Drop Probability Research Articles

Cross-Layer Optimization for Ultra-Reliable and Low-Latency Radio Access Networks

In this paper, we propose a framework for cross-layer optimization to ensure ultra-high reliability and ultra-low latency in radio access networks, where both transmission delay and queueing delay are considered. With short transmission time, the blocklength of channel codes is finite, and the Shannon capacity cannot be used to characterize the maximal achievable rate with given transmission error probability. With randomly arrived packets, some packets may violate the queueing delay. Moreover, since the queueing delay is shorter than the channel coherence time in typical scenarios, the required transmit power to guarantee the queueing delay and transmission error probability will become unbounded even with spatial diversity. To ensure the required quality-of-service (QoS) with finite transmit power, a proactive packet dropping mechanism is introduced. Then, the overall packet loss probability includes transmission error probability , queueing delay violation probability , and packet dropping probability . We optimize the packet dropping policy, power allocation policy, and bandwidth allocation policy to minimize the transmit power under the QoS constraint. The optimal solution is obtained, which depends on both channel and queue state information. Simulation and numerical results validate our analysis, and show that setting the three packet loss probabilities as equal causes marginal power loss.

QoE-Aware Intelligent Vertical Handoff Scheme Over Heterogeneous Wireless Access Networks

As a measurement, quality of service (QoS) has been commonly taken into account in the traditional vertical handoff schemes for the heterogeneous wireless access networks. However, the QoS is not sufficient to correlate well with the user satisfaction. In this paper, quality of experience (QoE) is introduced into the decision mechanism of the vertical handoff and a random neural network -based QoE estimation is proposed to determine the correlation between the QoE and the QoS in the heterogeneous networks. In addition, a Q-learning-based vertical handoff algorithm, designated as a QoE-Q algorithm, is presented in order to maximize the QoE utility for users. It can be observed from the simulation results that the proposed method not only outperforms the existing schemes with enhanced call blocking probability and handoff dropping probability property but also obtains better QoE performance in the service charges and the terminal power consumption than other schemes.

Research on Virtual Channel Multiplexing Algorithm Based on Advanced Orbiting Systems

To address multiple data types and high speeds in a business satellite network based on the virtual channel multiplexing technology of advanced orbiting systems (AOSs), an AOS virtual channel multiplexing system model is established. AOS queue management problems and the constraint problems in virtual channel scheduling are analyzed. On this basis, a priority adaptive random early detection and vaccine updating immune genetic algorithm is proposed. In queue management, based on the scheme of a multi-queue sharing cache with a minimum allocation, the algorithm adaptively adjusts packet dropping probability according to the packet priority. Based on an immune genetic algorithm, virtual channel scheduling automatically updates the vaccine database according to the matching degree of the vaccines and population. Meanwhile, the algorithm efficiently combines queue management and virtual channel scheduling. Experimental results show that the algorithm has excellent evolution performance and can maintain smaller queue lengths, smaller packet loss rates, less delay for high-priority virtual channels, and also has preferable fairness.

An Intelligent Fuzzy Logic System for Network Congestion Control

Network congestion is a major problem in all network environments as such it calls for ways to manage this problem. In this paper, we propose a Fuzzy Regulator Effective Random Early Detection (FRERED) system, which is an intelligent fuzzy logic based controller technique for early stage congestion detection, at the router buffer in the networks. The proposed technique extends the Fuzzy-Based system in the Fuzzy Hybrid ERED algorithm by considering the delay variable in its inference system to ease the problem of parameter initialization and parameter dependency. Unlike the Fuzzy-Based controller in the existing Fuzzy Hybrid ERED system which uses two parameter settings in its inference system that is, the queue size and average queue length in computing the dropping probability of packets. The proposed technique uses the queue size, average queue length and the delay approximation as input variables in computing the packet drop probability. The applied fuzzy logic system yields an output that denotes a packet dropping probability, which in turn controls and prevents congestion in early stage. This was achieved after simulating the proposed technique and the existing Fuzzy-Based controller using Matlab. The results obtained shows that this approach results in less packet drops for about the same link utilization as the existing Fuzzy-Based controller. Therefore, this technique, generally, controls network congestion and improves network performance. The methodology used to achieve this is the object oriented methodology and JAVA programming language was used to develop the system.

Road Constrained Monocular Visual Localization Using Gaussian-Gaussian Cloud Model

There are two main challenges, drift and scale ambiguity, restricting monocular visual odometry from an extensive application on real autonomous navigation. In this paper, an iterative localization framework is presented to globally localize a mobile vehicle equipped with a single camera and a freely available digital map. Inspired by the concept of cloud, a new Gaussian–Gaussian Cloud model is proposed to give a unified representation of the measurement randomness and scale ambiguity in monocular visual odometry. In this model, a collection of cloud drops is generated. Both the drift and scale ambiguity are considered and represented simultaneously in each cloud drop. To reduce the measurement uncertainties of any drop in Gaussian–Gaussian Cloud, road constraints from the open source map—OpenStreetMap—are utilized. The map is first converted to a template edge map and a shape matching step is then implemented to assign the probability of each cloud drop, indicating to what degree the drop accords with road constraints. A parameter estimation scheme is used to narrow down the scale ambiguity of monocular visual odometry while resampling cloud drops. Evaluations on the KITTI benchmark data set and our self-collected data set have demonstrated the stability and accuracy of the proposed approach.

Energy Management for Energy Harvesting Wireless Sensors With Adaptive Retransmission

This paper analyzes the communication between two energy harvesting wireless sensor nodes. The nodes use automatic repeat request and forward error correction mechanism for the error control. The random nature of available energy and arrivals of harvested energy may induce interruption to the signal sampling and decoding operations. We propose a selective sampling scheme, where the length of the transmitted packet to be sampled depends on the available energy at the receiver. The receiver performs the decoding when complete samples of the packet are available. The selective sampling information bits are piggybacked on the automatic repeat request messages for the transmitter use. This way, the receiver node manages more efficiently its energy use. Besides, we present the partially observable Markov decision process formulation, which minimizes the long-term average pairwise error probability and optimizes the transmit power. Optimal and suboptimal power assignment strategies are introduced for retransmissions, which are adapted to the selective sampling and channel state information. With finite battery size and fixed power assignment policy, an analytical expression for the average packet drop probability is derived. Numerical simulations show the performance gain of the proposed scheme with power assignment strategy over the conventional scheme.

A robust fractional-order PID controller design based on active queue management for TCP network

ABSTRACTIn this paper, a robust fractional-order controller is designed to control the congestion in transmission control protocol (TCP) networks with time-varying parameters. Fractional controllers can increase the stability and robustness. Regardless of advantages of fractional controllers, they are still not common in congestion control in TCP networks. The network parameters are time-varying, so the robust stability is important in congestion controller design. Therefore, we focused on the robust controller design. The fractional PID controller is developed based on active queue management (AQM). D-partition technique is used. The most important property of designed controller is the robustness to the time-varying parameters of the TCP network. The vertex quasi-polynomials of the closed-loop characteristic equation are obtained, and the stability boundaries are calculated for each vertex quasi-polynomial. The intersection of all stability regions is insensitive to network parameter variations, and results in robust stability of TCP/AQM system. NS-2 simulations show that the proposed algorithm provides a stable queue length. Moreover, simulations show smaller oscillations of the queue length and less packet drop probability for FPID compared to PI and PID controllers. We can conclude from NS-2 simulations that the average packet loss probability variations are negligible when the network parameters change.

Buffer-Aided Relay Selection for Cooperative Relay Networks With Certain Information Rates and Delay Bounds

In this paper, we propose a relay selection scheme for cooperative buffer-aided relay networks with specific information rates and delay bounds. The proposed scheme differs from most of the well-known schemes in the literature that assume the source is saturated with data and/or without delay constraints. The proposed scheme is designed to encompass the delay-sensitive applications that are subject to delay limits and have certain rates. The proposed scheme exploits the channel state information, buffer state information, and delay state information to minimize the outage probability and achieve higher throughput. To achieve that, it uses these information to compromise between the selections of relays for reception and transmission. The proposed scheme is analyzed in the independent and identically distributed and independent and nonidentically distributed Rayleigh fading channels. The analysis is in terms of outage probability, packet dropping probability of the source node, packet dropping probability of the entire system, and throughput. For systems with high delay constraints, simulation results show that the proposed scheme offers lower packet dropping probability and higher throughput as compared to the renowned relay selection schemes.

Impacts of Retransmission Limit on Stability and Throughput Regions of S-ALOHA Systems

Limiting the number of retransmissions in practical random access systems such as S-ALOHA and IEEE 802.11 systems has been used, since it was often considered as a way of preventing the system from being congested, by dropping packets in retransmission or letting users know network congestion after the maximum of retransmissions. Therefore, it can be expected that the smaller the maximum of retransmissions is allowed, the smaller the backlog size gets with a higher packet dropping probability. This paper explores how such a retransmission limit alters the shape of the stability and throughput regions of S-ALOHA systems. To do this, we first consider an S-ALOHA system, where two users with infinite queue length have different packet arrival rate and retransmission probability, which is called asymmetric user. Then, we obtain those results of the systems with $N$ symmetric users.

On the Design of Dual Energy Harvesting Communication Links With Retransmission

In this paper, we consider retransmission-based point-to-point dual energy harvesting (EH) links, where both the transmitter and receiver are EH nodes (EHNs). The transmitter needs to periodically send a packet to the receiver and the packet is dropped if it is not delivered within a given number of slots. The goal is to find a retransmission index-based power management policy (RIP), which minimizes the packet drop probability (PDP). To this end, first, we establish the near-optimality of policies that operate in the energy unconstrained regime (EUR) , i.e., the regime where the average rate of energy use at each EHN is less than the average harvesting rate. Specifically, we analytically show that for such policies, the gap between the PDP of the dual EH systems with finite and infinite capacity batteries decreases exponentially with the size of the battery at the transmitter and receiver. Next, we show that, in the EUR, the non-convex problem of designing optimal RIPs can be reformulated as a geometric program , which leads to a provably convergent and computationally efficient solution. We design the RIPs for both slow and fast fading channels, and with two different retransmission protocols, namely, the automatic repeat request (ARQ) and hybrid ARQ with chase combining. Numerical results obtained through Monte Carlo simulations show that the proposed RIPs outperform the state-of-the-art policies.

Optimized secondary user selection for quality of service enhancement of Two-Tier multi-user Cognitive Radio Network: A game theoretic approach

Cognitive Radio Networks (CRN) is the solution for the spectrum scarcity problem, that has surfaced with the exponential increase in number of mobile users. In CRN, the cognitive devices sense the spectrum, and transmits, on detecting an available channel. Thus CRN resourcefully utilize the idle spectrum bands. In CRN, the users are classified into two types - Primary users and Secondary users. Secondary users are further classified into two tiers- Real Time users (RT) and Non-Real Time users (NRT). Users from both the tiers share a single channel for transmission, resulting in efficient spectrum usage. However, with ever growing number of secondary mobile users having diverse QoS requirements, the cognitive interactions among them need to be optimized. This paper uses game theory to study the conflict and cooperation among the two tiers of secondary users. An auction game model is proposed that analyzes the complex decision making process and efficiently allocates an idle channel to a pair of RT and NRT secondary users from a pool of users. The game model is further extensively analyzed mathematically, using Markov chain, showing a reduction in user Blocking probability, user Dropping probability, Channel Saturation probability and increase in user Acceptance probability, compared to the Basic One-Tier CRN and Non-Optimized Two-Tier CRN. The optimized network model is then simulated using Qualnet 7.1. The simulation result shows improved Bandwidth Utilization Efficiency, Spectral efficiency and increased number of secondary users served, compared with respect to Basic One-Tier CRN and Non-Optimized Two-Tier CRN.

An Integrated Bandwidth Adaptation Scheme for Multimedia Wireless Networks and its Connection-Level Performance Analysis

This paper presents an integrated bandwidth adaptation scheme for multimedia wireless networks using application utility functions. With the proposed scheme, each call in the network is assigned a utility function according to itsadaptive characteristics. Depending on the network load theallocated bandwidth of ongoing calls are upgraded or degraded dynamically so that the achieved utility of the network is maximized. Appropriate call admission control and bandwidth reservation policies are also incorporated into the scheme to provide QoS guarantees to the new and handoff calls, respectively. Extensive simulation experiments have been conducted to evaluate the connection-level performance of the proposed scheme. Results show that our bandwidth adaptation scheme is effective in both increasing the utility and bandwidthutilization of wireless networks while keeping the call blocking and handoff dropping probabilities substantially low.

Energy Harvesting Wireless Sensor Node With Temporal Death: Novel Models and Analyses

Energy harvesting wireless sensor net-work (EH-WSN) is promising in applications, however the frequent occurrence of temporal death of nodes, due to the limited harvesting capability, presents a difficulty in meeting the quality-of-service requirements of the network. For a node with temporal death in an EH-WSN, this paper presents a new model, which consists of, a Markov model to trace the energy harvesting process, a queuing analytical model to model the working mechanism of the sensor node and a continuous fluid process to capture the evolution of the residual energy in the EH-WSN node. Using the Markov fluid queue (MFQ) theory, we discuss various performance aspects of the EH-WSN node with temporal death, including the temporal death occurrence probability, the probability density of the residual energy, the stationary energy consumption, the queue length distribution in the data buffer, the packet blocking probability, and so on. In order to obtain the dropping probability of a given packet, based on the structure of the MFQ, we develop an auxiliary MFQ and derive the formulations of two types of the packet dropping probabilities, i.e., the packet dropping probability due to energy depletion and that due to channel error. Numerical examples are provided to illustrate the theoretical findings, and new insights into understanding the impacts of the parameters on the performance metrics are presented.

Novel elastic protection against DDF failures in an enhanced software-defined SIEPON

Abstract Ever-increasing bandwidth demands on passive optical networks (PONs) are pushing the utilization of every fiber strand to its limit. This is mandating comprehensive protection until the end of the distribution drop fiber (DDF). Hence, it is important to provide refined protection with an advanced fault-protection architecture and recovery mechanism that is able to cope with various DDF failures. We propose a novel elastic protection against DDF failures that incorporates a software-defined networking (SDN) capability and a bus protection line to enhance the resiliency of the existing Service Interoperability in Ethernet Passive Optical Networks (SIEPON) system. We propose the addition of an integrated SDN controller and flow tables to the optical line terminal and optical network units (ONUs) in order to deliver various DDF protection scenarios. The proposed architecture enables flexible assignment of backup ONU(s) in pre/post-fault conditions depending on the PON traffic load. A transient backup ONU and multiple backup ONUs can be deployed in the pre-fault and post-fault scenarios, respectively. Our extensively discussed simulation results show that our proposed architecture provides better overall throughput and drop probability compared to the architecture with a fixed DDF protection mechanism. It does so while still maintaining overall QoS performance in terms of packet delay, mean jitter, packet loss, and throughput under various fault conditions.

ON/OFF Traffic Shaping in the Internet: Motivation, Challenges, and Solutions

Tremendous traffic on the Internet exhibits ON/OFF patterns. In the past, the generation of such ON/OFF traffic was mainly attributed to TCP and application characteristics. Nowadays, however, much traffic is often intentionally shaped into an ON/OFF pattern for achieving certain optimized system performance or resulting from characteristics of some new applications. In this article, we present a comprehensive survey on the ON/OFF traffic shaping in the current Internet. We first introduce the motivations behind ON/OFF traffic shaping in different fields based on different system optimization objectives and application characteristics. We then introduce the impacts of ON/OFF traffic on packet drop probability, real-time applications, and also its interaction with TCP's congestion control mechanism. We further present a survey on existing mechanisms for mitigating these impacts in various aspects. We introduce how each of these mechanisms works, and discuss their merits and deficiencies. Finally, we conclude this article with some future directions for ON/OFF traffic shaping in the Internet.

A QoS-Oriented High-Efficiency Resource Allocation Scheme in Wireless Multimedia Sensor Networks

Deadline constrained packet scheduling and transmission are important in real-time multimedia applications. This is because packets missing their deadlines would become useless and are frequently dropped, which seriously degrade the quality of service (QoS). As the utilization of Internet of Things has become mature, multimedia data transmission is a key component to promote the QoS of citizens. To fulfill the QoS requirement in wireless sensor networks (WSNs) with multimedia content, the combination of multiple transmission methods is encouraged for packet forwarding, including conventional network coding, analog network coding, plain routing, and direct transmission (i.e., no-relaying, NR). The diversity of transmission method is helpful to lower packet dropping probability, while complicating the packet transmitting and scheduling process instead. Therefore, we first introduce an exhaustive search method to obtain the optimal scheduling sequence and corresponding transmission method for deadline constrained multimedia transmissions in WSNs. With the objective of promoting computing efficiency for the formulated problem, we then propose two heuristic methods based on the Markov chain approximation and the dynamic graph, respectively. Simulation results illustrate that our methods can effectively reduce packet dropping probability and simulation time, so that QoS of individuals can be promoted.

Application of Wavelets to Detect Trend Reversals on Brazilian Stock Market

This study develops a method to detect trend reversals followed by significant drops in Brazilian Stock Market using wavelets. Applying the concept of the log-periodic power-law, whose oscillations present reduction in amplitude and period as the critical moment approaches (where there is a higher probability of market drop), it used the Continuous Wavelet Transform to detect the increasing oscillation frequency in the stock price, time series and generate sell signals. An algorithm was developed to test different kinds of wavelets and parameters to calculate the Wavelet Index, evaluating whose combination of parameters brings the best results and comparing these results with the existing Technical Analysis tools. The results show that the proposed method to calculate the Wavelet Index detects successfully the significant drops (over 10%) in the Brazilian Stock Market. Considering drops over 15%, there were losses due to early sales of 45% (average) in the search set and 43.9% in the test set, without false negatives, using mainly the Meyer wavelet. Its performance was also better than existing Technical Analysis tools, like MACD and RSI.

Coordination of SON Functions in Multi-Vendor Femtocell Networks

With the increase of network complexity, there is a high need for network management automation. This is achieved through SON principles that enable self-configuration, self-optimization, and self-healing. However, even though SON functions are meant to be autonomous, a high level of coordination among them is required. To this end, efficient conflict detection and resolution techniques are needed, especially in multi-vendor deployments. This article presents a design together with a sample implementation of a coordination scheme between three key SON functions in femtocell networks: cell ID assignment, coverage adjustment, and idle mode control. This ensures stability and continuity of the network operation even in a situation when the functions have contradicting objectives. The solution is based on the Broadband Forum TR-069 protocol and is applicable to multi-vendor networks. Simulation evaluation has shown that SON coordination reduces mean cell ID conflicts by over 30 percent and, resulting from that, call drop probability by over 40 percent.

Packet Drop Probability Analysis of Dual Energy Harvesting Links With Retransmission

In this paper, we consider point-to-point dual energy harvesting (EH) links, where both transmitter and receiver are EH nodes (EHNs), with a retransmission protocol: either an automatic repeat request (ARQ) or hybrid ARQ with chase combining. We develop a framework to analyze the impact of various physical layer parameters, e.g., the energy harvesting profiles, size of energy buffer, and power management policies , at both the transmitter and receiver, and the channel statistics and coherence time , on the packet drop probability (PDP) of dual EH links over block fading channels. We derive the closed-form expressions for the PDP of a retransmission index-based power management policy. The presented framework naturally extends to obtain the PDP of mono EH links, i.e., links where only one of the two nodes harvests energy. To obtain further insights, we analyze the PDP of links with zero and infinite energy buffer size, and characterize the energy unconstrained regime , where the PDP is governed only by the average harvesting rate. Through extensive Monte Carlo simulations, we demonstrate the accuracy of the theoretical expressions, compare performance against existing power management schemes, and illustrate the performance tradeoffs involved.

Energy efficient medium access scheme for visible light communication system based on IEEE 802.15.7 with unsaturated traffic

Visible light communication (VLC) networks can provide high-rate transmissions with advantages such as high security, low power consumption and so on. Multiple users get access to the VLC network according to the carrier sense multiple access with collision avoidance (CSMA/CA) mechanism defined by IEEE 802.15.7 media access control layer specifications. In this study, the authors propose an energy efficient medium access scheme to improve the performance of IEEE 802.15.7 CSMA/CA mechanism under unsaturated traffic conditions. Aiming at reducing the power consumed on unnecessary waiting and at improving the channel utilisation efficiency, they first apply a successive transmission scheme on the node, which has completed one successful transmission and gets the chance of transmitting the next packet without backoff delay period according to the network condition. Then, a dynamic contention window is exploited to mitigate the collisions, where they derive the optimal minimum contention window based on throughput analysis. The power consumption can be reduced with improved throughput, when both the traffic load and the number of nodes in the network are taken into account. Simulation results demonstrate that the authors’ proposed scheme outperforms the IEEE 802.15.7 CSMA/CA scheme with respect to the average power consumption, system throughput and packet dropping probability.