Annotation of embedaddon/strongswan/src/libstrongswan/processing/scheduler.h, revision 1.1.1.1
1.1 misho 1: /*
2: * Copyright (C) 2009-2015 Tobias Brunner
3: * Copyright (C) 2005-2007 Martin Willi
4: * Copyright (C) 2005 Jan Hutter
5: * HSR Hochschule fuer Technik Rapperswil
6: *
7: * This program is free software; you can redistribute it and/or modify it
8: * under the terms of the GNU General Public License as published by the
9: * Free Software Foundation; either version 2 of the License, or (at your
10: * option) any later version. See <http://www.fsf.org/copyleft/gpl.txt>.
11: *
12: * This program is distributed in the hope that it will be useful, but
13: * WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
14: * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
15: * for more details.
16: */
17:
18: /**
19: * @defgroup scheduler scheduler
20: * @{ @ingroup processing
21: */
22:
23: #ifndef SCHEDULER_H_
24: #define SCHEDULER_H_
25:
26: typedef struct scheduler_t scheduler_t;
27:
28: #include <library.h>
29: #include <processing/jobs/job.h>
30:
31: /**
32: * The scheduler queues timed events which are then passed to the processor.
33: *
34: * The scheduler is implemented as a heap. A heap is a special kind of tree-
35: * based data structure that satisfies the following property: if B is a child
36: * node of A, then key(A) >= (or <=) key(B). So either the element with the
37: * greatest (max-heap) or the smallest (min-heap) key is the root of the heap.
38: * We use a min-heap with the key being the absolute unix time at which an
39: * event is scheduled. So the root is always the event that will fire next.
40: *
41: * An earlier implementation of the scheduler used a sorted linked list to store
42: * the events. That had the advantage that removing the next event was extremely
43: * fast, also, adding an event scheduled before or after all other events was
44: * equally fast (all in O(1)). The problem was, though, that adding an event
45: * in-between got slower, as the number of events grew larger (O(n)).
46: * For each connection there could be several events: IKE-rekey, NAT-keepalive,
47: * retransmissions, expire (half-open), and others. So a gateway that probably
48: * has to handle thousands of concurrent connections has to be able to queue a
49: * large number of events as fast as possible. Locking makes this even worse, to
50: * provide thread-safety, no events can be processed, while an event is queued,
51: * so making the insertion fast is even more important.
52: *
53: * That's the advantage of the heap. Adding an element to the heap can be
54: * achieved in O(log n) - on the other hand, removing the root node also
55: * requires O(log n) operations. Consider 10000 queued events. Inserting a new
56: * event in the list implementation required up to 10000 comparisons. In the
57: * heap implementation, the worst case is about 13.3 comparisons. That's a
58: * drastic improvement.
59: *
60: * The implementation itself uses a binary tree mapped to a one-based array to
61: * store the elements. This reduces storage overhead and simplifies navigation:
62: * the children of the node at position n are at position 2n and 2n+1 (likewise
63: * the parent node of the node at position n is at position [n/2]). Thus,
64: * navigating up and down the tree is reduced to simple index computations.
65: *
66: * Adding an element to the heap works as follows: The heap is always filled
67: * from left to right, until a row is full, then the next row is filled. Mapped
68: * to an array this gets as simple as putting the new element to the first free
69: * position. In a one-based array that position equals the number of elements
70: * currently stored in the heap. Then the heap property has to be restored, i.e.
71: * the new element has to be "bubbled up" the tree until the parent node's key
72: * is smaller or the element got the new root of the tree.
73: *
74: * Removing the next event from the heap works similarly. The event itself is
75: * the root node and stored at position 1 of the array. After removing it, the
76: * root has to be replaced and the heap property has to be restored. This is
77: * done by moving the bottom element (last row, rightmost element) to the root
78: * and then "seep it down" by swapping it with child nodes until none of the
79: * children has a smaller key or it is again a leaf node.
80: */
81: struct scheduler_t {
82:
83: /**
84: * Adds a event to the queue, using a relative time offset in s.
85: *
86: * @param job job to schedule
87: * @param time relative time to schedule job, in s
88: */
89: void (*schedule_job) (scheduler_t *this, job_t *job, uint32_t s);
90:
91: /**
92: * Adds a event to the queue, using a relative time offset in ms.
93: *
94: * @param job job to schedule
95: * @param time relative time to schedule job, in ms
96: */
97: void (*schedule_job_ms) (scheduler_t *this, job_t *job, uint32_t ms);
98:
99: /**
100: * Adds a event to the queue, using an absolute time.
101: *
102: * The passed timeval should be calculated based on the time_monotonic()
103: * function.
104: *
105: * @param job job to schedule
106: * @param time absolute time to schedule job
107: */
108: void (*schedule_job_tv) (scheduler_t *this, job_t *job, timeval_t tv);
109:
110: /**
111: * Returns number of jobs scheduled.
112: *
113: * @return number of scheduled jobs
114: */
115: u_int (*get_job_load) (scheduler_t *this);
116:
117: /**
118: * Remove all scheduled jobs.
119: */
120: void (*flush)(scheduler_t *this);
121:
122: /**
123: * Destroys a scheduler object.
124: */
125: void (*destroy) (scheduler_t *this);
126: };
127:
128: /**
129: * Create a scheduler.
130: *
131: * @return scheduler_t object
132: */
133: scheduler_t *scheduler_create(void);
134:
135: #endif /** SCHEDULER_H_ @}*/
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