A huge number of devices like sensors in addition to computers are interconnected in the IoT (Internet of Things). In the cloud computing model , sensor data is transmitted to servers in networks and processed on the servers in a cloud. Here, networks are congested and servers are overloaded due to heavy traffic from sensors. In order to reduce the delay time and network traffic and increase the performance of the system, data and processes are distributed to not only servers in a cloud but also fog nodes in fog computing models. While the traffic of servers in a cloud can be reduced, the total electric energy consumed by fog nodes increases to process sensor data. In this paper, we newly propose a tree-based fog computing (TBFC) model to distribute processes and data to servers and fog nodes so that the total electric energy consumption of nodes can be reduced in the IoT. In the evaluation, we show the total electric energy consumption of nodes in the TBFC model is smaller than the cloud computing model.

An energy-efficient model for fog computing in the Internet of Things (IoT)

Recent advances in wireless technologies, micro-electro-mechanical systems, and embedded systems enable the popular usage of the Internet of Things (IoT) and wireless sensor networks (WSNs) in many important applications, such as smart buildings, security, target tracking, industrial automation, and so on. Typically, a WSN consists of a large number of tiny, low-cost sensor nodes that are limited in terms of their capabilities of computation, communication, memory, and power. In WSNs, energy-efficient algorithms are of paramount importance for a long lasting high throughput network. MAC protocol plays a prominent role in extending the life-time of WSNs. MAC protocols provide various schemes on how multiple nodes access a common wireless medium. To achieve a longer lifetime for the nodes and the networks, MAC protocols need to be energy-efficient and reduce the sources of energy wastage. Energy conservation in sensor nodes is generally achieved by duty cycling the radios, and it is the MAC layer protocol that controls when to switch on and off the radio. In this paper, we discuss the essential properties of MAC protocols, the MAC for IoT and the common causes of energy consumptions. Thereafter, we categorize the MAC layer protocols and discuss several protocols under each category in depth, emphasizing their strengths and weaknesses, and giving a detailed comparison of MAC protocols. Finally, we conclude the survey with the insights on future research directions.

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A Comprehensive Study of IoT and WSN MAC Protocols: Research Issues, Challenges and Opportunities

Quality of service‐aware approaches in fog computing

The fourth industrial revolution, widely known as Industry 4.0, is realizable through widespread deployment of Internet of Things (IoT) devices across the industrial ambiance. Due to communication latency and geographical distribution, Cloud-centric IoT models often fail to satisfy the Quality of Service requirements of different IoT applications assisting Industry 4.0 in real time. Therefore, Fog computing focuses on harnessing edge resources to place and execute these applications in the proximity of data sources. Since most of the Fog nodes are heterogeneous, distributed, and resource-constrained, it is challenging to place Industry 4.0-oriented applications (I4OAs) over them ensuring time-optimized service delivery. Diversified data sensing frequency of different industrial IoT devices and their data size further intensify the application placement problem. To address this issue, in this article we propose a context-aware application placement policy for Fog environments. Our policy coordinates the IoT device-level contexts with the capacity of Fog nodes and minimizes the service delivery time of various I4OAs such as image processing and robot navigation applications. It also ensures that the streams of input data flowing toward the placed applications neither congest the network nor increase the computing overhead of host Fog nodes significantly. Performance of the proposed policy is evaluated in both real-world and simulated Fog environments and compared with the existing placement policies. The experiment results show that our policy offers overall 16% improvement in service latency, network relaxation, and computing overhead management compared to other placement policies.

Context-Aware Placement of Industry 4.0 Applications in Fog Computing Environments

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.

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EMS: An Energy Management Scheme for Green IoT Environments

In information systems, a transaction may illegally read data stored in an object which the transaction is not allowed to read is stored in the object A transaction illegally writes data to an object after issuing illegal read A transaction suspiciously reads data in a suspicious object whose data is not allowed to flow to some object A transaction impossibly writes data to an object after issuing suspicious read In our previous studies, the write-abortion (WA) role-based synchronisation (RBS) and object-based synchronisation (OBS) protocols are proposed where a transaction illegally or impossibly writes data to objects is aborted In this paper, we newly propose a pair of read-write-abortion (RWA) RBS and OBS protocols where a transaction is aborted only if the transaction issues an illegal read or impossible write to an object In the evaluation, the execution time of each transaction in RWA protocols is shorter than the WA protocols

A read-write abortion protocol to prevent illegal information flow in role-based access control systems

A huge number and various types of devices like sensors and actuators are interconnected with clouds of servers in the IoT (Internet of Things). Here, a large volume of data created by sensors have to be efficiently transmitted and processed and actions have to be efficiently delivered to actuators at an opportune time. In order to reduce the delay time and increase the performance, data and processing are distributed to not only servers but also fog nodes in fog computing systems. On the other hand, the total electric energy consumed by fog nodes increases since a huge number of fog nodes are interconnected. In this paper, we newly propose a tree-based fog computing model to deploy processes and data to fog nodes so that the total electric energy consumption of nodes can be reduced in the IoT. In the evaluation, we show the total electric energy consumption of nodes in the tree-based model is smaller than the cloud model where processes and data are centralized.

A Tree-Based Model of Energy-Efficient Fog Computing Systems in IoT

In information systems, types of objects like multimedia objects are manipulated in var- ious applications like mobile systems. Here, information in objects may ow to another object. Suppose a transaction reads data in an object o1 and then writes data to another object o2. If a transaction reads the data in the object o2, the transaction can read data in the object o1 even if the transaction is not granted a read access right on the object o1. Here, the transaction illegally reads data in the object o2. Here, information in the object o1 might illegally ow to the object o2. A transaction illegally writes data to an object after illegally reading data in some object. In addition, we consider a suspicious object whose data is not allowed to ow to another object. A transaction suspiciously reads data in a suspicious object. A transaction impossibly writes data to an object after reading the data in a suspicious object. Write-abortion (WA) and read-write-abortion (RWA) protocols to prevent illegal information ow are already proposed in our pre- vious studies. In the WA protocol, a transaction is aborted once issuing an illegal or impossible write operation to an object. Read operations are meaninglessly performed since the read operations are undone due to the abortion of the transaction. In the RWA protocol, a transaction is aborted once issuing an illegal read or impossible write opera- tion to an object. Here, read operations to be performed after an illegal read operations are lost since a transaction is aborted just on issuing an illegal read operation. In this paper, we newly propose a exible read-write abortion (FRWA) protocol to reduce the number of meaningless and lost read operations. Here, a transaction is aborted with some probability if the transaction illegally reads data in an object. We evaluate the FRWA protocols compared with the WA and RWA protocols. We show the execution time of each transaction in the FRWA protocols is shorter than the WA protocols and more number of read operations can be performed in the RWA protocols.

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A flexible read-write abortion protocol to prevent illegal information flow among objects

A huge number of devices like sensors are interconnected in the IoT (Internet of Things). In the cloud computing model, processes and data are centralized in a cloud. Here, networks are congested and servers are overloaded due to heavy traffic from sensors. In order to reduce the delay time and increase the performance, data and processes to handle the data are distributed to not only servers but also fog nodes in fog computing models. On the other hand, the total electric energy consumed by fog nodes increases to process a sensor data. In this paper, we newly propose a tree-based fog computing model to distribute processes and data to servers and fog nodes so that the total electric energy consumption of nodes can be reduced in the IoT. In the evaluation, we show the total electric energy consumption of nodes in the tree-based model is smaller than the cloud computing model.

Shigenari Nakamura

Papers

An energy-efficient model for fog computing in the Internet of Things (IoT)

A read-write abortion protocol to prevent illegal information flow in role-based access control systems

A Tree-Based Model of Energy-Efficient Fog Computing Systems in IoT

A flexible read-write abortion protocol to prevent illegal information flow among objects

Evaluation of an Energy-Efficient Tree-Based Model of Fog Computing