Optimized Resource Allocation in IoT using Fuzzy Logic and Bio-Inspired Algorithms

Abstract IoT smart devices are a confluence of microprocessors, sensors, power source and transceiver modules to effectively sense, communicate and transfer data. Energy efficiency is a key governing value of the network performance of smart devices in distributed IoT networks.Low and discrete power and limited amount of memory and finite amount of resources form some major bottlenecks in the workflow.Dynamic load balancing, reliability and flexibility are heavily relied upon by cloud computing for its accessibility.Resources are dynamically provided to the end client in an as-come on-demand fashion with the global network that is the Internet. Proportionally the need for services is increasing at a rate that is astonishing compared to any other forms of development. Load balancing seems a major challenge faced due to the architecture and the modular nature of our cloud environment. Loads need to be distributed dynamically to all the nodes. In this paper, we have introduced a technique that combines fuzzy logic with various nature inspired algorithms - grey wolf algorithm and firefly algorithm in order to effectively balance the load in a network of IoT devices. The performances of various nature inspired algorithms are compared with a brute force approach on the basis of energy efficiency, network lifetime maximization, node failure rate and packet delivery ratio.

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RHLB: Improved Routing Load Balancing Algorithm Based on Hybrid Policy

Journal of University of Babylon for Engineering Sciences ◽

10.29196/jubes.v27i1.2005 ◽

2019 ◽

Vol 27 (1) ◽

pp. 324-337

Author(s):

Muna Mohammed Jawad ◽

Noor Mohammed Mahdi

Keyword(s):

Load Balancing ◽

Packet Loss ◽

Network Performance ◽

Delivery Ratio ◽

Network Simulator ◽

Network Load ◽

Dynamic Policy ◽

Network Load Balancing ◽

Load Balancing Algorithm ◽

Network Overhead

A network is defined as a set of nodes that are associated with a way to handle and transfer data and messages from source to destination. The congestion in the network occurs when a lot of traffic occurs, leads to delay, packet loss, bandwidth degradation, and high network overhead. Load balancing algorithms have been designed to reduce congestion in the network. Load Balancing is the redistribution of workload between two or more nodes to be executed at the same time. Two policies of load balancing algorithms: static and dynamic load balancing. This paper proposes a load balancing algorithm based on the hybrid (static and dynamic) policy using Network Simulator (version 2). The hybrid policy is used to improve network performance by redistributing the load between overloaded nodes to other nodes that are under loaded when congestion occurs. The simulation results show that the proposed algorithm used performance of the network with regard to throughput, packet delivery ratio, packet loss and the end-to-end delay.

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Multi-Objective Optimization Model for Clustering Based Secure Routing with Congestion Avoidance in Mobile ADHOC Networks

Recent Advances in Computer Science and Communications ◽

10.2174/2666255813999200909105620 ◽

2020 ◽

Vol 13 ◽

Author(s):

Srinivasan Murugan ◽

Jeyakarthic Mohan

Keyword(s):

Energy Efficiency ◽

Load Balancing ◽

Data Transmission ◽

Mobile Ad Hoc Network ◽

Secure Routing ◽

Congestion Avoidance ◽

Delivery Ratio ◽

Network Simulator ◽

Multi Objective Optimization ◽

Multi Objective

Introduction: In Mobile ad-hoc network (MANET), clustering, routing and security are considered as major design issues. Clustering and routing techniques offers distribution of load over many network correlations to attain better utilization of resources, improved throughput, reduces response time, and eliminates workload. Besides, Trust based schemes helps in sending messages in a secured manner as well as prevents the data from attackers by integrating authorized sender and receiver inside the network. Aim: The aim of the paper is to propose a new multi-objective optimization (MOO) technique is presented which intense to allocate the available networking resources properly, balances load in the network, security and effective data transmission. Method: The projected model operates on three major processes: clustering, secured routing and data aggregation based transmission scheme. The MOO model involves fuzzy logic (FL) based clustering process, LionWhale optimization algorithm with congestion avoidance (LW-CA) technique for routing process and integrated XOR and Huffman (IXH) based data transmission process. Therefore, the presented model is collectively called as FCAXH technique which achieves energy efficiency, proper load balancing and security. Results: The simulations are carried out using Network Simulator tool and the results are investigated with and without the presence of attackers. The proposed method attains maximum results interms of throughput, packet delivery ratio (PDR) and energy efficiency. Conclusion: The projected FCAXH model achieves energy efficiency, proper load balancing and security over the compared approaches even under the presence of attackers in the network.

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Fuzzy-Controlled Energy-Conservation Technique (FET) for Mobile ad hoc Networks

Handbook of Research on Computational Intelligence for Engineering, Science, and Business ◽

10.4018/978-1-4666-2518-1.ch021 ◽

2013 ◽

pp. 556-570

Author(s):

Anuradha Banerjee

Keyword(s):

Energy Efficiency ◽

Energy Conservation ◽

Ad Hoc Networks ◽

Network Performance ◽

Ad Hoc ◽

Network Connectivity ◽

Delivery Ratio ◽

Packet Delivery ◽

Battery Power ◽

Hoc Networks

Nodes in ad hoc networks have limited battery power; hence, they require energy efficient techniques to improve average node lifetime and network performance. Maintaining energy efficiency in network communication is really challenging because highest energy efficiency is achieved if all the nodes are switched off and maximum network throughput is obtained if all the nodes are fully operational, i.e. always turned on. A promising energy conservation technique for the ad hoc networks must maintain effective packet forwarding capacity while turning off the network interface of very busy nodes for some time and redirecting the traffic through some comparatively idle nodes roaming around them. This also helps in fair load distribution in the network and maintenance of network connectivity by reducing the death rate (complete exhaustion of nodes). The present chapter proposes a fuzzy-controlled energy conservation technique (FET) that identifies the busy and idle nodes to canalize some traffic of busy nodes through the idle ones. In simulation section, the FET embedded versions of several state-of-the-art routing protocols in ad hoc networks are compared with their ordinary versions and the results quite emphatically establish the superiority of FET-embedded versions in terms of packet delivery ratio, message cost, and network energy consumption. End-to-end delay also reduces significantly.

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On-Demand LoRa: Asynchronous TDMA for Energy Efficient and Low Latency Communication in IoT

Sensors ◽

10.3390/s18113718 ◽

2018 ◽

Vol 18 (11) ◽

pp. 3718 ◽

Cited By ~ 17

Author(s):

Rajeev Piyare ◽

Amy Murphy ◽

Michele Magno ◽

Luca Benini

Keyword(s):

Energy Efficiency ◽

Low Power ◽

Long Range ◽

Energy Efficient ◽

High Efficiency ◽

High Rate ◽

Smart Devices ◽

Delivery Ratio ◽

Ultra Low Power ◽

On Demand

Energy efficiency is crucial in the design of battery-powered end devices, such as smart sensors for the Internet of Things applications. Wireless communication between these distributed smart devices consumes significant energy, and even more when data need to reach several kilometers in distance. Low-power and long-range communication technologies such as LoRaWAN are becoming popular in IoT applications. However, LoRaWAN has drawbacks in terms of (i) data latency; (ii) limited control over the end devices by the gateway; and (iii) high rate of packet collisions in a dense network. To overcome these drawbacks, we present an energy-efficient network architecture and a high-efficiency on-demand time-division multiple access (TDMA) communication protocol for IoT improving both the energy efficiency and the latency of standard LoRa networks. We combine the capabilities of short-range wake-up radios to achieve ultra-low power states and asynchronous communication together with the long-range connectivity of LoRa. The proposed approach still works with the standard LoRa protocol, but improves performance with an on-demand TDMA. Thanks to the proposed network and protocol, we achieve a packet delivery ratio of 100% by eliminating the possibility of packet collisions. The network also achieves a round-trip latency on the order of milliseconds with sensing devices dissipating less than 46 mJ when active and 1.83 μW during periods of inactivity and can last up to three years on a 1200-mAh lithium polymer battery.

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Modified fuzzy-based greedy routing protocol for VANETs

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189154 ◽

2020 ◽

Vol 39 (6) ◽

pp. 8357-8364

Author(s):

Thompson Stephan ◽

Ananthnarayan Rajappa ◽

K.S. Sendhil Kumar ◽

Shivang Gupta ◽

Achyut Shankar ◽

...

Keyword(s):

Fuzzy Logic ◽

Routing Protocol ◽

Intelligent Transportation Systems ◽

Vehicular Ad Hoc Networks ◽

Ad Hoc ◽

Research Area ◽

Transportation Systems ◽

Delivery Ratio ◽

Greedy Routing ◽

Hoc Networks

Vehicular Ad Hoc Networks (VANETs) is the most growing research area in wireless communication and has been gaining significant attention over recent years due to its role in designing intelligent transportation systems. Wireless multi-hop forwarding in VANETs is challenging since the data has to be relayed as soon as possible through the intermediate vehicles from the source to destination. This paper proposes a modified fuzzy-based greedy routing protocol (MFGR) which is an enhanced version of fuzzy logic-based greedy routing protocol (FLGR). Our proposed protocol applies fuzzy logic for the selection of the next greedy forwarder to forward the data reliably towards the destination. Five parameters, namely distance, direction, speed, position, and trust have been used to evaluate the node’s stability using fuzzy logic. The simulation results demonstrate that the proposed MFGR scheme can achieve the best performance in terms of the highest packet delivery ratio (PDR) and minimizes the average number of hops among all protocols.

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An Efficient Cluster-Based Flooding Using Fuzzy Logic Scheme (CBF2S) In Mobile Adhoc Networks

Recent Patents on Engineering ◽

10.2174/1872212114666200117105819 ◽

2020 ◽

Vol 14 ◽

Author(s):

S. Mahima ◽

N. Rajendran

Keyword(s):

Fuzzy Logic ◽

Ad Hoc ◽

Link Quality ◽

Traffic Load ◽

Node Degree ◽

Communication Overhead ◽

Delivery Ratio ◽

Node Mobility ◽

Centralized Control ◽

Hop Count

: Mobile ad hoc networks (MANET) hold a set of numerous mobile computing devices useful for communication with one another with no centralized control. Due to the inherent features of MANET such as dynamic topology, constrained on bandwidth, energy and computing resources, there is a need to design the routing protocols efficiently. Flooding is a directive for managing traffic since it makes use of only chosen nodes for transmitting data from one node to another. This paper intends to develop a new Cluster-Based Flooding using Fuzzy Logic Scheme (CBF2S). To construct clusters and choose proper cluster heads (CHs), thefuzzy logic approach is applied with the use of three parameters namely link quality, node mobility and node degree. The presented model considerably minimizes the number of retransmissions in the network. The presented model instructs the cluster members (CM) floods the packets inside a cluster called intra-cluster flooding and CHs floods the packets among the clusters called inter-cluster flooding. In addition, the gateway sends a packet to another gateway for minimizing unwanted data retransmissions when it comes under different CH. The presented CBF2S is simulated using NS2 tool under the presence of varying hop count. The CBF2S model exhibits maximum results over the other methods interms of overhead, communication overhead, traffic load, packet delivery ratio and the end to end delay.

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Improving Energy Efficiency in Internet of Things using Artificial Bee Colony Algorithm

Recent Patents on Engineering ◽

10.2174/1872212114999200616164642 ◽

2020 ◽

Vol 14 ◽

Author(s):

M. Sivaram ◽

V. Porkodi ◽

Amin Salih Mohammed ◽

S. Anbu Karuppusamy

Keyword(s):

Energy Efficiency ◽

Energy Consumption ◽

Artificial Bee Colony ◽

Trust Model ◽

Sensor Nodes ◽

Remote Areas ◽

Bee Colony ◽

Important Concern ◽

Wide Range ◽

Iot Devices

Background: With the advent of IoT, the deployment of batteries with a limited lifetime in remote areas is a major concern. In certain conditions, the network lifetime gets restricted due to limited battery constraints. Subsequently, the collaborative approaches for key facilities help to reduce the constraint demands of the current security protocols. Aim: This work covers and combines a wide range of concepts linked by IoT based on security and energy efficiency. Specifically, this study examines the WSN energy efficiency problem in IoT and security for the management of threats in IoT through collaborative approaches and finally outlines the future. The concept of energy-efficient key protocols which clearly cover heterogeneous IoT communications among peers with different resources has been developed. Because of the low capacity of sensor nodes, energy efficiency in WSNs has been an important concern. Methods: Hence, in this paper, we present an algorithm for Artificial Bee Colony (ABC) which reviews security and energy consumption to discuss their constraints in the IoT scenarios. Results: The results of a detailed experimental assessment are analyzed in terms of communication cost, energy consumption and security, which prove the relevance of a proposed ABC approach and a key establishment. Conclusion: The validation of DTLS-ABC consists of designing an inter-node cooperation trust model for the creation of a trusted community of elements that are mutually supportive. Initial attempts to design the key methods for management are appropriate individual IoT devices. This gives the system designers, an option that considers the question of scalability.

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Spectrum Based Power Management for Congested IoT Networks

Sensors ◽

10.3390/s21082681 ◽

2021 ◽

Vol 21 (8) ◽

pp. 2681

Author(s):

Kedir Mamo Besher ◽

Juan Ivan Nieto-Hipolito ◽

Raymundo Buenrostro-Mariscal ◽

Mohammed Zamshed Ali

Keyword(s):

Power Management ◽

Network Performance ◽

Channel Allocation ◽

Battery Life ◽

Packet Routing ◽

Data Packets ◽

Increasing Demand ◽

Iot Devices ◽

Set Up

With constantly increasing demand in connected society Internet of Things (IoT) network is frequently becoming congested. IoT sensor devices lose more power while transmitting data through congested IoT networks. Currently, in most scenarios, the distributed IoT devices in use have no effective spectrum based power management, and have no guarantee of a long term battery life while transmitting data through congested IoT networks. This puts user information at risk, which could lead to loss of important information in communication. In this paper, we studied the extra power consumed due to retransmission of IoT data packet and bad communication channel management in a congested IoT network. We propose a spectrum based power management solution that scans channel conditions when needed and utilizes the lowest congested channel for IoT packet routing. It also effectively measured power consumed in idle, connected, paging and synchronization status of a standard IoT device in a congested IoT network. In our proposed solution, a Freescale Freedom Development Board (FREDEVPLA) is used for managing channel related parameters. While supervising the congestion level and coordinating channel allocation at the FREDEVPLA level, our system configures MAC and Physical layer of IoT devices such that it provides the outstanding power utilization based on the operating network in connected mode compared to the basic IoT standard. A model has been set up and tested using freescale launchpads. Test data show that battery life of IoT devices using proposed spectrum based power management increases by at least 30% more than non-spectrum based power management methods embedded within IoT devices itself. Finally, we compared our results with the basic IoT standard, IEEE802.15.4. Furthermore, the proposed system saves lot of memory for IoT devices, improves overall IoT network performance, and above all, decrease the risk of losing data packets in communication. The detail analysis in this paper also opens up multiple avenues for further research in future use of channel scanning by FREDEVPLA board.

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