This special issue mainly works on performance evaluation of ad hoc networks. Ad hoc wireless mobile networks are self-organizing and self-reconfiguring networks that can be establish anytime and anywhere without the presence of static radio base stations or fixed backbone infrastructures. Advances in battery technology have unfortunately fallen behind that of CPU technology. This issue contains the various key points for performance evaluation of the networks which are given below:

1. Verification of analytical models and simulation environments against real-life
2. Proven practices for validation of wireless networking solutions through simulation or experimentation
3. Benchmarking methods enabling fair comparison between competing solutions or subsequent developments
4. Unambiguous definitions of performance evaluation metrics and according methods for measurement and calculation
5. Tools specialized for realistic traffic generation and the creation of repeatable background environment properties (for example home, office, factory) in simulators or experimental settings
6. Methods and techniques to generate repeatable, reproducible, and reliable measurements in experimental homogeneous/heterogeneous settings
7. Analysis of control tools for configuring and driving experiments, e.g. management and control tools to conduct experiments with ease and efficiency, monitor the experiment conditions, and run-time modifying the experiment parameters
8. Distributed measurement techniques and tools for test-beds/experimental facilities including small to large-scale test-beds, federated test-beds, homogeneous/heterogeneous test-beds, etc
9. Run-time integration of modeling and simulation tools into test-beds/experimental facilities
10. Data-mining, interpretation, knowledge acquisition from simulation or experimental measurements
11. Statistical analysis of experimental data including multivariate analysis (e.g., analysis of variance, regression analysis, principal component analysis and variants, discriminant analysis and variants), analysis time series (e.g. frequency-domain/time-domain methods, parametric and non-parametric methods, univariate/multivariate), statistical inference (e.g., frequentist, Bayesian)