Piotr Arabas

Control system for reducing energy consumption in backbone computer network

SUMMARY Network optimization concerned with operational traffic management in existing data networks is typically oriented towards either maximizing throughput in congested networks while providing for adequate transmission quality, or towards balancing the traffic so as to maintain possibly large free capacity for carrying additional (new) traffic. Nowadays, the reduction of power consumption is a new key aspect in the development of modern wired networks. Power management capabilities allow modulating the energy consumption of devices that form a network by putting them into standby state, or by decreasing their performance in case of low incoming traffic volume. This paper presents a framework for backbone network management, which leads to the minimization of the energy used by this network. The policy for dynamic power management of the whole network through energy-aware routing, traffic engineering, and network equipment activity control is introduced and discussed. The concept of the system is to achieve the desired trade-off between total power consumption and the network performance according to the current load, incoming traffic, and user requirements. The effectiveness of our framework is illustrated by means of a numerical study. Copyright

Control system for reducing energy consumption in backbone computer network: CONTROL SYSTEM FOR REDUCING ENERGY CONSUMPTION IN BACKBONE NETWORK

Network optimization concerned with operational traffic management in existing data networks is typically oriented towards either maximizing throughput in congested networks while providing for adequate transmission quality, or towards balancing the traffic so as to maintain possibly large free capacity for carrying additional (new) traffic. Nowadays, the reduction of power consumption is a new key aspect in the development of modern wired networks. Power management capabilities allow modulating the energy consumption of devices that form a network by putting them into standby state, or by decreasing their performance in case of low incoming traffic volume. This paper presents a framework for backbone network management, which leads to the minimization of the energy used by this network. The policy for dynamic power management of the whole network through energy‐aware routing, traffic engineering, and network equipment activity control is introduced and discussed. The concept of the system is to achieve the desired trade‐off between total power consumption and the network performance according to the current load, incoming traffic, and user requirements. The effectiveness of our framework is illustrated by means of a numerical study. Copyright

On formulation of a network energy saving optimization problem

Possible formulations of mathematical programing problem concerning energy aware network are presented. Two main possibilities of reducing problem complexity are analysed: allocation of predefined paths and reformulation of task using continuous variables. Properties of both methods are analysed and hybrid formulation is proposed. Comparison of complexity is provided.

Simultaneous routing and flow rate optimization in energy-aware computer networks

Abstract The issue of energy-aware traffic engineering has become prominent in telecommunications industry in the last years. This paper presents a two-criteria network optimization problem, in which routing and bandwidth allocation are determined jointly, so as to minimize the amount of energy consumed by a telecommunication infrastructure and to satisfy given demands represented by a traffic matrix. A scalarization of the criteria is proposed and the choice of model parameters is discussed in detail. The model of power dissipation as a function of carried traffic in a typical software router is introduced. Then the problem is expressed in a form suitable for the mixed integer quadratic programming (MIQP) solver. The paper is concluded with a set of small, illustrative computational examples. Computed solutions are implemented in a testbed to validate the accuracy of energy consumption models and the correctness of the proposed traffic engineering algorithm.

Control Framework For High Performance Energy Aware Backbone Network.

Global optimization of the energy consumption in heterogeneous environments has been recently an important research issue in wired and wireless networks. This paper presents a general framework for flexible and cognitive backbone network management which leads to the minimization of the energy utilized by the network. The policy for activity control of all the modules and elements that form a network is introduced and discussed. The idea of the system is to achieve the desired trade-off between energy consumption and network performance according to the traffic load.

Preliminary results on the Linux libpcap model identification

The article presents the results of studies in which models of the Linux system packet capture operations were identified. Performance of the kernel-level packet filters was recorded in a series of adequately designed experiments. Based on the collected data linear models of CPU workload were estimated and analyzed in time and frequency domain. Models of low orders were obtained that provide satisfactory fit to estimation data with normally distributed residuals.

Energy-Aware Multilevel Control System for a Network of Linux Software Routers: Design and Implementation

The Linux operating system provides many well-developed tools that support the concept of energy-efficient networking. This paper outlines the results of research focused on the design and implementation of a control system reducing power consumption of IP-traffic processing in a network of Linux-based software routers. It is demonstrated how the standard ACPI-compliant system components can be adjusted to meet the requirements of adaptive energy-aware network control and what performance tradeoffs may there be expected. In particular, it is demonstrated how the abstraction layers provided by the Linux kernel can be used to exploit energy-saving mechanisms of packet processing servers. Formulations of the routing optimization and service rate control problems are presented and discussed. The results of the extensive experimental studies are presented as well.

Design and implementation of energy-aware application-specific CPU frequency governors for the heterogeneous distributed computing systems☆

Abstract This paper deals with the design of application-specific energy-aware CPU frequency scaling mechanisms. The proposed customized CPU controllers may optimize performance of data centers in which diverse tasks are allocated to servers with different characteristics. First, it is demonstrated that server power usage can be accurately estimated based on the measurements of CPU power consumption read from the model specific registers (MSRs). Next, a benchmarking methodology derived from the RFC2544 specification is proposed that allows to identify models of CPU workload dynamics. Finally, it is demonstrated how the identified models can be applied in the design of customized energy-aware controllers that dynamically adjust CPU frequency to the application-specific workload patterns. According to the results of experimental studies the customized controllers may outperform standard general-purpose governors of the Linux kernel both in terms of reachable server performance and power saving capabilities.

Energy and Power Efficiency in Cloud

Reduction of energy consumption is clearly one of the major technological challenges arising with development of cloud computing infrastructures. To meet the ever increasing demand for computing power, recent research efforts have been taking holistic view to energy-aware design of hardware, middleware, and data processing applications. Indeed, advances in hardware layer development require immediate improvements in the design of system control software. For this to be possible, new power management capabilities of hardware layer need to be exposed in the form of flexible Application Program Interfaces (APIs). Consequently, novel APIs and cluster management tools allow for system-wide regulation of energy consumption, capable of collecting and processing detailed cluster performance measurements, and taking real-time coordinated actions across the cloud infrastructure. This chapter presents an overview of techniques developed to improve energy efficiency of cloud computing. Power consumption models and energy usage profiles are presented together with energy efficiency measuring methods. Modeling of computing and network dynamics is discussed from the viewpoint of system identification theory, indicating basic experiment design problems and challenges. Novel approaches to cluster and network-wide energy usage optimisation are surveyed, including multi-level power and software control systems, energy-aware task scheduling, resource allocation algorithms and frameworks for backbone networks management. Software-development techniques and tools are also presented as a new promising way to reduce power consumption at the computing node level. Finally, energy-aware server-level and network-level control mechanisms are presented, including ACPI-compliant low power idle and service rate scaling solutions.

Maintaining The Feasibility Of Hard Real-Time Systems With A Reduced Number Of Priority Levels

Abstract When there is a mismatch between the cardinality of a periodic task set and the priority levels supported by the underlying hardware systems, multiple tasks are grouped into one class so as to maintain a specific level of confidence in their accuracy. However, such a transformation is achieved at the expense of the loss of schedulability of the original task set. We further investigate the aforementioned problem and report the following contributions: (i) a novel technique for mapping unlimited priority tasks into a reduced number of classes that do not violate the schedulability of the original task set and (ii) an efficient feasibility test that eliminates insufficient points during the feasibility analysis. The theoretical correctness of both contributions is checked through formal verifications. Moreover, the experimental results reveal the superiority of our work over the existing feasibility tests by reducing the number of scheduling points that are needed otherwise.