Data Delivery Scheme Research Articles

Encoding Scheme to Reduce Energy Consumption of Delivering Data in Radio Frequency Powered Battery-Free Wireless Sensor Networks

Wireless sensor networks (WSNs) have been widely deployed in intelligent transportation systems. Battery-free WSN (BF-WSN) scavenges energy from the environment. In the BF-WSN, whose nodes harvest radio frequency (RF) energy, delivering data with low energy consumption is important for the BF-WSN nodes to have a longer runtime. Some existing baseband encoding or carrier-modulation schemes exhibit the energy consumption disparity (ECD) between transmitting bit 0 and bit 1. An example is FM0 (bi-phase space) baseband encoding, which is widely applied in the backscattering communications in radio frequency identification systems and wireless identification sensing platform. With FM0, transmitting bit 0 consumes much greater energy than bit 1. To achieve energy-saving in delivering data with the ECD, we, in this paper, formulate the optimization problem (OP) that maximizes percentage of energy saving. The solution of the OP leads to the optimal energy-efficient codebook. Based on the derived codebook, we present the energy-efficient data delivery scheme (EEDDS), with which the sender transmits the codewords in the codebook and the receiver recovers the corresponding original data blocks using the codebook. Simulation results show that the proposed EEDDS outperforms the traditional data delivery scheme in terms of energy consumption in the case when the applied baseband encoding or carrier-modulation schemes occupy the ECD.

Reliability-Aware Cooperative Node Sleeping and Clustering in Duty-Cycled Sensors Networks.

Duty-cycled sensor networks provide a new perspective for improvement of energy efficiency and reliability assurance of multi-hop cooperative sensor networks. In this paper, we consider the energy-efficient cooperative node sleeping and clustering problems in cooperative sensor networks where clusters of relay nodes jointly transmit sensory data to the next hop. Our key idea for guaranteeing reliability is to exploit the on-demand number of cooperative nodes, facilitating the prediction of personalized end-to-end (ETE) reliability. Namely, a novel reliability-aware cooperative routing (RCR) scheme is proposed to select k-cooperative nodes at every hop (RCR-selection). After selecting k cooperative nodes at every hop, all of the non-cooperative nodes will go into sleep status. In order to solve the cooperative node clustering problem, we propose the RCR-based optimal relay assignment and cooperative data delivery (RCR-delivery) scheme to provide a low-communication-overhead data transmission and an optimal duty cycle for a given number of cooperative nodes when the network is dynamic, which enables part of cooperative nodes to switch into idle status for further energy saving. Through the extensive OPNET-based simulations, we show that the proposed scheme significantly outperforms the existing geographic routing schemes and beaconless geographic routings in wireless sensor networks with a highly dynamic wireless channel and controls energy consumption, while ETE reliability is effectively guaranteed.

Data delivery in wireless sensor networks with uncontrollable mobile nodes

Wireless sensor networks (WSNs) consist of low-powered devices that have computation, wireless communication and environment-sensing capabilities. These low-cost sensors are usually deployed in a dense and stationary manner for the periodic sensing of environmental phenomena. WSNs open the door for many monitoring applications in the military, in healthcare, and in environmental and urban studies. Mobile wireless sensor networks (MWSNs) are a subclass of WSNs in which some or all the sensors are mobile. Many environmental applications are designed and deployed on top of MWSNs in which the sensors' hosts are uncontrolled by end users (e.g., the OpenSense project for air pollution monitoring in the city of Zurich). MWSNs poses many challenges for newly designed applications. In this paper, we evaluate MWSNs with a location-based application. We test various data delivery schemes used by sensors in MWSNs, including GPRS, Wi-Fi, and Hybrid (both GPRS and Wi-Fi). We perform extensive simulation-based experiments using the ns2 simulator.

A Fuzzy‐Rule Based Data Delivery Scheme in VANETs with Intelligent Speed Prediction and Relay Selection

Data delivery in vehicular networks (VANETs) is a challenging task due to the high mobility and constant topological changes. In common routing protocols, multihop V2V communications suffer from higher network delay and lower packet delivery ratio (PDR), and excessive dependence on GPS may pose threat on individual privacy. In this paper, we propose a novel data delivery scheme for vehicular networks in urban environments, which can improve the routing performance without relying on GPS. A fuzzy‐rule‐based wireless transmission approach is designed to optimize the relay selection considering multiple factors comprehensively, including vehicle speed, driving direction, hop count, and connection time. Wireless V2V transmission and wired transmissions among RSUs are both utilized, since wired transmissions can reduce the delay and improve the reliability. Each RSU is equipped with a machine learning system (MLS) to make the selected relay link more reliably without GPS through predicting vehicle speed at next moment. Experiments show the validity and rationality of the proposed method.

Analyzing how we do Analysis and Consume Data, Results from the SciDAC-Data Project

One of the main goals of the Dept. of Energy funded SciDAC-Data project is to analyze the more than 410,000 high energy physics datasets that have been collected, generated and defined over the past two decades by experiments using the Fermilab storage facilities. These datasets have been used as the input to over 5.6 million recorded analysis projects, for which detailed analytics have been gathered. The analytics and meta information for these datasets and analysis projects are being combined with knowledge of their part of the HEP analysis chains for major experiments to understand how modern computing and data delivery is being used.We present the first results of this project, which examine in detail how the CDF, D0, NOvA, MINERvA and MicroBooNE experiments have organized, classified and consumed petascale datasets to produce their physics results. The results include analysis of the correlations in dataset/file overlap, data usage patterns, data popularity, dataset dependency and temporary dataset consumption. The results provide critical insight into how workflows and data delivery schemes can be combined with different caching strategies to more efficiently perform the work required to mine these large HEP data volumes and to understand the physics analysis requirements for the next generation of HEP computing facilities.In particular we present a detailed analysis of the NOvA data organization and consumption model corresponding to their first and second oscillation results (2014-2016) and the first look at the analysis of the Tevatron Run II experiments. We present statistical distributions for the characterization of these data and data driven models describing their consumption.

Multi-Method Data Delivery for Green Sensor-Cloud

Delivering sensory data to users anytime and anywhere if there is network connection, sensor-cloud (SC), which integrates WSNs and cloud computing, is attracting growing interest from both academia and industry. This article discusses the potential applications and recent work about SC and observes two issues regarding green SC. Further, motivated by solving these two issues, this article proposes a Multi-Method Data Delivery (MMDD) scheme for SC users. MMDD strategically incorporates four kinds of delivery: delivery from cloud to SC users; delivery from WSN to SC users; delivery from SC users to SC users; and delivery from cloudlet to SC users. Compared to exclusive data delivery from cloud to SC users, evaluation results show that MMDD could achieve lower delivery cost or less delivery time for SC users.

Data Delivery in Wireless Sensor Networks with Uncontrollable Mobile Nodes

Wireless sensor networks (WSNs) consist of low-powered devices that have computation, wireless communication and environment-sensing capabilities. These low-cost sensors are usually deployed in a dense and stationary manner for the periodic sensing of environmental phenomena. WSNs open the door for many monitoring applications in the military, in healthcare, and in environmental and urban studies. Mobile wireless sensor networks (MWSNs) are a subclass of WSNs in which some or all the sensors are mobile. Many environmental applications are designed and deployed on top of MWSNs in which the sensors' hosts are uncontrolled by end users (e.g., the OpenSense project for air pollution monitoring in the city of Zurich). MWSNs poses many challenges for newly designed applications. In this paper, we evaluate MWSNs with a location-based application. We test various data delivery schemes used by sensors in MWSNs, including GPRS, Wi-Fi, and Hybrid (both GPRS and Wi-Fi). We perform extensive simulation-based experiments using the ns2 simulator.

Reliable data delivery scheme for real-spatial information based group communication

Reliable data delivery scheme for real-spatial information based group communication

TPLE: A Reliable Data Delivery Scheme for On-Road WSN Traffic Monitoring.

In an on-road environment, motor-engines severely disturb the wireless link of a sensor node, leading to high package loss rate, high delivery delay, and poor radio communication quality. The existing data delivery mechanisms, such as the ACK-based retransmission mechanism and window-based link quality estimation mechanism, could not handle these challenges well. To solve this challenge, we propose a Target-Prediction-based Link quality Estimation scheme (TPLE) to realize high quality data delivery in an on-road environment. To perform on-road link quality estimation, TPLE dynamically calculates the track of a nearby vehicle target and estimates target impact on wireless link. Based on the local estimation of link quality, TPLE schedules radio communication tasks effectively. Simulations indicate that our proposed TPLE scheme produces a 94% data delivery rate, its average retransmission number is around 0.8. Our conducted on-road data delivery experiments also indicated a similar result as the computer simulation.

Two-way traffic link delay modeling in vehicular networks

This paper proposes a modeling of expected link delay (i.e., data delivery delay) on a two-way road segment for carry-and-forward data delivery schemes in vehicular networks. Recently, a lot of vehicles can communicate with each other by dedicated short-range communications (DSRC) for vehicular networking. In the near future, more vehicles will be equipped with DSRC devices because of governmental policies for driving safety. In this paper, we derive a link delay model on a two-way road segment. This link delay model is essential to support multihop infrastructure-to-vehicle or vehicle-to-vehicle data delivery in vehicular networks as disruption tolerant networks. Through simulation, it is shown that our two-way link delay model is more accurate than the legacy two-way link delay model. Furthermore, by applying our model to data unicasting, we show that our model is precise enough to support the efficient data unicasting on vehicular networks.

A Privileged Event Data Delivery Scheme in Wireless Sensor Network

A Privileged Event Data Delivery Scheme in Wireless Sensor Network

An Integrated Adapted Key Management and Quality Data Delivery over Wireless Network

ireless network broadcast the information with active node variance. Data delivery over wireless network is one of the key issues to be addressed. Many efficient data delivery methods are widely used in different network environments as they reduce the overhead traffic and delay. Hence they improve the network lifetime. However, they lack effective data delivery on different network environment and security. In this paper, to perform effective data delivery on different network environments, Routing Function Independent Data Delivery (RFIDD) scheme is introduced. The RFIDD scheme develops Observant Reasoning algorithms to identify concession nodes (i.e.,) packet dropping nodes. The Observant Reasoning (OR) algorithm provides suitable solution to ensure data delivery with average running formula in wireless network. OR-algorithm finds an optimal result in the sense that it recognizes every packet dropping nodes without introducing false negative rate. RFIDD Scheme also combines the Adapted Key Management Routing (AKMR) protocol to improve the security level while performing data delivery on wireless network. AKMR performs the encryption, authentication and decryption processes to attain higher security ratio in RFIDD Scheme. The integration of data delivery scheme with security measure is performed with three orders of magnitude which dynamically adjusts security level depending on the network state. In this paper, RFIDD scheme is analyzed to assess the data delivery ratio and packet dropping probability rate and compared to the state-of- the-art methods. RFIDD was also implemented NS2 and compared against Distributed Cache Invalidation Method and Redundancy Management of Multipath Routing to assess its performance experimentally. The security and average response time are reported versus several variables, where RFIDD showed to be superior when compared to the other methods. KeywordsIndependent, Data Delivery, Observant Reasoning,

Optimizations for High Performance Network Virtualization

The increasing requirements of intensive interoperaterbility among the distributed nodes desiderate the high performance network connections, owing to the substantial growth of cloud computing and datacenters. Network I/O virtualization aggregates the network resource and separates it into manageable parts for particular servers or devices, which provides effective consolidation and elastic management with high agility, flexibility and scalability as well as reduced cost and cabling. However, both network I/O virtualization aggregation and the increasing network speed incur higher traffic density, which generates a heavy system stress for I/O data moving and I/O event processing. Consequently, many researchers have dedicated to enhancing the system performance and alleviating the system overhead for high performance networking virtualization. This paper first elaborates the mainstreaming I/O virtualization methodologies, including device emulation, split-driver model and hardware assisted model. Then, the paper discusses and compares their specific advantages in addition to performance bottlenecks in practical utilities. This paper mainly focuses on the comprehensive survey of stateof-the-art approaches for performance optimizations and improvements as well as the portability management for network I/O virtualization. The approaches include various novel data delivery schemes, overhead mitigations for interrupt processing and adequate resource allocations for dynamic network states. Finally, we highlight the diversity of I/O virtualization besides the performance improvements in network virtualization infrastructure.

An Event Data Delivery Scheme in GTS-based Wireless Sensor Network

This paper presents an event data delivery scheme for wireless sensor networks that use a GTS-based channel allocation scheme. Many sensor nodes can share a GTS channel for sending their normal data to the sink node. When there is an event at a node, the node makes a temporal route to the sink node and the nodes of the route can use the GTS channel in a privileged access. This scheme controls the backoff number effectively so the data delivery priority is given to the nodes of that route. Simulation results show that the event data delivery of the proposed scheme outperforms at the end-to-end transfer delay and jitter characteristics. The proposed scheme can effectively gather the event data using the guaranteed GTS channel of the route in proposed scheme.

On-Road Caching Assistance for Ubiquitous Vehicle-Based Information Services

Smart vehicles are considered major providers of ubiquitous information services. In this paper, we propose a solution for expedited and cost-effective access to vehicular public sensing services. The proposed caching-assisted data delivery (CADD) scheme applies caching on the delivery path of the collected data. Cached information can be used for later interests without having to request similar data from vehicles. For the operation of CADD, we introduce a lightweight road caching spot (RCS) to work as an on-road caching and forwarding assistant. CADD utilizes these caching spots along with vehicles on roads for handling the data collection and delivery processes. The proposed scheme involves a novel caching mechanism that utilizes real-time information for selecting the caching RCSs while considering popularity in cache replacement. A data chunk to be replaced may be forwarded to another less-loaded RCS. CADD considers vehicles' headings to direct communication toward the destination. Mathematical analysis and a simulation-based evaluation of the scheme are conducted. The evaluation results show significant improvements achieved by CADD in terms of access cost, delivery delay, and packet delivery ratio, compared with other schemes that do not involve caching assistance and do not take vehicles' headings into consideration.

A reliable data delivery scheme with delay constraints for wireless sensor networks

Delay-sensitive applications require the capability to send data while meeting performance requirements. However, due to strict constrains on the resources available to the sensor nodes, wireless sensor networks (WSNs) pose critical challenges in network protocol design considering delay constraints. Biologically inspired modeling techniques have received considerable attention for achieving robust global behavior, while retaining individual simplicity. In this paper, we propose an epidemic-inspired node scheduling scheme (ENS) with aims of delay reduction and energy saving. The ENS controls the state of a sensor node depending on the delay requirements of a specific application. Simulation results indicate that the ENS achieves reliable data delivery while saving energy consumption.

VPOD: Virtual Parking Overlay Network based Data Delivery in Urban VANETs

Vehicular ad hoc networks (VANETs) have characteristics of intermittent connectivity, high mobility of vehicle nodes and dynamic topology, which make data delivery in VANETs very challenging. Pervious works that based on history traffic patterns to predict the current traffic conditions on the roads are not accurate. Moreover, deploying roadside units (RSUs) is a possible solution to overcome the challenges, but it often requires a large amount of investment. Motivated by the fact that there are large amounts of outside parked vehicles in urban areas, we propose a virtual parking overlay network based data delivery scheme (VPOD), which does not need any RSUs but leverages a parking overlay network formed by outside parked vehicles to disseminate messages among moving vehicles. Simulation results based on a real city map and realistic traffic situations show that VPOD achieves high performance in data delivery, especially in sparse traffic and multiple requests conditions.

Efficient Quality-of-Service (QoS) Support in Mobile Opportunistic Networks

This paper aims to support quality-of-service (QoS) provisioning, particularly the guarantee for end-to-end data delivery delay, in mobile opportunistic networks. The QoS-aware delivery probability (QDP) is introduced to reflect the capability of a node to deliver data to a destination within a given delay budget. Each node maintains a set of QDPs to make autonomous decisions for QoS-aware data transmission. At the same time, a prioritized queue is employed by each mobile node. To support efficient prioritization and redundancy control, the priority is determined by a function of traffic class and data redundancy. The former is predetermined by the corresponding application, whereas the latter is dynamically estimated during data delivery. Two experiments are carried out to demonstrate and evaluate the proposed QoS-aware data delivery scheme. The first experiment involves multiple clusters of static Crossbow sensors that are connected by air and ground mobile nodes with controlled mobility. The second experiment is under a mobile social network setting, where 23 Dell Streak Android tablets are carried by volunteers with arbitrary and diverse mobility patterns over a period of two weeks. Moreover, simulation results are obtained under DieselNet trace and power-law mobility model to study scalability and performance trends. Our experiments and simulations demonstrate that the proposed scheme achieves efficient resource allocation according to the desired delay budget and, thus, supports effective QoS provisioning.

A Low-Complexity Resource Allocation Algorithm for Multicast Service Delivery in OFDMA Networks

Allocating and managing radio resources to multicast transmissions in orthogonal frequency-division multiple access (OFDMA) systems is the challenging research issue addressed by this paper. A subgrouping technique, which divides the subscribers into subgroups according to the experienced channel quality, is considered to overcome the throughput limitations of conventional multicast data delivery schemes. A low complexity algorithm, designed to work with different resource allocation strategies, is also proposed to reduce the computational complexity of the subgroup formation problem. Simulation results, carried out by considering the Long Term Evolution system based on OFDMA, testify the effectiveness of the proposed solution, which achieves a near-optimal performance with a limited computational load for the system.

A dynamic cross-layer data queue management approach based on priority for delay-tolerant mobile sensor networks

This paper presents a Dynamic Cross-layer Data Queue Management approach (DC-DQM) based on priority to address the priority deviation problem in Delay-Tolerant Mobile Sensor Networks (DT-MSNs). Receiver-driven data delivery scheme is used for fast response to data transfers, and a priority based interaction model is adopted to identify the data priority. Three interactive parameters are introduced to prioritize and dynamically manage data queue. The experimental results show that it can ameliorate data delivery ratio and achieve good performance in terms of average delay.