The chapter discusses issues related to the implementation of the different steps of the cognitive cycle, especially focusing on reasoning, and applies this to energy saving for green networking. The application of cognition to networking and communications can be readily implemented into current TCP/IP networks. Indeed, the use of the cognitive paradigm represents a way: (i) to address the multiple temporal and spatial fluctuations in the operation of a network, and (ii) to gain and take advantage of additional causal information related to the network configuration and its performance. Network performance is a multi-faceted concept, including simple measures such as throughput as well as far more complicated or subjective measures such as user-level QoS. Recently, an additional parameter has been added to this equation: energy consumption. The need for identifying suitable methodologies to optimize performance from the above viewpoints, also including the contradictory requirement to save energy, is driving research interests towards the emergence of "green networks". Green networking represents an appropriate scenario where cognition and associated radio adaptation can immensely contribute to the given objectives. This chapter describes how cognitive networking can be implemented to support green network operation, proposing a test case demonstrating its potential in a 3G cellular context. Experimental results based on real traffic data demonstrate the capability of a 3G base station to implement cognition to the purpose to save energy without any a-priori information.
Cognition as a Tool for Green Next Generation Networks
Granelli, Fabrizio;
2014-01-01
Abstract
The chapter discusses issues related to the implementation of the different steps of the cognitive cycle, especially focusing on reasoning, and applies this to energy saving for green networking. The application of cognition to networking and communications can be readily implemented into current TCP/IP networks. Indeed, the use of the cognitive paradigm represents a way: (i) to address the multiple temporal and spatial fluctuations in the operation of a network, and (ii) to gain and take advantage of additional causal information related to the network configuration and its performance. Network performance is a multi-faceted concept, including simple measures such as throughput as well as far more complicated or subjective measures such as user-level QoS. Recently, an additional parameter has been added to this equation: energy consumption. The need for identifying suitable methodologies to optimize performance from the above viewpoints, also including the contradictory requirement to save energy, is driving research interests towards the emergence of "green networks". Green networking represents an appropriate scenario where cognition and associated radio adaptation can immensely contribute to the given objectives. This chapter describes how cognitive networking can be implemented to support green network operation, proposing a test case demonstrating its potential in a 3G cellular context. Experimental results based on real traffic data demonstrate the capability of a 3G base station to implement cognition to the purpose to save energy without any a-priori information.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione