Resource Constraints Of Devices Research Articles

A Novel Simulated-Annealing Based Electric Bus System Design, Simulation, and Analysis for Dehradun Smart City

Smart transportation network development with environmental issues into consideration has brought Industry 4.0 based solutions on priority. In this direction, battery-powered electric bus systems have been considered widely for ensuring flexibility, operation cost, and lesser pollutants emission. Industry 4.0 provides automation through a cyber-physical system (CPS), the interconnection of bus system entities with industrial internet-of-things (IIoT), remote information availability through cloud computing and scientific disciplines (human-computer interaction, artificial intelligence, machine learning etc.) integration. In this work, a discrete event-based simulation-optimization approach is integrated that take care of bus energy consumption according to real-time city's passenger needs and on-road friction levels. The proposed simulation optimization methodology utilizes multi-objective with dependent and independent variables for optimizing the overall system performance. In simulation optimization, objective functions are designed to tackle battery consumption, Internet-of-Thing (IoT) network performance, cloud operations efficiency and smart scientific discipline integration. Simulation parameters are based on a real-time bus system which is further analyzed, filtered and adapted as per the needs of the system. In another analysis, supercharger's capacities are varied to evaluate the performance of the proposed system and identify the low cost and efficient smart transportation system. Simulation results show different scenarios for variations in the number of buses, charging stations, bus-depots, mobile charging facilities, and bus-schedules. Simulation results show that the average passenger's waiting time in the waiting is (after ticket booking) varies between 0.2 minutes to 0.7 minutes in real-time traffic conditions. In similar traffic conditions, total passenger's time in system (ticket booking to travel) varies between 41.6 minutes (for 24 hours) to 45.5 minutes (for 1 year). In the simulation, priorities are given to those dependent and independent variables which save the battery consumption and elongate the utilization of buses. Lastly, it is also observed that the proposed system is suitable for resource-constraint devices because Gate Equivalent (GE) calculation shows that the proposed system can be implemented between 1986 GEs (communicational cost without confidentiality and authentication) and 7939 GEs (computational cost with HMAC for authentication in data storage). This ensures varies security primitivs such as confidentiality, availability and authentication.

A Versatile Out-of-Band Software-Defined Networking Solution for the Internet of Things

The Internet of Things (IoT) is gradually incorporating multiple environmental, people, or industrial monitoring deployments with diverse communication and application requirements. The main routing protocols used in the IoT, such as the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL), are focusing on the many-to-one communication of resource-constraint devices over wireless multi-hop topologies, i.e., due to their legacy of the Wireless Sensor Networks (WSN). The Software-Defined Networking (SDN) paradigm appeared as a promising approach to implement alternative routing control strategies, enriching the set of IoT applications that can be delivered, by enabling global protocol strategies and programmability of the network environment. However, SDN can be associated with significant network control overhead. In this paper, we propose VERO-SDN, an open-source SDN solution for the IoT, bringing the following novelties in contrast to the related works: (i) programmable routing control with reduced control overhead through inherent protocol support of a long-range control channel; and (ii) a modular SDN controller and an OpenFlow-like protocol improving the quality of communication in a wide range of IoT scenarios through supporting two alternative topology discovery and two flow establishment mechanisms. We carried out simulations with various topologies, network sizes and high-volume transmissions with alternative communication patterns. Our results verified the robust performance and reduced control overhead of VERO-SDN for alternative IoT deployments, e.g., achieved up to 47% reduction in network's overall end-to-end delay time compared to RPL and a packet delivery ratio of over 99.5%.

Towards Light Weight CryptographySchemes for Resource ConstraintDevices in IoT

Towards Light Weight CryptographySchemes for Resource ConstraintDevices in IoT

Lightweight Security Protocol for Efficient Information Transfer in Sensor Networks

Wireless Sensor Networks have become major integral components of various other technologies like- IoT, Big Data, Cloud Computing and many. This impact is also making WSNs to grow more rapidly and its global market size is predicted to grow $944.92 million by 2020, at a CAGR of 12.96%. In-spite of this impact some challenges and application requirements in WSNs is there limiting its performance. In this article a detailed analysis and research has been carried out to address and resolve some of the major issues in the WSNs. This paper mainly aims in identifying and analyzing the major challenges and requirements along with some existing works in WSNs. Based on the identified problems this article presents the solution to increase the performance of WSNs. The main focus is given to energy and security aspects in the WSNs. The proposed protocol provides more strengthening security parameters with a focus on increasing the lifetime of the network in the resource constraint devices. The outcome of this paper is resulted in better results than the existing security and energy mechanism in the field of the wireless sensor networks.

A Lightweight Authentication Method in Perception Layer of IoT Through Digital Watermarking

Introduction of IoT (Internet of Things) has enjoyed vigorous support from governments and research institutions around the world, and remarkable achievements have been obtained till date. IoT systems collect the voluminous amount of data in real time from hospitals, battlefield and daily living environment which is related to privacy and security of people. So, securing collected sensitive data is one of the major challenges in the development of IoT systems. Authenticating the source of collected data is utmost important because the adversary may act as a source which may lead to a breach in security and privacy of people using the IoT network. IoT devices are resource scarce so lightweight methods for network security and privacy need to develop to achieve future development goals. In this paper, a novel lightweight node to node authentication scheme based on watermark is proposed to solve the contradiction between the security and restricted resources of perception layer. To improve the security, Proposed scheme usage node identity and the number of neighbours as input to generate the watermark and use the watermark to calculate the embedding positions which makes node authentication based on temporal dynamics of sensing network. The generated watermark is embedded in fixed size message digest generated using the variable message as input into a low-cost one-way hashing algorithm LOCHA. The embedded bits of watermark extracted at the receiving node and matched to check the authenticity of the sender node. The security analysis and simulations of the proposed scheme show that it can be a good candidate to ensure the authentication of the resource constraint devices which are integral part of Internet of Things at low cost.

Design Considerations of Lightweight Block Ciphers for Low-Cost Embedded Devices

In the 21st century, Internet of Things (IoT) has become pivotal technology and has attracted worldwide attention in the smart computing environment. In order to enjoy the benefits of this new environment, security is considered as the main aspect in constrained end nodes. Ordinary cryptographic solutions are not sufficient for resource constraint devices. To fulfill this gap, a relatively new field of cryptography called lightweight cryptography came into existence. Furthermore, designing lightweight ciphers especially software oriented poses some significant limits and inherent conditions. Some design considerations of a lightweight encryption algorithm and tradeoffs for minimizing resource requirements are presented in this paper. Also, for a cipher, it is necessary to provide strong resistance against attacks. In this paper different countermeasures to prevent from attacks is also presented. By considering the performance-enhancing ideas presented in this paper, a new GFN based lightweight block cipher is proposed. A cipher design has two main parts; internal structure and key schedule. The internal structure of the proposed design has three layers in which operations are so arranged that it utilizes small code size and has fast diffusion. Besides, design of newly proposed cipher is such that it thwarts the effect of most of the attacks. In the nutshell, this paper serves as a base for designing good lightweight cipher for resource constraint smart IOT environment.

Hierarchical Key Management Scheme with Probabilistic Security in a Wireless Sensor Network (WSN)

Securing data transferred over a WSN is required to protect data from being compromised by attackers. Sensors in the WSN must share keys that are utilized to protect data transmitted between sensor nodes. There are several approaches introduced in the literature for key establishment in WSNs. Designing a key distribution/establishment scheme in WSNs is a challenging task due to the limited resources of sensor nodes. Polynomial-based key distribution schemes have been proposed in WSNs to provide a lightweight solution for resource-constraint devices. More importantly, polynomial-based schemes guarantee that a pairwise key exists between two sensors in the WSNs. However, one problem associated with all polynomial-based approaches in WSNs is that they are vulnerable to sensor capture attacks. Specifically, the attacker can compromise the security of the entire network by capturing a fixed number of sensors. In this paper, we propose a novel polynomial-based scheme with a probabilistic security feature that effectively reduces the security risk of sensor-captured attacks and requires minimal memory and computation overhead. Furthermore, our design can be extended to provide hierarchical key management to support data aggregation in WSNs.

A Novel Approach towards Resource Auto-Registration and Discovery of Embedded Systems Based on DNS

The Internet of Things (IoT) is expected to deliver a whole range of new services to all parts of our society, and improve the way we work and live. The challenges within the Internet of Things are often related to interoperability, device resource constraints, a device to device connection and security. One of the essential elements of identification for each Internet of Things devices is the naming system and addresses. With this naming system, Internet of Things devices can be able to be discoverable by users. In this paper, we propose the IoT resource auto-registration and accessing indoor services based on Domain Name System (DNS) in the Open Connectivity Foundation (OCF) environment. We have used the Internet of Things Platform and DNS server for IoT Resource auto-registration and discovery in the Internet Protocol version 4 (IPv4). An existing system called Domain Name Auto-Registration in Internet Protocol version 6 can be used for Internet of Things devices for auto-registration and resource discovery. However, this system is not acceptable in the existing internet networks, because the highest percentage of the networks on the Internet are configured in Internet Protocol version 4. Through the proposed auto-registration system, clients can be able to discover the resources and access the services in the OCF network. Constrained Application Protocol (CoAP) is utilized for the IoT device auto-registration and accessing the services in the OCF network.

Privacy preserving light weight authentication protocol (LEAP) for WBAN by exploring Genus-2 HEC

Wireless Body Area Network (WBAN) is evolving as the successful way of monitoring patient health and offers enhanced healthcare solutions to provide the better quality of life for the urban community. As it involves wireless communications, securing the privacy-related data is a key constraint in WBAN. To ensure privacy, it is essential to include authentication to prevent unauthorized access by intruders. This paper proposes the privacy preserving LightwEight two factors Authentication Protocol (LEAP) for WBAN based on genus-2 Hyper Elliptic Curve (HEC). Personal Digital Assistant (PDA) collects signals from sensors from the BAN. PDA transmits the healthcare data to the Healthcare Service Provider (HSP) connected in the public network. Hence, the two-factor mutual authentication protocol is established between PDA and HSP. Since PDA is considered as a resource constraint device, the lightweight mutual authentication is required. Genus 2 Hyper elliptic curve (HEC) is carefully designed to prevent all possible cryptographic attacks, which is more suitable for lightweight authentication since it provides the high degree of security with the lesser key size even as compared to the elliptic curve. Using the rigorous formal security analysis using BAN logic, it is proved that the proposed scheme is secure against possible attacks. Also, the privacy preserving lightweight authentication scheme is implemented using the most-widely accepted Automated Validation of Internet Security Protocols and Applications (AVISPA) tool, and the simulation results reveal that proposed scheme is secure and robust.

Analysis of Drone assisted Network Coded Cooperation for Next Generation Wireless Network

In this paper, use of drone as a relay node in Network Coded Cooperation (NCC) for upcoming wireless networks is proposed to achieve additional diversity as well as improve throughput. Unlike static relay cases, in drone assisted scenarios, better performance can be achieved simply by changing the position of relay. In order to quantify the network performance in drone assisted NCC, analytical closed form expression of outage probability has been calculated using two approaches namely, Analytical and Semi-analytical. Using a generalized system model, Probability Density Function (PDF) of Signal to Noise Ratio (SNR) of the path from source to destination via drone (relay) is derived. Closed form expression for outage probability in absence of direct link is also investigated. By analyzing Analog Network Coding (ANC) noise, statistical parameters of variance of ANC-noise have been obtained. Analytical findings have been verified through extensive simulations using MATLAB. Effects of drone height on system performance is also investigated through simulations. Framework presented here can be useful while analysing networks having resource constraint devices. PDF of SNR of relay path can be utilized for performing diversity calculations. Two outage expressions derived may be useful in determining system parameters for achieving any particular Quality of Service (QoS) in next generation wireless networks. Valuable insights obtained through the analysis of optimum height of drone are conducive while deploying the nodes in deterministic fashion for NCC.

Energy- and Latency-Aware Hybrid Offloading Algorithm for UAVs

One of the most promising use cases of 5G/IMT2020 is the unmanned aerial vehicle (UAV). Due to their small size, the UAVs are resource constraint devices. To this end, this paper proposes an offloading algorithm for UAVs to assist in the execution of computationally intensive tasks. The proposed algorithm provides two UAV offloading methods. The first offloading method is the air-offloading, where a UAV can offload its computing tasks to nearby UAVs that have available computing and energy resources. The second offloading method is the ground-offloading, which enables the offloading of tasks to an edge cloud server from the multi-level edge cloud units connected to ground stations. The proposed algorithm is energy- and latency-aware, i.e., it selects the execution device and the offloading method based on the latency and energy constraints. The intensive algorithm simulation over reliable conditions for various scenarios with different cases for each scenario is conducted and results are presented.

Cryptography-Based Misbehavior Detection and Trust Control Mechanism for Opportunistic Network Systems

Opportunistic networks (OppNets) are a subclass of delay tolerant networks and are characterized by intermittent end-to-end connections. The sparsity in the network and the resource constraint of devices always restricts the use of cryptographic solutions for security needs in the OppNets for thwarting selfishness of the nodes. The trust-based mechanisms are capable of providing social security in terms of access control in the network. But the trust-based protocols do not solve the problem of isolating, avoiding, and detecting the malicious intent nodes with the provision of security services such as authentication, confidentiality, and message integrity through cryptographic means. In this work, a robust and scalable infrastructure based security overlay is designed over the base trust-based routing for detecting malicious nodes and providing security services through the established cryptographic mechanism. The proposed security-based algorithm is general enough to accommodate and use latest cryptographic techniques in trust-based routing for ensuring more participation through building confidence in the network. The simulation results are taken using ONE simulator and the results confirm that the application of security overlay above the base trust-based protocol helps in increasing the average performance by 35%.

Availability Aspects Through Optimization Techniques Based Outlier Detection Mechanism in Wireless and Mobile Networks

Radio Frequency IDentification (RFID) and Wireless Sensor Networks (WSN) are the two most prominent wireless technologies for implementing a complete smart environment for the Internet of Things (IoT). Both RFID and WSN are resource constraint devices, which forces us to go for lightweight cryptography for security purposes. Security in terms of confidentiality, integrity, authentication, authorization, and availability. Key management is one of the major constraints for resource constraint mobile sensor devices. This work is an extension of the work done by Kumar et al. using efficient error prediction and limit of agreement for anomaly score. This work ensures cryptographic property, availability, in RFID-WSN integrated network through outlier detection mechanism for 50 to 5000 nodes network. Through detection ratios and anomaly scores system is tested against outliers. The proposed outlier detection mechanism identifies the inliers and outliers through anomaly score for protection against Denial-of-Service (DoS) attack. Intruders can be detected in few milliseconds without giving any conflict to the access rights. In terms of throughput, a minimum improvement of 6.2% and a maximum of 219.9% is observed for the proposed protocol as compared to Kumar et al. Protocol and in terms of percentage of Packet Delivery Ratio (PDR), a minimum improvement of 8.9% and a maximum of 19.5% is observed for the proposed protocol as compared to Kumar et al. protocol.

Availability Aspects Through Optimization Techniques Based Outlier Detection Mechanism in Wireless and Mobile Networks

Radio Frequency IDentification (RFID) and Wireless Sensor Networks (WSN) are the two most prominent wireless technologies for implementing a complete smart environment for the Internet of Things (IoT). Both RFID and WSN are resource constraint devices, which forces us to go for lightweight cryptography for security purposes. Security in terms of confidentiality, integrity, authentication, authorization, and availability. Key management is one of the major constraints for resource constraint mobile sensor devices. This work is an extension of the work done by Kumar et al. using efficient error prediction and limit of agreement for anomaly score. This work ensures cryptographic property, availability, in RFID-WSN integrated network through outlier detection mechanism for 50 to 5000 nodes network. Through detection ratios and anomaly scores system is tested against outliers. The proposed outlier detection mechanism identifies the inliers and outliers through anomaly score for protection against Denial-of-Service (DoS) attack. Intruders can be detected in few milliseconds without giving any conflict to the access rights. In terms of throughput, a minimum improvement of 6.2% and a maximum of 219.9% is observed for the proposed protocol as compared to Kumar et al. Protocol and in terms of percentage of Packet Delivery Ratio (PDR), a minimum improvement of 8.9% and a maximum of 19.5% is observed for the proposed protocol as compared to Kumar et al. protocol.

Secure Data Aggregation Techniques for Wireless Sensor Networks: A Review

Wireless sensor networks (WSN) are made up of energy constraint tiny sensing devices which are distributed geographically to monitor inhabited remote areas by collecting the physical phenomenon like temperature, pressure etc. They play a vital role in military surveillance, environment monitoring etc. Unstructured topology in WSN results in large amount of redundant data being transmitted over the resource constraint devices which leads to energy starvation problem. Since the nodes are prone to tamper, thanks to their environment, ensuring the privacy of sensitive data being aggregated and transmitted is important. Hence data aggregation schemes which minimize the data redundancy with the guarantee of security become the attraction of research. Many secured aggregation schemes have been proposed by researchers. In this survey the various existing solutions are surveyed and an attempt is made to classify them based on the node topology and mechanisms employed for assuring privacy.

Multi-key Modified Tiny Encryption Algorithm for HealthCare

Healthcare data is crucial in patient’s surveillance. To give the finest treatment to patients the data should be of the best quality. Many security threats affect the integrity and ingenuity of the medical data. In the recent times, medical data can be accessed anytime and anywhere with the help of an overwhelming technology called the Internet of Things (IoT). IoT has numerous applications based on healthcare, however, it facilitates data misuse such as data breach and health care fraud. Sensitive and protected data is stolen and modified by an unauthorized person. Due to these data abuses, it degrades the quality of medical data and service. In this paper, secure data transfer is done in IoT based healthcare to enhance the security of the medical data. Data confidentiality can be achieved using encryption algorithms such as Tiny Encryption Algorithm (TEA) which is lightweight and suitable for resource constraint devices. The results of the proposed system show that the modified TEA overcomes the drawback of the equivalent key and also provides a better security to healthcare data.

Secure Outsourcing of Large-scale Linear Programming

Linear programming (LP) is often used in reality production and life, such as the use of resources, human resource management, production arrangement. The client should pay out huge amounts of overhead to dispose huge data sets with its resource-constraint devices. Fortunately, Cloud computing can finish off this deficiency. The client outsources the computation to cloud servers. Then the servers accomplish the task and return the result to the client. But in the process, the correctness, verifiability and privacy should be emphasized. In our paper, based on the studies and analysis of previous protocols for secure outsourcing of linear programming in cloud computing, we find the obvious deficiencies in efficiency and safety. On the basis of the existing protocols, we propose a new protocol that combines the advantages of existing protocols and improves the shortcomings of existing protocols. We also analyze the security and efficiency of the new protocol and design a suitable simulation to verify the efficiency of this protocol.

An Adaptive Scheduler for Real-Time Operating Systems to Extend WSN Nodes Lifetime

Wireless Sensor Networks (WSNs) are a growing research area as a large of number portable devices are being developed. This fact makes operating systems (OS) useful to homogenize the development of these devices, to reduce design times, and to provide tools for developing complex applications. This work presents an operating system scheduler for resource-constraint wireless devices, which adapts the tasks scheduling in changing environments. The proposed adaptive scheduler allows dynamically delaying the execution of low priority tasks while maintaining real-time capabilities on high priority ones. Therefore, the scheduler is useful in nodes with rechargeable batteries, as it reduces its energy consumption when battery level is low, by delaying the least critical tasks. The adaptive scheduler has been implemented and tested in real nodes, and the results show that the nodes lifetime could be increased up to 70% in some scenarios at the expense of increasing latency of low priority tasks.

Feature reduction for classification of daily activities through kinematic data from smartphones

Abstract Linear acceleration and angular rotation data measured from a human body can provide insights on how a person moves. These kinematic data are typically analyzed and used to understand disease progression associated with movement disorders. Time and frequency domain features extracted from such data are often of large dimensions and not feasible for implementation on resource-constraint devices. In this paper, we propose two optimal feature selection schemes that can better characterize the kinematic measurements to distinguish the movements of a person. One of the proposed approach is based on principal component analysis and the other is based on combinatorial high frequency feature selection from multi-classification algorithms to reduce the features required to maintain high activity prediction rate. We apply three classification algorithms to differentiate the activities a subject was engaged in. Results show the features can be reduced from 561 to 15 with above 84% activity prediction accuracy.

Industrial Wireless Monitoring with Energy-Harvesting Devices

Vibration monitoring and analysis techniques are used increasingly for predictive maintenance. While traditional vibration monitoring relies on wired sensor networks, recent industrial technologies such as WirelessHART, ISA100.11a, and IEEE 802.15.4e have brought a paradigm shift in the automation sector by integrating the flexibility of wireless technologies with the versatility of Internet tools. However, these wireless technologies aren't designed to support strict resource constraint devices, and thus are still unable to fulfill the needs of many modern industrial applications. This article describes a new industrial wireless monitoring system capable of supporting energy-harvested devices through intelligent sensing and network management.