Reduce Transmission Latency Research Articles

Routing design in optical networks-on-chip based on gray code for optical loss reduction

An advanced electronics world and enhanced capability in nanoscale circuitry design require optimal integration in the design of electronic systems. Efforts are still being made to design and build integrated systems. In the old solutions, interconnections were established using the structure of buses. Bus-based solutions have lost their effectiveness against the demand for new technologies as a result of an increased number of circuits. Traffic was limited and, in some cases, even blocked by the buses. Systems-on-chip try to integrate processor, communication, and interface cores into one chip. One of the challenges facing this integration is routing between these cores. In networks-on-chip, bus-based structures have been replaced with networks very similar to computer networks. Communication is made between different parts by sending data packets through this network. Optical networks-on-chip include a new generation of chip-based networks, proposed as a new solution to the chip multiprocessor communications infrastructure, as well as a different solution to overcome the limitations of chip-based networks. Important features of these networks include increased communication bandwidth, reduced transmission latency, and reduced power consumption. They also face several challenges, such as routing for optical data transmission over optical layers. The current research proposes a routing algorithm based on mesh topology and gray code, which uses a packet switching method and a random traffic pattern to improve routing. The newly proposed method can select the different source and destination nodes by choosing the path with the lowest optical loss. A comparison between the result of the reduction in the optical loss in the proposed routing algorithm and that of the dimensional sequential algorithm shows a 40 % improvement in the proposed method.

An Effective Early Message Ahead Join Adaptive Data Aggregation Scheme for Sustainable IoT

The rapid development of Internet of Things (IoT) can promote the establishment of the smart connected world by using numerous devices and sensors. Collecting the data perceived by sensing devices in a fast and energy-saving style is critical for building a stable network in IoT. In this paper, we propose an Early Message Ahead Join Adaptive Data Aggregation (E-ADA) scheme for IoT. Firstly, an advance notification mechanism based on early message is introduced to improve the probability of data aggregation, thus optimizing energy consumption and network lifetime. In this mechanism, the routing of early message is faster than that of the data packet. Nodes with data packet send an early message forward to notice, and other data packets which monitor the early message can wait for that to aggregate under the delay deadline constraints. Secondly, we propose a Delay-optimized Convergence Routing based E-ADA (DOCR-E-ADA) data collection scheme which combines advance notification mechanism and convergence routings. The duty cycle of nodes in convergence routing is adaptively adjusted, which greatly reduces transmission latency. Finally, extensive experimental results demonstrate that our DOCR-E-ADA outperforms the existing schemes in terms of network delay and lifetime.

Lightweight Privacy-Preserving Medical Diagnosis in Edge Computing

With the development of machine learning, it is popular that mobile users can submit individual symptoms at any time anywhere for medical diagnosis. Edge computing is frequently adopted to reduce transmission latency for real-time diagnosis service. However, the data-driven machine learning, which requires to build a diagnosis model over vast amounts of medical data, inevitably leaks the privacy of medical data. It is necessary to provide privacy preservation. To solve above challenging issues, in this article, we design a lightweight privacy-preserving medical diagnosis mechanism on edge, called LPME. Our LPME redesigns the extreme gradient boosting (XGBoost) model based on the edge-cloud model, which adopts encrypted model parameters instead of local data to remove amounts of ciphertext computation to plaintext computation, thus realizing lightweight privacy preservation on resource-limited edge. In addition, LPME provides secure diagnosis on edge with privacy preservation for private and timely diagnosis. Our security analysis and experimental evaluation indicates the security, effectiveness, and efficiency of LPME.

Graph-Based File Dispatching Protocol With D2D-Enhanced UAV-NOMA Communications in Large-Scale Networks

As a newly emerging communication assistant equipment, unmanned aerial vehicles (UAVs) can be exploited to dispatch data files quickly to specific areas and support rapid deployment of communication links in complex terrain, which is of great significance for specific communication demands in disaster and remote areas. Nonorthogonal multiple access (NOMA), as a rosy technology in the fifth generation (5G) and future mobile communication systems, has been widely studied because of its ability in improving spectral efficiency and reducing transmission latency to enhance the overall Quality of Service (QoS) and meet the strict communication requirements. Based on these, in this article, we propose a device-to-device (D2D)-enhanced UAV-NOMA network architecture, in which D2D is introduced to increase the file dispatching efficiency. In our proposed D2D-enhanced UAV-NOMA network, the ground users (GUEs) that have already received file blocks (FBs) are allowed to reuse the time–frequency resources assigned to NOMA links to share their FBs with other GUEs, which significantly improves the efficiency of file dispatching. But this also leads to a complicated interference environment. In order to effectively manage the interference and minimize the UAV-assisted file dispatching mission time, we propose a graph-based file dispatching (GFD) protocol, in which the complicated joint optimization problem is decomposed to be solved efficiently and graph theory-based algorithms are proposed for resource allocation. The simulation results verify the advantages of our proposed D2D-enhanced UAV-NOMA network architecture and the efficiency of our designed GFD protocol in minimizing the total UAV-assisted file dispatching mission time.

NOMA With Index Modulation for Uplink URLLC Through Grant-Free Access

This paper proposes nonorthogonal sharing of available resources between latency-critical and latency-tolerant communication for fulfilling tight requirements of ultrareliable low-latency communication (URLLC) as well as avoiding inefficient spectrum utilization of grant-based (GB) access for sporadic URLLC traffic. In the proposed system, grant-free (GF) access is adopted for URLLC to reduce transmission latency, whereas GB access is used for latency-tolerant communication. Due to GF access, collision emerges between the communications, and use of OFDM technology for both communications leads to wideband interference (WB-I) on URLLC. Therefore, a novel nonorthogonal multiple accessing (NOMA) scheme based on orthogonal frequency division multiplexing (OFDM) and OFDM with index modulation (OFDM-IM) is proposed in order to reduce the impact of the collision on URLLC, that requires 99.999 ${\%}$ success probability within 1 ms. OFDM-IM technology is used for latency-tolerant communication since WB-I is converted to either narrowband dominant interference or narrowband interference by fractional subcarrier activation in OFDM-IM. In this way, URLLC is partially affected by latency-tolerant communication. It is shown that the proposed NOMA scheme significantly reduces the latency in comparison to classical NOMA scheme based on pure OFDM while guaranteeing $10^{-5}$ reliability for URLLC, via both computer-based simulations and theoretical analysis.

Mobile-edge computing framework with data compression for wireless network in energy internet

Under the situations of energy dilemma, energy Internet has become one of the most important technologies in international academic and industrial areas. However, massive small data from users, which are too scattered and unsuitable for compression, can easily exhaust computational resources and lower random access possibility, thereby reducing system performance. Moreover, electric substations are sensitive to transmission latency of user data, such as controlling information. However, the traditional energy Internet usually could not meet requirements. Integrating mobile-edge computing makes energy Internet convenient for data acquisition, processing, management, and accessing. In this paper, we propose a novel framework for energy Internet to improve random access possibility and reduce transmission latency. This framework utilizes the local area network to collect data from users and makes conducting data compression for energy Internet possible. Simulation results show that this architecture can enhance random access possibility by a large margin and reduce transmission latency without extra energy consumption overhead.

Android Unikernel: Gearing mobile code offloading towards edge computing

Recently, Mobile Cloud Computing (MCC) which utilizes cloud to enhance mobile device’s performance, is becoming more and more popular. A typical approach of MCC is to offload some computation-intensive tasks onto cloud servers to execute and fetch results back. However, this schema suffers greatly from the long-distance network transmission latency and server boot-up latency, leading to high-delay response, which is unacceptable for most real-time applications. Mobile Edge Computing (MEC) or Mobile Fog Computing (MFC) can drastically reduce transmission latency by offloading the tasks onto the edge servers without transferring to remote data centers. However, traditional virtual machines (VM) or containers used in MCC are too heavyweight for resource-constrained environment of edge or fog servers. In this paper, we argue that enhanced unikernel can be used as task runtime in MEC or MFC to efficiently support mobile code offloading. To achieve this goal, we put forward the concept of Rich-Unikernel which aims to support various applications in one unikernel while avoiding their time-consuming recompilation. Following the design of Rich-Unikernel, we implement a not only lightweight but also flexible runtime for offloaded codes, called Android Unikernel, by integrating basic Android system libraries into OSv unikernel. Our experiment shows, compared with VM and container, Android Unikernel introduces much less boot-up delay, memory footprint, image size and energy consumption.

On the Performance of Non-Orthogonal Multiple Access in Short-Packet Communications

This letter investigates the performance of non-orthogonal multiple access (NOMA) in short-packet communications. We aim to answer a fundamental question–for given reliability requirements of users: how much physical-layer transmission latency can NOMA reduce when compared with orthogonal multiple access in the finite blocklength regime? We derive closed-form expressions for the block error rates of users in NOMA. Further, we obtain the near-optimal power allocation coefficients and blocklength to ensure certain reliability. Numerical results validate our theoretical analysis and demonstrate the superior performance of NOMA in reducing transmission latency.

Green Data Gathering under Delay Differentiated Services Constraint for Internet of Things

Energy‐efficient data gathering techniques play a crucial role in promoting the development of smart portable devices as well as smart sensor devices based Internet of Things (IoT). For data gathering, different applications require different delay constraints; therefore, a delay Differentiated Services based Data Routing (DSDR) scheme is creatively proposed to improve the delay differentiated services constraint that is missed from previous data gathering studies. The DSDR scheme has three advantages: first, DSDR greatly reduces transmission delay by establishing energy‐efficient routing paths (E2RPs). Multiple E2RPs are established in different locations of the network to forward data, and the duty cycles of nodes on E2RPs are increased to 1, so the data is forwarded by E2RPs without the existence of sleeping delay, which greatly reduces transmission latency. Secondly, DSDR intelligently chooses transmission method according to data urgency: the direct‐forwarding strategy is adopted for delay‐sensitive data to ensure minimum end‐to‐end delay, while wait‐forwarding method is adopted for delay‐tolerant data to perform data fusion for reducing energy consumption. Finally, DSDR make full use of the residual energy and improve the effective energy utilization. The E2RPs are built in the region with adequate residual energy and they are periodically rotated to equalize the energy consumption of the network. A comprehensive performance analysis demonstrates that the DSDR scheme has obvious advantages in improving network performance compared to previous studies: it reduces transmission latency of delay‐sensitive data by 44.31%, reduces transmission latency of delay‐tolerant data by 25.65%, and improves network energy utilization by 30.61%, while also guaranteeing the network lifetime is not lower than previous studies.

A Smart High-Speed Backbone Path Construction Approach for Energy and Delay Optimization in WSNs

Quickly and efficiently transmitting data to sink via intelligent routing is an important issue in wireless sensor networks. In previous scenarios, there has existed the phenomenon of “energy hole,” which results in difficulties in synchronous optimization of energy and delay. Thus, a smart High-Speed Backbone Path (HSBP) construction approach is proposed in this paper. In the HSBP approach, several High-speed Backbone Paths (HBPs) are established at different locations of the network, and the duty cycles of nodes on the HBPs are increased to 1; therefore, the data are forwarded by HBPs without the existence of sleeping delay, which greatly reduces transmission latency. Furthermore, the HBPs are built in regions with adequate residual energy, and they are switched periodically; thus, more nodes can be utilized to equalize the energy consumption. A comprehensive performance analysis demonstrates that the HSBP approach has obvious advantages in improving network performance compared with previous studies; it reduces transmission delay by 48.10% and improves energy utilization by 38.21% while guaranteeing the same network lifetime.

Design of Contract-Based Trading Mechanism for a Small-Cell Caching System

Recently, content-aware-enabled distributed cach- ing relying on local small-cell base stations (SBSs), namely, small-cell caching, has been intensively studied for reducing transmission latency as well as alleviating the traffic load over backhaul channels. In this paper, we consider a commercialized small-cell caching system consisting of a network service provider (NSP), several content providers (CPs), and multiple mobile users (MUs). The NSP, as a network facility monopolist in charge of the SBSs, leases its resources to the CPs for gaining profits. At the same time, the CPs are intended to rent the SBSs for providing better downloading services to the MUs. We focus on solving the profit maximization problem for the NSP within the framework of contract theory. To be specific, we first formulate the utility functions of the NSP and the CPs by modeling the MUs and SBSs as two independent Poisson point processes. Then, we develop the optimal contract problem for an information asymmetric scenario, where the NSP only knows the distribution of CPs’ popularity among the MUs. Also, we derive the necessary and sufficient conditions of feasible contracts. Lastly, the optimal contract solutions are proposed with different CPs’ popularity parameter $\gamma $ . Numerical results are provided to show the optimal quality and the optimal price designed for each CP. In addition, we find that the proposed contract-based mechanism is superior to the benchmarks from the perspective of maximizing the NSP’s profit.

Network Coding in Relay-based Device-to-Device Communications.

Device-to-Device (D2D) communications has been realized as an effective means to improve network throughput, reduce transmission latency, and extend cellular coverage in 5G systems. Network coding is a well-established technique known for its capability to reduce the number of retransmissions. In this article, we review state-of-the-art network coding in relay-based D2D communications, in terms of application scenarios and network coding techniques. We then apply two representative network coding techniques to dual-hop D2D communications and present an efficient relay node selecting mechanism as a case study. We also outline potential future research directions, according to the current research challenges. Our intention is to provide researchers and practitioners with a comprehensive overview of the current research status in this area and hope that this article may motivate more researchers to participate in developing network coding techniques for different relay-based D2D communications scenarios.

Information-Centric Wireless Networks with Virtualization and D2D Communications

Wireless network virtualization and ICN are two promising technologies for next generation wireless networks. Although some excellent works have focused on these two technologies, D2D communications have not been investigated in information-centric virtualized cellular networks. Meanwhile, content caching in mobile devices has attracted much attention due to the saved backhaul consumption or reduced transmission latency in D2D-assisted cellular networks. However, when it comes to the multi-operator scenario, direct content sharing between different operators via D2D communications is typically infeasible. In this article, we propose a novel information-centric virtualized cellular network framework with D2D communications, enabling not only content caching in the air, but also inter-operator content sharing between mobile devices. We describe the key components in the proposed framework, and present the interactions among them. We incorporate and formulate the content caching strategies in resource allocation optimization, to maximize the total utility of mobile virtual network operators (MVNOs) by caching popular content in mobile devices. Simulation results demonstrate the effectiveness of the proposed framework and scheme with different system parameters.

Optimal Workload Allocation in Fog-Cloud Computing Towards Balanced Delay and Power Consumption

Mobile users typically have high demand on localized and location-based information services. To always retrieve the localized data from the remote cloud, however, tends to be inefficient, which motivates fog computing. The fog computing, also known as edge computing, extends cloud computing by deploying localized computing facilities at the premise of users, which prestores cloud data and distributes to mobile users with fast-rate local connections. As such, fog computing introduces an intermediate fog layer between mobile users and cloud, and complements cloud computing toward low-latency high-rate services to mobile users. In this fundamental framework, it is important to study the interplay and cooperation between the edge (fog) and the core (cloud). In this paper, the tradeoff between power consumption and transmission delay in the fog-cloud computing system is investigated. We formulate a workload allocation problem which suggests the optimal workload allocations between fog and cloud toward the minimal power consumption with the constrained service delay. The problem is then tackled using an approximate approach by decomposing the primal problem into three subproblems of corresponding subsystems, which can be, respectively, solved. Finally, based on simulations and numerical results, we show that by sacrificing modest computation resources to save communication bandwidth and reduce transmission latency, fog computing can significantly improve the performance of cloud computing.

A Commercial Video-Caching System for Small-Cell Cellular Networks Using Game Theory

Evidence indicates that requesting video clips on demand accounts for a dramatic increase in data traffic over cellular networks. Caching part of popular videos in the storage of small-cell base stations (SBS) in cellular networks is an efficient method to reduce transmission latency and mitigate redundant transmissions. In this paper, we propose a commercial caching system consisting of a video retailer (VR) and multiple network service providers (NSPs). Each NSP leases its SBSs, with some price, to the VR for the purpose of making profits, and the VR, after storing popular videos in the rented SBSs, can provide better local video services to the mobile users, thereby gaining more profits. We conceive this system within the framework of a Stackelberg game by treating the SBSs as a specific type of resources. Then, we establish the profit models for both the NSPs and the VR based on stochastic geometry. We further investigate the Stackelberg equilibrium by solving the optimization problems in two cases, i.e., whether or not the VR has a budget plan on renting the SBSs. Numerical results are provided for quantifying the proposed framework by showing its efficiency on pricing and resource allocation.

A Distributed LT Codes-based Data Transmission Technique for Multicast Services in Vehicular Ad-hoc Networks

In this paper, we consider an infrastructure-vehicle-vehicle (I2V2V) based Vehicle Ad-hoc Networks (VANETs), where one base station multicasts data to d vehicular users with the assistance of r vehicular users. A Distributed Luby Transform (DLT) codes based transmission scheme is proposed over lossy VANETs to reduce transmission latency. Furthermore, focusing on the degree distribution of DLT codes, a Modified Deconvolved Soliton Distribution (MDSD) is designed to further reduce the transmission latency and improve the transmission reliability. We investigate the network behavior of the transmission scheme with MDSD, called MDLT based scheme. Closed-form expressions of the transmission latency of the proposed schemes are derived. Performance simulation results show that DLT based scheme can reduce transmission latency significantly compared with traditional Automatic Repeat Request (ARQ) and Luby Transform (LT) codes based schemes. In contrast to DLT based scheme, the MDLT based scheme can further reduce transmission latency and improve FER performance substantially, when both the source-to-relay and relay-to-sink channels are erasure channels.

Analysis for bio-inspired thrown-box assisted message dissemination in delay tolerant networks

Inspired by biological communication, the strategy of deploying communication and storage equipment called thrown box is proposed to increase message delivery probability and to reduce transmission latency in delay tolerant networks. In this paper, we study the thrown-box assisted message dissemination models by analyzing a few cases on the message delivery rate and related latency distribution. We divide such communications into two processes. We first model the message delivering process among thrown boxes and derive time related message distribution on the boxes. Then we investigate the message collection process to obtain the expected number of informed collectors as a function of time. In addition, we analyze the latency distribution for message collection. Our analysis is derived based on a discrete Markov Chain model. The numerical examples are provided to validate our model and to examine the features of message dissemination under different network scenarios. The factors such as message relay and lifetime are considered. The results show that the tradeoff exists between the number of the boxes and the message lifetime, etc. In summary, our results will help storage management and delay management in DTNs and provide guidelines for applications of search and surveillance.

A Quorum-Based Energy-Saving MAC Protocol Design for Wireless Sensor Networks

Wireless sensor networks are mainly designed for environment surveillance, wherein wireless sensor nodes cooperate to get their job done. Generally, wireless sensors are battery powered; therefore, it is crucial for them to efficiently use their battery resources. Most of the existing power-saving protocols achieve power savings by periodically putting sensor nodes to sleep. Such a regular sleep/awake mechanism fails to adjust a sensor node's sleep duration based on its traffic load, thus causing either lower power efficiency or higher latency. Furthermore, sensors may be deployed in hostile environments and may thus unexpectedly fail. Most power-saving protocols do not promptly react to such link breakage, resulting in long transmission delays. In this paper, we propose a quorum-based medium access control (QMAC) protocol that enables sensor nodes to sleep longer under light loads. Since traffic flows toward the sink node in wireless sensor networks, a new concept, i.e., the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">next-hop group</i> , is also proposed to reduce transmission latency. Simulation results verify that the proposed QMAC saves more energy and keeps the transmission latency low.

On-demand transmission of 3D models over lossy networks

Three-dimensional (3D) meshes are used intensively in distributed graphics applications where model data are transmitted on demand to users’ terminals and rendered for interactive manipulation. For real-time rendering and high-resolution visualization, the transmission system should adapt to both data properties and transport link characteristics while providing scalability to accommodate terminals with disparate rendering capabilities. This paper presents a transmission system using hybrid unequal-error-protection and selective-retransmission for 3D meshes which are encoded with multi-resolutions. Based on the distortion-rate performance of the 3D data, the end-to-end channel statistics and the network parameters, transmission policies that maximize the service quality for a client-specific constraint is determined with linear computation complexity. A TCP-friendly protocol is utilized to further provide performance stability over time as well as bandwidth fairness for parallel flows in the network. Simulation results show the efficacy of the proposed transmission system in reducing transmission latency and providing smooth performance for interactive applications. For example, for a fixed rendering quality, the proposed system achieves 20–30% reduction in transmission latency compared to the system based on 3TP, which is a recently presented 3D application protocol using hybrid TCP and UDP.