Abstract — Recently, researchers have discovered that many of social, natural and biological networks are characterized by scale-free power-law connectivity distribution and a few densely populated nodes, known as hubs. We envision that wireless communication or sensor networks are directly deployed over such real-world networks to facilitate communication among participating entities. Here nodes move in such a way that they exhibit scale-free connectivity distribution at any instance, which cannot be modeled by most of the prior mobility models such as random waypoint (RWP) mobility model. This paper proposes clustered mobility model (CMM), which facilitates in forming hubs in a network satisfying the scale-free property. We call this a scale-free wireless network (SFWN). In CMM, it is possible to control the degree of node concentration or non-homogeneity to easily assess the strengths and weaknesses of the scale-free phenomena. To the best of the authors ’ knowledge, there has been no such mobility model reported in the literature and we believe the proposed CMM can be usefully used to investigate the properties of the SFWNs that are likely to occur in a real deployment of wireless multihop and sensor networks. Another important feature of CMM is that it does not possess any unintended spatial and temporal characteristics found in other mobility models such as RWP. Finally, to highlight the difference between a SFWN and a conventional wireless network, extensive simulation study has been conducted to measure network capacities at the physical, link and network layers. Index Terms — Connectivity distribution, mobility model, network capacity, random waypoint mobility, scale-free wireless networks. I.

Processor Sharing (PS) queuing systems have been historically applied for the estimation of file sojourn times. We present a model for web-pages sojourn times at the session-layer by incorporating the time spent by TCP in its slow-start and congestion avoidance phases. The model is a function of not only the residual capacity of the bottleneck link but also of the packet loss probability and Round Trip Time (RTT) delay. We show that the model effectively captures the web-pages sojourn times in high speed networks. I.