A web service‐based internet of things framework for mobile resource augmentation

The term Cloud has taken on a significant role in the computer industry and is now recognized as the forerunner of cutting-edge technology that makes possible an enormous variety of services and applications. Cloud computing servers are made up of a large resource pool that combines hardware and software that is readily available and serves users depending on demand, with pay-per-use consumers accessing services. Large amounts of resources that can be consolidated on an active network and cloud servers that can be distant users’ mobile handheld devices are both features of cloud services that may be offered to users. With the use of mobile device resources, this research suggests a novel method of cloud computing that would represent a ground-breaking development for the field. In this situation, virtualization technology may also be leveraged to benefit from the resources of mobile devices. Additionally, mobile devices can function as a backup virtual server for the cloud. Based on the outcomes of the relevant intelligent parameters, a dynamic optimization algorithm may categorize mobile devices that are linked to the cloud and operating as a part of it, and the result log would be stored in the server. Additionally, the log will act as the cloud’s main building block for effectively allocating and scheduling jobs to various types of categorized mobile devices based on the task’s complexity, which results in greater elasticity, flexibility, cost savings, and slick server performance. The potential solution adds a monetary incentive that is advantageous to both the service user and the service provider.

Despite of all progress in terms of computational power, communication bandwidth, and feature richness, limited battery capacity is the major bottleneck for using the resources of mobile devices in innovative distributed applications. Incentives are required for motivating a user to spend energy on behalf of other users and it must be ensured that providing these incentives neither consumes much energy by itself nor allows for free-riding and other types of fraud. In this paper, we present a novel incentive system that is tailored to the application scenario of energyaware resource-sharing between mobile devices. The system has low energy consumption due to avoiding the use of public key cryptography. It uses a virtual currency with reusable coins and detects forgery and other fraud when cashing coins at an off-line broker. A prototype-based measurement study indicates the energy-efficiency of the system, while simulation studies show its resilience to fraud. Even in scenarios with 75% of fraudulent users that are colluding to disguise their fraud only 3.2% of them get away with it while the energy overhead (about 3%) for the incentive system is still moderate

Video streaming applications and services (VASs) consume an enormous amount of scarce resources in mobile devices and cellular wireless networks due to the demand for high data rates of video streaming. The limited resource of wireless media and unreliable nature of wireless channels in cellular networks make VASs challenging to deliver videos at high quality of experience (QoE). Therefore, in this paper, we propose a femtocaching framework of QoE-oriented resource efficiency optimization for high performance of cooperative VASs over 5G two-tier cellular networks, where the collaboration between macro base stations (BSs) and femtocells are exploited to efficiently deliver videos to mobile users (MUs). Our proposed framework aims at solving two problems. The first problem is how to cache the videos in femtocells to minimize the bandwidth resource consumed at the BSs and wasted at femtocells while guaranteeing high hit rate and utilizing the available storage resource of femtocells. The second one is how to encode the videos into descriptions and assign them to each femtocell for transmission, so as to minimize the reconstructed distortion of received videos for high playback quality at the MUs. The simulation results are further provided to demonstrate the benefits of the proposed framework.

Internet of things (IoT) paradigm is becoming ubiquitous in everyday life. IoT-based systems are increasingly getting deployed in generic household, healthcare, public utilities, etc., related application. The reason for such rapid acceptance is in majority due to the internet's feature of connect from anywhere. However, due to some weaknesses inherent with the internet itself, IoT deployments also face certain challenges. Though there is a growing number of IoT-related reference architectures, frameworks, guidelines, platforms and standards, majority of them are yet to address the concerns due to internet outage. Furthermore, such growing numbers of architectures, frameworks, etc., also means bountiful amounts of both opportunities and risks for IoT vendors and original equipment manufacturers (OEMs). Of course, the IoT-device consumers also run the risks if the purchased products frameworks incompatible. We present One IoT version 2 (v2), an IoT framework and protocol that addresses the internet outage scenario. Similar to version 1 (v1), One IoT v2 is also forward compatible.

A recent trend in Internet of Things (IoT) is to connect billions of ordinary objects to the Internet and allows these objects to exchange data for smarter services. As smartphones have widely spread in the world and generate various data, it will represent a large portion of heterogeneous interconnected IoT devices. This trend influence users to perceive that the usability of the smartphone mobile application represents the usability of the general IoT service. This article introduces a novel IoT middleware framework to improve the usability of a mobile application, and thereby improve the usability of the IoT service provided through the mobile application. The core idea of our self-adaptive IoT middleware framework is to monitor and analyze application user's behavior, identify symptoms reducing application usability, and autonomously improve the application's interface for users without any intervention from the application developer. The effectiveness of the proposed framework is shown through case studies comparing several different mobile applications from a same business domain.

Internet of Things, cognitive systems, and blockchain technology are three fields which have created numerous revolutions in software development. It seems that a combination among these fields may results in emerging a high potential and interesting field. Therefore, in this paper, we propose a framework for Internet of Things based on cognitive systems and blockchain technology. To the best of our knowledge, there is no framework for Internet of Things based on cognitive systems and blockchain. In order to study the applicability of the proposed framework, a recommender system based on the proposed framework is suggested. Since the proposed framework is novel, the suggested recommender system is novel. The suggested recommender system is compared with the existing recommender systems. The results show that the suggested recommender system has several benefits which are not available in the existing recommender systems.

Exploiting composition of mobile devices for maximizing user QoS under energy constraints in mobile grid

Battery driven computing devices such as laptops and cellular phones have become a necessity in this era. Mobile applications help us in daily life activities and with the rise of Internet of Things (IoT) new opportunities are open up to automate different task. However, batteries have their own limitations such as weight, cost, and size. Multiple applications and background processes running in parallel easily drain phone’s battery within 24 hours consequently annoying users by limited battery capacity. Repeated charge, recharge cycles steadily diminish the full capacity of batteries resulting in the immense decreased performance of the device. Therefore, mobile devices and mobile applications are in great need of energy-aware modules. In this paper, a survey is performed to identify the needs of the mobile user in the context of energy consumption problem. The results of survey lead authors to propose a middle layer energy aware framework to address this issue. The proposed framework highly relies on the association between the operating system, application, and end user. The main objective of the proposed framework is to maintain an energy-aware capability to facilitate end user and mobile applications. The major components of the proposed framework are processing engine, application classifier, application resource management, system profiling, application modes, power estimator and power policy management. Proposed framework also offers a policy manager algorithm based on research community feedback and survey's results. Proposed framework emphasizes on energy efficient execution of mobile operations for end user and operating systems.

The Internet of things (IoT) ecosystem has grown exponentially with the convergence of various technologies such as deep learning, sensor systems, and advances in computing platforms. With such a highly pervasive nature of “smart” devices, the nature of data being collected and processed can be increasingly private and require safeguards to ensure the data’s integrity and security. Physically unclonable functions (PUFs) have emerged as a lightweight, viable security protocol in the Internet of Things (IoT) framework. Malicious modeling of PUF architectures has proven to be difficult due to the inherently stochastic nature of PUF architectures. In this work, we show that knowledge of the underlying PUF structure is unnecessary to clone a PUF. We tackle the problem of cloning PUF-based edge nodes in different settings such as unencrypted, encrypted, and obfuscated challenges in an IoT framework. We present a novel non-invasive, architecture-independent, machine learning attack for robust PUF designs and can handle encryption and obfuscation-based security measures on the transmitted challenge response pairs (CRPs). We show that the proposed framework can successfully clone different PUF architectures, including those encrypted using two (2) different encryption protocols in DES and AES and with varying degrees of obfuscation. We also show that the proposed approach outperforms a two-stage brute force attack model. Finally, we offer a machine learning-based countermeasure, a discriminator, which can distinguish cloned PUF devices and authentic PUFs with an average accuracy of 96%. The proposed discriminator can be used for rapidly authenticating millions of IoT nodes remotely from the cloud server.

The purpose of this paper is to introduce a technology-oriented SCM (Supply Chain Management) development methodology, which can be used in the design of IoT (Internet of Things) frameworks especially characterized by supply chain processes. In order to meet DSC (Digital Supply Chain) expectations, two areas are examined in detail during the literature review. Firstly, the current SCM models are studied. Secondly, Industry 4.0 requirements had to be surveyed. As a consequence, challenges and gaps are identified for which we seek the solution during our research. Based on the results, it can be stated that digitization has definitely required an improved technological solution that IoT frameworks can provide. The result is a technology-driven, IoT-based SCM development methodology that serves as a basis for the design of such platforms, which will manage supply chains. To prove the feasibility of the proposed development methodology, the Arrowhead industrial IoT framework is used for validation.

Internet of Things has had a tremendous effect in several fields, including the healthcare sector, to enhance network operation and users' quality of experience. In healthcare applications, people with cognitive, mental, and physical impairment rely on some form of assistive mobility device for their mobility needs and a better quality of life. The traditional wheelchairs are effective for physical impairments but poorly suited for individuals with a combination of physical and cognitive or perceptual impairments. To accommodate users with cognitive impairment, several researchers have used technologies originally developed for mobile robots to create smart mobility devices. With this significant interest, real-time autonomous navigation for the healthcare sector still requires more attention. This paper presents a review of the different existing literature on the internet of things frameworks and multi-sensor fusion techniques for assistive mobility devices (smart wheelchair). An Internet of things framework that takes into consideration scalability and security is proposed. A multi-sensor fusion pipeline for accurate localization and monitoring of assistive mobility devices for navigation purposes is also proposed.

Recently, there are significant improvements in the capabilities of mobile devices; rendering large terrain is tedious because of the constraint in resources of mobile devices. This paper focuses on the implementation of terrain rendering on mobile device to observe some issues and current constraints occurred. Experiments are performed using two datasets with results based on rendering speed and appearance to ascertain both the issues and constraints. The result shows a downfall of frame rate performance because of the increase of triangles. Since the resolution between computer and mobile device is different, the terrain surface on mobile device looks more unrealistic compared to on a computer. Thus, more attention in the development of terrain rendering on mobile devices is required. The problems highlighted in this paper will be the focus of future research and will be a great importance for 3D visualization on mobile device.

Remote correspondence frameworks are exceedingly disposed to security perils. The critical usages of remote correspondence frameworks are in military, business, human administrations, retail, and transportations. These structures use wired, cell, or ad hoc frameworks. Remote sensor frameworks, actuator frameworks, and vehicular frameworks have gotten a fantastic thought in the open eye and industry. Of late, the Internet of things (IoT) has become broad research thought. The IoT is considered as possible destiny of the Web. In future, IoT will accept a vital activity and change our living styles, standards, similarly to game plans. The use of IoT in different applications is required to rise rapidly in the coming years. The IoT grants billions of devices, society, and organizations to connect with others and exchange information. Due to the extended usage of IoT contraptions, the IoT frameworks are slanted to various security strikes. The presence of successful security and assurance shows that IoT frameworks are incredibly expected to ensure protection, get the chance to control, and decency, among others. In this chapter, a complete assessment on security and insurance issues in IoT frameworks is provided.

We introduce a novel personalized E-commerce system through mobile devices. By providing mobile clients’ preferred service category or items in a shopping mall website, the problem of the limitation of resource of mobile devices can be solved. In this paper, the preferred service items are inferred by analyzing customers’ statistical preference transactions and consumption behaviors in the website. In computing the statistical preference transactions, we consider the ratio of the length of each service page and customers’ staying time on it. Also, our system dynamically provides the personalized E-commerce service according to the three different cases such as the beginning stage, the positive response, and the negative response. In the experimental section, we demonstrate our personalized E-commerce service system and show how much the resource of mobile devices can be saved.

SummaryMobile devices play a vital role in people's day‐to‐day activities and are essential for communication, accessing Internet resources, entertainment, and so forth. In most cases, the performance of mobile applications is restricted due to the inadequate resources of mobile specifications such as controlled battery power, predetermined storage, and limited processing competence. Thus to improve the processing efficiency of resource‐constrained mobile devices, this research proposes a model developed on offloading technique based on the recent literature observations which transfer the resource‐consuming tasks from mobile devices to proximate computing entities. This generic architecture aiming for resource augmentation is formulated with five fundamental components including a mobile device, offloading engine, resource augmentation engine, scheduler, and synchronizer. The offloading engine identifies the resource‐intensive tasks that need to be executed on external entities using soft computing techniques such as neural network training algorithms, fuzzy logic, and neuro‐fuzzy logic processing. The augmentation engine chooses feasible edge computing entities such as Arduino, Raspberry PI controller, and fog devices. The scheduler prioritizes the resource‐consuming tasks for offloading based on their importance. The synchronizer coordinates all the central components by updating the execution status of tasks at regular intervals of time. Further extension of this research work, based on the proposed architecture three resource augmentation frameworks are developed namely (a) an adaptive proximate computing framework (b) a web service‐based IoT framework, and (c) a neuro‐fuzzy hybrid framework. Moreover, these frameworks are realized through the development of resource‐efficient intelligent edge computing IoT mobile apps namely (a) an inventory monitoring app (b) a lecture recording app, and (c) an intelligent transport app. The performance of these three resource augmentation frameworks is analyzed through the simulation results and it illustrates that the neuro‐fuzzy hybrid framework outperforms the other two. The outcome of the proposed research contributions improves the effectiveness of mobile communication by providing seamless services to mobile users regardless of their resource‐limited devices. Besides the devised edge computing architecture supports mobile application developers in the design and deployment of resource‐rich mobile applications in low‐specification mobile devices. Also, there is a strong scope for implementing the proposed generic architecture as an industrial smart product with adequate hardware and software configurations.