1. DATA STORAGE
Chapter 1

2. 1.1 BITS AND THEIR STORAGE
Data Storage1-2

3. BITS AND BIT PATTERNS
 Bit: Binary Digit (0 or 1)
 Bit Patterns are used to represent
information.
 Numbers
 Text characters
 Images
 Sound
 And others
1-3

4. BOOLEAN OPERATIONS
 Boolean Operation: An operation that manipulates
one or more true/false values
 Specific operations
 AND
 OR
 XOR (exclusive or)
 NOT
1-4

5. THE BOOLEAN OPERATIONS AND, OR, AND XOR
(EXCLUSIVE OR)
1-5

6. GATES
 Gate: A device that computes a Boolean operation
 Often implemented as (small) electronic circuits
 Provide the building blocks from which computers are
constructed
 VLSI (Very Large Scale Integration)
1-6

7. A PICTORIAL REPRESENTATION OF AND, OR, XOR, AND NOT
GATES AS WELL AS THEIR INPUT AND OUTPUT VALUES
1-7

8. FLIP-FLOPS
 Flip-flop: A circuit built from gates that can store one bit.
 One input line is used to set its stored value to 1
 One input line is used to set its stored value to 0
 While both input lines are 0, the most recently stored value is
preserved
1-8

9. A SIMPLE FLIP-FLOP CIRCUIT
1-9

10. 1.2 MAIN MEMORY
Data Storage1-10

11. MAIN MEMORY CELLS
 Cell: A unit of main memory (typically 8 bits
which is one byte)
 Most significant bit: the bit at the left (high-order) end
of the conceptual row of bits in a memory cell
 Least significant bit: the bit at the right (low-order) end
of the conceptual row of bits in a memory cell
1-11

12. THE ORGANIZATION OF A BYTE-SIZE MEMORY CELL
1-12

13. MAIN MEMORY ADDRESSES
 Address: A “name” that uniquely identifies
one cell in the computer’s main memory
 The names are actually numbers.
 These numbers are assigned consecutively starting at
zero.
 Numbering the cells in this manner associates an order
with the memory cells.
1-13

14. MEMORY CELLS ARRANGED BY ADDRESS
1-14

15. MEASURING MEMORY CAPACITY
 Kilobyte: 210 bytes = 1024 bytes
 Example: 3 KB = 3 times1024 bytes
 Sometimes “kibi” rather than “kilo”
 Megabyte: 220 bytes = 1,048,576 bytes
 Example: 3 MB = 3 times 1,048,576 bytes
 Sometimes “megi” rather than “mega”
 Gigabyte: 230 bytes = 1,073,741,824 bytes
 Example: 3 GB = 3 times 1,073,741,824 bytes
 Sometimes “gigi” rather than “giga”
1-15

16. 1.3 MASS STORAGE
Data Storage1-16

17. MASS STORAGE
 On-line versus off-line
 Typically larger than main memory
 Typically less volatile than main memory
 Typically slower than main memory
1-17

18. MASS STORAGE SYSTEMS
 Magnetic Systems
 Disk
 Tape (all but obsolete)
 Optical Systems
 CD
 DVD
 Blu-Ray
 Flash Drives
 Solid State Drives (SSDs)
1-18

19. MAGNETIC DISKS
1-19

20. GAP BETWEEN HEAD AND PLATTER
1-20
Head
Smoke
Particle
Human
Hair
Dust
Particle

21. DISK PERFORMANCE
1-21
Disk
Performance
Seek time
Rotational
latency
Transfer
rate

22. OPTICAL DISKS
1-22

23. CD AND DVD TRACK COMPARISON
1-23
CD DVD

24. FILES
 A file is a named collection of bits
 Files are often stored in pieces
 1 byte chunks in memory
 Sector-sized chunks on disk
1-24

25. 1.4 REPRESENTING INFORMATION AS BIT
PATTERNS
Data Storage1-26

26. REPRESENTING TEXT
 Each character (letter, punctuation, etc.) is
assigned a unique bit pattern
 ASCII
 American Standard Code for Information Interchange
 Uses patterns of 7-bits to represent most symbols used in
written English text
 128 (27) unique characters
 Unicode
 Uses patterns of 16-bits to represent the major symbols used
in languages world side
 65,536 (216) possible characters
 ISO
 International Organization for Standardization
 4,294,967,296 (232) possible characters
1-27

27. “HELLO.” IN ASCII
1-28

28. REPRESENTING NUMERIC VALUES
 Binary: a number system using only the digits 0
(zero) and 1 (one)
 Maps well to the internal characteristics of the
computer
 Limitations of computer representations of numeric
values
 Overflow: happens when a value is too big to be
represented
 Truncation: happens when a value is between two
representable values
1-32

29. REPRESENTING IMAGES
1-33
 Bit map techniques
 Pixel: short for “picture
element”
 RGB
 Luminance and
chrominance
 Vector techniques
 Scalable
 TrueType and
PostScript

30. SCALABLE VS. BITMAPPED FONTS
1-34

31. A SOUND WAVE REPRESENTED BY THE SEQUENCE 0,
1.5, 2.0, 1.5, 2.0, 3.0, 4.0, 3.0, 0
1-35

32. 1.5 THE BINARY SYSTEM
Data Storage1-36

33. THE BASE TEN AND BINARY SYSTEMS
1-37

34. DECODING THE BINARY REPRESENTATION 100101
1-38

35. FINDING THE BINARY REPRESENTATION OF 13
1-39

36. BINARY ADDITION
1-40

37. DECODING THE BINARY REPRESENTATION 101.101
1-41

38. 1-42
There are 10 kinds of people in
the world: those who understand
binary and those who don’t.

39. HEXADECIMAL NOTATION
 Hexadecimal notation: A shorthand notation for long
bit patterns
 Divides a pattern into groups of four bits each
 Represents each group by a single symbol
 Example: 1010 0011 becomes A3
1-43

40. THE HEXADECIMAL CODING SYSTEM
1-44

41. 1-45
How many people can read hex
if only you and DEAD people
can read hex? 57,006

42. 1.6 STORING INTEGERS
Data Storage1-46

43. STORING INTEGERS
 Two’s complement notation: The most popular
means of representing integer values
 Excess notation: Another means of representing
integer values
 Both can suffer from overflow errors.
1-47

44. TWO’S COMPLEMENT
1-48
 Fixed number of bits
 MSB is sign bit
 1 = negative
 0 = positive

45. ENCODING IN TWO’S COMPLEMENT NOTATION
1-49

46. ADDITION AND SUBTRACTION USING TWO’S
COMPLEMENT
1-50

47. TAKING ISSUE WITH THE BOOK
“The point is that computers
can make mistakes.”
-J. Glenn Brookshear, Computer Science, an Overview, p. 54
1-51

48. WRONG

49. TAKING ISSUE WITH THE BOOK
Computers don’t make
mistakes. They do exactly
what you tell them to.
1-61

50. EXCESS NOTATION
 Another system of representing signed integers
1. List all bit patterns of a given length
2. Find the first bit pattern with a 1 in the MSB; this will
represent zero
3. Patterns below our zero represent negative number,
patterns preceding it represent positive numbers
1-62

51. EXCESS EIGHT CONVERSION TABLE
1-63

52. 1.7 STORING FRACTIONS
Data Storage1-64

53. STORING FRACTIONS
 Floating-point Notation: Consists of a sign bit, a
mantissa field, and an exponent field.
 Related topics include
 Normalized form
 Truncation errors
1-65

54. FLOATING-POINT NOTATION COMPONENTS
1-66

55. ENCODING THE VALUE 25⁄8
1-67