scholarly journals An Energy and Load Aware Multipath Routing Protocol in the Internet of Things

2020 ◽  
Author(s):  
Rogayye Khaleghnasab ◽  
Karamolah Bagherifard ◽  
Bahman Ravaei ◽  
Hamid Parvin ◽  
Samad Nejatian
Keyword(s):  
Internet Of Things ◽  
Routing Protocol ◽  
Superior Performance ◽  
Hop Count ◽  
Routing Problem ◽  
Expiration Time ◽  
Link Expiration Time ◽  
Routing Methods ◽  
Smart Things ◽  
The Internet Of Things

Internet of things (IoT) is a network of smart things. This indicates the ability of these physical things to transfer information with other physical things. The characteristics of these networks, such as topology dynamicity and energy constraint, challenges the routing problem in these networks. Previous routing methods could not achieve the required performance in this type of network. Therefore, developers of this network designed and developed specific methods in order to satisfy the requirements of these networks. One of the routing methods is utilization of multipath protocols which send data to its destination using routes with separate links. One of such protocols is RPL routing protocol. In this paper, this method is improved using composite metrics which chooses the best paths used for separate routes to send packets. We propose Energy and Load aware RPL (ELaM-IoT) protocol, which is an enhancement of RPL protocol. It uses a composite metric, calculated based on remaining energy, hop count, Link Expiration Time (LET), load and battery depletion index (BDI) for the route selection. In order to evaluate and report the results, the proposed ELaM-IoT method is compared to the ERGID and ADRM-IoT approaches with regard to average remaining energy, and network lifetime. The results demonstrate the superior performance of the proposed ELaM-IoT compared to the ERGID and ADRM-IoT approaches.

scholarly journals Energy Efficient Multi-Path Routing Algorithm Using Gray System Theory for Improvement of Routing and Network Stability in Internet of Things

2020 ◽  
Author(s):  
Rogayye Khaleghnasab ◽  
Karamolah Bagherifard ◽  
Samad Nejatian ◽  
Bahman Ravaei
Keyword(s):  
System Theory ◽  
Internet Of Things ◽  
Signal To Noise Ratio ◽  
Routing Algorithm ◽  
Superior Performance ◽  
Routing Problem ◽  
Gray System Theory ◽  
Gray System ◽  
Routing Methods ◽  
Smart Things

Internet of things (IoT) is a network of smart things. This indicates the ability of these physical things to transfer information with other physical things. The characteristics of these networks, such as topology dynamicity and energy constraint, challenges the routing problem in these networks. Previous routing methods could not achieve the required performance in this type of network. Therefore, developers of this network designed and developed specific methods in order to satisfy the requirements of these networks. One of the routing methods is utilization of multi-path protocols which send data to its destination using routes with separate links. One of such protocols is AOMDV routing protocol. In this paper, this method is improved using gray system theory which chooses the best paths used for separate routes to send packets. To do this, AOMDV packet format is altered and some fields are added to it so that energy criteria, link expiration time, and signal to noise ratio can also be considered while selecting the best route. The proposed method named RMPGST-IoT is introduced which chooses the routes with highest rank for concurrent transmission of data, using a specific routine based on the gray system theory. In order to evaluate and report the results, the proposed RMPGST-IoT method is compared to the ERGID and ADRM-IoT approaches with regard to throughput, packet receiving rate, packet loss rate, average remaining energy, and network lifetime. The results demonstrate the superior performance of the proposed RMPGST-IoT compared to the ERGID and ADRM-IoT approaches.

scholarly journals Energy Efficient Multi-Path Routing Algorithm Using Gray System Theory for Improvement of Routing and Network Stability in Internet of Things

2020 ◽  
Author(s):  
Rogayye Khaleghnasab ◽  
Karamolah Bagherifard ◽  
Samad Nejatian ◽  
Bahman Ravaei
Keyword(s):  
System Theory ◽  
Internet Of Things ◽  
Signal To Noise Ratio ◽  
Routing Algorithm ◽  
Superior Performance ◽  
Routing Problem ◽  
Gray System Theory ◽  
Gray System ◽  
Routing Methods ◽  
Smart Things

Internet of things (IoT) is a network of smart things. This indicates the ability of these physical things to transfer information with other physical things. The characteristics of these networks, such as topology dynamicity and energy constraint, challenges the routing problem in these networks. Previous routing methods could not achieve the required performance in this type of network. Therefore, developers of this network designed and developed specific methods in order to satisfy the requirements of these networks. One of the routing methods is utilization of multi-path protocols which send data to its destination using routes with separate links. One of such protocols is AOMDV routing protocol. In this paper, this method is improved using gray system theory which chooses the best paths used for separate routes to send packets. To do this, AOMDV packet format is altered and some fields are added to it so that energy criteria, link expiration time, and signal to noise ratio can also be considered while selecting the best route. The proposed method named RMPGST-IoT is introduced which chooses the routes with highest rank for concurrent transmission of data, using a specific routine based on the gray system theory. In order to evaluate and report the results, the proposed RMPGST-IoT method is compared to the ERGID and ADRM-IoT approaches with regard to throughput, packet receiving rate, packet loss rate, average remaining energy, and network lifetime. The results demonstrate the superior performance of the proposed RMPGST-IoT compared to the ERGID and ADRM-IoT approaches.

A New Energy-Efficient Multipath Routing in Internet of Things Based on Gray Theory

2020 ◽  
Vol 19 (06) ◽  
pp. 1581-1617
Author(s):  
Rogayye Khaleghnasab ◽  
Karamollah Bagherifard ◽  
Samad Nejatian ◽  
Hamid Parvin ◽  
Bahman Ravaei
Keyword(s):  
System Theory ◽  
Internet Of Things ◽  
Ad Hoc ◽  
Signal To Noise Ratio ◽  
Specific Method ◽  
Routing Problem ◽  
Gray System Theory ◽  
Gray System ◽  
Routing Methods ◽  
Smart Things

Internet of Things (IoT) is a network of smart things. It indicates the ability that the mentioned physical things transfer information with each other. The characteristics of these networks, such as topology dynamicity and energy constraint, make the routing problem a challenging task in these networks. Traditional routing methods could not achieve the required performance in these networks. Therefore, developers of these networks have to consider specific routing methods in order to satisfy their requirements. One of the routing methods is utilization of the multipath protocols in which data are sent to its destination using multiple routes with separate links. One of such protocols is AOMDV routing protocol. In this paper, AOMDV is improved using gray system theory which chooses the best paths used for separate routes to send packets. To do this, Ad hoc On-demand Multipath Distance Vector (AOMDV) packet format is altered and some fields are added to it so that energy criteria, link expiration time, and signal-to-noise ratio can also be considered during selection of the best route. The proposed method named RMPGST-IoT is introduced which chooses the routes with highest rank for concurrent transmission of data, using a specific method based on the gray system theory. In order to evaluate the results, the proposed Routing Multipath based on Gray System Theory (RMPGST)-IoT method is compared to the Emergency Response IoT based on Global Information Decision (ERGID) and Ad hoc Delay-aware Distributed Routing Model (ADRM)-IoT approaches in terms of throughput, packet receiving rate, packet loss rate, average remaining energy, and network lifetime. The results demonstrate that the performance of the proposed RMPGST-IoT is superior to that of ERGID and ADRM-IoT approaches.

scholarly journals A Gray System Theory Based Multi-Path Routing Method for Improving Network Lifetime in Internet of Things Systems

2020 ◽  
Author(s):  
Meysam Zarei ◽  
Mohammadreza Soltanaghaei
Keyword(s):  
System Theory ◽  
Internet Of Things ◽  
Network Lifetime ◽  
Human Life ◽  
Residual Energy ◽  
Superior Performance ◽  
Routing Problem ◽  
Gray System Theory ◽  
Gray System ◽  
Routing Methods

Internet of things (IoT) is a network of smart things. This indicates the ability of these physical things to transfer information with other physical things. IoT has introduced various services and daily human life depends on its reliable and accessible operation. The characteristics of these networks, such as topology dynamicity and energy constraint, challenges the routing problem in these networks. Previous routing methods could not achieve the required performance in this type of network. Therefore, developers of this network designed and developed specific methods in order to satisfy the requirements of these networks. One of the routing methods is utilization of multi-path protocols which send data to its destination using routs with separate links. One of such protocols is AOMDV routing protocol. AOMDV protocol is a multi-path protocol which uses multiple different paths for sending information in order to maintain the network traffic balance, manage and control node energy, decrease latency, etc. In this paper, this method is improved using gray system theory which chooses the best paths used for separate routes to send packets. To do this, AOMDV packet format is altered and some fields are added to it so that energy criteria, link expiration time, and signal to noise ratio can also be considered while selecting the best route. The proposed method named GSTMPR-IoT is introduced which chooses the routs with highest rank for concurrent transmission of data, using a specific routine based on the gray system theory. In order to evaluate and report the results, the proposed GSTMPR-IoT method is compared to the EECRP and AOMDV approaches with regard to throughput, packet delivery rate, end to end delay, average residual energy, and network lifetime. The results demonstrate the superior performance of the proposed GSTMPR-IoT compared to the EECRP and AOMDV approaches.

scholarly journals A DHT-Based Discovery Service for the Internet of Things

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Federica Paganelli ◽  
David Parlanti
Keyword(s):  
Internet Of Things ◽  
Large Scale ◽  
Future Internet ◽  
Peer To Peer ◽  
The Internet ◽  
Dangerous Goods ◽  
Discovery Service ◽  
Single Attribute ◽  
Smart Things ◽  
The Internet Of Things

Current trends towards the Future Internet are envisaging the conception of novel services endowed with context-aware and autonomic capabilities to improve end users’ quality of life. The Internet of Things paradigm is expected to contribute towards this ambitious vision by proposing models and mechanisms enabling the creation of networks of “smart things” on a large scale. It is widely recognized that efficient mechanisms for discovering available resources and capabilities are required to realize such vision. The contribution of this work consists in a novel discovery service for the Internet of Things. The proposed solution adopts a peer-to-peer approach for guaranteeing scalability, robustness, and easy maintenance of the overall system. While most existing peer-to-peer discovery services proposed for the IoT support solely exact match queries on a single attribute (i.e., the object identifier), our solution can handle multiattribute and range queries. We defined a layered approach by distinguishing three main aspects: multiattribute indexing, range query support, peer-to-peer routing. We chose to adopt an over-DHT indexing scheme to guarantee ease of design and implementation principles. We report on the implementation of a Proof of Concept in a dangerous goods monitoring scenario, and, finally, we discuss test results for structural properties and query performance evaluation.

scholarly journals Energy Efficient Composite Metric Based Routing Protocol for Internet of Things

2020 ◽  
Vol 26 (11) ◽  
pp. 1366-1381
Author(s):  
Sathishkumar Natesan ◽  
Rajakumar Krishnan
Keyword(s):  
Internet Of Things ◽  
Low Power ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Link Quality ◽  
Traffic Load ◽  
Delivery Ratio ◽  
Lossy Networks ◽  
Hop Count ◽  
Battery Discharge

The Routing Protocol for Low Power and Lossy Networks (RPL) is operated by gadgets comprised of many devices of embedded type with limited energy, memory as well as resources that do their process. The improvements in the life of the network and energy conservation are the key challenging features in Low Power and Lossy Networks (LLN). Obviously, the LLN has a key strategic part in routing. The Internet of Things (IoT) device is expected to make the apt choice. In LLN, the poor routing choice leads to traffic congestion, reduction in power as well as packet loss ratio. The task in the proposal analyzes Delay (D), Load (L) and Battery Discharge Index (BDI) pivoted Energy Efficient Composite Metric Routing (EECMR) protocol for LLN. The performance of the work in the proposal is evaluated by the COOJA simulator. It outperforms with respect to Network Lifetime (NL), Delay as well as Packet Delivery Ratio (PDR) contrasted to the routing metrics like Traffic Load (TL), Link Quality (LQ), Residual Energy (RE), RE-Battery Discharge Index (RE-BDI) and Hop Count (HC).

scholarly journals Assessing Impacts of 5th Generation (5G) Cellular Telecommunications on Internet of Things (IoT) Deployments

2020 ◽  
Vol 4 (2) ◽  
Author(s):  
Michael Love ◽  
Marwan Jamal
Keyword(s):  
Internet Of Things ◽  
Denial Of Service ◽  
Holistic Approach ◽  
Chief Information Officer ◽  
Superior Performance ◽  
Cellular Transport ◽  
Government Accountability ◽  
Business Services ◽  
High Bandwidth ◽  
The Internet Of Things

The Internet of Things (IoT) is emerging as a primary enabler of the transformation to digital business services in today’s economy. At the same time, 5th Generation (5G) cellular transport technology is emerging as a viable means to support IoT data requirements. Although 5G is still in its infancy, DoD leaders need to understand the impacts that 5G will have on IoT projects as there are several challenges involved with integrating 5G into IoT. In order to achieve the maximum benefits of high bandwidth, low latency and superior performance, an entirely new grid of cell sites and access units must be installed. A second challenge is with malware and intrusion attacks. 5G is an IP-based network technology that will expose 5G connected devices to common IP-based malware and intrusion risks such as denial-of-service (DOS and DDOS) and intrusion attacks. A third challenge is with standardized security and encryption of data from end-devices. The larger challenge with standardization involves interoperability. In order for 5G to work seamlessly across carriers with device agnostic hardware and compatible software, a holistic approach should be considered. Hardware compatibility will determine interoperability between sensors, platforms and gateways. In addition, software compatibility will be governed by 5G standards as well as industry partnerships. 5G standards are currently still being developed. Organizations, including the DoD Chief Information Officer and Government Accountability Office should specifically address implications of 5G cellular technology for IoT-related studies and use cases in the DoD.

scholarly journals The 'Future Internet' and crime: Towards a criminology of the Internet of Things

Crimen ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 255-271
Author(s):  
Sanja Milivojević ◽  
Elizabeth Radulski
Keyword(s):  
Internet Of Things ◽  
Radio Frequency Identification ◽  
Future Internet ◽  
Natural World ◽  
The Internet ◽  
Starting Point ◽  
The Future ◽  
Emerging Issues ◽  
Smart Things ◽  
The Internet Of Things

The Internet of Things (IoT) is poised to revolutionise the way we live and communicate, and the manner in which we engage with our social and natural world. In the IoT, objects such as household items, vending machines and cars have the ability to sense and share data with other things, via wireless, Bluetooth, or Radio Frequency IDentification (RFID) technology. "Smart things" have the capability to control their performance, as well as our experiences and decisions. In this exploratory paper, we overview recent developments in the IoT technology, and their relevance for criminology. Our aim is to partially fill the gap in the literature, by flagging emerging issues criminologists and social scientists ought to engage with in the future. The focus is exclusively on the IoT while other advances, such as facial recognition technology, are only lightly touched upon. This paper, thus, serves as a starting point in the conversation, as we invite scholars to join us in forecasting-if not preventing-the unwanted consequences of the "future Internet".

scholarly journals Inequalities in the social use of the Internet of things: A capital and skills perspective

2019 ◽  
Vol 21 (6) ◽  
pp. 1344-1361 ◽  
Author(s):  
Alex van der Zeeuw ◽  
Alexander JAM van Deursen ◽  
Giedo Jansen
Keyword(s):  
Internet Of Things ◽  
Social Relations ◽  
The Internet ◽  
Internet Skills ◽  
The Social ◽  
Use Of The Internet ◽  
Social Use ◽  
Smart Things ◽  
Social Uses ◽  
The Internet Of Things

In this article, we set out to explain different types of social uses of the Internet of Things (IoT) using forms of capital and Internet skills. We argue that the IoT platform entices different manners of social communication that are easily overlooked when focusing on the novelty of smart “things.” How people use the IoT socially is crucial in trying to understand how people create, maintain, or absolve social relations in a networked society. We find inversed effects for social capital, income and education on private use, and on sharing IoT data with a partner. Sharing with acquaintances and strangers is predicted by cultural activities. Sharing IoT data with acquaintances can especially be attributed to social relations that escape the immediate household. We conclude that varying figurations of capital and Internet skills predict how the IoT is used socially.

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