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Due to the mobility of hosts, limited battery power and processing power of mobile hosts, and the low bandwidth of wireless channels, the existing distributed algorithms designed for the static distributed systems required to be restructured before these can be used in the cellular wireless networks. The group mutual exclusion (GME) problem is an interesting generalization of the classical mutual...
Mapping of applications onto multiprocessor system-on-chip (MPSoC) can be realized either at design-time or run-time. At any time the number of tasks executing in MPSoC platform can exceed the available resources, requiring efficient run-time mapping techniques to meet the real-time constraints of the applications. This paper presents two run-time mapping heuristics for mapping the tasks of an application...
In this paper, we have shown that recognition of machine printed characters can be modeled around the geometry of an alphabet. This geometry is used as a basis for recognizing various characters. The present technique can be implemented for any language, provided, the alphabets of the respective language are made up of geometrical shapes, which is typically true.
We develop a framework for minimizing the communication overhead of monitoring global system parameters in IP networks and sensor networks. A global system predicate is defined as a conjunction of the local properties of different network elements. A typical example is to identify the time windows when the outbound traffic from each network element exceeds a predefined threshold. Our main idea is...
Jayanti's algorithm is one of the best known abortable mutual exclusion algorithms. A randomized approach has been used to overcome an already known limitation of the algorithm while preserving its all important properties and elegance. The limitation is that the token number used to assign process identification number to new incoming processes is unbounded. We have used some suitably adapted alternative...
Probabilistic data have recently become popular in applications such as scientific and geospatial databases. For images and other spatial datasets, probabilistic values can capture the uncertainty in extent and class of the objects in the images. Relating one such dataset to another by spatial joins is an important operation for data management systems. We consider probabilistic spatial join (PSJ)...
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