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Proceedings ArticleDOI

EEIoT: Energy efficient mechanism to leverage the Internet of Things (IoT)

01 Oct 2016-Vol. 2016, pp 1-4
TL;DR: EEIoT proposes an Energy Efficient Internet of Things technique that deals and regulates energy factors in IoT efficiently and presents a comparative result against existing methods on energy consumption factors.
Abstract: IoT has become popular in smart vision of world development. It is more and more complex due to billions of heterogeneous wireless devices communicating each other. Each wireless sensor node or device consumes more energy for its communication. There are various techniques for reduction of this energy Minimum Energy Consumption Algorithm(MECA). But these techniques are inefficient due to direct deployment of Sensor nodes in the network without considering the more energy consume when transmitting. EEIoT proposes an Energy Efficient Internet of Things technique that deals and regulates energy factors in IoT efficiently. It is a self-adaptive technique that aims to minimize the energy harvesting in significant manner on Internet of Things. Finally, it presents a comparative result against existing methods on energy consumption factors.
Citations
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Journal ArticleDOI
TL;DR: Simulation results proved that the proposed IoT Energy Management Scheme outperformed the traditional IoT system with respect to the following performance metrics: energy consumption rate, number of failed nodes due to energy loss, throughput, and network lifetime.
Abstract: The Internet of Things (IoT) has important applications in all aspects of our lives in areas such as business, military, security, and health. It is known that most IoT node designs are energy constrained. Therefore, maintaining an ideal energy consumption rate has become one of the most important challenges in the IoT research field. In this paper, an IoT Energy Management Scheme (EMS) is proposed. In this system, heterogeneous types of energy-constrained nodes are considered. The proposed EMS comprises three strategies. The first strategy minimizes the volume of data that may be transmitted through the IoT environment. The second strategy schedules the work of the critical energy IoT nodes. The third strategy provides a fault tolerance scenario that can be applied to address inevitable energy problems faced by IoT nodes. Finally, to test the proposed EMS, the NS2 network simulator is used to construct an intensive simulation of the IoT environment. The simulation results proved that the proposed EMS outperformed the traditional IoT system with respect to the following performance metrics: energy consumption rate, number of failed nodes due to energy loss, throughput, and network lifetime.

57 citations


Cites background from "EEIoT: Energy efficient mechanism t..."

  • ...In addition, this considered that the WSN is an entire IoT system which is an inaccurate definition [27]....

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Book ChapterDOI
01 Jan 2019
TL;DR: Internet of Things (IoT) is the interconnection of physical entities to be combined with embedded devices like sensors, activators connected to the Internet which can be used to communicate from human to things for the betterment of the life.
Abstract: Internet of Things (IoT) is the interconnection of physical entities to be combined with embedded devices like sensors, activators connected to the Internet which can be used to communicate from human to things for the betterment of the life. Information exchanged among the entities or objects, intruders can attack and change the sensitive data. The authentication is the essential requirement for security giving them access to the system or the devices in IoT for the transmission of the messages. IoT security can be achieved by giving access to authorized and blocking the unauthorized people from the internet. When using traditional methods, it is not guaranteed to say the interaction is secure while communicating. Digital certificates are used for the identification and integrity of devices. Public key infrastructure uses certificates for making the communication between the IoT devices to secure the data. Though there are mechanisms for the authentication of the devices or the humans, it is more reliable by making the authentication mechanism from X.509 digital certificates that have a significant impact on IoT security. By using X.509 digital certificates, this authentication mechanism can enhance the security of the IoT. The digital certificates have the ability to perform hashing, encryption and then signed digital certificate can be obtained that assures the security of the IoT devices. When IoT devices are integrated with X.509 authentication mechanism, intruders or attackers will not be able to access the system, that ensures the security of the devices.

20 citations

Journal ArticleDOI
TL;DR: The authors jointly consider the compressive sensing (CS) theory, cluster-based routing, and sink mobility to propose a data collection method named WDAT-OMS, which uses the CS theory along with load-balanced data aggregation trees to route packets from sensors to the corresponding cluster heads (CHs).
Abstract: This study addresses the problems of energy and delay in wireless sensor networks equipped with mobile sinks. The authors jointly consider the compressive sensing (CS) theory, cluster-based routing, and sink mobility to propose a data collection method named `weighted data aggregation trees with optimal mobile sink(s) (WDAT-OMS)'. The proposed scheme relies on a two-level architecture in which sensors are clustered at the first level. WDAT-OMS uses the CS theory along with load-balanced data aggregation trees to route packets from sensors to the corresponding cluster heads (CHs). In this regard, they present an efficient metric named `energy-and distance-aware CH selection' to fairly distribute the energy consumption among different sensors. At the second level, one or more sinks traverse the network to collect the aggregated data of CHs. As an advantage, WDAT-OMS not only balances the energy consumption among different sensors but also increases the network scalability. Numerical results demonstrate that the proposed algorithm reduces energy consumption in comparison with `centralised clustering algorithm', `energy-aware CS-based data aggregation', and `energy-balanced high-level data aggregation tree `by 66%, 62%, and 63% for an average number of clusters, respectively. It also decreases the sink delay in comparison with the `single-hop data-gathering problem' by 10%.

12 citations

Book ChapterDOI
01 Jan 2020
TL;DR: This paper focuses on one of the most important research domains in MMBD IoT, Energy Conservation, and focuses on the investigation of existing technologies and mechanisms in the above domains.
Abstract: In the recent days, wide-ranging cellular devices and purchaser gadgets in the Internet of Things (IoT) have created immense multimedia information in different types of media (for example, content, pictures, video, and sound). Due to this, there is a great increase in the research challenges for creating strategies and tools in addressing Multimedia Big Data (MMBD) for future IoT. As the worldwide framework for the ongoing data society, IoT empowers progressed benefits by interconnecting (virtual as well as physical) things dependent on existing and advancing interoperable data and correspondence advancements. An immense measure of connected objects will be installed universally in a couple of years. In the meantime, the utilization of MMBD has been developing colossally since recent years, while organizations are rapidly getting on what they remain to pick up. Actually, these two advances are affecting and molding one another. In spite of the fact that they emerge from various application situations, MMBD can be together utilized with machine learning, AI, factual, and other progressed procedures, models, and techniques to investigate or locate the profound incentive behind the immense information originated from IoT. Actually, the registering knowledge, including transformative calculation, neural systems, and the fuzzy hypothesis, is relied upon to assume a vital job for these issues. It is as yet one of the most scorching and most challenging fields to create novel processing knowledge for the reasonable situations concerned with the MMBD for future IoT. In this paper, we focus on one of the most important research domains in MMBD IoT, Energy Conservation. IoT devices communicate through the wireless communication medium and are expected to transmit information whenever needed. The battery life of IoT devices is an important concern for researchers and device manufacturers. Many exhaustive efforts have been put by researchers in this area. Since most IoT devices are usually deployed in remote and hostile environments out of reach for human users, it may not be possible to charge and recharge batteries frequently. Moreover, in MMBD IoT applications, a large volume of multimedia traffic needs to be processed, which consumes precious network resources such as bandwidth and energy. Thus, devising protocols for conserving energy of IoT devices in such environments has become a very interesting topic of research. There are various ways to achieve energy conservation in the MMBD IoT environment. Some of the popular research inclinations are designing energy-efficient communication protocols, developing of mechanisms that enable IoT devices to self-generate, recycle, store and harvest energy, and modifying underlying protocol stack of communication technologies to support energy efficiency. Our paper mainly focuses on the investigation of existing technologies and mechanisms in the above domains. We first present the need for energy conservation briefly and then discuss the key points of existing solutions for saving energy in IoT communications. At the end of the paper, we summarize our findings to describe the advantages and limitations of existing mechanisms and provide insights into possible research directions.

7 citations

Proceedings ArticleDOI
01 Feb 2019
TL;DR: A survey on issues such as energy efficient communication among nodes, interoperability between different heterogeneous data and domains, and data management of huge sensed data is presented.
Abstract: The Internet has become an important part of today's human lifestyle. Due to massive demand and need, researchers went further than just using computers to access the internet. These researchers led to the birth of the Internet of Things. It also has some issues such as energy-efficient communication, installation cost, inconvenience to users, management of large sensed data and the interoperability among domains. This paper presents a survey on issues such as energy efficient communication among nodes, interoperability between different heterogeneous data and domains, and data management of huge sensed data.

5 citations


Cites background from "EEIoT: Energy efficient mechanism t..."

  • ...2) Based on Node Deployment K. Suresh et al.[8] proposed an EEIoT which addresses and manages energy factors in IoT efficiently....

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  • ...Sharma [8] 2016 NO YES NO NO NO Reduced power consumption...

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  • ...Suresh et al.[8] proposed an EEIoT which addresses and manages energy factors in IoT efficiently....

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References
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01 Jan 1999
TL;DR: The phrase "Internet of Things" started life as the title of a presentation I made at Procter & Gamble (P&G) in 1999 as mentioned in this paper, which was more than just a good way to get executive attention.
Abstract: Jun 22, 2009—I could be wrong, but I'm fairly sure the phrase "Internet of Things" started life as the title of a presentation I made at Procter & Gamble (P&G) in 1999. Linking the new idea of RFID in P&G's supply chain to the then-red-hot topic of the Internet was more than just a good way to get executive attention. It summed up an important insight—one that 10 years later, after the Internet of Things has become the title of everything from an article in Scientific American to the name of a European Union conference, is still often misunderstood.

2,608 citations

Journal ArticleDOI
TL;DR: In this paper, a compressed sensing-based data sampling and data acquisition in wireless sensor networks and the Internet of Things (IoT) has been investigated, in which the end nodes measure, transmit, and store the sampled data in the framework.
Abstract: The emerging compressed sensing (CS) theory can significantly reduce the number of sampling points that directly corresponds to the volume of data collected, which means that part of the redundant data is never acquired. It makes it possible to create standalone and net-centric applications with fewer resources required in Internet of Things (IoT). CS-based signal and information acquisition/compression paradigm combines the nonlinear reconstruction algorithm and random sampling on a sparse basis that provides a promising approach to compress signal and data in information systems. This paper investigates how CS can provide new insights into data sampling and acquisition in wireless sensor networks and IoT. First, we briefly introduce the CS theory with respect to the sampling and transmission coordination during the network lifetime through providing a compressed sampling process with low computation costs. Then, a CS-based framework is proposed for IoT, in which the end nodes measure, transmit, and store the sampled data in the framework. Then, an efficient cluster-sparse reconstruction algorithm is proposed for in-network compression aiming at more accurate data reconstruction and lower energy efficiency. Performance is evaluated with respect to network size using datasets acquired by a real-life deployment.

478 citations

01 Jan 2014
TL;DR: This paper briefly introduces the CS theory with respect to the sampling and transmission coordination during the network lifetime through providing a compressed sampling process with low computation costs, and proposes a CS-based framework for IoT and an efficient cluster-sparse reconstruction algorithm for in-network compression.

458 citations


"EEIoT: Energy efficient mechanism t..." refers background in this paper

  • ...based [1]Sensor network communication[17][21][22] is benefit more compare to continuous data communication[3]suggested Energy management optimization strategy has three phases....

    [...]

Journal ArticleDOI
TL;DR: Merging the virtual World Wide Web with nearby physical devices that are part of the Internet of Things gives anyone with a mobile device and the appropriate authorization the power to monitor or control anything.
Abstract: Merging the virtual World Wide Web with nearby physical devices that are part of the Internet of Things gives anyone with a mobile device and the appropriate authorization the power to monitor or control anything.

422 citations


"EEIoT: Energy efficient mechanism t..." refers background in this paper

  • ...A drastic progress of the current Internet into a Network of interconnected objects[24] that not only yields information from the sensing and interacts with real world objects, but also uses surviving Internet standards to provide services[9]....

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Journal ArticleDOI
TL;DR: This paper presents the authors' recent work in this area, which includes a centralized cognitive medium access control (MAC) protocol, a distributed cognitive MAC protocol, and a specially designed routing protocol for cognitive M2M networks.
Abstract: Machine-to-machine (M2M) communications enables networked devices to exchange information among each other as well as with business application servers and therefore creates what is known as the Internet-of-Things (IoT). The research community has a consensus for the need of a standardized protocol stack for M2M communications. On the other hand, cognitive radio technology is very promising for M2M communications due to a number of factors. It is expected that cognitive M2M communications will be indispensable in order to realize the vision of IoT. However cognitive M2M communications requires a cognitive radio-enabled protocol stack in addition to the fundamental requirements of energy efficiency, reliability, and Internet connectivity. The main objective of this paper is to provide the state of the art in cognitive M2M communications from a protocol stack perspective. This paper covers the emerging standardization efforts and the latest developments on protocols for cognitive M2M networks. In addition, this paper also presents the authors’ recent work in this area, which includes a centralized cognitive medium access control (MAC) protocol, a distributed cognitive MAC protocol, and a specially designed routing protocol for cognitive M2M networks. These protocols explicitly account for the peculiarities of cognitive radio environments. Performance evaluation demonstrates that the proposed protocols not only ensure protection to the primary users (PUs) but also fulfil the utility requirements of the secondary M2M networks.

310 citations


"EEIoT: Energy efficient mechanism t..." refers background in this paper

  • ...based [1]Sensor network communication[17][21][22] is benefit more compare to continuous data communication[3]suggested Energy management optimization strategy has three phases....

    [...]