the bucket at an (almost) constant rate. It can be used to determine whether some sequence of discrete events conforms to defined limits on their average and peak rates or frequencies, or to directly limit the actions associated to these events to these rates, and may be used to limit these actions to an average rate alone, i.e. remove any variation from the average. The leaky bucket is an algorithm based on an analogy of how a bucket with a leak will overflow if either the average rate at which water is poured in exceeds the rate at which the bucket leaks or if more water than the capacity of the bucket is poured in all at once, and how the water leaks from the bucket at an (almost) constant rate. It can be used to determine whether some sequence of discrete events conforms to defined limits on their average and peak rates or frequencies, or to directly limit the actions associated to these events to these rates, and may be used to limit these actions to an average rate alone, i.e. remove any variation from the average. It is used in packet switched computer networks and telecommunications networks in both the traffic policing and traffic shaping of data transmissions, in the form of packets, to define limits on bandwidth and burstiness (a measure of the unevenness or variations in the traffic flow). It can also be used as a scheduling algorithm to determine the timing of transmissions that will comply with the limits set for the bandwidth and burstiness applied by the network: see network scheduler. A version of the leaky bucket, the Generic Cell Rate Algorithm, is recommended for Asynchronous Transfer Mode (ATM) networks in Usage/Network Parameter Control at User–Network Interfaces or Inter-Network Interfaces or Network-Network Interfaces to protect a network from excessive traffic levels on connections routed through it. The Generic Cell Rate Algorithm, or an equivalent, may also be used to shape transmissions by a Network Interface Card onto an ATM network (i.e. on the user side of the User-Network Interface), e.g. to levels below the levels set for Usage/Network Parameter Control in the network to prevent it taking action to further limit that connection. The leaky bucket algorithm is also used in leaky bucket counters, e.g. to detect when the average or peak rate of random or stochastic events or stochastic processes, such as faults or failures, exceed defined limits. At least some implementations of the leaky bucket are a mirror image of the Token Bucket algorithm and will, given equivalent parameters, determine exactly the same sequence of events to conform or not conform to the same limits. However, there are at least two different descriptions of the leaky bucket that can and have caused confusion. Two different methods of applying this leaky bucket analogy are described in the literature. These give what appear to be two different algorithms, both of which are referred to as the leaky bucket algorithm and generally without reference to the other method. This has resulted in confusion about what the leaky bucket algorithm is and what its properties are. In one version of applying the analogy, the analogue of the bucket is a counter or variable, separate from the flow of traffic or scheduling of events. This counter is used only to check that the traffic or events conform to the limits: The counter is incremented as each packet arrives at the point where the check is being made or an event occurs, which is equivalent to the way water is added intermittently to the bucket. The counter is also decremented at a fixed rate, equivalent to the way the water leaks out of the bucket. As a result, the value in the counter represents the level of the water in the analogous bucket. If the counter remains below a specified limit value when a packet arrives or an event occurs, i.e. the bucket does not overflow, that indicates its conformance to the bandwidth and burstiness limits or the average and peak rate event limits. So in this version, the analogue of the water is carried by the packets or the events, added to the bucket on their arriving or occurring, and then leaks away. This version is referred to here as the leaky bucket as a meter. In the second version, the analogue of the bucket is a queue in the flow of traffic. This queue is used to directly control that flow: Packets are entered into the queue as they arrive, equivalent to the water being added to the bucket. These packets are then removed from the queue (first come, first served), usually at a fixed rate, e.g. for onward transmission, equivalent to water leaking from the bucket. As a result, the rate at which the queue is serviced directly controls the onward transmission rate of the traffic. Thus it imposes conformance rather than checking it, and where the queue is serviced at a fixed rate (and where the packets are all the same length), the resulting traffic stream is necessarily devoid of burstiness or jitter. So in this version, the traffic itself is the analogue of the water passing through the bucket. It is not clear how this version of applying the analogy might be used to check the rates of discrete events. This version is referred to here as the leaky bucket as a queue. The leaky bucket as a meter is exactly equivalent to (a mirror image of) the token bucket algorithm, i.e. the process of adding water to the leaky bucket exactly mirrors that of removing tokens from the token bucket when a conforming packet arrives, the process of leaking of water from the leaky bucket exactly mirrors that of regularly adding tokens to the token bucket, and the test that the leaky bucket will not overflow is a mirror of the test that the token bucket contains enough tokens and will not 'underflow'. Thus, given equivalent parameters, the two algorithms will see the same traffic as conforming or nonconforming. The leaky bucket as a queue can be seen as a special case of the leaky bucket as a meter. Jonathan S. Turner is credited with the original description of the leaky bucket algorithm and describes it as follows: “A counter associated with each user transmitting on a connection is incremented whenever the user sends a packet and is decremented periodically. If the counter exceeds a threshold upon being incremented, the network discards the packet. The user specifies the rate at which the counter is decremented (this determines the average bandwidth) and the value of the threshold (a measure of burstiness)”. The bucket (analogous to the counter) is in this case used as a meter to test the conformance of packets, rather than as a queue to directly control them. Another description of what is essentially the same meter version of the algorithm, the Generic Cell Rate Algorithm, is given by the ITU-T in recommendation I.371 and in the ATM Forum’s UNI Specification. The description, in which the term cell is equivalent to packet in Turner's description is given by the ITU-T as follows: “The continuous-state leaky bucket can be viewed as a finite capacity bucket whose real-valued content drains out at a continuous rate of 1 unit of content per time unit and whose content is increased by the increment T for each conforming cell... If at a cell arrival the content of the bucket is less than or equal to the limit value τ, then the cell is conforming; otherwise, the cell is non-conforming. The capacity of the bucket (the upper bound of the counter) is (T + τ).”. These specifications also state that, due to its finite capacity, if the contents of the bucket at the time the conformance is tested is greater than the limit value, and hence the cell is non-conforming, then the bucket is left unchanged; that is, the water is simply not added if it would make the bucket overflow.