scholarly journals Performance Evaluation of Cryptographic Algorithms over IoT Platforms and Operating Systems

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Geovandro C. C. F. Pereira ◽  
Renan C. A. Alves ◽  
Felipe L. da Silva ◽  
Roberto M. Azevedo ◽  
Bruno C. Albertini ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Operating Systems ◽  
Symmetric Cryptography ◽  
Significant Progress ◽  
Security Services ◽  
Iot Platform ◽  
Iot Platforms ◽  
Iot Devices ◽  
Time And Energy

The deployment of security services over Wireless Sensor Networks (WSN) and IoT devices brings significant processing and energy consumption overheads. These overheads are mainly determined by algorithmic efficiency, quality of implementation, and operating system. Benchmarks of symmetric primitives exist in the literature for WSN platforms but they are mostly focused on single platforms or single operating systems. Moreover, they are not up to date with respect to implementations and/or operating systems versions which had significant progress. Herein, we provide time and energy benchmarks of reference implementations for different platforms and operating systems and analyze their impact. Moreover, we not only give the first benchmark results of symmetric cryptography for the Intel Edison IoT platform but also describe a methodology of how to measure energy consumption on that platform.

scholarly journals Collaborative Offloading for UAV-enabled Time-Sensitive MEC Networks

2020 ◽  
Author(s):  
Wentao Li ◽  
Mingxiong Zhao ◽  
Yuhui Wu ◽  
Junjie Yu ◽  
Lingyan Bao ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Energy Consumption ◽  
Trajectory Optimization ◽  
Policy Design ◽  
Descent Method ◽  
Total Energy Consumption ◽  
Aerial Vehicle ◽  
Iot Devices ◽  
Mutually Independent

Abstract Recently, unmanned aerial vehicle (UAV) acts as the aerial mobile edge computing (MEC) node to help the battery-limited Internet of Things (IoT) devices relieve burdens from computation and data collection, and prolong the lifetime of operating. However, IoT devices can ONLY ask UAV for either computing or caching help, and collaborative offloading services of UAV is rarely mentioned in the literature. Moreover, IoT device has multiple mutually independent tasks, which make collaborative offloading policy design even more challenging. Therefore, we investigate a UAV-enabled MEC networks with the consideration of multiple tasks either for computing or caching. Taking the quality of experience (QoE) requirement of time-sensitive tasks into consideration, we aim to minimize the total energy consumption of IoT devices by jointly optimizing trajectory, communication and computing resource allocation at UAV, and task offloading decision at IoT devices. Since this problem has highly non-convex objective function and constraints, we first decompose the original problem into three subproblems named as trajectory optimization ($\mathbf{P_T}$), resource allocation at UAV ($\mathbf{P_R}$) and offloading decisions at IoT devices ($\mathbf{P_O}$), then propose an iterative algorithm based on block coordinate descent method to cope with them in a sequence. Numerical results demonstrate that collaborative offloading can effectively reduce IoT devices’ energy consumption while meeting different kinds of offloading services, and satisfy the QoE requirement of time-sensitive tasks at IoT devices.

scholarly journals IoT Platform for Seafood Farmers and Consumers

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4230
Author(s):  
Bjørn Jæger ◽  
Alok Mishra
Keyword(s):  
Sustainable Operations ◽  
Information Transparency ◽  
Value Network ◽  
Iot Platform ◽  
Global Standards ◽  
Seafood Industry ◽  
Demand Information ◽  
Enterprise Level ◽  
Iot Platforms ◽  
Iot Devices

There has been a strong growth in aquatic products supported by the global seafood industry. Consumers demand information transparency to support informed decisions and to verify nutrition, food safety, and sustainable operations. Supporting these needs rests on the existence of interoperable Internet of Things (IoT) platforms for traceability that goes beyond the minimum “one up, one down” scheme required by regulators. Seafood farmers, being the source of both food and food-information, are critical to achieving the needed transparency. Traditionally, seafood farmers carry the costs of providing information, while downstream actors reap the benefits, causing limited provision of information. Now, global standards for labelling, data from IoT devices, and the reciprocity of utility from collecting data while sharing them represent great potential for farmers to generate value from traceability systems. To enable this, farmers need an IoT platform integrated with other IoT platforms in the value network. This paper presents a case study of an enterprise-level IoT platform for seafood farmers that satisfies consumers’ end-to-end traceability needs while extracting data from requests for information from downstream actors.

scholarly journals Design and Implementation of an Interworking IoT Platform and Marketplace in Cloud of Things

2019 ◽  
Vol 11 (21) ◽  
pp. 5952 ◽  
Author(s):  
Faisal Mehmood ◽  
Shabir Ahmad ◽  
DoHyeun Kim
Keyword(s):  
Value Chain ◽  
Virtual Objects ◽  
Iot Applications ◽  
Iot Platform ◽  
Vital Component ◽  
Iot Platforms ◽  
Iot Devices ◽  
User Friendly ◽  
Software Services

An internet of things (IoT) platform is a multi-layer technology that enables automation of connected devices within IoT. IoT platforms serve as a middle-ware solution and act as supporting software that is able to connect different hardware devices, access points, and networks to other parts of the value chain. Virtual objects have become a vital component in every IoT platform. Virtual objects are the digital representation of a physical entity. In this paper, we design and implement a cloud-centric IoT platform that serves a purpose for registration and initialization of virtual objects so that technology tinkerers can consume them via the IoT marketplace and integrate them to build IoT applications. The proposed IoT platform differs from existing IoT platforms in the sense that they provide hardware and software services on the same platform that users can plug and play. The proposed IoT platform is separate from the IoT marketplace where users can consume virtual objects to build IoT applications. Experiments are conducted for IoT platform and interworking IoT marketplace based on virtual objects in CoT. The proposed IoT platform provides a user-friendly interface and is secure and reliable. An IoT testbed is developed and a case study is performed for a domestic environment to reuse virtual objects on the IoT marketplace. It also provides the discovery and sharing of virtual objects. IoT devices can be monitored and controlled via virtual objects. We have conducted a comparative analysis of the proposed IoT platform with FIWARE. Results conclude that the proposed system performs marginally better than FIWARE.

scholarly journals Reliable and Efficient Data Communication Protocol for WBAN-Based Healthcare Systems

2018 ◽  
Vol 9 (2) ◽  
pp. 19-37
Author(s):  
Nawel Yessad ◽  
Mawloud Omar
Keyword(s):  
Energy Consumption ◽  
Data Communication ◽  
Healthcare Systems ◽  
Efficient Computation ◽  
Power Efficient ◽  
Load Response ◽  
Efficient Data ◽  
Community Area ◽  
Time And Energy

Wireless Body Area Networks (WBANs) become very attractive in the research community area and are getting growing interest because of their suitability for medical applications. They are designed such, they can be located on, in or around the patient body and are used to monitor medical signs and forward them to medical servers. Proficient energy and Quality of Service (QoS) are the main requirements for a dependable design in a such networks. In this article, the authors propose a reliable and power efficient routing approach for healthcare systems with the aim to balance the trade-off between the QoS requirements and the energy consumption. Their approach operates in an efficient computation way, where the sink device manages the routing paths avoiding the sensors to be involved in computation and consequently on the energy consumption. They conducted intensive simulations and the obtained results show that Their approach offers effective results in terms of transmission load, response time and energy consumption.

scholarly journals Collaborative offloading for UAV-enabled time-sensitive MEC networks

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Wen-Tao Li ◽  
Mingxiong Zhao ◽  
Yu-Hui Wu ◽  
Jun-Jie Yu ◽  
Ling-Yan Bao ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Energy Consumption ◽  
Trajectory Optimization ◽  
Policy Design ◽  
Descent Method ◽  
Total Energy Consumption ◽  
Aerial Vehicle ◽  
Iot Devices ◽  
Mutually Independent

AbstractRecently, unmanned aerial vehicle (UAV) acts as the aerial mobile edge computing (MEC) node to help the battery-limited Internet of Things (IoT) devices relieve burdens from computation and data collection, and prolong the lifetime of operating. However, IoT devices can ONLY ask UAV for either computing or caching help, and collaborative offloading services of UAV are rarely mentioned in the literature. Moreover, IoT device has multiple mutually independent tasks, which make collaborative offloading policy design even more challenging. Therefore, we investigate a UAV-enabled MEC networks with the consideration of multiple tasks either for computing or caching. Taking the quality of experience (QoE) requirement of time-sensitive tasks into consideration, we aim to minimize the total energy consumption of IoT devices by jointly optimizing trajectory, communication and computing resource allocation at UAV, and task offloading decision at IoT devices. Since this problem has highly non-convex objective function and constraints, we first decompose the original problem into three subproblems named as trajectory optimization ($$\mathbf {P}_{\mathbf {T}}$$ P T ), resource allocation at UAV ($$\mathbf {P}_{\mathbf {R}}$$ P R ) and offloading decisions at IoT devices ($$\mathbf {P}_{\mathbf {O}}$$ P O ) and then propose an iterative algorithm based on block coordinate descent method to cope with them in a sequence. Numerical results demonstrate that collaborative offloading can effectively reduce IoT devices’ energy consumption while meeting different kinds of offloading services, and satisfy the QoE requirement of time-sensitive tasks at IoT devices.

scholarly journals Minimising Delay and Energy in Online Dynamic Fog Systems

2020 ◽  
Author(s):  
Faten Alenizi ◽  
Omer Rana
Keyword(s):  
Energy Consumption ◽  
Fog Computing ◽  
Cloud Services ◽  
Dynamic Task ◽  
Delay Sensitive ◽  
Reduce Energy Consumption ◽  
Iot Devices ◽  
User Tasks ◽  
Use Of Internet

The increasing use of Internet of Things (IoT) devices generates a greater demand for data transfers and puts increased pressure on networks. Additionally, connectivity to cloud services can be costly and inefficient. Fog computing provides resources in proximity to user devices to overcome these drawbacks. However, optimisation of quality of service (QoS) in IoT applications and the management of fog resources are becoming challenging problems. This paper describes a dynamic online offloading scheme in vehicular traffic applications that require execution of delay-sensitive tasks. This paper proposes a combination of two algorithms: dynamic task scheduling (DTS) and dynamic energy control (DEC) that aim to minimise overall delay, enhance throughput of user tasks and minimise energy consumption at the fog layer while maximising the use of resource-constrained fog nodes. Compared to other schemes, our experimental results show that these algorithms can reduce the delay by up to 80.79% and reduce energy consumption by up to 66.39% in fog nodes. Additionally, this approach enhances task execution throughput by 40.88%.

scholarly journals Large-Scale Software-Defined IoT Platform for Provisioning IoT Services on Demand

2020 ◽  
Vol 1 (1) ◽  
pp. 1-23
Author(s):  
Chau Thi Minh Nguyen ◽  
Doan B. Hoang
Keyword(s):  
Resource Sharing ◽  
Large Scale ◽  
Virtual Sensors ◽  
On Demand ◽  
Iot Platform ◽  
Proposed Model ◽  
Geographically Distributed ◽  
Iot Platforms ◽  
End To End ◽  
Iot Devices

Internet of things (IoT) has developed into an interconnected platform infrastructure for providing everyday services. Emerging end-to-end IoT services are being developed for local and multiple distributed regions. To realize the on-demand services in a timely and economically beneficial way, programmability and reusability are crucial for provisioning and reusing IoT resources. Existing IoT platforms are rigid and cannot be easily adapted to accommodate new services. This paper proposes a programmable large-scale software-defined IoT model for provisioning IoT services on demand with two levels of management and orchestration. One orchestrates services over geographically distributed clusters and the other orchestrates services over IoT devices within a cluster. The model entails the design of IoT-specific controllers, software-defined virtual sensors, and a new protocol for managing resource-constrained but enriched devices. The model allows provisioning and resource-sharing of end-to-end IoT services on demand. Implementation results demonstrate the feasibility and efficiency of the proposed model.

A Wi-Fi IoT prototype for ECG monitoring exploiting a novel Compressed Sensing method

ACTA IMEKO ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 38
Author(s):  
Eulalia Balestrieri ◽  
Pasquale Daponte ◽  
Luca De Vito ◽  
Francesco Picariello ◽  
Sergio Rapuano ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Compressed Sensing ◽  
Battery Life ◽  
Ecg Signal ◽  
Ecg Monitoring ◽  
Ecg Signals ◽  
Reconstruction Quality ◽  
Acquisition Device ◽  
Iot Devices

<p><span lang="EN-US">The paper presents an Internet of Things (IoT) prototype which consists of a data acquisition device wirelessly connected to Internet via Wi-Fi, for continuous electrocardiogram (ECG) monitoring. The proposed system performs a novel Compressed Sensing (CS) based method on ECG signal with the aim of reducing the amount of transmitted data, thus realizing an efficient way to increase the battery life of such devices. For the assessment of the energy consumption of the device, an experimental setup was arranged and its description is presented. The evaluation of the reconstruction quality of the ECG signal in terms of Percentage of Root-mean-squared Difference (PRD</span><span lang="EN-US">) is reported for several Compression Ratios (CRs</span><span lang="EN-US">). The obtained experimental results clearly demonstrate the robustness and usefulness of the Wi-Fi based IoT devices adopting the considered CS-method for data compression of ECG signals. Furthermore, it allows reducing the energy consumption of the IoT device, by increasing the CR</span><span lang="EN-US">, without significantly degrading the quality of the reconstructed ECG signal.</span></p>

scholarly journals Energy-Efficient IoT Service Brokering with Quality of Service Support

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 693
Author(s):  
Giacomo Tanganelli ◽  
Enzo Mingozzi
Keyword(s):  
Quality Of Service ◽  
Energy Efficient ◽  
Energy Aware ◽  
Allocation Policy ◽  
Service Support ◽  
Service Allocation ◽  
Iot Platforms ◽  
Iot Devices ◽  
The Internet Of Things

The Internet of Things (IoT) is becoming real, and recent studies highlight that the number of IoT devices will significantly grow in the next decade. Such massive IoT deployments are typically made available to applications as a service by means of IoT platforms, which are aware of the characteristics of the connected IoT devices–usually constrained in terms of computation, storage and energy capabilities–and dispatch application’s service requests to appropriate devices based on their capabilities. In this work, we develop an energy-aware allocation policy that aims at maximizing the lifetime of all the connected IoT devices, whilst guaranteeing that applications’ Quality of Service (QoS) requirements are met. To this aim, we formally define an IoT service allocation problem as a non-linear Generalized Assignment Problem (GAP). We then develop a time-efficient heuristic algorithm to solve the problem, which is shown to find near-optimal solutions by exploiting the availability of equivalent IoT services provided by multiple IoT devices, as expected especially in the case of massive IoT deployments.

scholarly journals Design and develop Quality of Service Framework using Fog Computing for Smart City Applications

2019 ◽  
Vol 9 (1S) ◽  
pp. 343-348
Keyword(s):  
Quality Of Service ◽  
Energy Consumption ◽  
Power Consumption ◽  
Smart City ◽  
Fog Computing ◽  
Cloud Data ◽  
Efficient Reduction ◽  
Iot Devices ◽  
Service Framework

In today's world, Internet of Things (IoT) is has become the most promising and life-changing technology. In the past few years, IoT has become most productive in the area of healthcare, to improve the quality of care to the patients. This paper aims to reduce the delay, energy consumption of cloud data-centers and minimized the power consumption IoT devices using fog devices. To solve the problem mentioned above, we proposed the Quality of Service framework using fog computing for smart city applications named FATEH, a three-tier architecture for IoT-based application. Various quality of services parameters are optimized as For minimizing the power consumption of IoT devices, the Routing Protocol for Low power and Lossy network (RPL). The other QoS parameter is computing the performance of the proposed framework which has been evaluated through the iFogsim toolkit and the Cooja simulator. Results show the efficient reduction in the delay as well as energy consumption in the proposed scenario and provide better QoS framework

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