Fabrizio Granelli

Energy-efficient data replication in cloud computing datacenters

Cloud computing is an emerging paradigm that provides computing, communication and storage resources as a service over a network. Communication resources often become a bottleneck in service provisioning for many cloud applications. Therefore, data replication which brings data (e.g., databases) closer to data consumers (e.g., cloud applications) is seen as a promising solution. It allows minimizing network delays and bandwidth usage. In this paper we study data replication in cloud computing data centers. Unlike other approaches available in the literature, we consider both energy efficiency and bandwidth consumption of the system. This is in addition to the improved quality of service QoS obtained as a result of the reduced communication delays. The evaluation results, obtained from both mathematical model and extensive simulations, help to unveil performance and energy efficiency tradeoffs as well as guide the design of future data replication solutions.

Cross-layer congestion control in ad hoc wireless networks

The paper presents the problem of performance degradation of transport layer protocols due to congestion of wireless local area networks. Following the analysis of available solutions to this problem, a cross-layer congestion avoidance scheme (C 3 TCP) is presented, able to obtain higher performance by gathering capacity information such as bandwidth and delay at the link layer. The method requires the introduction of an additional module within the protocol stack of the mobile node, able to adjust the outgoing data stream based on capacity measurements. Moreover, a proposal to provide optional field support to existing IEEE 802.11 protocol, in order to support the presented congestion control solution as well as many other similar approaches, is presented. Achieved results underline good agreement with design considerations and high utilization of the available resources. � 2005 Elsevier B.V. All rights reserved.

Electric Power Allocation in a Network of Fast Charging Stations

In order to increase the penetration of electric vehicles, a network of fast charging stations that can provide drivers with a certain level of quality of service (QoS) is needed. However, given the strain that such a network can exert on the power grid, and the mobility of loads represented by electric vehicles, operating it efficiently is a challenging and complex problem. In this paper, we examine a network of charging stations equipped with an energy storage device and propose a scheme that allocates power to them from the grid, as well as routes customers. We examine three scenarios, gradually increasing their complexity. In the first one, all stations have identical charging capabilities and energy storage devices, draw constant power from the grid and no routing decisions of customers are considered. It represents the current state of affairs and serves as a baseline for evaluating the performance of the proposed scheme. In the second scenario, power to the stations is allocated in an optimal manner from the grid and in addition a certain percentage of customers can be routed to nearby stations. In the final scenario, optimal allocation of both power from the grid and customers to stations is considered. The three scenarios are evaluated using real traffic traces corresponding to weekday rush hour from a large metropolitan area in the US. The results indicate that the proposed scheme offers substantial improvements of performance compared to the current mode of operation; namely, more customers can be served with the same amount of power, thus enabling the station operators to increase their profitability. Further, the scheme provides guarantees to customers in terms of the probability of being blocked (and hence not served) by the closest charging station to their location. Overall, the paper addresses key issues related to the efficient operation, both from the perspective of the power grid and the drivers satisfaction, of a network of charging stations.

Intelligent extended floating car data collection

The elaboration of data collected by vehicles moving on road network is relevant for traffic management and for private service providers, which can bundle updated traffic information with navigation services. Floating data, in its extended acceptation, contains not only time and location provided by a positioning system, but also information coming from various vehicle sensors. In this paper we describe our extended data collection system, in which vehicles are able to collect data about their local environment, namely the presence of roadworks and traffic slowdowns, by analyzing visual data taken by a looking forward camera and data from the on-board Electronic Control Unit. Upon detection of such events, a packet is set up containing time, position, vehicle data, results of on-board elaboration, one or more images of the road ahead and an estimation of the local traffic level. Otherwise, the transmitted packet containing only the minimal data, making its size adaptive to the environment surrounding the vehicle.

Local energy storage sizing in plug-in hybrid electric vehicle charging stations under blocking probability constraints

Plug-in hybrid electric vehicles (PHEV) are becoming gradually more attractive than internal combustion engine vehicles, even though the current electrical grid is not potentially able to support the required power demand increase to introduce charging stations. Acknowledging that design and development of charging stations has crucial importance, this paper introduces a candidate PHEV charging station architecture, along with a quantitative stochastic model, that allows us to analyze the performance of the system by using arguments from queuing theory and economics. A relevant component of the proposed architecture is the capability of the charging stations to store excess power obtained from the grid. The goal is to design a general architecture which will be able to sustain grid stability, while providing a required level of quality of service; and to describe a general methodology to analyze the performance of such stations with respect to the traffic characteristics, energy storage size, pricing and cost parameters. Our results indicate that significant gains in net cost/profit and useful insights can be made with the right choice of storage size. Such considerations are crucial in this early stage of designing the smart grid and charging stations of the future.

e-STAB: Energy-Efficient Scheduling for Cloud Computing Applications with Traffic Load Balancing

Energy consumption accounts for a large percentage of the operational expenses in data centers that are used as backend computing infrastructure for cloud computing. Existing solutions for energy efficiency and job scheduling are focusing on job distribution between servers based on the computational demands, while the communication demands are ignored. This work emphases the role of communication fabric and presents a scheduling solution, named e-STAB, which takes into account traffic requirements of cloud applications providing energy efficient job allocation and traffic load balancing in data center networks. Effective distribution of network traffic improves quality of service of running cloud applications by reducing the communication-related delays and congestion-related packet losses. The validation results, obtained from the Green Cloud simulator, underline benefits and efficiency of the proposed scheduling methodology.

Cognitive ultra wide band radio: a research vision and its open challenges

The paper introduces the concept of cognitive UWB radio, a wireless system based on UWB transmission able to self-adapt to the characteristics of the surrounding environment. First, salient features of UWB transmission are reviewed, and then, application of UWB characteristics to the problem of cognitive radio systems is discussed. Some preliminary studies on the physical level underline the potential value of the proposed framework.

Quality evaluation and nonuniform compression of geometrically distorted images using the quadtree distortion map

The paper presents an analysis of the effects of lossy compression algorithms applied to images affected by geometrical distortion. It will be shown that the encoding-decoding process results in a nonhomogeneous image degradation in the geometrically corrected image, due to the different amount of information associated to each pixel. A distortion measure named quadtree distortion map (QDM) able to quantify this aspect is proposed. Furthermore, QDM is exploited to achieve adaptive compression of geometrically distorted pictures, in order to ensure a uniform quality on the final image. Tests are performed using JPEG and JPEG2000 coding standards in order to quantitatively and qualitatively assess the performance of the proposed method.

Enhanced GPSR Routing in Multi-Hop Vehicular Communications through Movement Awareness

Providing reliable and efficient routing in presence of relative movement motivates the introduction of movement awareness to improve performance of existing position-based routing schemes in vehicular ad-hoc networks. The proposed algorithm represents a modification of well-known GPSR which exploits information about movement in order to improve the next forwarding node decision. Performance evaluation of the proposed protocol underlines a promising and robust basis for designing a routing strategy suitable for the automotive scenario.

Software defined and virtualized wireless access in future wireless networks: scenarios and standards

Future wireless networks are expected to provide augmented and data-intensive services in a multi-vendor multi-proprietor scenario. This scenario introduces relevant challenges to the networking infrastructure, especially in terms of flexibility and interoperability, that could be addressed by extending the concept of Virtualization and Software Defined Networking (SDN) to the wireless or wired-cum-wireless world. This paper provides a review of the perspectives to the extension of the SDN paradigm in the wireless domain by identifying current trends and proposed solutions, and providing the existing major standardization efforts and future trends in the field.