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In this paper, we study the problem of data gathering in ad-hoc sensor networks using a mobile entity called mule. The mule traverses the children of failed sensors, to prevent loss of data. Our objective is to define the optimal communication tree and the mule's placement such that the mule's overall traveling distance is minimized. We explore this problem in several network topologies including:...
Spectrum allocation is one of the most important problems in cognitive radio networks. However, the channel differentiated algorithms have not been emphasized in the current literature. This paper first proposes a classification criterion for heterogeneous channels. Then, an allocation algorithm for the channel classification is provided with the consideration of channel differences and spatial reuse...
We propose a novel distributed cross-layer optimization approach for cognitive radio wireless networks. A cognitive radio is a wireless device that is capable of sensing the prevailing environmental conditions and automatically adapting its operating parameters in order to enhance the performance of both the system and potentially the whole network. Given the lack of a centralized intelligence to...
In this paper, we introduce a pricing model that ensures efficient resource allocation that provides guaranteed quality of service while maximizing profit in multiservice networks. Specifically, a dynamic allocation policy is examined that relies on online measurements while each service class operates under a probabilistic bound delay constraint. We present a rigorous analysis of the properties of...
This paper explores the attributes, layering models and objective functions in cross layer designs for mobile ad hoc wireless networks by taking all the statistical characteristics and constraints from the physical (PHY) layer, media access control (MAC) layer and network (NET) layer into consideration. This paper reviews the entire network optimization across all the PHY/MAC/NET layers. At the PHY...
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