May 2026
Intermediate
272 pages
9h 39m
English
Content preview from Algorithms for Smart World Technologies
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Chapter 1Introduction to Complexities
The complexity of an algorithm refers to the amount of time and/or space it consumes when processing an input of size 
. More broadly, the total resources—or computational cost—required by an algorithm to produce the desired outcome is termed computational complexity, often simply referred to as complexity. This can be evaluated in terms of time complexity and space complexity.
In the context of smart systems, the theoretical analysis of algorithmic complexity is still in its formative phase. This is because such algorithms necessitate the consideration of advanced forms of complexity beyond traditional measures—such as communication complexity, input/output (I/O) complexity, data complexity, and other quantifiable constraints.
This chapter explores:
- the significance of complex systems and algorithms,
- various metrics used to assess efficiency,
- the challenges of deployment complexity, and
- the ethical and risk-related dimensions of complexity measurement.
By the end of this chapter, readers will gain a comprehensive understanding of complexities, supported by detailed explanations of the following key aspects:
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