Evaluation of the Precision-Privacy Tradeoff of Data Perturbation for Smart Metering

Abstract: Smart grid users and standardization committees require that utilities and third parties collecting metering data employ techniques for limiting the level of precision of the gathered household measurements to a granularity no finer than what is required for providing the expected service. Data aggregation and data perturbation are two such techniques. This paper provides quantitative means to identify a tradeoff between the aggregation set size, the precision on the aggregated measurements, and the privacy level. This is achieved by formally defining an attack to the privacy of an individual user and calculating how much its success probability is reduced by applying data perturbation. Under the assumption of time-correlation of the measurements, colored noise can be used to even further reduce the success probability. The tightness of the analytical results is evaluated by comparing them to experimental data

A privacy-friendly game-theoretic distributed scheduling system for domestic appliances

open3Game-theoretic Demand Side Management (DSM) systems have been investigated as a decentralized approach for the collaborative scheduling of the usage of domestic electrical appliances within a set of households. Such systems allow for the shifting of the starting time of deferrable devices according to the current energy price or power grid condition, in order to reduce the individual monthly bill or to adjust the power load experienced by the grid while meeting the users’ preferences about the time of use. The drawback of DSM distributed protocols is that they require each user to communicate his/her own energy consumption patterns to the other users, which may leak sensitive information regarding private habits. This paper proposes a distributed Privacy-Friendly DSM system which preserves users’ privacy by integrating data aggregation and perturbation techniques: users decide their schedule according to aggregated consumption measurements perturbed by means of Additive White Gaussian Noise (AWGN). We evaluate the noise power and the size of the set of users required to achieve a given privacy level, quantified by means of the Kullback-Leibler divergence. The performance of our proposed DSM system are compared to the ones obtained by a benchmark system which does not support privacy preservation in terms of social cost, peak demand and convergence time. Results show that privacy can be preserved at the cost of increasing the peak demand and the number of game iterations, whereas social cost is only marginally incremented.C Rottondi; A Barbato; G VerticaleRottondi, CRISTINA EMMA MARGHERITA; Barbato, Antimo; Verticale, Giacom

Impact of Processing Costs on Service Chain Placement in Network Functions Virtualization

The Network Functions Virtualization (NFV) paradigm is the most promising technique to help network providers in the reduction of capital and energy costs. The deployment of virtual network functions (VNFs) running on generic x86 hardware allows higher flexibility than the classical middleboxes approach. NFV also reduces the complexity in the deployment of network services through the concept of service chaining, which defines how multiple VNFs can be chained together to provide a specific service. As a drawback, hosting multiple VNFs in the same hardware can lead to scalability issues, especially in the processing-resource sharing. In this paper, we evaluate the impact of two different types of costs that must be taken into account when multiple chained VNFs share the same processing resources: the upscaling costs and the context switching costs. Upscaling costs are incurred by VNFs multi-core implementations, since they suffer a penalty due to the needs of load balancing among cores. Context switching costs arise when multiple VNFs share the same CPU and thus require the loading/saving of their context. We model through an ILP problem the evaluation of such costs and we show their impact in a VNFs consolidation scenario, when the x86 hardware deployed in the network is minimized

Energy-Efficient VoD content delivery and replication in integrated metro/access networks

Today's growth in the demand for access bandwidth is driven by the success of the Video-on-Demand (VoD) bandwidth-consuming service. At the current pace at which network operators increase the end users' access bandwidth, and with the current network infrastructure, a large amount of video traffic is expected to flood the core/metro segments of the network in the near future, with the consequent risk of congestion and network disruption. There is a growing body of research studying the migration of content towards the users. Further, the current trend towards the integration of metro and access segments of the network makes it possible to deploy Metro Servers (MSes) that may serve video content directly from the novel integrated metro/access segment to keep the VoD traffic as local as possible. This paper investigates a potential risk of this solution, which is the increase in the overall network energy consumption. First, we identify a detailed power model for network equipment and MSes, accounting for fixed and load-proportional contributions. Then, we define a novel strategy for controlling whether to switch MSes and network interfaces on and off so as to strike a balance between the energy consumption for content transport through the network and the energy consumption for processing and storage in the MSes. By means of simulations and taking into account real values for the equipment power consumption, we show that our strategy is effective in providing the least energy consumption for any given traffic load

Optimal Content Placement in ICN Vehicular Networks

Information Centric Networking (ICN) is a networking framework for content distribution. The communication is based on a request/response model where the attention is centered on the content. The user sends interest messages naming the content it desires and the network chooses the best node from which delivers the content. This way for retrieving contents naturally fits a context where users continuously change their location. One of the main problems of user mobility is the intermittent connectivity that causes loss of packets. This work shows how in a Vehicle-to-Infrastructure scenario, the network can exploit the ICN architecture with content pre-distribution to maximize the probability that the user retrieves the desired content. We give an ILP formulation of the problem of optimally distributing the contents in the network nodes and discuss how the system assumptions impact the success probability. Moreover, we validate our model by means of simulations with ndnSIM

Secure and Differentially Private Detection of Net Neutrality Violations by Means of Crowdsourced Measurements

Evaluating Network Neutrality requires comparing the quality of service experienced by multiple users served by different Internet Service Providers. Consequently, the issue of guaranteeing privacy-friendly network measurements has recently gained increasing interest. In this paper we propose a system which gathers throughput measurements from users of various applications and Internet services and stores it in a crowdsourced database, which can be queried by the users themselves to verify if their submitted measurements are compliant with the hypothesis of a neutral network. Since the crowdsourced data may disclose sensitive information about users and their habits, thus leading to potential privacy leakages, we adopt a privacy-preserving method based on randomized sampling and suppression of small clusters. Numerical results show that the proposed solution ensures a good trade-off between usefulness of the system, in terms of precision and recall of discriminated users, and privacy, in terms of differential privacy

Runtime Management of Artificial Intelligence Applications for Smart Eyewears

Artificial Intelligence (AI) applications are gaining popularity as they seamlessly integrate into end-user devices, enhancing the quality of life. In recent years, there has been a growing focus on designing Smart EyeWear (SEW) that can optimize user experiences based on specific usage domains. However, SEWs face limitations in computational capacity and battery life. This paper investigates SEW and proposes an algorithm to minimize energy consumption and 5G connection costs while ensuring high Quality-of-Experience. To achieve this, a management software, based on Q-learning, offloads some Deep Neural Network (DNN) computations to the user’s smartphone and/or the cloud, leveraging the possibility to partition the DNNs. Performance evaluation considers variability in 5G and WiFi bandwidth as well as in the cloud latency. Results indicate execution time violations below 14%, demonstrating that the approach is promising for efficient resource allocation and user satisfaction

TCP throughput guarantee in the DiffServ Assured Forwarding service: what about the results?

Since the proposition of Quality of Service architectures by the IETF, the interaction between TCP and the QoS services has been intensively studied. This paper proposes to look forward to the results obtained in terms of TCP throughput guarantee in the DiffServ Assured Forwarding (DiffServ/AF) service and to present an overview of the different proposals to solve the problem. It has been demonstrated that the standardized IETF DiffServ conditioners such as the token bucket color marker and the time sliding window color maker were not good TCP traffic descriptors. Starting with this point, several propositions have been made and most of them presents new marking schemes in order to replace or improve the traditional token bucket color marker. The main problem is that TCP congestion control is not designed to work with the AF service. Indeed, both mechanisms are antagonists. TCP has the property to share in a fair manner the bottleneck bandwidth between flows while DiffServ network provides a level of service controllable and predictable. In this paper, we build a classification of all the propositions made during these last years and compare them. As a result, we will see that these conditioning schemes can be separated in three sets of action level and that the conditioning at the network edge level is the most accepted one. We conclude that the problem is still unsolved and that TCP, conditioned or not conditioned, remains inappropriate to the DiffServ/AF service

To be neutral or not neutral? the in-network caching dilemma

Caching allows Internet Service Providers (ISPs) to reduce network traffic and Content Providers (CPs) to increase the offered QoS. However, when contents are encrypted, effective caching is possible only if ISPs and CPs cooperate. We suggest possible forms of non-discriminatory cooperation that make caching compliant with the principles of Net-Neutrality (NN

BER evaluation of post-meter PLC services in CENELEC-C band

Low voltage, in-home power-line communications (PLC) networks allow direct communication between smart meters (SM) and in-home devices (IHD). In order to minimize security issues, in many deployment scenarios transmission takes place only towards the IHD to display consumption data, with no backwards channel. As a result, channel estimation is difficult and it is necessary to use robust transmission techniques to mitigate the effect of the impulsive noise within the PLC channel. Performance of such system must be evaluated by taking into account realistic interference and channel models for a broad range of configurations. In this work we focus on performance in terms of bit error rate (BER) of a narrowband PLC (NB-PLC) operating in the CENELEC-C band (125–140 kHz) taking into account realistic noise models. Our system is based on binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) modulation