FIFO vs. LIFO: 4 Differences | Spiceworks - Spiceworks (2024)

This data structure follows the FIFO principle, meaning new entities are added to the back of the queue, and the entities at the front of the queue are processed first.

Like a regular queue of people at a movie theater ticket booth or a supermarket checkout counter, the queue-type data structure has two ends. One end is the front, where entities are removed for processing. The other end is the back, where new entities are added.

When a new entity needs to be added to the back of the queue, the ‘enqueue’ process is executed. On the other hand, when an entity needs to be removed from the front of the queue for processing, the ‘dequeue’ process is executed.

Another operation carried out in queue-type data structures is known as ‘peek,’ where the entity at the front of the queue is displayed without its removal.

This data structure is used in many computing systems to store and process data. For instance, network switches, bridges, and routers use FIFO to hold data packets while they are transported to their destination.

Queue implementation takes place using varying data structures, including arrays and linked lists. A queue has no theoretical capacity limit; however, in practice, ‘bounded queues’ might feature a fixed capacity.

Numerous efficient implementations of FIFO queues exist. They can perform entity addition and removal processes in constant time (O(1)). Some programming languages provide in-built queue support; for instance, the ‘queue’ interface in the Java library and the ‘queue’ templated class in the C++ Standard Template Library.

While the former operation adds an element to the collection, the latter removes the most recently added element yet to be removed. The LIFO order of elements is followed in a stack.

Just like a real-life stack of physical items placed one on top of the other (such as a stack of plates), the data elements on the top must be removed before those deeper in the stack.

Like a queue-type data structure, a stack is also linear. More abstractly, it may be seen as a sequential collection wherein the push and pop operations only occur at one end of the structure — the ‘top’ of the stack.

This data structure allows implementing a stack as a singly linked list and a pointer to the top element.

In several implementations, stacks have more operations than the simple ‘push’ and ‘pop.’ For instance, the ‘top of stack’ operation, similar to the ‘peek’ operation in a queue, allows observing the top element without removing it from the stack.

If an empty stack is encountered, an underflow condition will occur upon execution of the ‘top of stack’ or ‘pop’ operations. Additionally, implementations exist to allow for checks on whether the stack is empty and the size of the stack.

Stack implementation can take place either through a linked list or an array. Stacks can be seen as special cases of lists and are identified not by the implementation but by the interface — the user can only push or pop elements onto the linked list or array with a few other helper operations.

A key application of FIFO is in disk scheduling algorithms where disk controllers use FIFO to set the order of process execution.

Besides this, numerous data structures use FIFO for data processing. The main structure that uses FIFO is the queue; however, other variants also utilize the FIFO technique.

FIFO is also used in communications and networking, where data packets stay between the routers in the required order by leveraging FIFO. This technique allows the router to specify the order in which packets must be transferred.

Finally, FIFO is used in operating system algorithms. Processes are selected for CPU time in the order of arrival. For instance, when several processes are awaiting CPU access, the processes that arrived earlier are prioritized by the operating system. This ensures that all processes receive CPU time fairly.

A common use of LIFO is in data structures. The stack is the main data structure following the LIFO approach. It is used in several programming languages for data storage and management. The stack data structure has several applications, including expression evaluation, memory management, and function calls.

LIFO also sees usage in memory management. For instance, the stack memory allocation algorithm leverages LIFO. Here, memory allocation and deallocation take place in a stack-like structure. Upon being called, the data of the function is stored in the stack and is removed upon return.

A common application of LIFO is in the ‘History’ feature of web browsers. When a user visits a web page, its URL is captured and added to the ‘top’ of the stack, along with other URLs visited. Once the ‘Back’ button is pressed, the most recently visited web page is removed from the top of the stack and displayed to the user.

Another example of LIFO is undo and redo operations in computing. For instance, if you’re using a word processor and want to undo a formatting change, you use the Control (or Command) and Z keys together. The previous state of formatting is then retrieved and reapplied by the word processor software using a LIFO data structure. Similarly, if a user has just sent a file to the bin on their device and wishes to undo the deletion, they simply tap the ‘undo’ button, and the application fetches and restores the most recently deleted file from the top of the deleted files data stack.

Finally, computer networks use LIFO in the ‘last-in-first-out queue.’ This helps routers specify the order in which data packets must be transmitted between systems. Here, LIFO helps ensure that the data packets reach the intended recipient in a logical order.

Another advantage of the FIFO method is its fair approach across processes. The first process to be received will be the first to be executed, per the principle of first come, first served (FCFS). This ensures an equal opportunity for CPU usage for all processes and minimizes the possibility of untimely termination or malfunction.

In terms of chronology, FIFO ensures that the oldest element in the queue receives preferential processing. This is achieved by keeping the oldest element at the beginning of the queue and allowing swift access.

As the need to find the oldest element is removed, the retrieval process becomes more efficient. The FIFO method also eliminates the ‘wait and hold’ criteria, decreasing data processing time.

Lastly, the FIFO approach features fixed memory consumption. This is a noteworthy advantage because it allows memory utilization to stay constant regardless of the number of operations executed. This advantage is a byproduct of the fact that FIFO does not need any extra data structures to manage its elements.

The LIFO approach gives preferential processing to the last element to enter. This is especially useful when the most newly added items need to be processed swiftly without the rest of the operation having to be completed.

Lastly, LIFO is beneficial for applications wherein users need access to the freshest information in terms of chronology, such as stock market tracking or financial data analysis.

Additionally, FIFO does not allow the elements to be accessed randomly. This prevents the CPU from accessing any queued element except the first one and might lead to inefficiency in certain processes where the CPU might need to access a particular element in the middle of the queue.

Finally, while FIFO is known for its fairness during process execution, it cannot support process prioritization. This might cause critical processes to wait for regular or lower-priority processes to get done, affecting system effectiveness.

Another drawback of LIFO is its inflexibility; it might not be an efficient choice for applications requiring a more sophisticated algorithm.

Finally, LIFO is not efficient in memory management. This is because, unlike FIFO (where memory consumption is fixed), memory utilization in LIFO changes with each operation, and a fixed size cannot be provided for memory consumed. Since memory consumption for LIFO is not predetermined, ensuring efficient resource allocation is challenging.