Licensed assisted access (LAA) enables the coexistence of long-term evolution (LTE) and WiFi in unlicensed bands, while potentially offering improved coverage and data rates. However, cooperation with the conventional random-access protocols that employ listen-before-talk (LBT) considerations makes meeting the LTE performance requirements difficult, since delay and throughput guarantees should be delivered. In this paper, we propose a novel channel sharing mechanism for the LAA system that is capable of simultaneously providing the fairness of resource allocation across the competing LTE and Wi-Fi sessions as well as satisfying the quality-of-service guarantees of the LTE sessions in terms of their upper delay bound and throughput. Our proposal is based on two key mechanisms: 1) LAA connection admission control for the LTE sessions and 2) adaptive duty cycle resource division. The only external information necessary for the intended operation is the current number of active Wi-Fi sessions inferred by monitoring the shared channel. In the proposed scheme, LAA-enabled LTE base station fully controls the shared environment by dynamically adjusting the time allocations for both Wi-Fi and LTE technologies, while only admitting those LTE connections that should not interfere with Wi-Fi more than another Wi-Fi access point operating on the same channel would. To characterize the key performance trade-offs pertaining to the proposed operation, we develop a new analytical model. We then comprehensively investigate the performance of the developed channel sharing mechanism by confirming that it allows to achieve a high degree of fairness between the LTE and Wi-Fi connections as well as provides guarantees in terms of upper delay bound and throughput for the admitted LTE sessions. We also demonstrate that our scheme outperforms a typical LBT-based LAA implementation
Today, direct contacts between users are being facilitated by the network-assisted device-to-device (D2D) technology, which employs the omnipresent cellular infrastructure for the purposes of control to facilitate advanced mobile social applications. Together with its undisputed benefits, this novel type of connectivity creates new challenges in constructing meaningful proximity-based services with high levels of user adoption. They call for a comprehensive investigation of user sociality and trust factors jointly with the appropriate technology enablers for secure and trusted D2D communications, especially in the situations where cellular control is not available or reliable at all times. In this paper, we study the crucial aspects of social trust associations over proximity-based direct communications technology, with a primary focus on developing a comprehensive proof-of-concept implementation. Our recently developed prototype delivers rich functionality for dynamic management of security functions in proximate devices, whenever a new device joins a secure group of users or an existing one leaves it. To characterize the behavior of our implemented demonstrator, we evaluate its practical performance in terms of computation and transmission delays from the user perspective. In addition, we outline a research roadmap leveraging our technology-related findings to construct a holistic user perspective behind dynamic, social-aware, and trusted D2D applications and services.
IEEE 802.11ah, a new amendment to the Wi-Fi standard, adapts Wi-Fi networks to the emerging Internet of Things (IoT). A key component of .11ah is the Restricted Access Window (RAW), a new channel access mechanism, which reduces contention when even thousands of IoT devices operate in the same area by assigning them different channel times. This paper shows that existing studies incorrectly understand the RAW behavior, oversimplify its modeling and thereby overestimate the real system throughput in several times, especially for short durations of the reserved RAW slots. The core contribution of this paper is a new mathematical model based on a completely different approach, which yields more accurate results and thereby enables better IoT system dimensioning. The developed model is suitable for many scenarios typical for IoT. It allows finding RAW parameters that optimize system performance in terms of throughput, power consumption, and packet loss ratio. The proposed solution is can be used for various traffic patterns: when each device transmits a single packet, a batch of packets of random size, or it has full-buffer traffic.
The advancements in multi-core central processing units have attracted new designs ranging from mechanisms of packing higher number of transistors into the small space, new techniques for communications (e.g., wireless network on chips), or new methodologies for cooling the chip. The latter two design aspects are the focus of this paper, where a microfluidic system is utilized for performing both functions. The miniaturization of microfluidic channels makes it attractive to embed them into the chips to transport fluids that can remove the heat from the processor cores. The extension of the cooling purpose of on-chip microfluidic channels is done by integrating communication feature. The communication process is achieved by transporting fluid through the channel and injecting information through air droplets. Protocols for microfluidic communications are applied, including physical layer functionalities and medium access protocols. The protocol design takes into considerations various properties of the microfludics. Based on the proposed system, the tradeoffs between the data rate and its impact on the amount of heat that can be removed from the processor are evaluated. This system provides new forms of condensed processor design of the future, in which integration of multiple functionalities of microfluidic channel system embedded into multi-core processors.
Mobile social networks (MSNs) are the networks of individuals with similar interests connected to each other through their mobile devices. Recently, MSNs are proliferating fast supported by emerging wireless technologies that allow to achieve more efficient communication and better networking performance across the key parameters, such as lower delay, higher data rate, and better coverage. At the same time, most of the MSN users do not fully recognize the importance of security on their handheld mobile devices. Due to this fact, multiple attacks aimed at capturing personal information and sensitive user data become a growing concern, fueled by the avalanche of new MSN applications and services. Therefore, the goal of this work is to understand whether the contemporary user equipment is susceptible to compromising its sensitive information to the attackers. As an example, various information security algorithms implemented in modern smartphones are thus tested to attempt the extraction of the said private data based on the traces registered with inexpensive contemporary audio cards. Our obtained results indicate that the sampling frequency, which constitutes the strongest limitation of the off-the-shelf side-channel attack equipment, only delivers low-informative traces. However, the success chances to recover sensitive data stored within a mobile device may increase significantly when utilizing more efficient analytical techniques as well as employing more complex attack equipment. Finally, we elaborate on the possible utilization of neural networks to improve the corresponding encrypted data extraction process, while the latter part of this paper outlines solutions and practical recommendations to protect from malicious side-channel attacks and keep the personal user information protected.
Recently standardized millimeter-wave (mmWave) band 3GPP New Radio systems are expected to bring extraordinary rates to the air interface efficiently providing commercial-grade enhanced mobile broadband services in hotspot areas. One of the challenges of such systems is efficient offloading of the data from access points (AP) to the network infrastructure. This task is of special importance for APs installed in remote areas with no transport network available. In this paper, we assess the packet level performance of mmWave technology for cost-efficient backhauling of remote 3GPP NR APs connectivity “islands”. Using a queuing system with arrival processes of the same priority competing for transmission resources, we assess the aggregated and per-AP packet loss probability as a function environmental conditions, mmWave system specifics, and generated traffic volume. We show that the autocorrelation in aggregated traffic provides a significant impact on service characteristics of mmWave backhaul and needs to be compensated by increasing either emitted power or the number of antenna array elements. The effect of autocorrelation in the per-AP traffic and background traffic from other APs also negatively affects the per-AP packet loss probability. However, the effect is of different magnitude and heavily depends on the load fraction of per-AP traffic in the aggregated traffic stream. The developed model can be used to parameterize mmWave backhaul links as a function of the propagation environment, system design, and traffic conditions.
For description of dynamics of changes random loads of information flows we examine the stochastic model of Double Stochastic Poisson process which manages points of changes the random loads. A special case of a discrete distribution for the random intensity provides the following covariance property to the corresponding Double Stochastic Poisson subordinator for a sequence of the random loads. Such covariance exactly coincides with the covariance of the fractional Ornstein-Uhlenbeck process. Applying the Lamperti transform we obtain a self-similar random process with continuous time, stationary in the wide sense increments, and one dimensional distributions scaling the distribution of a term of the the initial subordinated sequence of the random loads. The Central Limit Theorem for vectors allows us to obtain in a limit, in the sense of convergence of finite dimensional distributions, the fractional Gaussian Brownian motion and the fractional Ornstein-Uhlenbeck process.
Massive multi-core processing has recently attracted significant attention from the research community as one of the feasible solutions to satisfy constantly growing performance demands. However, this evolution path is nowadays hampered by the complexity and limited scalability of bus-oriented intra- chip communications infrastructure.The latest advantages of terahertz (THz) band wireless communications providing extraordinary capacity at the air interface offer a promising alternative to conventional wired solutions for intra-chip communications. Still, to invest resources in this field manufacturers need a clear vision of what are the performance and scalability gains of wireless intra-chip communications. Using the comprehensive hybrid methodology combining THz ray-tracing, direct CPU traffic measurements, and cycle-accurate CPU simulations, we perform the scalability study of x86 CPU design that is backward compatible with the current x86 architecture. We show that preserving the current cache coherence protocols mapped into the star wireless communications topology that allows for tight centralized medium access control a few hundreds of active cores can be efficiently supported without any notable changes in the x86 CPU logic. This important outcome allows for incremental development, where THz-assisted x86 CPU with a few dozens of cores can serve as an intermediate solution, while the truly massive multi-core system with broadcast-enabled medium access and enhanced cache coherence protocols can be an ultimate goal.