Total Network Power Consumption Research Articles

Energy-efficient optical access networks: issues and technologies

This article discusses and clarifies the issues and technologies for the next-generation energy efficient optical access network from the viewpoints of its mid-term upgrade and long-term evolution. For reducing the total power consumption in the mid-term upgrade to 10-gigabit access, it is necessary to optimize the network configuration as well as the usage of various technologies while avoiding any service degradation in the next-generation broadband services. In the long-term evolution, wavelength routing will play a key role by drastically decreasing the total power consumption of the access network.

Deployment Strategies and Energy Efficiency of Cellular Networks

The energy efficiency of cellular networks is explored for different network deployment strategies and traffic conditions. The total network power consumption and the ratios Watts/kbps, Watts/user are used as metrics to quantify the performance and it is shown that efficiency depends on the deployment strategy and the state of operation of the network (underutilized-overutilized). As a general conclusion it is shown that a microcell based network, comprising a large number of low power stations, is the most efficient strategy but it does not present traffic proportional characteristics. For the purpose of the investigation, the paper presents a pre-processing of the database 3D ray tracing algorithm that is enhanced with an image test procedure and multiple slope diffraction mechanisms to achieve fast and accurate predictions. The algorithm is used for channel estimations over a real urban environment described in a vector format. In addition, a power control algorithm is developed that explicitly considers power levels of neighbor base stations and is used for the network power consumption estimation. Finally, network planning is achieved through an evolutionary optimization technique that combines the above mentioned algorithms.

Power Constrained Linear Estimation in Wireless Sensor Networks With Correlated Data and Digital Modulation

We study the problem of joint quantization and power allocation in wireless sensor networks where spatially distributed sensors observe a Gaussian random source, quantize the resulting noisy observations, and transmit over orthogonal fading channels to a remote fusion center (FC). The role of the FC is to reconstruct the source with minimal distortion using linear minimum mean square error estimation rule. In this paper, we undertake the design of joint quantization and power allocation based on the following optimization problem: minimize the reconstruction distortion for a given total network power consumption. To address this problem, at each sensor node uniform scalar quantization is assumed. Moreover, assuming pseudo-quantization noise model we show that the problem can be solved using a block-coordinate descent type algorithm which iteratively optimizes the quantization bits and the power allocations. The algorithm takes into account the spatial correlation, the observation noise, and the channel quality of the sensors. Numerical and simulation examples corroborate the analytical results. The examples illustrate that the proposed design holds a considerable performance gain compared to a quantization scheme based on uniform power allocation to the sensors.

Homogeneous 2-hop broadcast in 2D

In this paper, two variations of the minimum cost homogeneous range assignment problem for 2-hop broadcast from a given source are considered. A set S = { s 0 , s 1 , … , s n } of radio stations are pre-placed in R 2 , and a source station s 0 (say) is marked. In our first problem, the objective is to find a real number r such that 2-hop homogeneous broadcast from s 0 is possible with range r, and the total power consumption of the entire network is minimum. In the second problem, a real number r is given and the objective is to identify the smallest subset of S for which range r can be assigned to accomplish the 2-hop broadcast from s 0 , provided such an assignment is possible. The first problem is solved in O ( n 2.376 log n ) time and O ( n 2 ) space. For the second problem, a 2-factor approximation algorithm is proposed that runs in O ( n 2 ) time and O ( n ) space.

Minimizing the dynamic and sub-threshold leakage power consumption using least leakage vector-assisted technology mapping

Power consumption due to the temperature-dependent leakage current becomes a dominant part of the total power dissipation in systems using nanometer-scale process technology. To obtain the minimum power consumption for different operating conditions, logic synthesis tools are required to take into consideration the leakage power as well as the operating characteristics during the optimization. Conventional logic synthesis flows consider dynamic power only and use an over-simplified cost function in modeling the total power consumption of the logic network. In this paper, we propose a complete model of the total power consumption of the logic network, which includes both the active and standby sub-threshold leakage power, and the operating duty cycle of the applications. We also propose a least leakage vector (LLV) assisted technology mapping algorithm to optimize the total power of the final mapped network. Instead of finding the LLV after the logic network is synthesized and mapped, we use the LLV found in the technology-decomposed network to help in obtaining the lowest total power match during technology mapping. Experimental results on MCNC benchmarks show that on average more than 30% reduction in total power consumption is obtained comparing with the conventional low power technology mapping algorithm.