Big Data Analytics Embedded Smart City Architecture for Performance Enhancement through Real-Time Data Processing and Decision-Making

The concept of the smart city is widely favored, as it enhances the quality of life of urban citizens, involving multiple disciplines, that is, smart community, smart transportation, smart healthcare, smart parking, and many more. Continuous growth of the complex urban networks is significantly challenged by real-time data processing and intelligent decision-making capabilities. Therefore, in this paper, we propose a smart city framework based on Big Data analytics. The proposed framework operates on three levels: (1) data generation and acquisition level collecting heterogeneous data related to city operations, (2) data management and processing level filtering, analyzing, and storing data to make decisions and events autonomously, and (3) application level initiating execution of the events corresponding to the received decisions. In order to validate the proposed architecture, we analyze a few major types of dataset based on the proposed three-level architecture. Further, we tested authentic datasets on Hadoop ecosystem to determine the threshold and the analysis shows that the proposed architecture offers useful insights into the community development authorities to improve the existing smart city architecture

IoT-B&B: Edge-Based NFV for IoT Devices with CPE Crowdsourcing

For embracing the ubiquitous Internet-of-Things (IoT) devices, edge computing and Network Function Virtualization (NFV) have been enabled in branch offices and homes in the form of virtual Customer-Premises Equipment (vCPE). A Service Provider (SP) deploys vCPE instances as Virtual Network Functions (VNFs) on top of generic physical Customer-Premises Equipment (pCPE) to ease administration. Upon a usage surge of IoT devices at a certain part of the network, vCPU, memory, and other resource limitations of a single pCPE node make it difficult to add new services handling the high demand. In this paper, we present IoT-B&B, a novel architecture featuring resource sharing of pCPE nodes. When a pCPE node has sharable resources available, the SP will utilize its free resources as a "bed-and-breakfast" place to deploy vCPE instances in need. A placement algorithm is also presented to assign vCPE instances to a cost-efficient pCPE node. By keeping vCPE instances at the network edge, their costs of hosting are reduced. Meanwhile, the transmission latencies are maintained at acceptable levels for processing real-time data burst from IoT devices. The traffic load to the remote, centralized cloud can be substantially reduced

Achieving reliable and enhanced communication in vehicular ad hoc networks (VANETs)

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirement for the degree of Doctor of PhilosophyWith the envisioned age of Internet of Things (IoTs), different aspects of Intelligent Transportation System (ITS) will be linked so as to advance road transportation safety, ease congestion of road traffic, lessen air pollution, improve passenger transportation comfort and significantly reduce road accidents. In vehicular networks, regular exchange of current position, direction, speed, etc., enable mobile vehicle to foresee an imminent vehicle accident and notify the driver early enough in order to take appropriate action(s) or the vehicle on its own may take adequate preventive measures to avert the looming accident. Actualizing this concept requires use of shared media access protocol that is capable of guaranteeing reliable and timely broadcast of safety messages. This dissertation investigates the use of Network Coding (NC) techniques to enrich the content of each transmission and ensure improved high reliability of the broadcasted safety messages with less number of retransmissions. A Code Aided Retransmission-based Error Recovery (CARER) protocol is proposed. In order to avoid broadcast storm problem, a rebroadcasting vehicle selection metric η, is developed, which is used to select a vehicle that will rebroadcast the received encoded message. Although the proposed CARER protocol demonstrates an impressive performance, the level of incurred overhead is fairly high due to the use of complex rebroadcasting vehicle selection metric. To resolve this issue, a Random Network Coding (RNC) and vehicle clustering based vehicular communication scheme with low algorithmic complexity, named Reliable and Enhanced Cooperative Cross-layer MAC (RECMAC) scheme, is proposed. The use of this clustering technique enables RECMAC to subdivide the vehicular network into small manageable, coordinated clusters which further improve transmission reliability and minimise negative impact of network overhead. Similarly, a Cluster Head (CH) selection metric ℱ(\u1d457) is designed, which is used to determine and select the most suitably qualified candidate to become the CH of a particular cluster. Finally, in order to investigate the impact of available radio spectral resource, an in-depth study of the required amount of spectrum sufficient to support high transmission reliability and minimum latency requirements of critical road safety messages in vehicular networks was carried out. The performance of the proposed schemes was clearly shown with detailed theoretical analysis and was further validated with simulation experiments