Application areas of leaky bucket algorithm and token bucket algorithm

In this article we discuss about the applications of the leaky bucket algorithm and the token bucket algorithm.  

Applications of Leaky Bucket Algorithm

- The leaky bucket algorithm is implemented in different versions. 

- For example, the generic cell rate algorithm is a version of this algorithm which is often implemented in the networks using ATM (asynchronous transfer mode).  

- The algorithm is applied at the user interfaces in the usage/network parameter control in order to provide protection to the network from the problems of congestive collapse or excess traffic. 

- An algorithm equivalent to the generic cell rate algorithm might be used in shaping the transmissions made by the network interface card to a network using ATM. 

There are two major applications of the leaky bucket algorithm. 

- The first is using it as a counter only for checking whether the events or the traffics confirm to the defined limits or not.

- Whenever a packet arrives at the check point, the counter is incremented. 

- This is same as adding water to the bucket in an intermittent way. 

- In the same way, the counter is decremented as the water leaks out at a constant rate. 

- Because of this, the conformance of the packet to the burstiness and bandwidth limits is indicated by the value of this counter whenever a packet arrives. 

- Or if an event occurs, the counter checks whether it confirms to the peak and average rate limits. 

- So, when the packets arrive or an event occurs, water is added to the bucket and then leaks out. We call this version of the leaky bucket algorithm as a meter.

- Another application of the leaky bucket algorithm involves its use as queue implemented for controlling the flow of traffic. 

- This queue maintains a direct control over the flow. 

- When the packets arrive, they are put in to the queue. 

- This is same as adding water to the bucket. 

- The packets are then removed in the order they arrived at a constant rate. 

- This is same as water leaking out. 

- As a result of this, there is no jitter or burstiness in the traffic flow.

Applications of Token Bucket Algorithm

- The token bucket algorithm finds its application in the telecommunications and packet switched computer networks.

- This algorithm is implemented for checking whether the data transmissions confirm to the burstiness and bandwidth predefined limits. 

- The token bucket algorithm used in traffic policing and traffic shaping. 

- In the former, the packets that are non-conformant are discarded or assigned low priorities. 

- This is done for the management of the downstream traffic. 

- On the other hand, the packets are kept in delay unless they are conformed in traffic shaping. 

- Both of these are used in protecting the network against the burstiness of the traffic. 

- Bursty traffic gives rise to congestion problems. 

- These algorithms help in managing the bandwidth as well congestion of the network. 

- Network interfaces commonly use the traffic shaping process for preventing the discarding of the transmissions by the network’s traffic management functions. 

- This algorithm is based up on the analogy of a bucket with fixed capacity. 

- Tokens are added to this bucket at a fixed rate and represent a single packet of a fixed size. 

- When the packet has to be checked whether it confirms to the predefined limits or not, first the bucket is checked if it contains sufficient tokens. 

- If sufficient tokens are there, tokens equal to the number of bytes in the packet are removed and the packet is transmitted. 

- If sufficient tokens are not there, the packet is said to be non-conformant and the number of tokens in the bucket remain unchanged.

When is a situation called as congestion?

- Network congestion is quite a common problem in the queuing theory and data networking. 

- Sometimes, the data carried by a node or a link is so much that its QoS (quality of service) starts deteriorating. 

- This situation or problem is known as the network congestion or simply congestion. 

This problem has the following two typical effects:

Ø  Queuing delay

Ø  Packet loss and

Ø  Blocking of the new connections

- The last two effects lead to two other problems. 

- As the offered load increases by the increments, either the throughput of the network is actually reduced or the throughput increases by very small amounts. 

- Aggressive re-transmissions are used by the network protocols for compensating for the packet loss. 

- The network protocols thus tend to maintain a state of network congestion for the system even if the actual initial load is too less that it cannot cause the problem of network congestion. 

- Thus, two stable states are exhibited by the networks that use these protocols under similar load levels. 

- The stable state in which the throughput is low is called the congestive collapse. 

- Congestive collapse is also called congestion collapse.

- In this condition, the switched computer network that can be reached by a packet when because of congestion there is no or little communication happening.

- In such a situation even if a little communication happens it is of no use. 

- There are certain points in the network called the choke points where the congestion usually occurs.

- At these points, the outgoing bandwidth is lesser than the incoming traffic. 

- Choke points are usually the points which connect the wide area network and a local area network. 

- When a network falls in such a condition, it is said to be in a stable state. 

- In this state, the demand for the traffic is high but the useful throughput is quite less.

- Also, the levels of packet delay are quite high. 

- The quality of service gets extremely bad and the routers cause the packet loss since their output queues are full and they discard the packets. 

- The problem of the network congestion was identified in the year of 1984. 

- The problem first came in to the scenario when the backbone of the NSF net phase dropped 3 times of its actual capacity. 

- This problem continued to occur until the Van Jacobson’s congestion control method was implemented at the end nodes.

Let us now see what is the cause of this problem? 

- When the number of packets being set to a router exceeds its packet handling capacity, many packets are discarded by the routers that are intermediate. 

- These routers expect the re-transmission of the discarded information. 

- Earlier, the re-transmission behavior of the TCP implementations was very bad. 

- Whenever a packet was lost, the extra packets were sent in by the end points, thus repeating the lost information. 

- But this doubled the data rate. 

- This is just the opposite of what routine should be carried out during the congestion problem. 

- The entire network is thus pushed in a state of the congestive collapse resulting in a huge loss of packets and reducing the throughput of the network. 

- Congestion control as well as congestion avoidance techniques are used by the networks of modern era for avoiding the congestive collapse problem. 

- Various congestion control algorithms are available that can be implemented for avoiding the problem of network congestion. 

- There are various criteria based up on which these congestion control algorithms are classified such as amount of feedback, deploy-ability and so on. 

Explain the page replacement algorithms - FIFO, LRU, and Optimal

- Paging is used by most of the computer operating systems for the purpose of virtual memory management. 

- Whenever a page fault occurs, some pages are swapped in and swapped out. Who decides which pages are to be replaced and how? 

- This purpose is served by the page replacement algorithms. 

- Page replacement algorithms only decide which pages are to be page out or written to the disk when a page of the memory has to be allocated. 

- Paging takes place only upon the occurrence of a page fault.

- In such situations a free cannot suffice because either one is not available or because the number of available pages is less than threshold. 

- If a previously paged out page is reference again, then it has to be read in from the disk again. 

- But for doing this, the operating system has to wait for the completion of the input/ output operation. 

- The quality of a page replacement algorithm is denoted by the time it takes for a page in. 

- The lesser it is, the better the algorithm is. 

- The information about the access to page as provided by the hardware is studied by the page replacement algorithm and then it decides which pages should be replaced so that the number of page faults can be minimized. 

In this article we shall see about some of the page replacement algorithms.

FIFO (first – in, first – out): 

- This one being the simplest of all the page replacement algorithms has the lowest overhead and works by book – keeping in place of the OS. 

- All pages are stored in a queue in the memory by the operating system.

- The ones that have recently arrived are kept at the back while the old ones stand at the front end of the queue.

- While making replacement, the oldest page is selected and replaced. 

- Even though this replacement algorithm is cheap as well as intuitive, practically it does not perform well. 

- Therefore, it is rarely used in its original form. 

- VAX/ VMS operating systems make use of the FIFO replacement algorithm after making some modifications. 

- If a limited number of entries are skipped you get a partial second chance. 

Least recently used (LRU): 

- This replacement algorithm bears resemblance in name with the NRU. 

- However, difference is there which is that this algorithm follows that the page usage is tracked for a certain period of time. 

- It is based on the idea that the pages being used many times in current set of instructions will be used heavily in the next set of the instructions also. 

- Near optimal performance is provided by LRU algorithm in the theory however in practical it is quite expensive to be implemented. 

- For reducing the costs of the implementation of this algorithm, few implementation methods have been devised. 

- Out of these the linked list method proves to be the costliest. 

- This algorithm is so expensive because it involves moving the items about the memory which is indeed a very time consuming task. 

- There is another method that requires hardware support.

Optimal page replacement algorithm: 

- This is also known as the clairvoyant replacement algorithm. 

- The page that has to be swapped in, it is placed in place of the page which according to the operating system will be used in future after a very long time. - In practical, this algorithm is impossible to be implemented in case of the general purpose OS because approximate time when a page will be used is difficult to be predicted. 

Explain the Round Robin CPU scheduling algorithm

There are number of CPU scheduling algorithms, all having different properties thus making them appropriate for different conditions. 

- Round robin scheduling algorithm or RR is commonly used in the time sharing systems. 

- This is the most appropriate scheduling algorithm for time sharing operating systems. 

- This algorithm shares many similarities with the FCFS scheduling algorithm but there is an additional feature to it. 

- This feature is preemption in the context switch occurring between two processes. 

- In this algorithm a small unit of time is defined and is termed as the time slice or the time quantum. 

- These time slices or quantum range from 10ms to 100 ms.

- The ready queue in round robin scheduling is implemented in a circular fashion. 

How to implement Round Robin CPU scheduling algorithm

Now we shall see about the implementation of the round robin scheduling:

1. The ready queue is maintained as the FIFO (first in first out) queue of the processes.
2. Addition of new processes is made at the rear end of the ready queue and selection of the process for execution by the processor is made at the front end.
3. The process first in the ready queue is thus picked by the CPU scheduler. A timer is set that will interrupt the processor when the time slice elapses. When this happens the process will be dispatched.
4. In some cases the CPU burst of some processes may be less than the size of the time slice. If this is the case, the process will be voluntarily released by the CPU. The scheduler will then jump to the process next in the ready queue and fetch it for execution.
5. While in other cases the CPU burst for some processes might be higher than the size of the time slice. In this case the timer set will send an interrupt to the processor, thus dispatching the process and putting it at the rear end of the ready queue. The scheduler will then jump to the next process in the queue.

- The waiting time in round robin scheduling algorithm has been observed to be quite long at an average rate. 

- In this algorithm, not more than one time slice can be allocated to any process under any conditions in a row. 

- However, there is an exception to this if there is only one process to be executed.

- If the CPU burst is exceeded by the process, the process is put back at the tail of the queue after preemption.

- Thus, we can call this algorithm as a preemptive algorithm also. 

- The size of the time quantum greatly affects the performance of the round robin algorithm.

- If the size of the time quantum is kept too large then it resembles the FCFS algorithm. 

- On the other hand if the quantum is of too small size, then this RR approach is called the processor sharing approach. 

- An illusion is created in which it seems every process has its own processor that runs at the fraction of the speed of the actual processor. 

- Further, the effect of the context switching up on the performance of the RR scheduling algorithm.

- A certain amount of time is utilized in switching from one process to another. 

- In this time the registers and the memory maps are loaded, a number of lists and tables are updated; memory cache is flushed and reloaded etc.

- Lesser the size of the time quantum, context switching will occur more number of times. 

What is Process State Diagram?

In the systems where multiple processors or multitasking is involved, a process has to go through a number of states. In this article we shall discuss about these states. 

The kernel of the operating system may not recognize these states distinctly but still for the understanding of how the processes are executed they act as useful abstractions. 

These various states can be looked up in a process state diagram for a systematic view. This diagram shows the transitions of the process between various states with arrows. Processes can be stored both in the secondary or virtual memory and in the main memory as per the situation.

Process States

- The primary process states occur in all types of the systems. 

- Processes in these states are usually stored in the main memory. 

Basically there are 5 major states of any process as discussed below:

Ø  Created: 

- It is also known as the ‘new’ state. 

- A process occupies this state up on it creation. 

- While waiting for being admitted to the next ready state this process lies in this state. 

- The admission scheduler will decide whether to admit the process to next state or to delay it on a short or long term. 

- However, this admission is approved in an automatic way in most of the desktop computers. 

- But in the systems with real time operating systems this is not true. 

- Here, the admission might be delayed by a certain amount of time.

- If too many states are admitted to the ready state in a real time operating system, condition of over contention and over saturation might occur disabling the system to meet its deadlines.

Ø  Ready or Waiting: 

- This state is taken up a process when it has been loaded in to the physical memory of the system and is waiting to be executed by the processor or precisely waiting to be context switched by the dispatcher. 

- At any instant of time there might be a number of processes waiting for their execution. 

- Here the processes have to wait in a queue called the run queue out of which only one process will be taken up by a processor. 

- Processes that are waiting for obtaining input from some event are not put in to this ready queue.

Ø  Running: 

- When a process is selected by the CPU for execution, its state is changed to running. 

- One of the processors executes the instructions of the process one by one. 

- Only one process can be run by the process at a time.

Ø Blocked: 

- When a process is blocked because of some event such as I/O operations is put in to the blocked state. 

- Another reason for a process being a blocked state can be its running out of the CPU time allocated to it.

Ø  Terminated: 

- Termination of a process may occur when either its execution is complete or it has been explicitly killed.

- This state is called the terminated or halted. 

- This process is called a zombie process if after coming in the terminated state it is not removed from the main memory. 

There are two additional states for supporting the virtual memory. In these states the process is usually stored in the secondary memory of the system:

Ø Swapped out or Waiting: 

- A process is said to be swapped out when it is removed from the primary memory and placed in the secondary memory. 

- This is done by the mid - term scheduler. 

- After this the state of this process changes to waiting.  

Ø  Swapped out and Blocked:

- In some cases, the processes that were in blocked state might be swapped out. 

- The same process might be again swapped in providing the conditions remain the same.

What are different types of schedulers and their workings?

Scheduling is an important part of the working of operating systems. 

- The scheduler is the component that provides access to the resources to the processes, threads and data flows. 

- These resources may include time of the processor and the communications bandwidth. 

- Scheduling is necessary for effectively balancing the load of the system and achieving the target of QoS or quality of service. 

- Scheduling is also necessary for the systems that do multitasking and multiplexing on a single processor since they need to divide the CPU time between many processes. 

- In multiplexing, it is required for timing the simultaneous transmission of the multiple flows.

Important things about Scheduler

There are 3 things which most concern the scheduler:

1. Throughput
2. Latency inclusive of the response time and the turnaround time
3. Waiting time or the fairness time

- But when practically implemented, conflicts arise between these goals for example between latency and throughput. 

- It is the scheduler that can make a compromise between any two goals. 

- Based on the user’s requirements and the objectives it is decided to which goal the preference has to be given. 

- In systems such as the embedded systems and robotics that operate in real time environment, it has to be ensured by the scheduler that the processes are capable of meeting the deadlines. 

- This is a very critical factor in maintaining the stability of the system. 

- The administrative back end is used for managing the scheduled tasks that are then sent to the mobile devices.  

Types of Schedulers

There are 3 different types of schedulers available which we discuss below:

Long term Schedulers or Admission Schedulers: 

- The purpose of this type of scheduler is to decide about the processes and jobs to be admitted or added to the ready queue. 

- When a program makes an attempt for executing a process, it is the responsibility of the long – term scheduler to delay or authorize the request for admitting the process to the ready queue. 

- Thus, what all processes will be executed by the system is dictated by this scheduler. 

- It also dictates about the degree of the concurrency and handling of the CPU intensive and I/O intensive processes. 

- Modern operating systems use this for making sure that there is enough time for the processes to finish of their tasks. 

- Modern GUIs would be of very less use if there was no real time scheduling. 

- The long term queue resides in the secondary memory.

Medium term Schedulers: 

- This scheduler serves the purpose of removing the processes from the physical memory and placing them in the virtual memory and even vice versa. 

- This process is called swapping out and swapping in. 

- A process that has been inactive for some time might be swapped by the scheduler. 

- It may also swap a process with frequent page faulting, low priority or more amount of memory etc. 

- This is necessary since this makes the space available for other processes.

Short term Schedulers: 

- These schedulers are more commonly known as the CPU schedulers.

- It decides which one out of all the processes will be executed after the clock interrupt, a system call, an I/O interrupt, hardware interrupt and so on. 

- Thus, we can say that the frequency of the short term schedulers of making decisions is much higher than that of the long term and medium term schedulers since after every time slice these schedulers have to decide.

- There is one more component that is involved in CPU scheduling but is not counted under schedulers. It is called dispatcher.