Proceedings of the 2000 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Minimizing communication costs in hierarchically-clustered networks of wireless sensors
Computer Networks: The International Journal of Computer and Telecommunications Networking
SCORE: a scalable communication protocol for large-scale virtual environments
IEEE/ACM Transactions on Networking (TON)
Data storage placement in sensor networks
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
Mining call and mobility data to improve paging efficiency in cellular networks
Proceedings of the 13th annual ACM international conference on Mobile computing and networking
Stochastic geometry and random graphs for the analysis and design of wireless networks
IEEE Journal on Selected Areas in Communications - Special issue on stochastic geometry and random graphs for the analysis and designof wireless networks
Palm calculus for stationary Cox processes on iterated random tessellations
WiOPT'09 Proceedings of the 7th international conference on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks
Dynamic random replication for data centric storage
Proceedings of the 13th ACM international conference on Modeling, analysis, and simulation of wireless and mobile systems
Distributed energy-efficient hierarchical clustering for wireless sensor networks
DCOSS'05 Proceedings of the First IEEE international conference on Distributed Computing in Sensor Systems
Measurement and modeling of paging channel overloads on a cellular network
Computer Networks: The International Journal of Computer and Telecommunications Networking
STARR-DCS: Spatio-temporal adaptation of random replication for data-centric storage
ACM Transactions on Sensor Networks (TOSN)
| Hi-index | 0.01 |
We define a family of random trees in the plane. Their nodes of level k, k = 0,...,m are the points of a homogeneous Poisson point process Πk, whereas their arcs connect nodes of level k and k + 1, according to the least distance principle: If V denotes the Voronoi cell w.r.t. Πk+1 with nucleus x, where x is a point of Πk+1, then there is an arc connecting x to all the points of Πk that belong to V. This creates a family of stationary random trees rooted in the points of Πm. These random trees are useful to model the spatial organization of several types of hierarchical communication networks. In relation to these communication networks, it is natural to associate various cost functions with such random trees. Using point process techniques, like the exchange formula between two Palm measures, and integral geometry techniques, we show how to compute these average costs as functions of the intensity parameters of the Poisson processes. The formulas derived for the average value of these cost functions can then be exploited for parametric optimization purposes. Several applications to classical and mobile cellular communication networks are presented.