Clustered Mobility Model for Scale-Free Wireless Networks

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

[1]  Lester Lipsky,et al.  Long-lasting transient conditions in simulations with heavy-tailed workloads , 1997, WSC '97.

[2]  Mor Harchol-Balter,et al.  Exploiting process lifetime distributions for dynamic load balancing , 1995, SIGMETRICS.

[3]  Paolo Santi,et al.  A Statistical Analysis of the Long-Run Node Spatial Distribution in Mobile Ad Hoc Networks , 2004 .

[4]  B. Bollobás The evolution of random graphs , 1984 .

[5]  P. R. Kumar,et al.  Power Control in Ad-Hoc Networks: Theory, Architecture, Algorithm and Implementation of the COMPOW Protocol , 2002 .

[6]  Mustafa Ergen,et al.  Extension of Basic Service Set by Multihop Routing in IEEE 802 . 11 Wireless LAN Standard , 2003 .

[7]  Guang Wan,et al.  Cost reduction in location management using semi‐realtime movement information , 1999, Wirel. Networks.

[8]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[9]  Paolo Santi,et al.  A Statistical Analysis of the Long-Run Node Spatial Distribution in Mobile Ad Hoc Networks , 2002, MSWiM '02.

[10]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[11]  Walter Willinger,et al.  On the self-similar nature of Ethernet traffic , 1993, SIGCOMM '93.

[12]  Louise E. Moser,et al.  An analysis of the optimum node density for ad hoc mobile networks , 2001, ICC 2001. IEEE International Conference on Communications. Conference Record (Cat. No.01CH37240).

[13]  Walter Willinger,et al.  The origin of power laws in Internet topologies revisited , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[14]  Kang G. Shin,et al.  Power-stepped protocol: enhancing spatial utilization in a clustered mobile ad hoc network , 2004, IEEE Journal on Selected Areas in Communications.

[15]  Reuven Cohen,et al.  Geographical embedding of scale-free networks , 2003 .

[16]  Tracy Camp,et al.  Stationary distributions for the random waypoint mobility model , 2004, IEEE Transactions on Mobile Computing.

[17]  Tracy Camp,et al.  A survey of mobility models for ad hoc network research , 2002, Wirel. Commun. Mob. Comput..

[18]  Vikas Kawadia,et al.  Power control and clustering in ad hoc networks , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[19]  Hannes Hartenstein,et al.  Stochastic Properties of the Random Waypoint Mobility Model , 2004, Wirel. Networks.

[20]  Michele Zorzi,et al.  Capture and retransmission control in mobile radio , 1994, IEEE J. Sel. Areas Commun..

[21]  Martin F. Arlitt,et al.  Web server workload characterization: the search for invariants , 1996, SIGMETRICS '96.

[22]  David Tse,et al.  Mobility increases the capacity of ad hoc wireless networks , 2002, TNET.

[23]  Kaixin Xu,et al.  Group and swarm mobility models for ad hoc network scenarios using virtual tracks , 2004, IEEE MILCOM 2004. Military Communications Conference, 2004..

[24]  Paolo Santi,et al.  The Node Distribution of the Random Waypoint Mobility Model for Wireless Ad Hoc Networks , 2003, IEEE Trans. Mob. Comput..

[25]  W. Stegner One Nation , 1945 .

[26]  WillingerWalter,et al.  On the self-similar nature of Ethernet traffic , 1993 .

[27]  M. Barthelemy,et al.  Connectivity distribution of spatial networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[28]  M. Newman,et al.  Fast Approximation Algorithms for Finding Node-Independent Paths in Networks , 2001 .

[29]  Andrew T. Campbell,et al.  HMP: hotspot mitigation protocol for mobile ad hoc networks , 2003, IWQoS'03.

[30]  Amotz Bar-Noy,et al.  Mobile users: To update or not to update? , 1995, Wirel. Networks.

[31]  Ahmed Helmy,et al.  The IMPORTANT framework for analyzing the Impact of Mobility on Performance Of RouTing protocols for Adhoc NeTworks , 2003, Ad Hoc Networks.

[32]  Guevara Noubir,et al.  Mobility models for ad hoc network simulation , 2004, IEEE INFOCOM 2004.

[33]  Baochun Li,et al.  Group mobility and partition prediction in wireless ad-hoc networks , 2002, 2002 IEEE International Conference on Communications. Conference Proceedings. ICC 2002 (Cat. No.02CH37333).

[34]  Albert-László Barabási,et al.  Scale-free networks , 2008, Scholarpedia.

[35]  S. Strogatz Exploring complex networks , 2001, Nature.

[36]  Mingyan Liu,et al.  Random waypoint considered harmful , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[37]  Kevin C. Almeroth,et al.  Towards realistic mobility models for mobile ad hoc networks , 2003, MobiCom '03.

[38]  I. Glauche,et al.  Continuum percolation of wireless ad hoc communication networks , 2003, cond-mat/0304579.

[39]  David A. Maltz,et al.  Dynamic Source Routing in Ad Hoc Wireless Networks , 1994, Mobidata.

[40]  Albert,et al.  Topology of evolving networks: local events and universality , 2000, Physical review letters.

[41]  P. Erdos,et al.  On the evolution of random graphs , 1984 .

[42]  Walter Willinger,et al.  On the Self-Similar Nature of Ethernet Traffic ( extended version ) , 1995 .

[43]  J. Broch,et al.  Dynamic source routing in ad hoc wireless networks , 1998 .

[44]  G Németh,et al.  Giant clusters in random ad hoc networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.