@article {79,
	title = {Dynamic resource management in QoS controlled networks},
	journal = {Telecommunication Systems},
	volume = {32},
	year = {2006},
	pages = {11{\textendash}30},
	abstract = {<p>This paper addresses the problem of resource fragmentation (RF) in QoS controllednetworks. Resources are said to be fragmented when they are available in non-contiguousblocks and hence cannot be utilized by incoming calls with high resource demands. This paper shows the effect of resource fragmentation on QoS controlled networks and presents the Dynamic Resource Redistribution (DRR) algorithm to counteract RF. The DRR algorithm reduces the effects of RF by attempting to redistribute resources in different paths to make resources to incoming calls. A variety of simulation experiments were conducted to study the performance of the DRR algorithm on different network topologies with varying traffic characteristics. The DRR algorithm, when used, increased the number of calls accommodated in the network as well as the overall resource allocation in the network.</p>
},
	issn = {1572-9451},
	doi = {10.1007/s11235-006-8200-4},
	url = {http://dx.doi.org/10.1007/s11235-006-8200-4},
	author = {Prasanna, Venkatesan and Mikler, Armin and Ram Dantu and Abbas, Kaja}
}
@conference {48,
	title = {Data centric modeling of environmental sensor networks},
	booktitle = {Global Telecommunications Conference Workshops, 2004. GlobeCom Workshops 2004. IEEE},
	year = {2004},
	month = {Nov},
	abstract = {<p>Meteorological and hydrological sensors deployed over several hundred kilometers of geographical area comprise an environmental sensor network. Large amounts of data need to be processed in minimal time and transmitted over the available low speed and low bandwidth links. This paper describes algorithms for optimal data collection and data fusion. An inductive model using exponential back-off policy is used to collect optimal amount of data. The data measurements for temperature, pH and specific conductance collected for a year from the sensors deployed at Lake Lewisville are used to test the inductive model. Energy savings of 90\% are achieved even with 1\% of degree of tolerance. The problem of data fusion is addressed by the introduction of a novel concept of a super-sensor, based on self-organization and collaboration among sensors. A histogram application is described that uses recursive doubling for global collaboration between sensors. The performance of the networked super-sensor in comparison to a centralized polling approach is analyzed for optimality on two different geographical areas.</p>
},
	keywords = {Bandwidth, biosensors, data centric modeling, data fusion, environmental sensor network, exponential back-off policy, Histograms, hydrological sensor, International collaboration, Lakes, meteorological, Meteorology, networked super-sensor, optimal data collection, sensor fusion, Sensor phenomena and characterization, Temperature measurement, temperature sensors, Testing},
	doi = {10.1109/GLOCOMW.2004.1417621},
	author = {Ram Dantu and Abbas, Kaja and O{\textquoteright}Neill, Marty and Mikler, Armin}
}
