To deliver an end-to-end service in the Network Function Virtualization (NFV) environment, Service Function Chain (SFC) is used to define the sequence of Virtual Network Functions (VNFs) that needs to be applied to the data stream of the service. In the literature, SFC is typically regarded as a linear topology that represents the sequence of the VNFs that a data stream is navigated through. Our recent study, however, reveals a group of real-life use cases for which a linear topology is in-sufficient to describe the complexity of the SFC: the data stream can branch out into multiple streams due to multiple reasons (e.g., load-balance the web/non-web traffic). In this paper, we study representative use cases with presence of branching, categorize traffic branching into three major categories, and introduce policies to specify the service requirement that involves traffic branching. In addition, we define the resulting problem and discuss directions for further exploration.
Using public transportation can be a major challenge for individuals with visual impairments. To navigate a mass transit system independently and safely, one needs to be able to gather information about their surroundings. We propose a Conscious GPS system to assist a user with visual impairment to navigate the public transit system. The system utilizes computer vision to autonomously record the users surroundings by taking various pictures in sequence and leveraging image processing techniques and machine learning to identify and extract information about key objects around the user. Our target object is the circular bus sign on an NYC MTA bus stop. We use Haar Cascade computer vision techniques to detect and locate the sign in an image through feature-based image classification. The proposed system experiences no misclassification after training the Haar Cascade classifier with a minimum hit rate of 0.99 and a maximum false alarm rate of 0.20 when navigating the daily city landscape and can accurately detect a bus stop sign.
This work presents two explanatory mathematical models explaining how network traffic features that display Gaus-sian tendencies in single devices and small networks aggregate to alpha-stable processes in larger networks. The first model shows how self-similarity originates from an impulsive-noise-based representation of individual processes. A second model uses renewal processes to justify impulsive process aggregation to alpha-stable or Gaussian end states and permits estimating network traffic alpha-stable rates of convergence. We develop a model based on this first method to empirically validate this aggregation approach.
A self-organizing swarm of autonomous unmanned areal vehicles (UAVs) can provide a quick response to cyber-attacks in austere civilian and military environments. However, if a UAV swarm relies on centralized control, synchronization of swarm members, pre-planned actions or rule-based systems, it may not provide adequate and timely response against cyber attacks. We introduce game theory (GT) and biology inspired flight control algorithms to be run by each autonomous UAV to detect, localize and counteract rogue electromagnetic signal emitters. Each UAV positions itself such that the swarm tracks mobile adversaries while maintaining uniform node distribution and connectivity of the mobile ad-hoc network (MANET). UAVs use only their respective local neighbor information to determine their individual actions. Simulation experiments in OPNET show that our algorithms can provide an adequate area coverage over mobile interference sources. Our solution can be employed for civilian and military applications that require agile responses in dynamic environments.
Availability of large array usage in millimeter wave communications gives the opportunity to create narrow beams that yield to high antenna gains. However, in some cases, wider beams are of interest in order to increase the coverage area or reduce the outages caused by the channel variations. To address this need, beam broadening approaches with no increase in the hardware complexity have been described without studying the implementation difficulties. This paper proposes a simplified broadening model while adopting a strategy in which neighbor beams are concatenated to create a wider beam dividing the antenna into subarrays. The beamwidth and power loss analysis along with the beam broadening bounds in the design parameters are expressed in detail. Next, introduced broadening model is integrated to the hybrid beamforming system without changing its hardware structure. Simulation results that verify the analytical expressions for both broadening system and its hybrid beamforming implementation are provided.
Antenna consolidation on the topside of shipboard platforms reduces the amount of different antennas needed to perform various capabilities at different frequencies. Parabolic antenna stacking consolidates antenna capabilities and saves space on shipboard platforms. This paper presents the design and simulated radiation pattern results of a tri-band parabolic stacked antenna that reduces the number of antennas required on shipboard platforms. This tri-band parabolic stacked antenna is focused on providing a Q, X and Ka band capable solution on a single antenna pedestal.
Applying the Cognitive Radio paradigm to short-range systems inside buildings, it is intended to control two major drawbacks. The first one refers to controlling the efficiency in the use of the spectrum in interior scenarios, and the second is to overcome the inconvenience in the quality of service that arises when there are large quantities of short-range systems interfering with each other. Estimating the effective spectrum available inside a smart building is a big challenge. To do so, we must consider the deployment of users of the primary system, whose band would be reused. Large amounts of spectral opportunities have been found for the primary band, especially on the lower floors of the building. However, when considering the effect of shadowing on the interior of the building, it is shown that effective spectrum availability decreases.
In this paper, we propose a set of three media access control (MAC) schemes for an indirect diffused light free-space optical communications (ID-FSOCs). ID-FSOC has been recently proposed to establish wireless high-speed (i.e., ≥1 Gbps) network access using FSO from stations that have no line-of-sight (LOS) with the access point. ID-FSOC employs a diffuse reflector (DR) to uniformly reflect diffused light from an incident laser to all directions, except towards the DR. To establish a link, ID-FSOC requires LOS between the transmitter and the DR and between DR and the receiver. In this way, ID-FSOC relaxes the location of stations as long as they keep LOS to the DR. We analyze the performance and scalability of proposed schemes. We also consider the impact of the zoom-in time of a receiver in our evaluations. Our results show that our proposed MAC schemes achieve high channel utilization and higher throughput than carrier-sense multiple access schemes.
Bitcoin is a well-known cryptocurrency in which records of transactions are maintained by a P2P network to create a distributed ledger. Due to the complex nature of maintaining highly efficient, transparent and speed transactions between nodes, security is one of the primary concerns of this system. The most prominent modern-day attacks to this system are the selfish mining and double spending attacks. This survey is organized around the aspects pertaining to countermeasures of selfish mining and double spending attacks. We selected a total of 20 primary studies from recent years as a result of a systematic analysis approach. In this study we will aim to classify, analyze, and evaluate these proposed methods in order to create a secure blockchain system. These countermeasures are being developed and are being experimented with in order to mitigate and/or even eliminate these attacks from occurring. These proposed frameworks and research papers will outline the keys to improving the blockchain architecture with code scripts and design parameters to increase the functionality of the blockchain. We aim to identify implications of these countermeasures to address vulnerabilities in the blockchain network for future research on this topic.
Multipath TCP (MPTCP) can improve overall throughput of an end-to-end connection by leveraging different network paths. However, the heterogeneity of these paths can significantly hamper MPTCP’s performance. In this paper, we propose to send acknowledgments (ACKs) along the lowest-latency path. This can help improve the performance of MPTCP when subflow throughput is constrained by packet loss by reacting to loss events faster. An active probing module is also developed to dynamically select the lowest-latency path against the potential change of path condition. Experiments demonstrate that overall throughput improvement generally ranges from 10% to 50%.
Low-Power and Lossy Network (LLN) is composed of embedded devices with limited power, memory, and processing resources. LLN has a wide variety of applications including industrial monitoring, connected home, health care, urban sensor networks and environmental monitoring. LLN uses Routing Protocol for Low-power and lossy networks (RPL) protocol. The RPL maintains directed acyclic graphs for routing packets. By exploiting some features, a Distributed Denial-of-Service (DDoS) attack can be conducted easily. DDoS attacks are very popular and well studied in the context of the Internet, but not in the context of LLNs. In this paper, we propose a powerful DDoS attack framework in LLNs. We formulate the attack as an optimization problem for selecting an optimal set of attackers and their targeted neighbors constrained by a limited link bandwidth. We propose an optimal solution by transforming the optimization problem into a max-flow problem. We provide simulations to support our model.
We describe an optical computation technology that can be used for optical communication, sensing and imaging. We demonstrate intelligent optical computation for online signal processing in optical coherence tomography.
Internet of Things (IoT) applications are anticipated to bloom in the future, and two popular industry areas related to Internet of Things (IoT) are smart houses and smart factories. To make a home or factory smart, hundreds or thousands of sensors need to work and communicate together with simple, secure and stable connectivity. Thus, the design of smart homes and smart factories relies on wireless sensor networks, whose transmission is often characterized to be sporadic. Classical approaches to multiuser communications rely on tight time synchronization achieved by employing coordinating infrastructure, but in a mass sensor transmission system, sensors may communicate with each other directly without relying on coordinating mechanisms. Our study explores the possibilities of simple and reliable multiuser detection in DS-CDMA system for few data and short distance mass sensor connectivity with joint synchronization of data. Furthermore, we discussed a scenario where spreading sequences are overused. We show that our system has strong potential for excellent mass sensors detection performance without synchronizing infrastructure.
With the proliferation of the delay sensitive applications and services in cellular networks, the outage probability becomes an important metric that should be minimized to support the low latency requirement of the 5G network. In this paper, the analytical model is proposed to calculate the system outage probability as a closed form expression under the Rayleigh fading channel for the NOMA downlink system. We utilize the model to obtain the optimum power allocation that minimizes the system outage probability as a closed form expression. The accuracy of the proposed analytical model and optimum power allocation is validated by the Monte Carlo simulations. The numerical results show that the outage probability depends on the power allocation and the outage probability of OMA with the fractional power allocation is lower than NOMA with the optimum power allocation. The results indicate that the trade-off between the outage and spectral efficiency in NOMA should be carefully controlled to meet higher throughput and lower latency objectives of 5G.
Network automation promises to improve network operations by increasing efficiency and consistency but is difficult to achieve in practice due to the large variety of infrastructure devices within the network as well as vendor specific management and control interfaces. This paper explores options for the tactical deployment of network automation to provide maximum return on investment as organizations explore strategic approaches to network automation.
Recently, multiple research teams aimed to address the scalability and fault-tolerance issues of Network Functions (NFs) by implementing a storage system (or distributed shared object) to share state across NF instances. Each system demonstrated promising performance under specific scenarios. However, there are many more technical challenges to be addressed to build a production-ready storage system for NFs.In this paper, we enumerate these challenges, explain how some of them were addressed by previous systems, and discuss alternative promising solutions to tackle them. Most challenges remain as open problems, while others deserve more thorough study. The first goal of the paper is to provide a broad research agenda around this topic, by discussing more problems than solutions. Moreover, we advocate that the first step towards a production-ready system is to build a realistic yet extensible benchmarking tool to deploy, test, and analyze "network function storages" comprehensively. Toward this end, we present our tool - Network Function Storage Benchmarking (NFSB). Finally, we present some preliminary results using NFSB.
The main advantage of Blockchain technology is the immutability of data maintained by decentralized systems. Earlier studies introduce the probability of attackers succeeding in modifying legitimate data in the blocks. We propose "immutability measure", a metric that indicates the degree of difficulty in modifying existing data in Blockchain. We propose different blockchain structures that can be more appropriate for different applications. There are several parameters that determine the difficulty of modifying data in Blockchain. We analyze the impact of each of these parameters on the immutability measure of various blockchain structures. We also study the required computational and electrical power as well as the time for a successful attack in various blockchain structures. We demonstrate that our proposed blockchain structures can exponentially improve the immutability measure with a nominal increase in computing resources.
Multiple-input multiple-output (MIMO) techniques are currently the de facto approach for increasing the capacity and reliability of communication systems. Spatial modulation (SM) is presently one of the most eminent MIMO techniques. As, it combines the advantages of having higher spectral efficiency than repetition coding (RC) while overcoming the inter-channel interference (ICI) faced by spatial multiplexing (SMP). Moreover, SM reduces system complexity. In this paper, for the first time in literature, the use of MIMO techniques is explored in Internet-of-Things (IoT) deployments by introducing a novel technique called security aware spatial modulation (SA-SM). SA-SM provides a low complexity, secure and spectrally efficient technique that harvests the advantages of SM, while facing the arising security concerns of IoT systems. Using an undemanding modification at the receiver, SA-SM gives an extra degree of technology independent physical layer security. Our results show that SA-SM forces the bit-error-rate (BER) of an eavesdropper to not exceed the range of 10, which is below the forward-error-correction (FEC) threshold. Hence, it eradicates the ability of an eavesdropper to properly decode the transmitted signal. Additionally, the efficiency of SA-SM is verified in both the radio and visible light ranges. Furthermore, SA-SM is capable of reducing the peak-to-average-power-ratio (PAPR) by 26.2%.
We consider an $M/M/1$ update-and-decide system where Poisson distributed decisions are made based on the received updates. We propose to characterize the freshness of the received updates at decision epochs with Age upon Decisions (AuD). Under the first-come-first-served policy (FCFS), the closed form average AuD is derived. We show that the average AuD of the system is determined by the arrival rate and the service rate, and is independent of the decision rate. Thus, merely increasing the decision rate does not improve the timeliness of decisions. Nevertheless, increasing the arrival rate and the service rate can decrease the average AuD efficiently.
Walkers have been used to help the elderly and individuals with movement disorders as an assistive and rehabilitation tool. This study presents a smart walker, a system which guides the users to navigate in an indoor environment. The Walker can be controlled by voice commands to create location markers and navigate the user while avoiding obstacles. We evaluated three localization implementations, namely, Adaptive Monte Carlo Localization (AMCL), Gmapping and Hector_Slam for this system and compared their navigation accuracy with an ideal path. We collected the data on the paths of AMCL, Gmapping and Hector_Slam and applied statistical tests on the data. The results show that AMCL achieves the lowest mean absolute error while navigating to its goal with an error of 2.15% over the path distance, as compared to Gmapping and Hector in this implementation.
