Resource Constraints Of Sensor Nodes Research Articles

A novel and optimized computational framework for energy efficient data dissemination in wireless sensor network

Wireless sensor network (WSN) is an integral part of internet-of-things (IoT), where a large scale of data transmission and various complex services are identified to be delivered. In order to facilitate these services, energy efficiency is one critical demand for resource-constraint sensor nodes. Carrier sense multiple access (CSMA) has been considered for effective traffic management for high-end data delivery services. A review of existing literature on CSMA-based schemes shows that it has not yet achieved an optimal case of energy efficiency. Hence, the proposed study presents a novel computational framework in order to address this research gap. The prime contribution of the proposed study is towards presenting an optimal computational model for maximized fairness in data dissemination services in WSN especially focusing on energy efficiency. The presented study model also contributes towards optimizing route buffer and buffer power, which facilitates towards availability of energy-efficient path information. The study also introduces a mobile auxiliary node that aggregates the data from sensor nodes and delivers it to the sink node considering dynamic location updates for seamless transmission. Scripted in MATLAB, the proposed scheme exhibited 70% energy saving compared to conventional schemes of CSMA in WSN.

Secure Key Management and Mutual Authentication Protocol for Wireless Sensor Network by Linking Edge Devices using Hybrid Approach

Wireless Sensor Networks (WSNs) play a crucial role in developing the Internet of Things (IoT) by collecting data from hostile environments like military and civil domains with limited resources. IoT devices need edge devices to perform real-time processing without compromising the security with the help of key management and authentication schemes. The above applications are prone to eavesdropper due to cryptographic algorithms' weaknesses for providing security in WSNs. The security protocols for WSNs are different from the traditional networks because of the limited resource of sensor nodes. Existing key management schemes require large key sizes to provide high-security levels, increasing the computational and communication cost for key establishment. This paper proposes a Hybrid Key Management Scheme for WSNs linking edge devices which use Elliptic Curve Cryptography (ECC) and a hash function to generate key pre-distribution keys. The Key establishment is carried out by merely broadcasting the node identity. The main reason for incorporating a hybrid approach in the key pre-distribution method is to achieve mutual authentication between the sensor nodes during the establishment phase. The proposed method reduces computational complexity with greater security and the proposed scheme can be competently applied into resource constraint sensor nodes.

Secure and Energy-Efficient Network Topology Obfuscation for Software-Defined WSNs

Network topology obfuscation (NTO) is generally considered as a promising proactive mechanism to mitigate traffic analysis attacks. The main challenge is to strike a balance among energy consumption, reliable routing, and security levels due to resource constraints in sensor nodes. Furthermore, software-defined wireless sensor networks (WSNs) are more vulnerable to traffic analysis attacks due to the uncovered pattern of control traffic between the controller and the nodes. In this article, a new energy-aware NTO mechanism is proposed, which maximizes the attack costs and is efficient and practical to be deployed. Specifically, first, a route obfuscation method is proposed by utilizing ranking-based route mutation, based on four different critical criteria: 1) route overlapping; 2) energy consumption; 3) link costs; and 4) node reliability. Then, a sink node obfuscation method is introduced by selecting several fake sink nodes that are indistinguishable from actual sink nodes, according to the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> -anonymity model. As a result, the most suitable routes and sink nodes can be selected, and a highest obfuscation level can be reached without sacrificing energy efficiency. Finally, extensive simulation results demonstrate that the proposed methods can strongly mitigate traffic analysis attacks and achieve effective NTO for software-defined WSNs. In addition, the proposed methods can reduce the success rate of the attacks while achieving lower energy consumption and higher network lifetime.

Enhanced Security with Improved Defensive Routing Mechanism in Wireless Sensor Networks

In recent scenario of Wireless Sensor Networks (WSNs), there are many application developed for handling sensitive and private data such as military information, surveillance data, tracking, etc. Hence, the sensor nodes of WSNs are distributed in an intimidating region, which is non-rigid to attacks. The recent research domains of WSN deal with models to handle the WSN communications against malicious attacks and threats. In traditional models, the solution has been made for defending the networks, only to specific attacks. However, in real-time applications, the kind of attack that is launched by the adversary is not known. Additionally, on developing a security mechanism for WSN, the resource constraints of sensor nodes are also to be considered. With that note, this paper presents an Enhanced Security Model with Improved Defensive Routing Mechanism (IDRM) for defending the sensor network from various attacks. Moreover, for efficient model design, the work includes the part of feature evaluation of some general attacks of WSNs. The IDRM also includes determination of optimal secure paths and Node security for secure routing operations. The performance of the proposed model is evaluated with respect to several factors; it is found that the model has achieved better security levels and is efficient than other existing models in WSN communications. It is proven that the proposed IDRM produces 74% of PDR in average and a minimized packet drop of 38% when comparing with the existing works.

Improving multimedia data transmission quality in wireless multimedia sensor networks though priority-based data collection

&lt;span&gt;Wireless multimedia sensor networks (WMSNs) are special kinds of wireless sensor networks (WSN) that can send multimedia data such as audio and video streams. Sensors used in WMSNs are smart, tiny, and resource constraint sensor nodes (SNs) distributed in a large area. Typically, multimedia data are large in comparison to other data types. As a result, WMSNs have to deal with high volumes of packet transmission, leading to a high rate of packet loss and network congestion. Network congestion can significantly affect the quality of service and usually lead to high energy consumption. Thus, to improve the quality of service (QoS) and transmission performance, it is necessary to deal with network congestion. In the past, different packet prioritizing methods were proposed to deal with this issue. However, improving QoS usually requires high energy to function correctly. Consequently, using rechargeable sensor nodes to reduce energy consumption is an acute solution. In this research, priority-based data collection is considered to cut down on data distortion and improve the QoS of the multimedia sensor network. Additionally, energy harvesting sensor nodes were used to reduce energy consumption due to the high transmission rate. The simulation result shows a noticeable improvement in the performance of our proposed method in comparison to previous methods.&lt;/span&gt;

An Improved 2-Factor Authentication Scheme for WSN Based on ECC

The Internet of Things (IoT) stands as one of the emerging technologies because of its novel innovations and solutions for countless domains. As one of the enabling components for IoT, Wireless Sensor Network (WSN) is utilized for various real-world appliances to collect valuable raw sensed data. Here, valuable data from the sensor nodes are suitable to access with the help of a gateway node through the registered user. However, due to the resource constraints of sensor nodes and the exposed nature of the wireless frequency, security has turned out to a considerable task in WSN. Authentication is a primary security facility that can ensure the legitimacy of data access in WSN. There are numerous 2-factor verification protocols in related work based on a smartcard, public-key, and password. However, most of them have trouble reconciling proficiency and security necessities; hence, it is still challenging to implement a 2-factor authentication scheme to satisfy security topographies while preserving suitable proficiency. We designed an enhanced 2-factor verification scheme based on ECC and biometric information in this work. Our proposed scheme accomplishes distinct security features and protocol-designed logic verified with the AVISPA tool. Simulation results demonstrate that the projected scheme is robust, energy-efficient, and well-suited to WSN environments.

Modeling of lightweight security framework for identifying efficient route for secure communication in WSN

PurposeIn the past recent years, wireless sensor network (WSN) has progressively grown as an emerging technology. Various research efforts have been made in the literature to address the problem associated with WSN security. Based on the review analysis, it is found that the existing methods are mostly associated with complex security operations that are not suitable for resource constraint sensor nodes. The proposed paper has presented cost-effective modeling of the security framework that addresses the problem of security and energy in WSN.Design/methodology/approachThe proposed security framework implements two different protocols to attain maximum security services and optimizes the security operation of the proposed security models to achieve higher energy efficiency and privacy preservation against a majority of the lethal attacks. The first security model introduces a novel cost-efficient pairwise key-based authentication mechanism to identify the availability of optimal routes under the presence of adversary in the network. The second security model introduces an integrated part of the first security model that optimizes security operation to perform secure communication using a lightweight encryption mechanism.FindingsBased on the experimental outcome and analysis, the proposed system attains a 60% performance improvement in terms of security and computational efficiency compared to the existing Sec-LEACH. The second security model has achieved a 50% improvement in terms of overall aspects like reduction in transmission delay, packet delivery ratio, remaining energy and communication performance.Originality/valueThe proposed study has presented a computationally efficient model that provides lightweight security operations based on secure hash function. It also focuses on the security associations between WSN nodes and the selection of reliable routes for secure data transmission. The design of the proposed security model is best suited for homogeneous and heterogeneous sensor networks, which will be robust to any attacking scenario.

Snapshot of Energy Optimization Techniques to Leverage Life of Wireless Sensor Network

Energy Optimization in Wireless Sensor Network (WSN) deals with the techniques which targets higher degree of energy efficiency using resource-constraint sensor nodes with minimal inclusion of any different variants of resources. At present, there are various approaches and techniques towards addressing the problems of energy but not all the research implications can be considered as optimized approach. Therefore, this paper reviews all the existing energy optimization schemes, categorizes them, briefly discuss about their strength and weakness to offer a compact snapshot of existing energy optimization techniques in WSN. The paper also contributes towards exploring the updates research trends and highlights about the open-end research problems in WSN. It is anticipated that the study findings of this manuscript will offer a true picture of study effectiveness in dealing with energy challenges so that favorable direction of investigation towards evolving up optimized solution comes up with promising outcome.

Efficient FEC Scheme for Solar-Powered WSNs Considering Energy and Link-Quality

In solar-powered wireless sensor networks (SP-WSNs), the best use of harvested energy is more important than minimizing energy consumption since energy can be supplied periodically. Meanwhile, as is well known, the reliability of the communication between sensor nodes is very limited due to the resource constraints of sensor nodes. In this paper, we propose an efficient forward error correction (FEC) scheme which can give solar-powered wireless sensor networks more reliable communication. First, the proposed scheme provides energy-adaptive operation for the best use of solar energy. It calculates the amount of surplus energy which can be used for extra operations and then determines the number of additional parity bits for FEC according to this amount of surplus energy. At the same time, it also provides a link quality model that is used to calculate the appropriate number of parity bits for error recovery required for the current data communication environment. Finally, by considering these two parity sizes, it is possible to determine the number of parity bits that can maximize the data reliability without affecting the blacking out of nodes. The evaluation of the performance of the approach was performed by comparing the amount of data collected at the sink node and the number of blackout nodes with other schemes.

UCFL: User Categorization using Fuzzy Logic towards PUF based Two-Phase Authentication of Fog assisted IoT devices

Internet of Things (IoT) makes the daily life easier by increasing the connectivity between the devices. The increase in number of connected devices makes the network vulnerable to various threats. The resource constraint sensor nodes added more challenge for the researchers to implement security schemes in IoT network. In this paper a three layer framework for IoT environment is designed where the users of first layer are intended to collect data from the sensor nodes of third layer through the fog devices that are belongs to second layer. The resource constraint sensor nodes are released from checking the authenticity of users to save their energy. Thus some high capacity nodes, called fog devices, are involved to check the authentication of users. The users are categorized as high, medium or low trusted by using fuzzy logic. Further it delves for the authentication of low and medium trusted user by implementing a lightweight two phase authentication scheme. Physical Unclonable Function (PUF) is used to generate unique identity for individual users and to create Challenge Response Pairs (CRPs). The performance is evaluated by using Raspberry Pi as a user and a laptop as a fog device. The simulation results show that the proposed scheme outperforms the existing schemes in terms of average response time, handshake duration, memory utilization and communication cost. Moreover this scheme is resilience against replay attack, DoS attack, false data injection and man in the middle attack.

Signature Gateway: Offloading Signature Generation to IoT Gateway Accelerated by GPU

The emergence of Internet of Things (IoT) brings us the possibility to form a well connected network for ubiquitous sensing, intelligent analysis, and timely actuation, which opens up many innovative applications in our daily life. To secure the communication between sensor nodes, gateway devices and cloud servers, cryptographic algorithms (e.g., digital signature, block cipher, and hash function) are widely used. Although cryptographic algorithms are effective in preventing malicious attacks, they involve heavy computation that may not be executed efficiently in resource constraint sensor nodes. In particular, the authentication of a sensor node is usually performed through a digital signature (e.g., RSA and elliptic curve cryptography), which can be slow when executed on a microcontroller. In this paper, an IoT architecture that offloads the digital signature generation to a nearby signature gateway equipped with graphic processing unit (GPU) accelerator are proposed. The communication process for signature offloading, together with optimized implementation techniques for RSA in signature gateway, are also presented in this paper. We have evaluated two different ways to implement modular exponentiation in RSA, namely residue number system and multiprecision montgomery multiplication (MPMM). The experimental results show that our RSA implementation using MPMM is 10.1% faster than the best RSA implementation in GPU. Our proposed IoT architecture with signature gateway can successfully reduce the burden of sensor nodes to generate signatures, at the same time preserve the ability to authenticate the sensor nodes.

An Opportunistic Spectrum Access Scheme for Multicarrier Cognitive Sensor Networks

In this paper, we consider a broadband cognitive radio wireless sensor network operating in a crowded spectrum scenario, where a sensor transmitter (i.e., a sensor node that needs to transmit information to another sensor node or to a sink) opportunistically uses the channel of a primary system adopting an underlay paradigm. Both the primary and sensor systems employ an orthogonal frequency-division multiplexing (OFDM) modulation scheme. The proposed approach is reminiscent of additive superposition coding: specifically, the sensor transmitter behaves as an amplify-and-forward relay for the primary system, by sending a linearly weighted combination of the received primary signal and its own block of symbols. Such a superposition is performed by the sensor transmitter on the fly, in a single OFDM symbol of the primary system. Moreover, the proposed scheme does not require spectrum sensing at the sensor nodes and does not demand any cooperation between primary and sensor systems, thereby accounting for the inherent resource constraints of sensor nodes. With reference to both primary and sensor communications, we address the problem of power allocation by considering different amounts of channel state information and develop a worst case analysis of the achievable information rates. The developed algorithms and the derived formulas, which are corroborated by numerical Monte Carlo simulations, allow one to recognize and discuss interesting tradeoffs between the main parameters of the cognitive radio sensor transmission.

Localization-Free Detection of Replica Node Attacks in Wireless Sensor Networks Using Similarity Estimation with Group Deployment Knowledge.

Due to the unattended nature and poor security guarantee of the wireless sensor networks (WSNs), adversaries can easily make replicas of compromised nodes, and place them throughout the network to launch various types of attacks. Such an attack is dangerous because it enables the adversaries to control large numbers of nodes and extend the damage of attacks to most of the network with quite limited cost. To stop the node replica attack, we propose a location similarity-based detection scheme using deployment knowledge. Compared with prior solutions, our scheme provides extra functionalities that prevent replicas from generating false location claims without deploying resource-consuming localization techniques on the resource-constraint sensor nodes. We evaluate the security performance of our proposal under different attack strategies through heuristic analysis, and show that our scheme achieves secure and robust replica detection by increasing the cost of node replication. Additionally, we evaluate the impact of network environment on the proposed scheme through theoretic analysis and simulation experiments, and indicate that our scheme achieves effectiveness and efficiency with substantially lower communication, computational, and storage overhead than prior works under different situations and attack strategies.

Gravitational outlier detection for wireless sensor networks

SummaryAccuracy of sensed data and reliable delivery are the key concerns in addition to several other network‐related issues in wireless sensor networks (WSNs). Early detection of outliers reduces subsequent unwanted transmissions, thus preserving network resources. Recent techniques on outlier detection in WSNs are computationally expensive and based on message exchange. Message exchange‐based techniques incur communication overhead and are less preferred in WSNs. On the other hand, machine learning‐based outlier detection techniques are computationally expensive for resource constraint sensor nodes. The novelty of this paper is that it proposes a simple, non message exchange based, in‐network, real‐time outlier detection algorithm based on Newton's law of gravity. The mechanism is evaluated for its accuracy in detecting outliers, computational cost, and its influence on the network traffic and delay. The outlier detection mechanism resulted in almost 100% detection accuracy. Because the mechanism involves no message exchanges, there is a significant reduction in network traffic, energy consumption and end‐to‐end delay. An extension of the proposed algorithm for transient data sets is proposed, and analytic evaluation justifies that the mechanism is reactive to time series data. Copyright © 2016 John Wiley &amp; Sons, Ltd.

A Survey on Secure Routing Protocols in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are typically formed by the collaboration of the large amount of partial sensor nodes, which are connected through a wireless medium. In wireless sensor network, security is an essential aspect because of its usage in applications like monitoring, tracking, controlling, surveillance etc. Secure communication is extremely crucial in delivering vital information accurately and on the time through resource constraint sensor nodes. In this paper, our contribution is threefold. Firstly, we have summarized the network layer routing attacks on WSNs. Secondly, we have provided a taxonomy of secure routing protocols of WSNs. Thirdly, we have provided a qualitative comparison of existing secure routing protocols. Results show that most of the existing secure routing schemes are not very efficient due to various reasons like high-energy consumption, and large communication overhead.

USEE: A uniform data dissemination and energy efficient protocol for communicating materials

A new Internet of Things area is coming with communicating materials, which are able to provide diverse functionalities to users all along the product lifecycle. As example, it can track its own evolution which leads to gather helpful information. This new paradigm is fulfilled via the integration of specific electronic components into the product material. In this work, ultra-small Wireless Sensor Networks (WSN) are used for large scale materials such as concrete in smart building. Indeed, storage of lifecycle information and data dissemination in communicating materials are very important issues. Therefore, this paper provides solution for storing data by systematic dissemination through the integrated WSN. It presents USEE, a uniform data storage protocol for large scale communicating material. USEE guarantees that information could be retrieved in each piece of the material by intelligently managing data replication among each neighborhood of the WSN. Unlike related protocols of the literature, USEE considers in the same set uniformity storage in the whole network, the data importance level, and the resource constraints of sensor nodes. When compared with related protocols such as RaWMS, DEEP, and Supple, USEE shows a uniform dissemination and low communication overhead tradeoff for all the data importance levels.

WiSEGATE: Wireless Sensor Network Gateway framework for internet of things

With internet of things vision, computing systems get the ubiquity of real world. Wireless Sensor Network (WSN) technology plays a critical role for the construction of this paradigm. Hence, WSN technology should be adapted to support interoperability with the commodity internet entities. Since technological background of WSN and IP networks do not fit each other, this effort is not a straightforward process. In this paper, we introduce WiSEGATE which addresses end-to-end reliable interconnection problem between multiple internet entities and sensor nodes. WiSEGATE is a prototype of a new web server which supports three tier service scheme with a data acquisition mechanism of WSN to access the physical data in particular locations in the real world. In WiSEGATE, an interconnection gateway handles operations required for the interoperability. Since this gateway maintains reliable TCP/IP connections of the interconnected entities, the resource constraint sensor nodes on WSN do not require a TCP/IP stack for handling end-to-end connections. A lightweight service layer is implemented on a sensor node for operations required by the interconnection. The strength and novelty of the model lies in the fact that this lightweight service layer relieves extra memory usage for end-to-end connection management. For determining limits of the proposed model, firstly, we examined the steps for request/response mechanism and modeled the gateway as a queueing system. By doing this, we derive a definition of the request traffic. For proof of concept, we performed comprehensive tests in simulation and real testbed environments for WLAN connection. WiSEGATE can achieve reasonable response times up to 80 simultaneous connections from remote entities to WSN when WLAN PER is less than 0.2.

Localizing Wireless Sensors with Diverse Granularities in Wireless Sensor Networks

To obtain accurate location information of individual sensor nodes is of vital importance in wireless sensor networks (WSNs), especially for objective tracking applications. However, it is challenging to acquire fine-grained localization accuracy because of resource constraints of sensor nodes, unreliable wireless communication, and cost. Moreover, heterogeneous characteristics of both sensor nodes and applications make this problem even harder to solve. In this paper, we propose NLMR, a novel on-demand node localization technology based on multiresolution model. NLMR comprises three phases: (1) subregion classification, which categorizes regions into subregions with either uniform node deployment or nonuniform node deployment; (2) multiresolution model construction, which creates a multiresolution model that caters for diverse localization granularity; (3) node localization, which allows the control center to estimate the locations of sensor nodes in a centralized manner. Our analysis and simulation results demonstrate the performance of NLMR and verify that our scheme can provide diverse localization granularity with high probability.

A Task Allocation Algorithm Based on Score Incentive Mechanism for Wireless Sensor Networks

A wireless sensor network (WSN) consists of many resource constraint sensor nodes, which are always deployed in unattended environment. Therefore, the sensor nodes are vulnerable to failure and malicious attacks. The failed nodes have a heavily negative impact on WSNs’ real-time services. Therefore, we propose a task allocation algorithm based on score incentive mechanism (TASIM) for WSNs. In TASIM, the score is proposed to reward or punish sensor nodes’ task execution in cluster-based WSNs, where cluster heads are responsible for task allocation and scores’ calculation. Based on the task scores, cluster members can collaborate with each other to complete complex tasks. In addition, the uncompleted tasks on failed nodes can be timely migrated to other cluster members for further execution. Furthermore, the uncompleted tasks on death nodes can be reallocated by cluster heads. Simulation results demonstrate that TASIM is quite suitable for real-time task allocation. In addition, the performance of the TASIM is clearly better than that of conventional task allocation algorithms in terms of both network load balance and energy consumption.

A probabilistic approach to statistical QoS provision of event detection in sensor networks

It is of significant importance to provide network-wide Quality of Service (QoS) for a wide range of event detection applications in wireless sensor networks. This paper investigates the important problem of QoS provision to abnormal event detection. For event detection applications, there are two key performance metrics, i.e., detection probability and detection latency. This paper considers both metrics, aiming to provide statistical QoS for abnormal event detection. It is, however, a challenging issue because of stringent resource constraints of sensor nodes and unpredictable randomness of physical events. We propose a probabilistic approach to statistical QoS provision for event detection in sensor networks. We propose a distributed algorithm that iteratively determines the active probability of each sensor node. The probability is kept small for energy efficiency but sufficiently large to provide the required detection QoS. Our approach is flexible and can detection QoS customized by applications. Comprehensive simulation experiments have been conducted, which demonstrate that our approach is able to provide the required detection QoS for event detection and achieves considerably longer the system lifetime compared with other competing schemes.