It takes the average reader 2 hours and 31 minutes to read Restless Multi-Armed Bandit in Opportunistic Scheduling by Kehao Wang
Assuming a reading speed of 250 words per minute. Learn more
This book provides foundations for the understanding and design of computation-efficient algorithms and protocols for those interactions with environment, i.e., wireless communication systems. The book provides a systematic treatment of the theoretical foundation and algorithmic tools necessarily in the design of computation-efficient algorithms and protocols in stochastic scheduling. The problems addressed in the book are of both fundamental and practical importance. Target readers of the book are researchers and advanced-level engineering students interested in acquiring in-depth knowledge on the topic and on stochastic scheduling and their applications, both from theoretical and engineering perspective.
Restless Multi-Armed Bandit in Opportunistic Scheduling by Kehao Wang is 151 pages long, and a total of 37,901 words.
This makes it 51% the length of the average book. It also has 46% more words than the average book.
The average oral reading speed is 183 words per minute. This means it takes 3 hours and 27 minutes to read Restless Multi-Armed Bandit in Opportunistic Scheduling aloud.
Restless Multi-Armed Bandit in Opportunistic Scheduling is suitable for students ages 10 and up.
Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.
When deciding what to show young students always use your best judgement and consult a professional.
Restless Multi-Armed Bandit in Opportunistic Scheduling by Kehao Wang is sold by several retailers and bookshops. However, Read Time works with Amazon to provide an easier way to purchase books.
To buy Restless Multi-Armed Bandit in Opportunistic Scheduling by Kehao Wang on Amazon click the button below.
Buy Restless Multi-Armed Bandit in Opportunistic Scheduling on Amazon