Optimising for energy or robustness? Trade-offs for VM consolidation in virtualized datacenters under uncertainty

The final publication is available at Springer via http://dx.doi.org/10.1007/s11590-016-1065-xReducing the energy consumption of virtualized datacenters and the Cloud is very important in order to lower CO2 footprint and operational cost of a Cloud operator. However, there is a trade-off between energy consumption and perceived application performance. In order to save energy, Cloud operators want to consolidate as many Virtual Machines (VM) on the fewest possible physical servers, possibly involving overbooking of resources. However, that may involve SLA violations when many VMs run on peak load. Such consolidation is typically done using VM migration techniques, which stress the network. As a consequence, it is important to find the right balance between the energy consumption and the number of migrations to perform. Unfortunately, the resources that a VM requires are not precisely known in advance, which makes it very difficult to optimise the VM migration schedule. In this paper, we therefore propose a novel approach based on the theory of robust optimisation. We model the VM consolidation problem as a robust Mixed Integer Linear Program and allow to specify bounds for e.g. resource requirements of the VMs. We show that, by using our model, Cloud operators can effectively trade-off uncertainty of resource requirements with total energy consumption. Also, our model allows us to quantify the price of the robustness in terms of energy saving against resource requirement violations.Peer ReviewedPostprint (author's final draft

Predicting expected TCP throughput using genetic algorithm

Predicting the expected throughput of TCP is important for several aspects such as e.g. determining handover criteria for future multihomed mobile nodes or determining the expected throughput of a given MPTCP subflow for load-balancing reasons. However, this is challenging due to time varying behavior of the underlying network characteristics. In this paper, we present a genetic-algorithm-based prediction model for estimating TCP throughput values. Our approach tries to find the best matching combination of mathematical functions that approximate a given time series that accounts for the TCP throughput samples using genetic algorithm. Based on collected historical datapoints about measured TCP throughput samples, our algorithm estimates expected throughput over time. We evaluate the quality of the prediction using different selection and diversity strategies for creating new chromosomes. Also, we explore the use of different fitness functions in order to evaluate the goodness of a chromosome. The goal is to show how different tuning on the genetic algorithm may have an impact on the prediction. Using extensive simulations over several TCP throughput traces, we find that the genetic algorithm successfully finds reasonable matching mathematical functions that allow to describe the TCP sampled throughput values with good fidelity. We also explore the effectiveness of predicting time series throughput samples for a given prediction horizon and estimate the prediction error and confidence.Peer ReviewedPostprint (author's final draft

Profesores de la UPC trabajan para optimizar las redes inalámbricas

Esta primavera, el Ministerio de Ciencia e Innovación ha concedido una ayuda de investigación de tres años de duración para un proyecto liderado por la Dra. Enrica Zola y el Dr. Israel Martín Escalona, profesores de la UPC e investigadores del grupo de investigación en Redes de Comunicaciones Celulares y Adhoc del Departamento de Ingeniería Telemática de la UPC. La investigación del grupo se centra en el ámbito de la planificación de recursos en redes inalámbricas, y en el aprovechamiento de los datos disponibles en dichas redes para localizar los terminales.Postprint (published version

Improving fingerprint-based positioning by using IEEE 802.11mc FTM/RTT observables

Received signal strength (RSS) has been one of the most used observables for location purposes due to its availability at almost every wireless device. However, the volatile nature of RSS tends to yield to non-reliable location solutions. IEEE 802.11mc enabled the use of the round trip time (RTT) for positioning, which is expected to be a more consistent observable for location purposes. This approach has been gaining support from several companies such as Google, which introduced that feature in the Android O.S. As a result, RTT estimation is now available in several recent off-the-shelf devices, opening a wide range of new approaches for computing location. However, RTT has been traditionally addressed to multilateration solutions. Few works exist that assess the feasibility of the RTT as an accurate feature in positioning methods based on classification algorithms. An attempt is made in this paper to fill this gap by investigating the performance of several classification models in terms of accuracy and positioning errors. The performance is assessed using different AP layouts, distinct AP vendors, and different frequency bands. The accuracy and precision of the RTT-based position estimation is always better than the one obtained with RSS in all the studied scenarios, and especially when few APs are available. In addition, all the considered ML algorithms perform pretty well. As a result, it is not necessary to use more complex solutions (e.g., SVM) when simpler ones (e.g., nearest neighbor classifiers) achieve similar results both in terms of accuracy and location error.This research was partially supported by MCIN/AEI/10.13039/ 501100011033 and ERDF “A way of making Europe” under grant PGC2018-099945-BI00, and by the European GNSS Agency (GSA) under grant GSA/GRANT/04/2019/BANSHEEPeer ReviewedPostprint (published version

Passive round-trip-time positioning in dense ieee 802.11 networks

The search for a unique and globally available location solution has attracted researchers for a long time. However, a solution for indoor scenarios, where high accuracy is needed, and Global Positioning System (GPS) is not available, has not been found yet. Despite the number of proposals in the literature, some require too long a calibration time for constructing the fingerprinting map, some rely on the periodic broadcast of positioning information that may downgrade the data communication channel, while others require specific hardware components that are not expected to be carried on commercial off-the-shelf (COTS) wireless devices. The scalability of the location solution is another key parameter for next-generation internet of things (IoT) and 5G scenarios. A passive solution for indoor positioning of WiFi devices is first introduced here, which merges a time-difference of arrival (TDOA) algorithm with the novel fine time measurements (FTM) introduced in IEEE 802.11mc. A proof of concept of the WiFi passive TDOA algorithm is detailed in this paper, together with a thorough discussion on the requirements of the proposed algorithmThis work was funded by the Spanish Government and European Regional Development Fund (ERDF) through Comisión Interministerial de Ciencia y Tecnología (CICYT) under Project PGC2018-099945-B-I00.Peer ReviewedPostprint (published version

IEEE 802.11mc ranging performance in a real NLOS environment

Since IEEE 802.11 defined a couple of enhancements that allow accurate time measurements in COTS Wi-Fi devices, the possibility of achieving precise low-cost distance estimations in Wi-Fi has become a reality. However, many sources of error, such as bandwidth limitations of the Wi-Fi signal, limited clock rate in the device, multipath propagation due to the obstacles in the indoor environment, etc., may add noise to the time measurements and therefore distort the estimated ranging. This study aims at covering the gap existing in the literature by assessing the performance of the ranging estimation in real IEEE 802.11mc stations in a typical NLOS environment. The impact on the accuracy is also explored when the station is held in different positions with respect to the floor.The Article Processing Charges were funded by the Spanish Government and ERDF through CICYT project under grant PGC2018-099945-B-I00. This research was partially supported by PGC2018-099945-BI00 and by the European GNSS Agency under grant GSA/GRANT/04/2019/BANSHEE.Postprint (published version

User association in 5G heterogeneous networks with mesh millimeter wave backhaul links

Fifth generation (5G) wireless networks will target at energy and spectrum efficient solutions to cope with the increasing demands in capacity and energy efficiency. To achieve this joint goal, dense networks of small cells (SCs) are expected to overlay the existing macro cells. In parallel, for the SC connection to the core network, a promising solution lies in a mesh network of high capacity millimeter wave backhaul (BH) links. In the considered 5G architecture, each SC is able to forward its BH traffic to the core network through alternative paths, thus offering high BH network reliability. In this context, the joint problem of user association and BH routing becomes challenging. In this paper, we focus on this problem targeting at energy and spectrum efficient solutions. A low-complexity algorithm is proposed, which bases its user association and BH routing decision i) on minimizing the spectrum resources to guarantee the user rate, so as to provide high spectrum efficiency, and ii) on minimizing both the access network and BH route power consumption to provide high energy efficiency. Our results show that our solution provides better trade-offs between energy and spectrum efficiency than the state-of-the-art in 3GPP scenariosPostprint (author's final draft

Minimizing the impact of the handover for mobile users in WLAN: a study on performance optimization

IEEE 802.11 based Wireless LANs are an important piece in today’s communication infrastructure in order to provide high speed wireless Internet access to static or quasi mobile users. For large WLAN deployments (i.e., Campus or enterprise WLAN), it is important to understand the impact of user mobility and handovers on the system performance. In this article, we have developed a performance model for a set of networked 802.11 based WLAN Access Points, which is based on a Mixed Integer Linear Program (MILP). The objective function tries simultaneously to maximize the total system rate while at the same time minimizing the number of handovers for a configurable handover signaling rate. Because of the conflicting nature of the two objective functions, such multi-objective optimization is difficult to explore. A detailed evaluation of the model using several scenarios involving both different numbers of static and mobile users shows that our formulation allows trading off those two objectives in a robust way.Postprint (author's final draft

DYMO self forwarding: a simple way for reducing the routing overhead in MANETs

Current routing protocols in Mobile Ad hoc Networks tend to use information on the position of the nodes in order to improve their features. In fact, without this information, protocols are hardly scalable since they tend to overflow the radio media with control packets, most of them being useless at the end. This paper presents the assessment of a modification of the DYMO protocol in order to include and use positioning information. The evaluation is carried out through simulations in realistic environments and connectivity condition. The possible error in the position is seldom considered in this kind of studies but here taken into account to catch the impact of realistic GPS devices or other sources of location techniques.Peer ReviewedPostprint (published version

Optimal user association, backhaul routing and switching off in 5G heterogeneous networks with mesh millimeter wave backhaul links

Next generation, i.e., fifth generation (5G), cellular networks will provide a significant higher capacity per area to support the ever-increasing traffic demands. In order to achieve that, many small cells need to be deployed that are connected using a combination of optical fiber links and millimeter-wave (mmWave) backhaul architecture to forward heterogeneous traffic over mesh topologies. In this paper, we present a general optimization framework for the design of policies that optimally solve the problem of where to associate a user, over which links to route its traffic towards which mesh gateway, and which base stations and backhaul links to switch o¿ in order to minimize the energy cost for the network operator and still satisfy the user demands. We develop an optimal policy based on mixed integer linear programming (MILP) which considers different user distribution and traffic demands over multiple time periods. We develop also a fast iterative two-phase solution heuristic, which associates users and calculates backhaul routes to maximize energy savings. Our strategies optimize the backhaul network configuration at each timeslot based on the current demands and user locations. We discuss the application of our policies to backhaul management of mmWave cellular networks in light of current trend of network softwarization (Software-Defined Networking, SDN). Finally, we present extensive numerical simulations of our proposed policies, which show how the algorithms can efficiently trade-off energy consumption with required capacity, while satisfying flow demand requirements.Postprint (author's final draft