Benefits and Challenges of Internet of Things for Telecommunication Networks

Recently, Internet of things (IoTs) has become the main issue in designing monitoring systems such as smart environments, smart cars, and smart wearable devices. IoTs has transformed the life of people to be more adaptable and intelligent. For example, in a healthcare monitoring system, using smart devices will improve the performance of doctors, nurses, patients, and the healthcare industry. The IoTs revolution is known as the fourth industrial revolution and would change the way humans interact with machines and lead the way to a high-technology machine-to-machine interaction. In fact, almost every device around us would be connected to Internet, collecting and exchanging data with other devices on the cloud. In this chapter, we will introduce the benefits of IoTs on telecommunication networks and its challenges to give a complete overview for researchers to know how to improve our life and society by building smart IoTs systems

EOCC-TARA for Software Defined WBAN

Wireless Body Area Network (WBAN) is a promising cost-effective technology for the privacy confined military applications and healthcare applications like remote health monitoring, telemedicine, and e-health services. The use of a Software-Defined Network (SDN) approach improves the control and management processes of the complex structured WBANs and also provides higher flexibility and dynamic network structure. To seamless routing performance in SDN-based WBAN, the energy-efficiency problems must be tackled effectively. The main contribution of this paper is to develop a novel Energy Optimized Congestion Control based on Temperature Aware Routing Algorithm (EOCC-TARA) using Enhanced Multi-objective Spider Monkey Optimization (EMSMO) for SDN-based WBAN. This algorithm overcomes the vital challenges, namely energy-efficiency, congestion-free communication, and reducing adverse thermal effects in WBAN routing. First, the proposed EOCC-TARA routing algorithm considers the effects of temperature due to the thermal dissipation of sensor nodes and formulates a strategy to adaptively select the forwarding nodes based on temperature and energy. Then the congestion avoidance concept is added with the energy-efficiency, link reliability, and path loss for modeling the cost function based on which the EMSMO provides the optimal routing. Simulations were performed, and the evaluation results showed that the proposed EOCC-TARA routing algorithm has superior performance than the traditional routing approaches in terms of energy consumption, network lifetime, throughput, temperature control, congestion overhead, delay, and successful transmission rate

On the Deployment of Healthcare Applications over Fog Computing Infrastructure

Fog computing is considered as the most promising enhancement of the traditional cloud computing paradigm in order to handle potential issues introduced by the emerging Interned of Things (IoT) framework at the network edge. The heterogeneous nature, the extensive distribution and the hefty number of deployed IoT nodes will disrupt existing functional models, creating confusion. However, IoT will facilitate the rise of new applications, with automated healthcare monitoring platforms being amongst them. This paper presents the pillars of design for such applications, along with the evaluation of a working prototype that collects ECG traces from a tailor-made device and utilizes the patient's smartphone as a Fog gateway for securely sharing them to other authorized entities. This prototype will allow patients to share information to their physicians, monitor their health status independently and notify the authorities rapidly in emergency situations. Historical data will also be available for further analysis, towards identifying patterns that may improve medical diagnoses in the foreseeable future

A Survey and Future Directions on Clustering: From WSNs to IoT and Modern Networking Paradigms

Many Internet of Things (IoT) networks are created as an overlay over traditional ad-hoc networks such as Zigbee. Moreover, IoT networks can resemble ad-hoc networks over networks that support device-to-device (D2D) communication, e.g., D2D-enabled cellular networks and WiFi-Direct. In these ad-hoc types of IoT networks, efficient topology management is a crucial requirement, and in particular in massive scale deployments. Traditionally, clustering has been recognized as a common approach for topology management in ad-hoc networks, e.g., in Wireless Sensor Networks (WSNs). Topology management in WSNs and ad-hoc IoT networks has many design commonalities as both need to transfer data to the destination hop by hop. Thus, WSN clustering techniques can presumably be applied for topology management in ad-hoc IoT networks. This requires a comprehensive study on WSN clustering techniques and investigating their applicability to ad-hoc IoT networks. In this article, we conduct a survey of this field based on the objectives for clustering, such as reducing energy consumption and load balancing, as well as the network properties relevant for efficient clustering in IoT, such as network heterogeneity and mobility. Beyond that, we investigate the advantages and challenges of clustering when IoT is integrated with modern computing and communication technologies such as Blockchain, Fog/Edge computing, and 5G. This survey provides useful insights into research on IoT clustering, allows broader understanding of its design challenges for IoT networks, and sheds light on its future applications in modern technologies integrated with IoT.acceptedVersio

Can SDN Technology Be Transported to Software-Defined WSN/IoT?

© 2016 IEEE. Wireless sensor networks (WSNs) are essential elements of the Internet of Things ecosystem, as such, they encounter numerous IoT challenging architectural, management and application issues. These include inflexible control, manual configuration and management of sensor nodes, difficulty in an orchestration of resources, and virtualizing sensor network resources for on-demand applications and services. Addressing these issues presents a real challenge for WSNs and IoTs. By separating the network control plane from the data forwarding plane, Software-defined networking (SDN) has emerged as network technology that addresses similar problems of current switched-networks. Despite the differences between switched network and wireless sensor network domains, the SDN technology has a real potential to revolutionize WSNs/IoTs and address their challenging issues. However, very little has been attempted to bring the SDN paradigm to WSNs. This paper identifies weaknesses of existing research efforts that aims to bring the benefits of SDN to WSNs by mapping the control plane, the OpenFlow protocol, and the functionality between the two network domains. In particular, the paper investigates the difficulties and challenges in the development of software-defined wireless sensor networking (SDWSN). Finally, the paper proposes VSensor, SDIoT controller, SFlow components with specific and relevant functionality for an architecture of an SDWSN or SDIoT infrastructure

GRAPH-BASED FOG COMPUTING NETWORK MODEL

IoT networks generate numerous amounts of data that is then transferred to the cloud for processing. Transferring data cleansing and parts of calculations towards these edge-level networks improves system’s, latency, energy consumption, network bandwidth and computational resources utilization, fault tolerance and thus operational costs. On the other hand, these fog nodes are resource-constrained, have extremely distributed and heterogeneous nature, lack horizontal scalability, and, thus, the vanilla SOA approach is not applicable to them. Utilization of Software Defined Network (SDN) with task distribution capabilities advocated in this paper addresses these issues. Suggested framework may utilize various routing and data distribution algorithms allowing to build flexible system most relevant for particular use-case. Advocated architecture was evaluated in agent-based simulation environment and proved its’ feasibility and performance gains compared to conventional event-stream approach