TY - GEN
T1 - Understanding wireless mobile systems
T2 - 4th International Workshop on Distributed Computing, IWDC 2002
AU - Tripathi, Satish K.
AU - Jobin, J.
AU - Faloutsos, Michalis
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2002.
PY - 2002
Y1 - 2002
N2 - Simulation is a widely used technique in understanding and analyzing the properties and behavior of wireless networks. Simulation models abound in the wireless domain. Most of these models suffer from an abundance of parameters. Different models might use different parameters. Moreover, even for common parameters, there are no universally accepted standard values. This makes the task of analyzing simulation results a complicated one. We propose a framework to address this problem. One component of our framework is based on the reduction of the vast parameter space to a smaller, more compact one that encompasses only a few essential parameters. These parameters try to aggregate other parameters and hide the specifics of the underlying system, thereby easing the task of evaluating simulation results. The other component is based on a novel concept called steady state utilization which tries to capture the inherent capacity of a network. Using steady state utilization as the maximum potential capacity (without loss) of a network, we show how it can be used in the task of comparing results from different simulation models.
AB - Simulation is a widely used technique in understanding and analyzing the properties and behavior of wireless networks. Simulation models abound in the wireless domain. Most of these models suffer from an abundance of parameters. Different models might use different parameters. Moreover, even for common parameters, there are no universally accepted standard values. This makes the task of analyzing simulation results a complicated one. We propose a framework to address this problem. One component of our framework is based on the reduction of the vast parameter space to a smaller, more compact one that encompasses only a few essential parameters. These parameters try to aggregate other parameters and hide the specifics of the underlying system, thereby easing the task of evaluating simulation results. The other component is based on a novel concept called steady state utilization which tries to capture the inherent capacity of a network. Using steady state utilization as the maximum potential capacity (without loss) of a network, we show how it can be used in the task of comparing results from different simulation models.
UR - https://www.scopus.com/pages/publications/84958758103
U2 - 10.1007/3-540-36385-8_11
DO - 10.1007/3-540-36385-8_11
M3 - Conference contribution
AN - SCOPUS:84958758103
SN - 354000355X
SN - 9783540003557
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 108
EP - 117
BT - Distributed Computing - Mobile andWireless Computing 4th InternationalWorkshop, IWDC 2002 Calcutta, India, December 28-31, 2002 Proceedings
A2 - Bhattacharya, Swapan
A2 - Das, Sajal K.
PB - Springer Verlag
Y2 - 28 December 2002 through 31 December 2002
ER -