Modeling the interaction between TCP and Rate Adaptation

In this paper, we model and investigate the interaction between the TCP protocol and rate adaptation at intermediate routers. Rate adaptation aims at saving energy by controlling the offered capacity of links and adapting it to the amount of traffic. However, when TCP is used at the transport layer, the control loop of rate adaptation and one of the TCP congestion control mechanism might interact and disturb each other, compromising throughput and Quality of Service (QoS). Our investigation is lead through mathematical modeling consisting in depicting the behavior of TCP and of rate adaption through a set of Delay Differential Equations (DDEs). The model is validated against simulation results and it is shown to be accurate. The results of the sensitivity analysis of the system performance to control parameters show that rate adaptation can be effective but a careful parameter setting is needed to avoid undesired disruptive interaction among controllers at different levels, that impair QoS

A Survey of Green Networking Research

Reduction of unnecessary energy consumption is becoming a major concern in wired networking, because of the potential economical benefits and of its expected environmental impact. These issues, usually referred to as "green networking", relate to embedding energy-awareness in the design, in the devices and in the protocols of networks. In this work, we first formulate a more precise definition of the "green" attribute. We furthermore identify a few paradigms that are the key enablers of energy-aware networking research. We then overview the current state of the art and provide a taxonomy of the relevant work, with a special focus on wired networking. At a high level, we identify four branches of green networking research that stem from different observations on the root causes of energy waste, namely (i) Adaptive Link Rate, (ii) Interface proxying, (iii) Energy-aware infrastructures and (iv) Energy-aware applications. In this work, we do not only explore specific proposals pertaining to each of the above branches, but also offer a perspective for research.Comment: Index Terms: Green Networking; Wired Networks; Adaptive Link Rate; Interface Proxying; Energy-aware Infrastructures; Energy-aware Applications. 18 pages, 6 figures, 2 table

System for improving the efficiency of wireless networks

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.Includes bibliographical references (p. 30-31).Wireless data networks are widespread and growing quickly. As their use increases, many wireless networks are becoming congested. In addition, as wireless data capability moves into ever-smaller devices, power becomes a significant issue. This thesis presents a system that increases network bandwidth and decreases energy use without changing existing network hardware or protocols. We use specialized proxy servers to transparently modify the traffic sent over the mobile link such that the total energy used by the receiver is reduced and the effective bandwidth is increased. Our techniques include optimizing packet size, eliminating unnecessary traffic, and masking wireless packet losses. We design and implement two proxies--one for access points and one for mobile devices--which when used together, achieve up to a 20% decrease in energy and 38% increase in throughput.by Hans Robertson.M.Eng

From Measurements to Modeling The Trade-off between Energy Efficiency and System Performance

In this thesis, the work is based on experimental and modeling methodologies. I applied this starting from measurements of Asymmetric Digital Subscriber Line (ADSL) technology, which is the preferred high-speed access to the Internet. The work focuses on the problem of determining the maximum stable bandwidth that an Internet Service Provider (ISP) can offer. This task was accomplished by monitoring and analyzing a large set of ADSL end-users. Huge amount of collected data allowed us to get a detailed statistical analysis of the behavior of ADSL lines, such as the distribution, variable dependencies and correlation of effective bitrate with the physical measurements exposed by network devices. Analysis of collected data suggest that there is no clear trend to predict a downstream bandwidth of ADSL line based on line conditions, and thus requires an intelligent way of analyzing the ADSL lines. Thus, a Neural Network (NN) was employed, which is an intelligent machine learning tool to (i) learn the behavior of ADSL lines, (ii) extract useful information from huge set of measurements, (iii) automatically suggest maximum stable bandwidth. The results indicate that NN performs well in predicting end-users available bandwidth. However, NN is required to be properly trained, as well as needs careful selection of design parameters. Later, the focus of the work was centered over the energy efficiency of telecommunication systems using mathematical modeling approach. Motivation of first work was to know how much energy efficient is Voice over Internet Protocol (VoIP) architecture as compared to traditional Public-Switched Telephone Network (PSTN) architecture used for voice communication. To answer this, these two architectures already implemented at our campus were extensively examined by means of measuring real power consumption. To generalize or estimate power consumption for any given number of users, a mathematical model of power consumption for both the architectures is built. The results indicate that VoIP architecture consumes a lot of power, yet VoIP system have the flexibility to be made energy efficient by adding some sort of energy-wise schemes. The last part of the work investigates the interaction between the Transmission Control Protocol (TCP) and rate adaptation mechanism. Where rate adaptation is an approach to save energy by adapting the transmission rates or capacity according to traffic dynamics. To have deep insight of the interaction, a mathematical model based on fluid based framework is built to depict the behavior of TCP and rate adaptation scheme. The model is then tested for its accuracy and stability by conducting simulation experiments and steady state analysis. Later, the model is used to study the impact of tuning the parameters on system performance. The results suggest that the implementation of rate adaptation scheme can be effective but a careful parameter setting is needed to avoid undesired disruptive interaction among controllers at different levels, that impair QoS

Improving the Performance of Wireless LANs

This book quantifies the key factors of WLAN performance and describes methods for improvement. It provides theoretical background and empirical results for the optimum planning and deployment of indoor WLAN systems, explaining the fundamentals while supplying guidelines for design, modeling, and performance evaluation. It discusses environmental effects on WLAN systems, protocol redesign for routing and MAC, and traffic distribution; examines emerging and future network technologies; and includes radio propagation and site measurements, simulations for various network design scenarios, numerous illustrations, practical examples, and learning aids

VirtFogSim: A parallel toolbox for dynamic energy-delay performance testing and optimization of 5G Mobile-Fog-Cloud virtualized platforms

It is expected that the pervasive deployment of multi-tier 5G-supported Mobile-Fog-Cloudtechnological computing platforms will constitute an effective means to support the real-time execution of future Internet applications by resource- and energy-limited mobile devices. Increasing interest in this emerging networking-computing technology demands the optimization and performance evaluation of several parts of the underlying infrastructures. However, field trials are challenging due to their operational costs, and in every case, the obtained results could be difficult to repeat and customize. These emergingMobile-Fog-Cloud ecosystems still lack, indeed, customizable software tools for the performance simulation of their computing-networking building blocks. Motivated by these considerations, in this contribution, we present VirtFogSim. It is aMATLAB-supported software toolbox that allows the dynamic joint optimization and tracking of the energy and delay performance of Mobile-Fog-Cloud systems for the execution of applications described by general Directed Application Graphs (DAGs). In a nutshell, the main peculiar features of the proposed VirtFogSim toolbox are that: (i) it allows the joint dynamic energy-aware optimization of the placement of the application tasks and the allocation of the needed computing-networking resources under hard constraints on acceptable overall execution times, (ii) it allows the repeatable and customizable simulation of the resulting energy-delay performance of the overall system; (iii) it allows the dynamic tracking of the performed resource allocation under time-varying operational environments, as those typically featuring mobile applications; (iv) it is equipped with a user-friendly Graphic User Interface (GUI) that supports a number of graphic formats for data rendering, and (v) itsMATLAB code is optimized for running atop multi-core parallel execution platforms. To check both the actual optimization and scalability capabilities of the VirtFogSim toolbox, a number of experimental setups featuring different use cases and operational environments are simulated, and their performances are compared

Congestion control, energy efficiency and virtual machine placement for data centers

Data centers, facilities with communications network equipment and servers for data processing and/or storage, are prevalent and essential to provide a myriad of services and applications for various private, non-profit, and government systems, and they also form the foundation of cloud computing, which is transforming the technological landscape of the Internet. With rapid deployment of modern high-speed low-latency large-scale data centers, many issues have emerged in data centers, such as data center architecture design, congestion control, energy efficiency, virtual machine placement, and load balancing. The objective of this thesis is multi-fold. First, an enhanced Quantized Congestion Notification (QCN) congestion notification algorithm, called fair QCN (FQCN), is proposed to improve rate allocation fairness of multiple flows sharing one bottleneck link in data center networks. Detailed analysis on FQCN and simulation results is provided to validate the fair share rate allocation while maintaining the queue length stability. Furthermore, the effects of congestion notification algorithms, including QCN, AF-QCN and FQCN, are investigated with respect to TCP throughput collapse. The results show that FQCN can significantly enhance TCP throughput performance, and achieve better TCP throughput than QCN and AF-QCN in a TCP Incast setting. Second, a unified congestion detection, notification and control system for data center networks is designed to efficiently resolve network congestion in a uniform solution and to ensure convergence to statistical fairness with “no state” switches simultaneously. The architecture of the proposed system is described in detail and the FQCN algorithm is implemented in the proposed framework. The simulation results of the FQCN algorithm implemented in the proposed framework validate the robustness and efficiency of the proposed congestion control system. Third, a two-level power optimization model, namely, Hierarchical EneRgy Optimization (HERO), is established to reduce the power consumption of data center networks by switching off network switches and links while still guaranteeing full connectivity and maximizing link utilization. The power-saving performance of the proposed HERO model is evaluated by simulations with different traffic patterns. The simulation results have shown that HERO can reduce the power consumption of data center networks effectively with reduced complexity. Last, several heterogeneity aware dominant resource assistant heuristic algorithms, namely, dominant residual resource aware first-fit decreasing (DRR-FFD), individual DRR-FFD (iDRR-FFD) and dominant residual resource based bin fill (DRR-BinFill), are proposed for virtual machine (VM) consolidation. The proposed heuristic algorithms exploit the heterogeneity of the VMs’ requirements for different resources by capturing the differences among VMs’ demands, and the heterogeneity of the physical machines’ resource capacities by capturing the differences among physical machines’ resources. The performance of the proposed heuristic algorithms is evaluated with different classes of synthetic workloads under different VM requirement heterogeneity conditions, and the simulation results demonstrate that the proposed heuristics achieve quite similar consolidation performance as dimension-aware heuristics with almost the same computational cost as those of the single dimensional heuristics

From Measurements to Modeling The Trade-off between Energy Efficiency and System Performance

In this thesis, the work is based on experimental and modeling methodologies. I applied this starting from measurements of Asymmetric Digital Subscriber Line (ADSL) technology, which is the preferred high-speed access to the Internet. The work focuses on the problem of determining the maximum stable bandwidth that an Internet Service Provider (ISP) can offer. This task was accomplished by monitoring and analyzing a large set of ADSL end-users. Huge amount of collected data allowed us to get a detailed statistical analysis of the behavior of ADSL lines, such as the distribution, variable dependencies and correlation of effective bitrate with the physical measurements exposed by network devices. Analysis of collected data suggest that there is no clear trend to predict a downstream bandwidth of ADSL line based on line conditions, and thus requires an intelligent way of analyzing the ADSL lines. Thus, a Neural Network (NN) was employed, which is an intelligent machine learning tool to (i) learn the behavior of ADSL lines, (ii) extract useful information from huge set of measurements, (iii) automatically suggest maximum stable bandwidth. The results indicate that NN performs well in predicting end-users available bandwidth. However, NN is required to be properly trained, as well as needs careful selection of design parameters. Later, the focus of the work was centered over the energy efficiency of telecommunication systems using mathematical modeling approach. Motivation of first work was to know how much energy efficient is Voice over Internet Protocol (VoIP) architecture as compared to traditional Public-Switched Telephone Network (PSTN) architecture used for voice communication. To answer this, these two architectures already implemented at our campus were extensively examined by means of measuring real power consumption. To generalize or estimate power consumption for any given number of users, a mathematical model of power consumption for both the architectures is built. The results indicate that VoIP architecture consumes a lot of power, yet VoIP system have the flexibility to be made energy efficient by adding some sort of energy-wise schemes. The last part of the work investigates the interaction between the Transmission Control Protocol (TCP) and rate adaptation mechanism. Where rate adaptation is an approach to save energy by adapting the transmission rates or capacity according to traffic dynamics. To have deep insight of the interaction, a mathematical model based on fluid based framework is built to depict the behavior of TCP and rate adaptation scheme. The model is then tested for its accuracy and stability by conducting simulation experiments and steady state analysis. Later, the model is used to study the impact of tuning the parameters on system performance. The results suggest that the implementation of rate adaptation scheme can be effective but a careful parameter setting is needed to avoid undesired disruptive interaction among controllers at different levels, that impair Qo