Efficient Data Delivery Scheme Research Articles

Efficient Data Delivery Scheme for Large-Scale Microservices in Distributed Cloud Environment

The edge computing paradigm has emerged as a new scope within the domain of the Internet of Things (IoT) by bringing cloud services to the network edge in order to construct distributed architectures. To efficiently deploy latency-sensitive and bandwidth-hungry IoT application services, edge computing paradigms make use of devices on the network periphery that are distributed and resource-constrained. On the other hand, microservice architectures are becoming increasingly popular for developing IoT applications owing to their maintainability and scalability advantages. Providing an efficient communication medium for large-scale microservice-based IoT applications constructed from small and independent services to cooperate to deliver value-added services remains a challenge. This paper introduces an event-driven communication medium that takes advantage of Edge–Cloud publish/subscribe brokers for microservice-based IoT applications at scale. Using the interaction model, the involved microservices can collaborate and exchange data through triggered events flexibly and efficiently without changing their underlying business logic. In the proposed model, edge brokers are grouped according to their similarities in event channels and the proximity of their geolocations, reducing the data delivery latency. Moreover, in the proposed system a technique is designed to construct a broker-based utility matrix with constraints in order to strike a balance between delay, relay traffic, and scalability while arranging brokers into proper clusters for efficient data delivery. Rigorous simulation results prove that the proposed publish/subscribe model can provide an efficient interaction medium for microservice-based IoT applications to collaborate and exchange data with low latency, modest relay traffic, and high scalability at scale.

An Efficient Data Delivery Scheme in WBAN to Deal with Shadow Effect due to Postural Mobility

The body movement and change in posture exhibit high mobility in sensor nodes which causes shadowing in the Wireless Body Area Network (WBAN). Due to this, the connectivity between the nodes in WBAN is affected which further causes failure in data delivery. This article presents a MAC protocol in WBAN to deal with the problem of data delivery due to body movement and postural mobility. It uses an Improved Initial Centroid K-means clustering technique for classification of various human body postures followed by back propagation neural network as a classifier to recognize human body posture. This article proposes a posture aware dynamic data delivery (PA-DDD) protocol to deliver data dynamically. The PA-DDD protocol can be used under varying speed walking scenario. The simulation results show that it prolongs the network lifetime and is energy efficient.

Loss-Aware CMT-Based Multipathing Scheme for Efficient Data Delivery to Heterogeneous Wireless Networks

With the rapid development of wireless networks, multiple network interfaces are gradually being designed into more and more mobile devices. When it comes to data delivery, Stream Control Transmission Protocol (SCTP)-based Concurrent Multipath Transfer (CMT) has proven to be quite useful solution for multiple home networks, and it could become the key transport protocol for the next generation of wireless communications. The CMT delay caused by data rearrangement has been noticed by researchers, but they have seldom considered the frequent occurrence of packet loss that occurs in the high-loss networks. In this paper, we proposed an original loss-aware solution for multipath concurrent transmission (CMT-LA) that achieves the following goals: (1) identifying packet loss on all paths, (2) distributing packets adaptively across multiple available paths according to their packet loss and loss variation, and (3) maintaining the features of bandwidth aggregation and parallel transmission of CMT while improving the throughput performance. The results of our simulations showed that the proposed CMT-LA reduces reordering delay and unnecessary fast retransmissions, thereby demonstrating that CMT-LA is a more efficient data delivery scheme than classic CMT.

A cross-layer approach for real-time multimedia streaming on wireless peer-to-peer ad hoc network

Peer-to-peer (P2P) live streaming over mobile ad hoc network (MANET) is a state-of-the-art technique for wireless multimedia applications, such as entertainments and disaster recovery. The peers share the live streaming over MANET via multi-hop wireless link, so an efficient data delivery scheme must be required. However, the high churn rate and the frequent mobility baffle the P2P membership management and overlay maintenance. The unreliable wireless connection of MANET leads to the difficulties of large-scale and real-time streaming distribution, and a lack of overlay proximity leads to the inefficient streaming delivery. We present a cross-layer design for P2P over MANET to manage and maintain the overlay, and select efficient routing path to multicast media streams. Our proposed scheme (COME-P2P) integrates both P2P DHT-based lookup and IPv6 routing header to improve the delivery efficiency. Through the cross-layer design, the low layer detects mobility for informing high layer to refine the finger table, and high layer maintains the efficient multicast path for informing low layer to refine the routing table. How to keep stable routing paths for live streaming via IPv6 routing is the main contribution of this paper. The overlay proximity can shorten routing propagation delay, and the hop-by-hop routing can avoid the traffic bottleneck. Through the mathematical analysis and simulation results, COME-P2P can be demonstrated to achieve high smoothness and reduce signaling overhead for live streaming.

Delay/Fault-Tolerant Mobile Sensor Network (DFT-MSN): A New Paradigm for Pervasive Information Gathering

This paper focuses on the delay/fault-tolerant mobile sensor network (DFT-MSN) for pervasive information gathering. We develop simple and efficient data delivery schemes tailored for DFT-MSN, which has several unique characteristics, such as sensor mobility, loose connectivity, fault tolerability, delay tolerability, and buffer limit. We first study two basic approaches, namely, direct transmission and flooding. We analyze their performance by using queuing theory and statistics. Based on the analytic results that show the trade-off between data delivery delay/ratio and transmission overhead, we introduce an optimized flooding scheme that minimizes transmission overhead in flooding. Then, we propose two simple and effective DFT-MSN data delivery schemes, namely, the replication-based efficient data delivery scheme (RED) and the message fault tolerance-based adaptive data delivery scheme (FAD). The RED scheme utilizes the erasure coding technology in order to achieve the desired data delivery ratio with minimum overhead. It consists of two key components for data transmission and message management. The former makes the decision on when and where to transmit data messages according to the delivery probability, which is the likelihood that a sensor can deliver data messages to the sink. The latter decides the optimal erasure coding parameters (including the number of data blocks and the needed redundancy) based on its current delivery probability. The FAD scheme employs the message fault tolerance, which indicates the importance of the messages. The decisions on message transmission and dropping are made based on fault tolerance for minimizing transmission overhead. The system parameters are carefully tuned on the basis of thorough analyses to optimize network performance. Extensive simulations are carried out for performance evaluation. Our results show that both schemes achieve a high message delivery ratio with acceptable delay. The RED scheme results in lower complexity in message and queue management, while the FAD scheme has a lower message transmission overhead.