Spatial networks with wireless applications

Many networks have nodes located in physical space, with links more common between closely spaced pairs of nodes. For example, the nodes could be wireless devices and links communication channels in a wireless mesh network. We describe recent work involving such networks, considering effects due to the geometry (convex,non-convex, and fractal), node distribution, distance-dependent link probability, mobility, directivity and interference.Comment: Review article- an amended version with a new title from the origina

Distributed video coding in wireless multimedia sensor network for multimedia broadcasting

Recently the development of Distributed Video Coding (DVC) has provided the promising theory support to realize the infrastructure of Wireless Multimedia Sensor Network (WMSN), which composed of autonomous hardware for capturing and transmission of quality audio-visual content. The implementation of DVC in WMSN can better solve the problem of energy constraint of the sensor nodes due to the benefit of lower computational encoder in DVC. In this paper, a practical DVC scheme, pixel-domain Wyner-Ziv(PDWZ) video coding, with slice structure and adaptive rate selection(ARS) is proposed to solve the certain problems when applying DVC into WMSN. Firstly, the proposed slice structure in PDWZ has extended the feasibility of PDWZ to work with any interleaver size used in Slepian-wolf turbo codec for heterogeneous applications. Meanwhile, based on the slice structure, an adaptive code rate selection has been proposed aiming at reduce the system delay occurred in feedback request. The simulation results clearly showed the enhancement in R-D performance and perceptual quality. It also can be observed that system delay caused by frequent feedback is greatly reduced, which gives a promising support for WMSN with low latency and facilitates the QoS management

Deterministic scheduling for energy efficient and reliable communication in heterogeneous sensing environments in industrial wireless sensor networks

The present-day industries incorporate many applications, and complex processes, hence, a large number of sensors with dissimilar process deadlines and sensor update frequencies will be in place. This paper presents a scheduling algorithm, which takes into account the varying deadlines of the sensors connected to the cluster-head, and formulates a static schedule for Time Division Multiple Access (TDMA) based communication. The scheme uses IEEE802.15.4e superframe as a baseline and proposes a new superframe structure. For evaluation purposes the update frequencies of different industrial processes are considered. The scheduling algorithm is evaluated under varying network loads by increasing the number of nodes affiliated to a cluster-head. The static schedule generated by the scheduling algorithm offers reduced energy consumption, improved reliability, efficient network load management and improved information to control bits ratio

Dynamic Queue Utilization Based MAC for multi-hop Ad Hoc networks

The end-to-end throughput in single flow multi-hop Ad Hoc networks decays rapidly with path length. Along the path, the success rate of delivering packets towards the destination decreases due to higher contention, interference, limited buffer size and limited shared bandwidth constraints. In such environments the queues fill up faster in nodes closer to the source than in the nodes nearer the destination. In order to reduce buffer overflow and improve throughput for a saturated network, this paper introduces a new MAC protocol named Dynamic Queue Utilization Based Medium Access Control (DQUB-MAC). The protocol aims to prioritise access to the channel for queues with higher utilization and helps in achieving higher throughput by rapidly draining packets towards the destination. The proposed MAC enhances the performance of an end-to-end data flow by up to 30% for a six hop transmission in a chain topology and is demonstrated to remain competitive for other network topologies and for a variety of packet sizes

IEEE Access special section editorial: Artificial intelligence enabled networking

With today’s computer networks becoming increasingly dynamic, heterogeneous, and complex, there is great interest in deploying artificial intelligence (AI) based techniques for optimization and management of computer networks. AI techniques—that subsume multidisciplinary techniques from machine learning, optimization theory, game theory, control theory, and meta-heuristics—have long been applied to optimize computer networks in many diverse settings. Such an approach is gaining increased traction with the emergence of novel networking paradigms that promise to simplify network management (e.g., cloud computing, network functions virtualization, and software-defined networking) and provide intelligent services (e.g., future 5G mobile networks). Looking ahead, greater integration of AI into networking architectures can help develop a future vision of cognitive networks that will show network-wide intelligent behavior to solve problems of network heterogeneity, performance, and quality of service (QoS)