Reduce Network Delay Research Articles

An adaptive path selection model for WSN multipath routing inspired by metabolism behaviors

In multipath routing of wireless sensor network (WSN), greedy path selection is always prone to cause path oscillation (frequent path changes) between each couple of sensor and sink nodes. To alleviate the side effect, we propose an adaptive path selection model (called a WSN path selection model based on the adaptive response by attractor selection (ARAS) model (WARAS)) inspired by metabolism behaviors of Escherichia Coli . The model consists of two main features. The first one is a new formula for a parameter called path-activity used to indicate adaptation goodness of multipath traffic transmission in dynamic network environments, which is inversely proportional to absolute value of difference between current path quality and best path quality. The second one is a novel attractor expression for attractors of multi-attractor equations to concretely specify stochastic effect of noise items in the equations on the path selection. Then, in an experimental WSN scenario composed of many source nodes and their shared neighbor nodes, we validate a dynamic-adaptive selection characteristic of the WARAS on distributing loads of the neighbor nodes. Subsequently, we design a path quality probe scheme in a multipath ad hoc on-demand distance vector routing (AODV) protocol. Compared with the greedy path selection through the path quality probe scheme, simulation results show the WARAS can perform better on reducing network delay and the path oscillation.

Preserving privacy and efficiency in data communication and aggregation for AMI network

Due to the evolution of smart grid technologies, the number of smart meters deployed in a consumer area is rapidly increasing. As a consequence, network traffic issues in advanced metering infrastructure (AMI) have been raised. In smart gird, satisfying latency requirement and privacy-preserving are important issues. Intuitively, latency requirement can be met by reducing network delay and processing time. However, preserving privacy and security of user data has negative effects on both the network delay and the processing time due to the increased message size and cryptographic overhead. To overcome these problems, various types of message aggregation schemes with cryptographic algorithms have been proposed, but they have limitation in processing time and applicability to diverse scenarios. In this paper, we propose a data communication scheme for AMI network that can reduce the network traffic and the processing time while preserving each user׳s privacy. With the proposed scheme, the cryptographic overhead incurred during message aggregation can be significantly reduced compared to other existing schemes. We model the network characteristic, analyze the complexity of the proposed scheme, and simulate the proposed scheme under diverse topologies and application scenarios. Through the results, we show that the proposed scheme has lower computational overhead than other schemes, and it can be applied to various smart grid applications.

Efficient subspace skyline query based on user preference using MapReduce

Subspace skyline, as an important variant of skyline, has been widely applied for multiple-criteria decisions, business planning. With the development of mobile internet, subspace skyline query in mobile distributed environments has recently attracted considerable attention. However, efficiently obtaining the meaningful subset of skyline points in any subspace remains a challenging task in the current mobile internet. For more and more mobile applications, subspace skyline query on mobile units is usually limited by big data and wireless bandwidth. To address this issue, in this paper, we propose a system model that can support subspace skyline query in mobile distributed environment. An efficient algorithm for processing the Subspace Skyline Query using MapReduce (SSQ) is also presented which can obtain the meaningful subset of points from the full set of skyline points in any subspace. The SSQ algorithm divides a subspace skyline query into two processing phases: the preprocess phase and the query phase. The preprocess phase includes the pruning process and constructing index process which is designed to reduce network delay and response time. Additionally, the query phase provides two filtering methods, SQM-filtering and ε-filtering, to filter the skyline points according to user preference and reduce network cost. Extensive experiments on real and synthetic data are conducted and the experimental results indicate that our algorithm is much efficient, meanwhile, the pruning strategy can further improve the efficiency of the algorithm.

SACRP: A Spectrum Aggregation-Based Cooperative Routing Protocol for Cognitive Radio Ad-Hoc Networks

Cooperative routing and spectrum aggregation are two promising techniques for Cognitive Radio Ad-Hoc Networks (CRAHNs). In this paper, we propose a spectrum aggregation-based cooperative routing protocol, termed as SACRP, for CRAHNs. To the best of our knowledge, this is the first contribution on spectrum aggregation-based cooperative routing for CRAHNs. The primary objective of SACRP is to provide higher energy efficiency, improve throughput, and reduce network delay for CRAHNs. In this regard, we design the MAC and Physical (PHY) layer, and proposed different spectrum aggregation algorithms for cognitive radio (CR) users. We propose two different classes of routing protocols; Class A for achieving higher energy efficiency and throughput, and Class B for reducing end-to-end latency. Based on stochastic geometry approach, we build a comprehensive analytical model for the proposed protocol. Besides, the proposed protocol is compared with the state of the art cooperative and non-cooperative routing algorithms with spectrum aggregation. Performance evaluation demonstrates the effectiveness of SACRP in terms of energy efficiency, throughput, and end-to-end delay.

TDOCP: A two-dimensional optimization integrating channel assignment and power control for large-scale WLANs with dense users

In order to improve the throughput of high-density and large-scale wireless local area networks (WLANs), a novel heuristic algorithm Two-DimensionalOptimization IntegratingChannel Assignment andPower Control (TDOCP) is proposed. Based on the traffic characteristic analyzed from real network, we take both uplink and downlink traffic into account in network modeling. The analysis of network utility shows that it has a controllable upper bound. So this paper develops a scheme to maximize the upper bound of network utility, and then make network utility converge to the enhanced upper bound. Both channel assignment (CA) and power control (PC) are performed in each iteration. To illustrate the advantages of TDOCP, a compared algorithm One-DimensionalOptimization IntegratingChannel Assignment andPower Control (ODOCP) is designed, which implements the least congested channel search (LCCS) in CA, and the power control for AP performance (PCAP) in PC. Only one-dimensional optimization is implemented in each iteration of ODOCP. Extensive simulations show that the network model in this paper is effective, and TDOCP outperforms current popular one-dimensional optimization algorithms LCCS, PCAP, and the compared ODOCP in the aspect of increasing throughput and reducing network delay.

On the Performance of Lossy Compression Schemes for Energy Constrained Sensor Networking

Lossy temporal compression is key for energy-constrained wireless sensor networks (WSNs), where the imperfect reconstruction of the signal is often acceptable at the data collector, subject to some maximum error tolerance. In this article, we evaluate a number of selected lossy compression methods from the literature and extensively analyze their performance in terms of compression efficiency, computational complexity, and energy consumption. Specifically, we first carry out a performance evaluation of existing and new compression schemes, considering linear, autoregressive, FFT-/DCT- and wavelet-based models , by looking at their performance as a function of relevant signal statistics. Second, we obtain formulas through numerical fittings to gauge their overall energy consumption and signal representation accuracy. Third, we evaluate the benefits that lossy compression methods bring about in interference-limited multihop networks, where the channel access is a source of inefficiency due to collisions and transmission scheduling. Our results reveal that the DCT-based schemes are the best option in terms of compression efficiency but are inefficient in terms of energy consumption. Instead, linear methods lead to substantial savings in terms of energy expenditure by, at the same time, leading to satisfactory compression ratios, reduced network delay, and increased reliability performance.

Delay reduction via Lagrange multipliers in stochastic network optimization

In this paper, we consider the problem of reducing network delay in stochastic network utility optimization problems. We start by studying the recently proposed quadratic Lyapunov function based algorithms (QLA, also known as the MaxWeight algorithm). We show that for every stochastic problem, there is a corresponding deterministic problem, whose dual optimal solution “exponentially attracts” the network backlog process under QLA. In particular, the probability that the backlog vector under QLA deviates from the attractor is exponentially decreasing in their Euclidean distance. This is the first such result for the class of algorithms built upon quadratic Lyapunov functions. The result quantifies the “network gravity” role of Lagrange Multipliers in network scheduling. It not only helps to explain how QLA achieves the desired performance but also suggests that one can roughly “subtract out” a Lagrange multiplier from the system induced by QLA.

Optimization of multiple gateway deployment for underwater acoustic sensor networks

This research aims to develop novel technologies to efficiently integrate wireless communication networks and Underwater Acoustic Sensor Networks (UASNs). Surface gateway deployment is one of the key techniques for connecting two networks with different channels. In this work, we propose an optimization method based on the genetic algorithm for surface gateway deployment, design a novel transmission mechanism-simultaneous transmission, and realize two efficient routing algorithms that achieve minimal delay and payload balance among sensor nodes. We further develop an analytic model to study the delay, energy consumption and packet loss ratio of the network. Our simulation results verify the effectiveness of the model, and demonstrate that the technique of multiple gateway deployment and the mechanism of simultaneous transmission can effectively reduce network delay, energy consumption and packet loss rate.

Backoff algorithm of MAC protocol in Ad Hoc networks based on logarithmic function

Based on logarithmic function, a new backoff algorithm was presented by introducing the parameter which could change with the network state, in allusion to the deficiencies of Binary Exponential Backoff algorithm of IEEE 802.11 MAC. This algorithm dynamically changed the initial value of collision window and the increasing extent of backoff by using the logarithmic function which took the numbers of network nodes as variable and reduced the probability of collision of data transmission, and the network simulations were carried out by the OPNET software. The results of simulation show that the backoff algorithm based on logarithmic function is obviously effective in improving the capability of throughput and fairness of Ad Hoc network, reducing network delay and the ratio of packet loss, and the capability of new backoff algorithm is better than that of Binary Exponential Backoff algorithm.

Providing QoS for Networked Peers in Distributed Haptic Virtual Environments

Haptic information originates from a different human sense (touch), therefore the quality of service (QoS) required to support haptic traffic is significantly different from that used to support conventional real‐time traffic such as voice or video. Each type of network impairment has different (and severe) impacts on the user′s haptic experience. There has been no specific provision of QoS parameters for haptic interaction. Previous research into distributed haptic virtual environments (DHVEs) have concentrated on synchronization of positions (haptic device or virtual objects), and are based on client‐server architectures. We present a new peer‐to‐peer DHVE architecture that further extends this to enable force interactions between two users whereby force data are sent to the remote peer in addition to positional information. The work presented involves both simulation and practical experimentation where multimodal data is transmitted over a QoS‐enabled IP network. Both forms of experiment produce consistent results which show that the use of specific QoS classes for haptic traffic will reduce network delay and jitter, leading to improvements in users′ haptic experiences with these types of applications.

Haptic Media Synchronization for Remote Surgery through Simulation

Network delay affects the operational instability of haptic displays for telehaptic remote surgery applications using simulation. A synchronization control mechanism for haptic media reduces network delay's effects and enhances telehaptic capability in these applications

Replica placement in ring based content delivery networks

The recent introduction of Content Distribution Networks (CDNs) enhances the delivery of high quality multimedia content to end users. In a CDN architecture, the content is replicated to so-called surrogate servers, generally at the edge of the transport network, to improve the quality of service (QoS) of streaming multimedia delivery services. By using peer-to-peer (P2P) technologies, these edge servers can co-operate and provide a more scalable and robust service in a self-organizing CDN. In this paper, we propose a set of distributed replica placement algorithms (RPAs), based on an Integer Linear Programming (ILP) formulation of the centralized content placement problem. These algorithms further enhance the CDN performance by optimizing the network and server load, reducing network delays and avoiding congestion. Although the proposed algorithms are designed for and tested on different network topologies, we focus on robust ring based CDNs in this study. Content placement on such a network topology can be calculated analytically and can be used for comparison.

Enabling Collaborative Medical Diagnosis Over the Internet via Peer-to-Peer Distribution of Electronic Health Records

Recent developments in networking and computing technologies and the expansion of the electronic health record system have enabled the possibility of online collaboration between geographically distributed medical personnel. In this context, the paper presents a Web-based application, which implements a collaborative working environment for physicians by enabling the peer-to-peer exchange of electronic health records. The paper treats technological issues such as Video, Audio and Message Communication, Workspace Management, Distributed Medical Data Management and exchange, while it emphasizes on the Security issues arisen, due to the sensitive and private nature of the medical information. In the paper, we present initial results from the system in practice and measurements regarding transmission times and bandwidth requirements. A wavelet based image compression scheme is also introduced for reducing network delays. A number of physicians were asked to use the platform for testing purposes and for measuring user acceptance. The system was considered by them to be very useful, as they found that the platform simulated very well the personal contact between them and their colleagues during medical meetings.

A tentative commit protocol for composite web services

Composite web services provide promising prospects for conducting cross-organizational business transactions. Such transactions: are generally complex, require longer processing time, and manipulate financially critical data. It is therefore crucial to ensure stronger reliability, higher throughput and enhanced performance of transactions. In order to meet these requirements, this paper proposes a new commit protocol for managing transactions in composite web services. Specifically, it aims to improve the performance by reducing network delays and the processing time of transactions. The proposed protocol is based on the concept of tentative commit that allows transactions to tentatively commit on the shared data of web services. The tentative commit protocol avoids resource blocking thus improving performance. The proposed protocol is tested through various simulation experiments. The outcomes of these experiments show that the proposed protocol outperforms existing protocols in terms of transaction performance.

SCOOT and Incidents: Performance Evaluation in Simulated Environment

SCOOT is a widely used adaptive signal control system. There have been many evaluations of SCOOT during normal traffic conditions. It is hypothesized that SCOOT's ability to adapt to varying traffic during incidents provides an added benefit over its normal congestion-relieving capability. Through an interface between CORSIM and an actual SCOOT system, this study evaluates, in a simulated environment, SCOOT's performance during incidents to quantify these additional benefits. The evaluation is made over a range of volumes and incident durations. A theoretical test network and two real-world networks are simulated. Network and intersection delay, travel time, and queue length are used as measures of effectiveness (MOEs) throughout the comparison to quantify total and marginal benefits. During a 45-min incident within the Salt Lake City downtown area network, SCOOT reduced network delay, travel time, intersection delay, and queue length by 28.3%, 22.8%, 30.7 %, and 24.2 %, respectively, relative to the optimized plan-based control. Similar results were observed on the other real-world network. Although adaptive control has benefits above plan-based signal control, the findings indicate that during incidents, SCOOT provides an additional increase in benefits. The findings indicate that average SCOOT MOEs improve by 7% for a 15-min incident, by 12% for a 30-min incident, and by 18% for a 45-min incident depending on congestion level. The additional benefits that SCOOT adaptive control provides during incidents are quantified through the system's inherent ability to respond to traffic conditions in real time.

Optimal Distributed Routing for Virtual Line-Switched Data Networks

An algorithm that provides minimum delay routing in a data communication network using virtual line-switching is presented. The algorithm uses distributed computation in the sense that the nodes of the network update their information in an orderly fashion based on messages received from their neighbors. Receipt of these messages also triggers the various steps of the update and rerouting, so that these operations are performed in appropriate sequencing. For stationary input requirements and fixed topology the algorithm reduces network delay at each step and provides loop-free routing in the network. The method also provides an algorithm for quasi-static routing, when the input flows are slowly changing.