Download e-book for iPad: Analytical modeling of wireless communication systems by Chiasserini, Carla-Fabiani; Gribaudo, Marco; Manini, Daniele

By Chiasserini, Carla-Fabiani; Gribaudo, Marco; Manini, Daniele

ISBN-10: 1061071081

ISBN-13: 9781061071086

ISBN-10: 1119307724

ISBN-13: 9781119307723

ISBN-10: 1119307732

ISBN-13: 9781119307730

ISBN-10: 1119307740

ISBN-13: 9781119307747

ISBN-10: 184821944X

ISBN-13: 9781848219441

Wireless networks characterize a cheap and handy option to hook up with the net. even though, regardless of their functions throughout a number of applied sciences, one problem nonetheless continues to be: to appreciate the habit of instant sensor networks and investigate their functionality in large-scale scenarios.

When loads of community nodes have to engage, constructing compatible analytical types is vital to make sure definitely the right assurance and throughput of those networks and to reinforce person mobility. this is often intrinsically tricky a result of dimension and variety of assorted community nodes and users.

This publication highlights a few examples which express how this challenge might be conquer with using assorted options. a radical parameter research exhibits the reader the way to the make the most analytical versions for a good improvement and administration of other different types of instant networks.

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Extra resources for Analytical modeling of wireless communication systems

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1. Single message transfer The behavior of a single message, generated by a sensor and transferred to the central controller, is described by using HA. 1, where each box represents a state of the HA. The variable named Hop takes on the identifier of the link that the message is currently traversing. Hop is initialized to first_hop, which, in a single-hop topology, is the identifier of the link between the sensor that has generated the message and the central controller. 1 only the portion of the HA marked with a continuous line has to be considered.

Consider a generic sequence ξ(r) of h points aligned on the same segment. The distance between two consecutive points is written as: dist(r j , r j+1 ) = αj , with 0 ≤ j ≤ h − 2, and the one between the last two points as: dist(r h−1 , r h ) = dist(r 0 , r h ) − h−2 j=0 αj . Then, it follows that ⎡ E(ξ(r)) = 2h(E ele + E proc ) + Cd ⎣ h−2 ⎛ αjη + ⎝dist(r 0 , r n ) − j=0 h−2 ⎞η ⎤ αj ⎠ ⎦ j=0 The partial derivatives of E(ξ(r)) along αj , 0 ≤ j ≤ h − 2, are as follows, ⎡ ⎛ ∂E(ξ(r)) = Cd ⎣ηαjη−1 − η ⎝dist(r 0 , r h ) − ∂αj h−2 ⎞η−1 ⎤ αj ⎠ ⎦ j=0 It can be easily seen that all partial derivatives are equal to 0 if the distance between any two consecutive nodes αj is constant and equal to α = dist(rh0 ,r h ) .

8] otherwise where r is the point that minimizes the energy required to send a packet from r to the sink. Note that, if point r is within distance dc from the sink, either a one-hop or a multi-hop communication may take place, depending on their energy cost. When a multi-hop communication is required, the definition of r turns out to be exceedingly complicated. Thus, m (r , r ) is aproximated with min (r ) that is the minimum possible energy needed to send a packet from r Fluid Models and Energy Issues to the sink.

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Analytical modeling of wireless communication systems by Chiasserini, Carla-Fabiani; Gribaudo, Marco; Manini, Daniele

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