Internet-of-things-based smart environments: state of the art, taxonomy, and open research challenges

Ahmed, Ejaz; Yaqoob, Ibrar; Gani, Abdullah; Imran, Muhammad; Guizani, Mohsen

doi:10.1109/mwc.2016.7721736

Cited by 383 publications

(204 citation statements)

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“…The architectures and frameworks of cognitive radio-based IoT systems are surveyed in [26], while highlighting open issues, research challenges and applications related to it. The research efforts in IoT-based smart environments have been surveyed on the basis of network types, local area wireless standards, technologies and human life [27]. The framework of the Internet of Vehicles is presented in [3], while emphasizing motivation, five layered architecture with functionalities of each layer, network model, challenges and future aspects inside the IoT.…”

Section: Related Literature Reviewsmentioning

confidence: 99%

Cross-Layer Energy Optimization for IoT Environments: Technical Advances and Opportunities

Kumar

Kaiwartya

et al. 2017

Energies

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Abstract:Energy efficiency is a significant characteristic of battery-run devices such as sensors, RFID and mobile phones. In the present scenario, this is the most prominent requirement that must be served while introducing a communication protocol for an IoT environment. IoT network success and performance enhancement depend heavily on optimization of energy consumption that enhance the lifetime of IoT nodes and the network. In this context, this paper presents a comprehensive review on energy efficiency techniques used in IoT environments. The techniques proposed by researchers have been categorized based on five different layers of the energy architecture of IoT. These five layers are named as sensing, local processing and storage, network/communication, cloud processing and storage, and application. Specifically, the significance of energy efficiency in IoT environments is highlighted. A taxonomy is presented for the classification of related literature on energy efficient techniques in IoT environments. Following the taxonomy, a critical review of literature is performed focusing on major functional models, strengths and weaknesses. Open research challenges related to energy efficiency in IoT are identified as future research directions in the area. The survey should benefit IoT industry practitioners and researchers, in terms of augmenting the understanding of energy efficiency and its IoT-related trends and issues.

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Section: Related Literature Reviewsmentioning

confidence: 99%

Cross-Layer Energy Optimization for IoT Environments: Technical Advances and Opportunities

Kumar

Kaiwartya

et al. 2017

Energies

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“…Containers allow for avoiding the overhead due to virtualized hardware requested by hypervisor‐based virtualization, thus enabling fast initialization and dense deployment of services, as experimented in a previous study . All these features make containers extremely attractive for usage not only in datacentres, but also in edge nodes, such as cloudlets and IoT gateways . Nevertheless, enhanced orchestration solutions are required to fully exploit the potential of containerized services for IoT devices at the edge of the network …”

Section: Introductionmentioning

confidence: 99%

“…14 All these features make containers extremely attractive for usage not only in datacentres, but also in edge nodes, such as cloudlets and IoT gateways. 15,16 Nevertheless, enhanced orchestration solutions are required to fully exploit the potential of containerized services for IoT devices at the edge of the network. [17][18][19] In this paper, we investigate a novel approach to better support user mobility for stateless microservices.…”

Section: Introductionmentioning

confidence: 99%

Providing ultra‐short latency to user‐centric 5G applications at the mobile network edge

Farris

Taleb

Flinck

2017

Trans Emerging Tel Tech

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Mobile Edge Computing (MEC) will play a key role in next-generation mobile networks to extend the range of supported delay-sensitive applications. Furthermore, an increasing attention is paid to provide user-centric services, to better address the strict requirements of novel immersive applications. In this scenario, MEC solutions need to efficiently cope with user mobility, which requires fast relocation of service instances to guarantee the desired Quality of Experience. However, service migration is still an open issue, especially for resource-constrained edge nodes interconnected by high-latency and low-bandwidth links. In this paper, by leveraging the potential of lightweight container-based virtualization techniques, we investigate a novel approach to support service provisioning in dynamic MEC environments. In particular, we present a framework where proactive service replication for stateless applications is exploited to drastically reduce the time of service migration between different cloudlets and to meet the latency requirements. The performance evaluation shows promising results of our approach with respect to classic reactive service migration. INTRODUCTIONSeveral classes of new applications are challenging the current network and cloud infrastructures. As illustrated in a recent report from International Telecommunication Union, 1 applications such as tactile internet, mobile gaming, and augmented reality are pushing new requirements, especially in terms of latency. To guarantee the desired Quality of Experience (QoE) for the end user, not only the network access delay, but also the cloud service processing should be performed within a few milliseconds. To achieve the 1 ms latency dream for the next-generation 5G cloud-enabled services, both network and cloud providers should jointly cooperate and investigate novel approaches. In this regard, academic and industrial research communities have focused on Mobile Edge Computing (MEC) solutions to exploit processing and storage capabilities at the edge of the network, as near as possible to the end user. 2,3 Indeed, the deployment of micro datacentres in the network access points, known as cloudlets, 4,5 can guarantee remarkable benefits of low latency interaction and scalability, by balancing the workload over the distributed edge infrastructure. Furthermore, bringing the cloudlet concept into the Internet of Things (IoT) scenario results in the definition of the so-called Fog Computing paradigm, which envisages a highly virtualized infrastructure composed of distributed edge nodes to monitor and analyse the most time-sensitive data generated by network connected devices. [6][7][8] In a MEC environment, a key challenge is represented by the user mobility, which could cause significant application degradation, even in small scenarios, as reported in a previous study.9,10 To guarantee service continuity and to meet the strict requirements of application latency, the MEC framework needs to properly cope with service migration between edge nodes. I...

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“…Protecting data is today an essential prerequisite in different applications. Hence, the implementation and the construction of security systems for smart homes network between the sensing nodes and the electricity management server are a major concern to reduce energy consumption . The confidentiality and integrity of electrical information must be provided to assure timely response …”

Section: Introductionmentioning

confidence: 99%

“…Hence, the implementation and the construction of security systems for smart homes network between the sensing nodes and the electricity management server are a major concern to reduce energy consumption. 6,7 The confidentiality and integrity of electrical information must be provided to assure timely response. 8,9 However, the implementation of a secure and efficient energy management system in smart home is very difficult because of the following challenges.…”

Section: Introductionmentioning

confidence: 99%

A secure electric energy management in smart home

Mbarek

Meddeb

Jaballah

et al. 2017

Int J Communication

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Summary We formulate and study an intelligent and secure house electricity system on the basis of the Internet of Things. The security of sensitive data collected and transmitted by sensor nodes installed in home appliances and household electrical devices is critical, since the transmitted data can be easily manipulated by different types of attacks. The confidentiality and integrity of household electrical devices information must be assured to insure appropriate and timely response. Providing a secure aggregation mechanism is thus very essential to protect the integrity and the privacy of data aggregation. In this paper, we propose a secure data aggregation scheme that exploits compressed sensing (CS) to reduce the communication overhead of collected electrical power measurement. Then, the data will be encrypted by each sensor node after the compressing phase, and a cryptography hash algorithm is used to ensure data integrity. Finally, we apply an aggregation function for data priorities and then send the data for diagnosis. Then, we will present simulation results for the evaluation of the proposed electric energy management system.

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Internet-of-things-based smart environments: state of the art, taxonomy, and open research challenges

Cited by 383 publications

References 10 publications

Cross-Layer Energy Optimization for IoT Environments: Technical Advances and Opportunities

Cross-Layer Energy Optimization for IoT Environments: Technical Advances and Opportunities

Providing ultra‐short latency to user‐centric 5G applications at the mobile network edge

A secure electric energy management in smart home

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