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Dissecting the Mobile Ecosystem with the Lumen Privacy Monitor
No full textAs a society we have come to rely upon our mobile phones for myriad daily tasks. It is striking how little insight we, as mobile users and researchers, have into the operation and performance of our devices and network, into how (or whether) mobile apps protect the information we entrust to them, and with whom they share it. The research community (including the speaker) have energetically used a variety of approaches to gain empirical understanding of the mobile device/network ecosystem; however, these techniques have had to make trade-offs that affect either the scale, scope or granularity of
measurements.
This talk describes how we leverage ideas from this prior work to design and develop the Lumen Privacy Monitor. The talk will demonstrate its utility to researchers and average users alike by providing case studies on mobile traffic characterization, identification of privacy risks inflicted by mobile apps, and perform network performance measurements.TRUEpu
How CSMA/CA With Deferral Affects Performance and Dynamics in Power-Line Communications
Get PDFPower-line communications (PLC) are becoming a key component in home networking, because they provide easy and high-throughput connectivity. The dominant MAC protocol for high data-rate PLC, the IEEE 1901, employs a CSMA/CA mechanism similar to the backoff process of 802.11. Existing performance evaluation studies of this protocol assume that the backoff processes of the stations are independent (the so-called decoupling assumption). However, in contrast to 802.11, 1901 stations can change their state after sensing the medium busy, which is regulated by the so-called deferral counter. This mechanism introduces strong coupling between the stations and, as a result, makes existing analyses inaccurate. In this paper, we propose a performance model for 1901, which does not rely on the decoupling assumption. We prove that our model admits a unique solution for a wide range of configurations and confirm the accuracy of the model using simulations. Our results show that we outperform current models based on the decoupling assumption. In addition to evaluating the performance in steady state, we further study the transient dynamics of 1901, which is also affected by the deferral counter.pu
Illuminating the Third Party Mobile Ecosystem with the Lumen Privacy Monitor
No full texthttps://www.ftc.gov/news-events/events-calendar/2017/01/privacyconDespite our growing reliance on mobile phones for a wide range of daily tasks, their operation remains largely opaque. A number of previous studies have addressed elements of this problem in a partial fashion, trading off analytic comprehensiveness and deployment scale. We overcome the barriers to large scale deployment (e.g., requiring rooted devices) and comprehensiveness of previous efforts by taking a novel approach that leverages the VPN API on mobile devices to design Haystack, an in-situ mobile measurement platform that operates exclusively on the device, providing full access to the device’s network traffic and local context without requiring root access. We present the design of Haystack and its implementation in an Android app that we deploy via standard distribution channels. Using data collected from 450 users of the app, we exemplify the advantages of Haystack over the state of the art and demonstrate its seamless experience even under
demanding conditions. We also demonstrate its utility to users and researchers in characterizing mobile traffic and privacy risks.FALSEpu
CrowdSenSim: a Simulation Platform for Mobile Crowdsensing in Realistic Urban Environments
Get PDFSmart cities take advantage of recent ICT developments
to provide added value to existing public services and improve quality of life for the citizens. The Internet of Things (IoT) paradigm makes the Internet more pervasive
where objects equipped with computing, storage and sensing
capabilities are interconnected with communication technologies. Because of the widespread diffusion of IoT devices, applying the IoT paradigm to smart cities is an excellent solution to build sustainable Information and Communication Technology (ICT) platforms. Having citizens involved in the process through mobile crowdsensing (MCS) techniques augments capabilities of these ICT platforms without additional costs. For proper operation, MCS systems require the contribution from a large number of participants. Simulations are therefore a candidate tool to assess the performance of MCS systems. In this paper, we illustrate the design of CrowdSenSim, a simulator for mobile
crowdsensing. CrowdSenSim is designed specifically for realistic urban environments and smart cities services. We demonstrate the effectiveness of CrowdSenSim for the most popular MCS sensing paradigms (participatory and opportunistic) and we present its applicability using a smart public street lighting scenario.TRUEpu
Data-Driven Performance Evaluation of Carrier Aggregation in LTE-Advanced
Get PDFCarrier aggregation increases the throughput of LTE mobile networks by aggregating bandwidth at different
frequencies. The theoretical effectiveness of carrier aggregation has been widely studied in the literature and operators claim it substantially increases the network data rate. However, to the best of our knowledge no practical evaluation of the performance of carrier aggregation has been performed using real traffic data. We perform a thorough measurement-based study to assess how carrier aggregation improves the service offered in selected locations in Madrid, Spain. Although the best results for data rate boost are in line with the operator claims, we find that resource usage in aggregated bands is frequently suboptimal, and higher data rates could be achieved by simply overloading a single band. On the other hand, the quality of service achieved by users effectively exploiting carrier aggregation could not be achieved without it.TRUEpu
Network Slicing via Function Decomposition and Flexible Network Design
Get PDFWe argue for flexible network design as an architec- ture prototype for next generation networks. Such flexible design is developed by capitalizing on the concept of network function decomposition in conjunction with with its relation to network slicing. A detailed view of the proposed functional architecture is put forward, where the role of specific network function blocks for forming network slices with given requirements is underlined. We further highlight the impact of common architecture over multiple tenants and elaborate on the emerging business models associated with multi-tenancy together with the resulting implications on security.TRUEpu
Achieving Reliability and Fairness in Online Task Computing Environments
Get PDFWe consider online task computing environments such as volunteer computing platforms running on BOINC (e.g., SETI@home) and crowdsourcing platforms such as Amazon Mechanical Turk. We model the computations as an Internet-based task computing system under the master-worker paradigm. A master entity sends tasks across the Internet, to worker entities willing to perform a computational task. Workers execute the tasks, and report back the results, completing the computational round. Unfortunately, workers are untrustworthy and might report an incorrect result. Thus, the first research question we answer in this work is how to design a reliable master-worker task computing system. We capture the workers’ behavior through two realistic models:
(1) the “error probability model” which assumes the presence of altruistic workers willing to provide correct results and the presence of troll workers aiming at providing random incorrect results. Both types of workers suffer from an error probability altering their intended response.
(2) The “rationality model” which assumes the presence of altruistic workers, always reporting a correct result, the presence of malicious workers always reporting an incorrect result, and the presence of rational workers following a strategy that will maximize their utility (benefit). The
rational workers can choose among two strategies: either be honest and report a correct result, or cheat and report an incorrect result. Our two modeling assumptions on the workers’ behavior are supported by an experimental evaluation we have performed on Amazon Mechanical Turk.
Given the error probability model, we evaluate two reliability techniques: (1) “voting” and (2) “auditing” in terms of task assignments required and time invested for computing correctly a set of tasks with high probability. Considering the rationality model, we take an evolutionary game theoretic approach and we design mechanisms that eventually achieve a reliable computational platform where the master receives the correct task result with probability one and with minimal auditing cost. The designed mechanisms provide incentives to the rational workers, reinforcing
their strategy to a correct behavior, while they are complemented by four reputation schemes that cope with malice. Finally, we also design a mechanism that deals with unresponsive workers by keeping a reputation related to the workers’ response rate. The designed mechanism selects the
most reliable and active workers in each computational round. Simulations, among other, depict the trade-off between the master’s cost and the time the system needs to reach a state where the master always receives the correct task result. The second research question we answer in
this work concerns the fair and efficient distribution of workers among the masters over multiple computational rounds. Masters with similar tasks are competing for the same set of workers at each computational round. Workers must be assigned to the masters in a fair manner; when the
master values a worker’s contribution the most. We consider that a master might have a strategic behavior, declaring a dishonest valuation on a worker in each round, in an attempt to increase its benefit. This strategic behavior from the side of the masters might lead to unfair and inefficient assignments of workers. Applying renown auction mechanisms to solve the problem at hand can be infeasible since monetary payments are required on the side of the masters. Hence, we present an alternative mechanism for fair and efficient distribution of the workers in the presence of strategic masters, without the use of monetary incentives. We show analytically that our designed mechanism guarantees fairness, is socially efficient, and is truthful. Simulations favourably compare our designed mechanism with two benchmark auction mechanisms.MathematicsUniversidad Carlos III de Madrid, Spainpu
Finite Horizon Opportunistic Multicast Beamforming
Get PDFWireless multicasting suffers from the problem that the transmit rate is usually determined by the receiver with the worst channel conditions. Composite or adaptive beamforming allows using beamforming patterns that trade off antenna gains between receivers, which can be used to overcome this problem. A common solution for wireless multicast with beamforming is to select the pattern that maximizes the minimum rate among all receivers. However, when using opportunistic multicast to transmit a finite number of packets to all receivers – the finite horizon problem – this is no longer optimal. Instead, the optimum beamforming pattern depends on instantaneous channel conditions as well as the number of received packets at each receiver. We formulate the finite horizon multicast beamforming problem as a dynamic programming problem to obtain an optimal solution. We further design a heuristic that has sufficiently low complexity to be implementable in practice. To deal with imperfect feedback, and in particular feedback delay, we extend the algorithm to work with estimated state and channel information. We show through extensive simulations that our algorithms significantly outperform prior solutions.pu
Convergence to multi-resource fairness under end-to-end window control
No full textThe paper relates to multi-resource sharing between
flows with heterogeneous requirements as arises in networks with wireless links or software routers implementing network function virtualization. Bottleneck max fairness (BMF) is a sharing objective in this context with good performance. The paper shows that BMF results when local fairness is imposed at each resource while flow rates are controlled by an end-to-end window. We analytically prove convergence to BMF under a fluid model when flows share a network limited to 2 resources while numerical results confirm BMF convergence for larger networks. Simulation results illustrate the impact of packetized transmission.TRUEpu
