Solving the queue-based cache eviction policy problem in C++

10 Oct 2023

When implementing caching systems, choosing the right cache eviction policy is crucial for optimizing performance and memory usage. One commonly used policy is the queue-based eviction policy, where the least recently used (LRU) item is evicted from the cache when it is full and a new item needs to be inserted.

In this article, we will discuss how to solve the queue-based cache eviction policy problem in C++. We will present an efficient implementation using a combination of a doubly linked list and a hashmap.

Understanding the Queue-Based Cache Eviction Policy

Before diving into the implementation details, let’s briefly understand how the queue-based cache eviction policy works.

In this policy, the cache is treated as a queue, with the most recently used items at the front and the least recently used items at the back. When a new item is accessed or inserted into the cache, it is moved to the front of the queue. When the cache is full and a new item needs to be inserted, the item at the back of the queue (i.e., the least recently used item) is evicted.

Implementation Using Doubly Linked List and Hashmap

To efficiently implement the queue-based eviction policy, we can combine a doubly linked list and a hashmap. The doubly linked list will maintain the order of the items based on their usage, and the hashmap will provide fast access to individual items in the list.

Here’s a step-by-step approach to implementing the cache eviction policy:

Define a data structure to represent each item in the cache. This structure should contain the necessary fields to store the key, value, and pointers to the previous and next items in the doubly linked list.
```
struct CacheItem {
    int key;
    int value;
    CacheItem* prev;
    CacheItem* next;
};
```
Create a hashmap to store the key-value pairs of the cache items. This hashmap will allow us to quickly access the cache items by their keys.
```
std::unordered_map<int, CacheItem*> cacheMap;
```
Maintain a doubly linked list to keep track of the items in the cache. The head of the list will represent the most recently used item, while the tail will represent the least recently used item.
```
CacheItem* head;  // Points to the most recently used item
CacheItem* tail;  // Points to the least recently used item
```

When a cache item is accessed (read or updated), update its position in the doubly linked list by moving it to the front (head) of the list.

// Pseudocode for updating the position of a cache item:
item->prev->next = item->next;
item->next->prev = item->prev;
item->prev = nullptr;
item->next = head;
head->prev = item;
head = item;

When a new cache item is inserted, check if the cache is full. If it is full, evict the item at the back (tail) of the list and remove it from the hashmap. Insert the new item at the front (head) of the list and add it to the hashmap.

// Pseudocode for inserting a new cache item:
if (cacheMap.size() >= CACHE_SIZE) {
    // Evict the item at the back (tail) of the list
    CacheItem* toEvict = tail;
    tail = tail->prev;
    cacheMap.erase(toEvict->key);
    delete toEvict;
}
CacheItem* newItem = new CacheItem;
// Set the necessary fields of newItem
// ...
newItem->prev = nullptr;
newItem->next = head;
head->prev = newItem;
head = newItem;
cacheMap[newItem->key] = newItem;

When a cache item is removed, update the pointers of the previous and next items in the doubly linked list and remove it from the hashmap.

// Pseudocode for removing a cache item:
item->prev->next = item->next;
item->next->prev = item->prev;
cacheMap.erase(item->key);
delete item;

By combining the doubly linked list and hashmap, we can efficiently implement the queue-based cache eviction policy in C++. This implementation provides fast access to the cache items through the hashmap and ensures efficient eviction of the least recently used items.

Now that you have a solid understanding of the queue-based cache eviction policy and its implementation in C++, you can apply this knowledge to build efficient caching systems that enhance the performance of your applications.

#caching #eviction