It is known that multicasting is an efficient method of supporting group communication as it allows the transmission of packets to multiple destinations using fewer network resources. Thus, service providers are incre...
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The wide expansion and increasing demand for Networked Virtual Environments resulted in efforts for the optimization of these environments with the enhancement of advanced features, which offered extended functionalit...
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In this work we study the distributed implementation of multicost routing in mobile ad hoc networks. In contrast to single-cost routing, where each path is characterized by a scalar, in multicost routing a vector of c...
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ISBN:
(纸本)9781605580555
In this work we study the distributed implementation of multicost routing in mobile ad hoc networks. In contrast to single-cost routing, where each path is characterized by a scalar, in multicost routing a vector of cost parameters is as- signed to each link, from which the cost vectors of the paths are calculated. These parameters are combined according to an optimization function for selecting the optimal path. Up until now the performance of multicost routing in ad hoc networks has been evaluated either at a theoretical level or by assuming that nodes are static and have full knowledge of the network topology and nodes' state. In the present paper we assess the performance of multicost routing, based on energy-related parameters, in mobile ad hoc networks by embedding its logic in the Dynamic Source Routing (DSR) algorithm, which is a well-known distributed routing algo- rithm. We compare the performance of the multicost-DSR algorithm to that of the original DSR algorithm under var- ious node mobility scenarios. The results confirm that the multicost-DSR algorithm improves the performance of the network in comparison to the original DSR, by reducing en- ergy consumption overall in the network, spreading energy consumption more uniformly across the network, and reduc- ing the packet drop probability and delivery delay. Copyright 2008 ACM.
In this paper, we present an improved approach integrating rules, neural networks and cases, compared to a previous one. The main approach integrates neurules and cases. Neurules are a kind of integrated rules that co...
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In this paper, we present an improved approach integrating rules, neural networks and cases, compared to a previous one. The main approach integrates neurules and cases. Neurules are a kind of integrated rules that combine a symbolic (production rules) and a connectionist (adaline unit) representation. Each neurule is represented as an adaline unit. The main characteristics of neurules are that they improve the performance of symbolic rules and, in contrast to other hybrid neuro-symbolic approaches, retain the modularity of production rules and their naturalness in a large degree. In the improved approach, various types of indices are assigned to cases according to different roles they play in neurule-based reasoning, instead of one. Thus, an enhanced knowledge representation scheme is derived resulting in accuracy improvement. Experimental results demonstrate its effectiveness.
The 3rd Generation Partnership Project (3GPP) has introduced the evolved Multimedia Broadcast/Multicast Service (e-MBMS) feature for cellular systems as an evolution to the existing MBMS service. To support e-MBMS in ...
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This paper proposes a power control mechanism for the efficient radio bearer selection in the Multimedia Broadcast/Multicast Service (MBMS) framework of Universal Mobile Telecommunications System (UMTS). The selection...
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Case-based reasoning is a popular approach used in intelligent systems. Whenever a new case has to be dealt with, the most similar cases are retrieved from the case base and their encompassed knowledge is exploited in...
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Case-based reasoning is a popular approach used in intelligent systems. Whenever a new case has to be dealt with, the most similar cases are retrieved from the case base and their encompassed knowledge is exploited in the current situation. Combinations of case-based reasoning with other intelligent methods have been explored deriving effective knowledge representation schemes. Although some types of combinations have been mostly explored, other types have not been thoroughly investigated. In this paper, we briefly outline popular case-based reasoning combinations. More specifically, we focus on combinations of case-based reasoning with rulebased reasoning, soft computing and ontologies. We illustrate basic types of such combinations and discuss future directions.
The BART model is an advanced adaptation of transformers introduced by Facebook. It has incorporated elements from both BERT and GPT transformers, enabling significant advancements in language understanding and genera...
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In the dynamic landscape of online social networks, recognizing sensitive content is essential for safeguarding user privacy, fostering inclusivity, and enhancing diversity awareness. Building on prior research, this ...
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A well-studied approach to the design of voting rules views them as maximum likelihood estimators;given votes that are seen as noisy estimates of a true ranking of the alternatives, the rule must reconstruct the most ...
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