Changes between Initial Version and Version 1 of DataStructures

Timestamp:

May 30, 2006, 4:44:49 PM (18 years ago)

Author:

soujak

Comment:

--

DataStructures

@@ +1 @@
+= Data structures =
+
+A well-designed data structure allows a variety of critical operations to be
+performed, using as little resources, both execution time and memory space, as
+possible. Moreover a carefully chosen data structure will allow a more efficient
+algorithm to be used; consequently such choice assume a primary importance in 
+this project.
+[[BR]]
+The two fundamental data structures on which Phase 1 layer is founded are lists
+and trees, implemented in various ways, depending on the singular case
+evaluations.
+
+Here below we are going to describe the two most significative flavour of them.
+
+ == 1. Linear single linked list ==
+This simple data structure has been choosen for trivial structures
+implementation. We are talking about lists of non-allocated PCBs or SDs:
+respectively pcbFree and semdFree.
+
+In fact, because of element insertion and deletion may involve only the first
+one, a stack with a ''O(1)'' computational cost is what we was looking for. And
+is what we implemented with a linear single linked list, appreciating its
+simplicity. 
+
+
+== 2. Circular double linked list ==
+List management operations, such as element insertion and deletion, require
+predecessor and successor updating. Because of this, a previous element pointer
+(`p_prev`) is added to the PCB standard structure, performing these operations
+scanning the list only once.
+
+Kaya Phase 1 will take advantage of double circularly linked list benefits in
+every processes queue, which is widely used by operating system.
+
+
+== 3. Semaphore binary tree ==
+The importance of the '''choice''' of data structure increases directly with the
+performance relevance and for semaphore descriptors management becomes a primary
+goal. That is because semaphores queue's phisical address is obfuscated in a
+higher level view, so Phase 1 layer must encapsulate the association between
+semaphore address (semAdd) and its queue into the Semaphore descriptors (SDs).
+
+Such association must be searched between them and if they are managed in a sorted
+structure computational costs decrease, avoiding scanning everyone. For this
+reason we opted for a data structure that is more complex and difficult to
+mantain but, on the other hand, is more performant and scalable: a binary search
+tree.
+
+Let us show in detail a BSTs '''comparison''' with sorted list.
+[[BR]]
+The major part of mantainence costs depends on the fact that it is sorted and,
+consequently, on the search cost. In fact, while a list search costs ''O(n)'', a
+binary tree takes only ''O(log(n))'', because of the number of scanned elements
+is at most equal to the tree height. By the way, input distribution influences
+BST's height in a determining way, deciding tree balance, making ''O(log(n))''
+an estimate of the average case cost. In particularly adverse situations BSTs
+collapse into a ''f**ked/s**t'' list.
+[[BR]]
+Summing up, in order to appreciate BSTs performance improvements and scalability,
+input cardinality should be sufficiently large and well-distributed.
+
+Like often happens, performance and '''memory usage''' risk to collide and a good
+compromise is needed.
+[[BR]]
+Therefore we tried to limit wastes, just single-linking the tree with `s_rightC`
+and `s_leftC` pointers, increasing module complexity and consequent
+implementation and mantainance [wiki:doc/devel difficulties].