Efficient IoT Research Articles

An Energy Efficient Architecture of IoT based on Service Oriented Architecture (SOA)

In present scenario, IoT is a platform where every day gadgets become smarter, each day processing will become shrewd, and every day verbal exchange becomes informative. Even as the IoT is still searching for its possess form, its results have already stared in making exquisite strides as a universal solution media for the associated situation. Study focused on architecture does always pave the conformation of associated discipline. The shortage of overall architectural abilities is at this time resisting the researchers to get by way of the scope of procedures based on energy efficient IoT. In this manuscript a Cloud Centric View of IoT Framework and an energy efficient architecture of IoT based on Service Oriented Architecture (SoA) with the algorithm has been proposed.

An efficient IoT cloud energy consumption based on genetic algorithm

Cloud computing is a promising technology which enables processing a great amount of data. In a large scale IoT infrastructure, optimum allocation of virtual machines to the physical hosts leads to reduce energy consumption of data centers. Moreover, it may prevent pollution of the environment and improve the efficiency. The comprehensive study of this research shows that employing the various methods of virtualization, proper combination of these methods and applying evolutionary strategies is promising to develop new algorithms. The developed novel algorithms could improve the energy efficiency of cloud computing. In this study, an effort is made to provide an optimum virtual machines allocation to physical hosts with employing imperialistic competitive (IC) and genetic algorithms (GA). Toward that end, the crossover operation from GA is mixed with IC. Cloudsim software is used for simulation and Netbean software for implementation. Considerable improvement on energy consumption is achieved through the proposed method.

Development of Power Consumption Models for ESP8266-Enabled Low-Cost IoT Monitoring Nodes

The development of energy and cost efficient IoT nodes is very important for the successful deployment of IoT solutions across various application domains. This paper presents energy models, which will enable the estimation of battery life, for both time-based and event-based low-cost IoT monitoring nodes. These nodes are based on the low-cost ESP8266 (ESP) modules which integrate both transceiver and microcontroller on a single small-size chip and only cost about $2. The active/sleep energy saving approach was used in the design of the IoT monitoring nodes because the power consumption of ESP modules is relatively high and often impacts negatively on the cost of operating the nodes. A low energy application layer protocol, that is, Message Queue Telemetry Transport (MQTT) was also employed for energy efficient wireless data transport. The finite automata theory was used to model the various states and behavior of the ESP modules used in IoT monitoring applications. The applicability of the models presented was tested in real life application scenarios and results are presented. In a temperature and humidity monitoring node, for example, the model shows a significant reduction in average current consumption from 70.89 mA to 0.58 mA for sleep durations of 0 and 30 minutes, respectively. The battery life of batteries rated in mAh can therefore be easily calculated from the current consumption figures.

Energy Efficient IoT Virtualization Framework With Peer to Peer Networking and Processing

In this paper, an energy efficient IoT virtualization framework with peer-to-peer (P2P) networking and edge processing is proposed. In this network, the IoT task processing requests are served by peers. The peers in our work are represented by IoT objects and relays that host virtual machines (VMs). We have considered three scenarios to investigate the saving in power consumption and the system capabilities in terms of task processing. The first scenario is a ‘relays only’ scenario, where the task requests are processed using relays only. The second scenario is an ‘objects only’ scenario, where the task requests are processed using the IoT objects only. The last scenario is a hybrid scenario, where the task requests are processed using both IoT objects and VMs. We have developed a mixed integer linear programming (MILP) model to maximize the number of processing tasks served by the system, and minimize the total power consumed by the IoT network. Based on the MILP model principles, we developed an energy efficient virtualized IoT P2P networks heuristic (EEVIPN). Our results show that the hybrid scenario serves up to 77% (57% on average) processing task requests, but with higher energy consumption compared to the other scenarios. The relays only scenario serve 74% (57% on average) of the processing task requests with 8% saving in power consumption compared to the hybrid scenario. In contrast, 28% (22% on average) of task requests can be handled by the objects only scenario with up to 62% power saving compared to the hybrid scenario.

Energy efficient fog-assisted IoT system for monitoring diabetic patients with cardiovascular disease

Blood glucose plays an important role in maintaining body’s activities. For example, brain only uses glucose as its energy source. However, when blood glucose level is abnormal, it causes some serious consequences. For instance, low-blood glucose phenomenon referred to as hypoglycemia can cause heart repolarization and induce cardiac arrhythmia causing sudden cardiac deaths. Diabetes, which can be viewed as a high-blood glucose level for a long period of time, is a dangerous disease as it can directly or indirectly cause heart attack, stroke, heart failure, and other vicious diseases. A solution for reducing the serious consequences caused by diabetes and hypoglycemia is to continuously monitor blood glucose level for real-time responses such as adjusting insulin levels from the insulin pump. Nonetheless, it is a misstep when merely monitoring blood glucose without considering other signals or data such as Electrocardiography (ECG) and activity status since they have close relationships. When hypoglycemia occurs, a fall can easily occur especially in case of people over 65 years old. Fall’s consequences are more hazardous when a fall is not detected. Therefore, we present a Fog-based system for remote health monitoring and fall detection. Through the system, both e-health signals such as glucose, ECG, body temperature and contextual data such as room temperature, humidity, and air quality can be monitored remotely in real-time. By leveraging Fog computing at the edge of the network, the system offers many advanced services such as ECG feature extraction, security, and local distributed storage. Results show that the system works accurately and the wearable sensor node is energy efficient. Even though the node is equipped with many types of sensors, it can operate in a secure way for up to 157 h per a single charge when applying a 1000 mAh Lithium battery.

IoT Enabled RFID Authentication and Secure Object Tracking System for Smart Logistics

Object tracking is a fundamental problem in Supply Chain Management (SCM). Recent innovations eliminate the difficulties in traditional approach such as manual counting, locating the object, and data management. Radio Frequency Identification (RFID) implementation in SCM improves the visibility of real-time object movement and provide solutions for anti-counterfeiting. RFID is a major prerequisite for the IoT, which connects physical objects to the Internet. Various research works have been carried out to perform object tracking using GPS, video cameras, and wifi technology. These methods just hope to see the actual object, but not the characteristic changes of the object due to environmental changes. After reviewing the implementation of latest technologies in object tracking system, it is expected that the security and privacy risks in large-scale IoT systems are to be eliminated and an efficient IoT services are provided to SCM. In this work, an architecture is proposed for a fine-grained IoT-enabled online object tracking system. Cloud storage used in this architecture enhances the scalability and data management. We propose a novel secure and efficient end to end authentication protocol that is based on a symmetric key cryptosystem and one-way hash function. A new scheme is also proposed to address object tracking communication flow which uses the secret key established in the authentication process. A formal security analysis method, GNY logic is used and proved that the proposed protocol achieves an end to end authentication. Tag/Reader impersonation attack and replay attack are prevented in the proposed scheme. It also preserves forward and backward secrecy. Performance analysis shows that the proposed protocol is not storage and computationally intensive.

RF Energy Harvesting and Transfer for Spectrum Sharing Cellular IoT Communications in 5G Systems

This paper proposes an energy and spectrum efficient IoT network for 5G systems where spectrum is shared with the cellular system for spectrum efficiency and energy harvesting and energy transfer are utilized for energy efficiency. The IoT network, which consists of sensor nodes and a cluster head with a reliable energy source, reuses part of the cellular band whenever the cellular network does not utilize it. The cluster head performs spectrum sensing, random scheduling of the sensor nodes, and schedules some idle time for energy transfer. The sensor nodes harvest RF energy from the cellular traffic and the transferred energy from the cluster head. Provided the sensor nodes have sufficient energy, they transmit collected sensory data when scheduled. The inter-play between the cellular and IoT network introduces trade-offs between the spectrum availability, energy availability, information, and energy transfer. This paper shows that for the same cellular traffic level, as the number of sensor nodes in the network increases, the IoT network utilization increases resulting in a multi-user gain thanks to the broadcast nature of the energy transfer. The results offer insights into different operational regimes and exposes what type of IoT applications may be feasible with such networks.

Level Converters for Ultra Low Power IoT Applications

For efficient ultra-low power IoT applications, working with various communication devices and sensors which operating voltages from subthreshold to superthreshold levels which requires wide variety of robust level converters for signal interfacing with low power dissipation. This paper proposes two topologies of level converter circuits that offer dramatic improvement in power and performance when compared to the existing level converters that shift signals from sub to super threshold levels for IoT applications. At 250 mV, the first proposed circuit - a modification of a tradition al current mirror level converter - offers the best energy efficiency with approximately seven times less energy consumption per operation than the existing design, but suffers from a slight reduction in performance. However, a second proposed circuit - based on a two-stage level converter - at the same voltage enhances performance by several orders of magnitude while still maintaining a modest improvement in energy efficiency. The Energy Delay Products (EDP) of the two proposed designs are equivalent and are approximately four times better than the best existing design. Consequently, the two circuit options either optimizes power or performance with improved overall EDP.

An Efficient IoT Based Smart Irrigation System and Plant Diseases Detection: A Review

The irrigation control and monitoring of the involved variables on the plant growth are actions that farmers must implement in their crops to save water resources and assessing the growth of the plant. In this paper, the literature is conducted on several authors’ works, their modern way of doing agriculture with IoT and image processing combination, thus the paper gives information about various techniques, algorithms, and architectures employed to detect the crop diseases in advance so that proper care can be taken to avoid it. Hence incorporating IoT with image processing gives improved detection ability in the agricultural system. The survey comprises several authors’ workouts of automated Irrigation and crop diseases Detection practices which are currently in use..

Deployment of Multi-Fuzzy Model Based Routing in RPL to Support Efficient IoT

IPv6 routing protocol for Low Power Lossy Network (LLN) is known as RPL protocol designed for the Internet of Things. In RPL, multicasting is performed by using SMRF and BMRF algorithm. These conventional multicast algorithms were not able to suppress the duplicate packets which minimize the Quality of Service (QoS) especially delay metric. Hence the main focus of this paper is to address the use of the RPL routing protocol, by proposing an objective function based on fuzzy logic. In RPL QoS is constructed by Destination Oriented Directed Acyclic Graph (DODAG) that plays a major role. The defined Objective function is achieved by novel Multi-fuzzy Logic (Ml-FL) model which includes three significant categories of metrics as (i) node oriented metrics, (ii) channel oriented metrics and (iii) link oriented metrics. Each metric is defined with three other parameters for effective parent node selection. To solve the complexity of Fuzzy logic, parallel processing of multiple fuzzy logic blocks is proposed. An enhanced-BMRF algorithm is proposed with the minimum of delay and duplicate packets. The effectiveness of the proposed RPL protocol is evaluated using IEEE 802.15.4 standard that is applied over OMNeT++ simulator. Finally, the simulation shows promising results of proposed RPL in terms of end-to-end delay, energy, hop count, packet delivery ratio and packet loss rate.

Deployment of Multi-Fuzzy Model Based Routing in RPL to Support Efficient IoT

IPv6 routing protocol for Low Power Lossy Network (LLN) is known as RPL protocol designed for the Internet of Things. In RPL, multicasting is performed by using SMRF and BMRF algorithm. These conventional multicast algorithms were not able to suppress the duplicate packets which minimize the Quality of Service (QoS) especially delay metric. Hence the main focus of this paper is to address the use of the RPL routing protocol, by proposing an objective function based on fuzzy logic. In RPL QoS is constructed by Destination Oriented Directed Acyclic Graph (DODAG) that plays a major role. The defined Objective function is achieved by novel Multi-fuzzy Logic (Ml-FL) model which includes three significant categories of metrics as (i) node oriented metrics, (ii) channel oriented metrics and (iii) link oriented metrics. Each metric is defined with three other parameters for effective parent node selection. To solve the complexity of Fuzzy logic, parallel processing of multiple fuzzy logic blocks is proposed. An enhanced-BMRF algorithm is proposed with the minimum of delay and duplicate packets. The effectiveness of the proposed RPL protocol is evaluated using IEEE 802.15.4 standard that is applied over OMNeT++ simulator. Finally, the simulation shows promising results of proposed RPL in terms of end-to-end delay, energy, hop count, packet delivery ratio and packet loss rate.

Energy Efficient IoT Sensor With RF Wake-Up and Addressing Capability

In this article, we present a complete design for an optimized energy-efficient sensor for use in Internet of Things networks based on the concept of radio wake-up, with embedded addressing capability. Experimental and analytical results demonstrate the validity of the proposed design in terms of low power consumption and efficient functionality compared to existing solutions that are based on periodic wake-up patterns.

Extracting and Exploiting Inherent Sparsity for Efficient IoT Support in 5G: Challenges and Potential Solutions

Besides enabling an enhanced mobile broadband, the next generation of mobile networks (5G) are envisioned for the support of massive connectivity for heterogeneous Internets of Things. These IoTs are envisioned for a large number of use cases including smart cities, environment monitoring, smart vehicles, and so on. Unfortunately, most IoTs have very limited computing and storage capabilities and need cloud services. Hence, connecting these devices through 5G systems requires huge spectrum resources in addition to handling massive connectivity and improved security. This article discusses the challenges facing the support of IoTs through 5G systems. The focus is devoted to discussing physical layer limitations in terms of spectrum resources and radio access channel connectivity. We show how sparsity can be exploited for addressing these challenges, especially in terms of enabling wideband spectrum management and handling the connectivity by exploiting device-to-device communications and edge cloud. Moreover, we identify major open problems and research directions that need to be explored toward enabling the support of massive heterogeneous IoTs through 5G systems.

Lightweight adaptive Random-Forest for IoT rule generation and execution

The area of the Internet of Things is growing rapidly. The volume of transmitted data over the various sensors is growing accordingly. Sensors typically are low in resources of storage, memory and processing power. Data security and privacy are part of the major concerns and drawbacks of this growing domain. Sensor traffic analysis has become an increasingly important domain to protect IoT infrastructures from intruders. An IoT network intrusion detection system is required to monitor and analyze the traffic and predict possible attacks. Machine leaning techniques can automatically extract normal and abnormal patterns from a large set of training sensors data. Due to the high volume of traffic and the need for real-time reaction, accurate threat discovery is mandatory. This work focuses on designing a lightweight comprehensive IoT rules generation and execution framework. It is composed of three components, a machine learning rule discovery, a threat prediction model builder and tools to ensure timely reaction to rules violation and un-standardized and ongoing changes in traffic behavior. The generated detection model is expected to identify in real-time exceptions and notify the system accordingly. We use Random-Forest (RF) as the machine learning platform for rules discovery and real-time anomaly detection. To allow RF adaptation to IoT we propose several improvements to make it lightweight and propose a process that combines IoT network capabilities; messaging and resource sharing, to build a comprehensive and efficient IoT security framework.

Efficient IoT Gateway over 5G Wireless: A New Design with Prototype and Implementation Results

The growth of IoT is expected to herald a better quality of life and open up new industrial opportunities. However, it is also raising new challenges in resource constrained wireless networks. Originally designed for human-to-human wireless communications, present wireless networks fail to satisfy the huge connectivity and varying traffic requirements of IoT. Next generation 5G wireless networks are expected to exploit emerging features, like mmWave, massive MIMO, and C-RAN, for providing the enormous connectivity, resource pooling, and energy efficiency required to support commercial rollout of IoT. Exploring these emerging features, we develop 5G-enabled IoT gateways to communicate with the RRHs of 5G C-RAN. The gateways are endowed with efficient compression schemes to significantly improve uplink resource utilization. Our 5G C-RAN prototyping and laboratory experimental results point out a huge opportunity for supporting a massive number of IoT-enabled devices by sophisticated 5G C-RAN deployment and efficient IoT gateway development.

Manhole-cover Shaped Antenna Design for Underground Facilities Monitoring System

In this paper, system requirements to implement efficient underground IoT systems are overviewed, and novel manhole-cover shaped antenna is proposed. To verify its performance, the antenna prototype is designed for 900MHz-band operation, and it provides an omni-directional radiation pattern for reaching wide coverage.

Bio Inspired Routing Algorithm and Efficient Communications within IoT

IoT does not stop integrating and connecting more complex objects with different architectures, resources and constraints. This is why the conventional communication architectures and protocols designed for the existing wireless networks become ineffective in the context of IoT. Indeed, IoT communications parameters and constraints must be taken into account by all the important mechanisms that intervene in the communication process, such as routing. This article surveys a number of proposed routing algorithms for efficient communications within wireless networks and IoT. Based on the limitations of these works, a novel routing algorithm, called EICAntS (Efficient IoT Communications based on Ant System), is proposed to improve the route selection mechanism by exploiting the advantages of an ant colony system. The evaluation results of EICAntS recorded an improvement in delay, throughput, lifetime and conservation of energy.

A Novel Scheme for an Energy Efficient Internet of Things Based on Wireless Sensor Networks.

One of the emerging networking standards that gap between the physical world and the cyber one is the Internet of Things. In the Internet of Things, smart objects communicate with each other, data are gathered and certain requests of users are satisfied by different queried data. The development of energy efficient schemes for the IoT is a challenging issue as the IoT becomes more complex due to its large scale the current techniques of wireless sensor networks cannot be applied directly to the IoT. To achieve the green networked IoT, this paper addresses energy efficiency issues by proposing a novel deployment scheme. This scheme, introduces: (1) a hierarchical network design; (2) a model for the energy efficient IoT; (3) a minimum energy consumption transmission algorithm to implement the optimal model. The simulation results show that the new scheme is more energy efficient and flexible than traditional WSN schemes and consequently it can be implemented for efficient communication in the IoT.

A network architecture solution for efficient IOT WSN backhauling: challenges and opportunities

At present, Sensor Networks and the emerging Internet of Things paradigm are playing a key role in the industry and in academic research. In this article we outline a common scenario, currently arising standards, and other emerging technologies having a direct impact on network architecture. In particular we introduce a novel network architecture based on an M2M Gateway and discuss it in relation to smart building applications. The proposed network architecture will improve services for users and will offer new opportunities for both service providers and network operators.

Design of Landslide Monitoring and Early Warning System Based on Internet of Things

This paper designed a kind of efficient IOT transmission platform based on wireless sensor network and GPRS network. Using the multi-mode sensor nodes composed of temperature-humidity senor and acceleration sensor, realize the effective detection of geological disaster, such as landslide and debris flow. After experimental verification, the IOT platform based on the two levels of network structures, can effectively transmit the monitoring point's information, such as the surface humidity, tilt angle and displacement. The system has long transmission distance and low power consumption.The system will have certain engineering value in the field of geological monitoring.