Wireless Sensor Networks Domain Research Articles

Energy Efficient MAC Protocol for Heterogeneous Wireless Sensor Network using Cross-Layer Design

Over the last decade, Wireless Sensor Network (WSN) has gained considerable attention in various real-time applications. Since WSN works with battery operated nodes, utilization and optimization of node energy is one the primary challenge. For effectively handling and controlling the energy consumption problem in WSN, cross-layer optimization is one of the important methods. For a researcher working in the domain of WSN, energy constraint is a huge challenge to deal with. MAC layer is one of the major source of energy consumption so, an innovative energy efficient MAC protocol using a cross-layer approach in the heterogeneous wireless sensor network is proposed. In this protocol, first, packet retransmission by reducing packet loss is addressed by considering buffer space, channel state and remaining energy. Second, the synchronization scheme for a global schedule is implemented by deliberating adaptive listening using the length of the transmission queue. Finally, sleep time issue is worked out to reduce energy consumption. In this scenario, the nodes will be in sleep mode unless it has some packets to send or receive. The proposed protocol is implemented in Network Simulation (NS2). The simulation results show that the heterogeneous wireless network performs better in terms of energy consumption, packet data rate and energy buffer state while implementing through the proposed protocol.

The Amalgamative Sharp Wireless Sensor Networks Routing and with Enhanced Machine Learning

Wireless sensor networks (WSN) are most prominent domain in present networking world. Sensors are the devices used to sense the information transfer, routing, processing time, energy calculation and also to know the physical and environmental conditions. Many researchers worked on WSN to improve the performance of the sensors. Various algorithms are discussed about routing in WSN, information transfer and many sub domains. Machine Learning is used to control the process without any human interaction. In this paper, the amalgamative sharp WSN algorithm is introduced to show the performance based on information transfer, routing, processing time, and energy calculation. For the better results the ML algorithms are adopted with proposed algorithm. Results show the performance of the ASWSN algorithm.

Evaluation of Data Compression Techniques for Video Transmission over Wireless Sensor Networks

Video transmission over WSN is a challenging task because, video data is inherently huge in size and its transmission requires high bandwidth and processing requires more memory and more power. Presently majority of the research work in this area is focused on improving battery life, optimizing network parameters and increasing energy efficiency. The area of best suitable compression scheme for WSN is rarely being explored. This paper focuses on finding out a suitable compression technique for video transmission over WSN. Wireless sensor network (WSN) is an ad-hoc network of sensor nodes, where each node is able to communicate with every other node in the network in single hop or multi-hop manner. It is a low cost, low power and low bandwidth network with each node having limited battery life and limited memory. In order to overcome these challenges, initially image compression is applied on each frame extracted from given video. To find out most suitable compression technique for WSN, the various existing 2D image transforms like DCT, KLT, Slant, Hartley, Hadamard and DST are compared based upon their energy compaction property. The transform that gives more energy compaction is best suitable for WSN. Thus, after selecting a suitable transform for WSN domain, it is applied to obtain compressed video frames. Zigbee protocol based hardware setup is used for serial transmission of RGB video data frames between the nodes. Different parameters are evaluated for received image frames and transmitted image frames. Experimental evaluation shows that zigbee hardware set up improves the reliability and efficiency of video data transmission. This type of WSN set-up can be used for capturing video in any remote and hard-lying (border, mountains, forest) area, where any other types of networks are not available.

Regulating the Packet Transmission Cost of Source Location Privacy Routing Schemes in Event Monitoring Wireless Networks

Sensor nodes in wireless sensor networks (WSNs) are usually battery-operated and resource-constrained. The sensor nodes are often deployed in remote areas where the batteries cannot easily be recharged or replaced. Consequently, power becomes a limited resource in WSNs. Thus, energy consumption of the sensor nodes is among parameters of paramount importance. Subsequently, source location privacy (SLP) routing schemes must be energy-efficient and overall cost-effective. Angle-based routing schemes can cost-effectively protect the SLP. The goal of this study is to propose a new path node offset angle routing algorithm to improve the packet transmission cost of two existing SLP routing schemes. The proposed algorithm considers path node offset angles, arbitrary factors, and contrived regions to compute relatively short but greatly randomized routing paths. The routes offer a reduced number of packet forwarding events in the near-sink region and eventually diminish the packet transmission cost. Performance analysis results verify that the proposed path node offset angle routing algorithm effectively improves the packet transmission cost of the schemes and guarantees strong SLP protection throughout the WSN domain. Furthermore, the routing algorithm is capable of alleviating the energy-hole problem.

Protean Authentication Scheme – A Time-Bound Dynamic KeyGen Authentication Technique for IoT Edge Nodes in Outdoor Deployments

The IoT edge/sensor nodes are exposed to large attack surface and could easily succumb to several well-known attacks in the wireless sensor network (WSN) domain. Authenticating edge nodes before they join a network, especially after a sleep state, is a critical step to maintain the overall trust of any given IoT local area network (IoT LAN). The low resources and computational constraints of such IoT nodes make this a challenging and non-trivial problem. As many IoT deployments are in uncontrolled environments, the IoT devices are often placed in the open so that physical access to them is inevitable. Due to easy physical access of the devices, common attacks, including cloning of devices or stealing secret keys stored in an edge node, are some of the most common attacks on the IoT deployments. This paper focuses on developing an extremely lightweight authentication scheme for constrained end-devices that are part of a given IoT LAN. Authentication occurs between the end-device and the gateway that acts as an edge computing device. The proposed authentication scheme is put through both formal and informal security verification. Voltage drop, current, and power are measured to gauge the overall impact of the security scheme. All the three parameters were measured while configuring the edge node as an end-device or as a router. Our testing results show that the impact on the resources was minimal.

Relay node placement under budget constraint

The relay node placement problem in the wireless sensor network domain has been studied extensively. But under a fixed budget, it may be impossible to procure the minimum number of relay nodes needed to design a connected network of sensor and relay nodes. Nevertheless, one would still like to design a network with high level of connectedness, or low disconnectedness. In this paper, we introduce the notion of a measure of the “connectedness” of a disconnected graph. We study a family of problems whose goal is to design a network with “maximal connectedness” subject to a fixed budget constraint.

Strength of Crowd (SOC)—Defeating a Reactive Jammer in IoT with Decoy Messages

We propose Strength of Crowd (SoC), a distributed Internet of Things (IoT) protocol that guarantees message broadcast from an initiator to all network nodes in the presence of either a reactive or a proactive jammer, that targets a variable portion of the radio spectrum. SoC exploits a simple, yet innovative and effective idea: nodes not (currently) involved in the broadcast process transmit decoy messages that cannot be distinguished (by the jammer) from the real ones. Therefore, the jammer has to implement a best-effort strategy to jam all the concurrent communications up to its frequency/energy budget. SoC exploits the inherent parallelism that stems from the massive deployments of IoT nodes to guarantee a high number of concurrent communications, exhausting the jammer capabilities and hence leaving a subset of the communications not jammed. It is worth noting that SoC could be adopted in several wireless scenarios; however, we focus on its application to the Wireless Sensor Networks (WSN) domain, including IoT, Machine-to-Machine (M2M), Device-to-Device (D2D), to name a few. In this framework, we provide several contributions: firstly, we show the details of the SoC protocol, as well as its integration with the IEEE 802.15.4-2015 MAC protocol; secondly, we study the broadcast delay to deliver the message to all the nodes in the network; and finally, we run an extensive simulation and experimental campaign to test our solution. We consider the state-of-the-art OpenMote-B experimental platform, adopting the OpenWSN open-source protocol stack. Experimental results confirm the quality and viability of our solution.

Self-Learning-Based Data Aggregation Scheduling Policy in Wireless Sensor Networks

The problems of reducing the transmission delay and maximizing the sensor lifetime are always hot research topics in the domain of wireless sensor networks (WSNs). By excluding the influence of routing protocol on the transmission direction of data packets, the MAC protocol which controls the time point of transmission and reception is also an important factor on the communication performance. Many existing works attempt to address these problems by using time slot scheduling policy. However, most of them exploit the global network knowledge to construct a stationary scheduling, which violates the dynamic and scalable nature of WSNs. In order to realize the distributed computation and self-learning, we propose to integrate the Q-learning into the exploring process of an adaptive slot scheduling with high efficiency. Due to the convergence nature, the scheduling quickly approaches an approximate optimal sequence along with the execution of frames. By conducting the corresponding simulations, the feasibility and the high efficiency of the proposed method can be validated.

Multipath Routing Protocols in Wireless Sensor Networks: A Retrospective Review

Objectives: To review the basic principles of Multi-path Routing Protocols (MRPs) design and its performance metrics. To discuss the assortment of MRPs overview for Wireless Sensor Networks (WSNs) based on its arrangement and delivery. Methods/Statistical Analysis: The enhanced reliability, load balance and security promote the multi-path routing as an appropriate tool in the domain of Wireless Sensor Networks (WSNs). In order to obtain simultaneous data transfer with reduced delay period, critical review is made based on the performance metrics, taxonomy of MRPs, and qualitative comparison. Findings: From the discussions, it can be concluded that most of the protocols achieved better load balance with improved performance. Coding based MRPs can perform with better reliability when compared to other protocols. Application/Improvements: The survey of earlier reports led to the decisions that the energy-efficient, reduced transmission delay with multiple pairs is the details to be studied in the domain of MRPs.

An energy efficient and optimized load balanced localization method using CDS with one-hop neighbourhood and genetic algorithm in WSNs

Localization has always been a research concern in the domain of wireless sensor networks. The varying range of its applications has given it a wide acceptability along with the need of accuracy of the location estimation. A number of algorithms has been introduced for the purpose. While developing such algorithms, the concern of network lifetime has received a setback as wireless sensor networks are always resource constrained. The proposed algorithm balances the computational load among anchor nodes for location calculation of unknown nodes. Moreover the algorithm has been optimized using genetic algorithm. The optimized backbone is used to locate the unknown nodes. The simulation results show that our algorithm significantly improves the network lifetime as the computational load has been distributed efficiently among the anchor nodes.

Implementation and performance evaluation of IEEE 802.15.4 unslotted CSMA/CA protocol on Contiki OS

In the wireless sensor networks domain, one of the most used standards is IEEE 802.15.4. This standard has been made available on many low power operating systems such as TinyOS and Contiki OS. It is crucial for the implementation to be compliant with the specifications of the standard. In the case of Contiki OS, the provided version of the main medium access algorithm, unslotted Carrier Sensing Multiple Access with Collision Avoidance (CSMA/CA), presents many flaws. In this paper, we discuss the implementation of the provided CSMA/CA algorithm and we point out to the parts that do not respect the standard specifications. We also propose and implement a compliant version of this algorithm and show through simulation the correctness of the implementation.

Cross Layered MAC Design for RF Energy Harvesting Sensor Network

The main research objective in wireless sensor networks (WSN) domain is to develop algorithms and protocols to ensure minimal energy consumption with maximum network lifetime. In this paper, we propose a novel design for energy harvesting sensor node and cross-layered MAC protocol using three adjacent layers (Physical, MAC and Network) to economize energy for WSN. The basic idea behind our protocol is to re-energize the neighboring nodes using the radio frequency (RF) energy transmitted by the active nodes. This can be achieved by designing new energy harvesting sensor node and redesigning the MAC protocol. The results show that the proposed cross layer CL_EHSN improves the life time of the WSN by 40%.

Sociopsychological trust model for Wireless Sensor Networks

Trust plays a crucial role in establishing and retaining relationships. Sociopsychological analysis identifies three major constructs, such as ability, benevolence and integrity, upon which trust is being built up. On a similar note, in a Wireless Sensor Network (WSN), it is indispensable to have trust among nodes since nodes collectively sense physical parameters and send them to the base station. The nodes, however, can behave fraudulently and send bad information, mostly due to hardware and software faults. Taking inspiration from the sociopsychological account, the present paper introduces a novel model for computing trust of sensor nodes. Additionally, the immune inspired model is suggested for removing fraudulent nodes whose trust ratings fall below the threshold. Roles of the three factors, viz. ability, benevolence and integrity, are examined in WSN domain. The proposed model proves itself to be more advantageous than other methods that adopt machine learning and neural network models in performance metrics such as detection time, reliability, scalability, efficiency and complexity. Proposed work has been implemented on LabVIEW platform and the results substantiate the reliability of the proposed mathematical model.

Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures.

Distributed video coding (DVC) is a relatively new video coding architecture originated from two fundamental theorems namely, Slepian–Wolf and Wyner–Ziv. Recent research developments have made DVC attractive for applications in the emerging domain of wireless video sensor networks (WVSNs). This paper reviews the state-of-the-art DVC architectures with a focus on understanding their opportunities and gaps in addressing the operational requirements and application needs of WVSNs.

Analytical Event Based Investigations Over Delphi Random Generator Distributions for Data Dissemination Routing Protocols in Highly Dense Wireless Sensor Network

This paper focuses on the event based investigations over different data dissemination routing protocols for highly dense wireless sensor networks. Initially for the wireless sensor network domain, we analyzed data dissemination flooding and gossiping routing protocols. We etude and exemplify our proposed model for data dissemination based evaluation with Delphi random generator distribution strategy. We calculated performance metrics as sense count, transmit count, receive count and receive redundant count. At the end, simulations analysis has been carried out to prove the validity of our designed scenario.

EDAL: An Energy-Efficient, Delay-Aware, and Lifetime-Balancing Data Collection Protocol for Heterogeneous Wireless Sensor Networks

Our work in this paper stems from our insight that recent research efforts on open vehicle routing (OVR) problems, an active area in operations research, are based on similar assumptions and constraints compared to sensor networks. Therefore, it may be feasible that we could adapt these techniques in such a way that they will provide valuable solutions to certain tricky problems in the wireless sensor network (WSN) domain. To demonstrate that this approach is feasible, we develop one data collection protocol called EDAL, which stands for Energy-efficient Delay-aware Lifetime-balancing data collection. The algorithm design of EDAL leverages one result from OVR to prove that the problem formulation is inherently NP-hard. Therefore, we proposed both a centralized heuristic to reduce its computational overhead and a distributed heuristic to make the algorithm scalable for large-scale network operations. We also develop EDAL to be closely integrated with compressive sensing, an emerging technique that promises considerable reduction in total traffic cost for collecting sensor readings under loose delay bounds. Finally, we systematically evaluate EDAL to compare its performance to related protocols in both simulations and a hardware testbed.

An Encryption Scheme Using Chaotic Map and Genetic Operations for Wireless Sensor Networks

Over the past decade, the application domain of wireless sensor networks has expanded steadily, ranging from environmental management to industry control, and from structural health monitoring to strategic surveillance. With the proliferation of sensor networks at home, work place, and beyond, securing data in the network has become a challenge. A number of security mechanisms have been proposed for sensor networks to provide data confidentiality: 1) advanced encryption system; 2) KATAN; 3) LED; and 4) TWINE. However, these schemes have drawbacks, including security vulnerabilities, need for hardware-based implementation, and higher computational complexity. To address these limitations, we propose a lightweight block cipher based on chaotic map and genetic operations. The proposed cryptographic scheme employs elliptic curve points to verify the communicating nodes and as one of the chaotic map parameters to generate the pseudorandom bit sequence. This sequence is used in XOR, mutation, and crossover operations in order to encrypt the data blocks. The experimental results based on Mica2 sensor mote show that the proposed encryption scheme is nine times faster than the LED protocol and two times faster than the TWINE protocol. We have also performed a number of statistical tests and cryptanalytic attacks to evaluate the security strength of the algorithm and found the cipher provably secure.

Dynamic rough-based clustering for vehicular ad-hoc networks

Due to the spatio-temporal aspects of vehicles within vehicular ad-hoc networks, traditional clustering techniques are not effective as they rely on static configuration. In this paper, we proposed a dynamic clustering technique that is based on rough theory of grouping data. The contributions of this research are to propose: A self-organising clustering technique as an extension to dynamic rough clustering and a framework that manages the integration among different algorithmic components, which are required to develop such soft computing systems. We performed extensive experiments in order to evaluate the effectiveness of the proposed technique in terms of: communication load, inter and intra connectivity, threshold analysis, and relationship among data clusters. Furthermore, a performance comparison with relevant techniques has been reported. The results indicated that the proposed technique is robust and promising in comparison with existing techniques in the domain of wireless sensor networks.

Radio frequency identification and wireless sensor networks application domains integration using DASH7 Mode 2 standard in agriculture

In the last decades, agriculture has been transformed from a traditionally labor-intensive production activity to a highly knowledge-intensive industrial activity. Advanced technologies for networking, measurements, control, decision making and management have been adopted by modern agriculture in order to increase quality and quantity of products and to minimise materials and energy. Wireless sensor networks and radio frequency identification are two of the most challenging technologies used in agriculture that are traditionally separated from each other. Recently, the integration of these technologies has attracted the interest of researchers targeting to systems interoperability and compatibility as well as the support of concepts as the 'from farm-to-fork'. This paper presents the standards associated with the integration of the radio frequency identification (RFID) and wireless sensor networks (WSN) technologies and describes the advantages of the DASH7 standard for agriculture. In addition, the design of a DASH7-based wireless node is presented with emphasis on real-life applications in agriculture. Finally, an architecture of the RFID and WSN domains integration from systems perspective is presented.

Implementation of WirelessHART in the NS-2 simulator and validation of its correctness.

One of the first standards in the wireless sensor networks domain, WirelessHART (HART (Highway Addressable Remote Transducer)), was introduced to address industrial process automation and control requirements. This standard can be used as a reference point to evaluate other wireless protocols in the domain of industrial monitoring and control. This makes it worthwhile to set up a reliable WirelessHART simulator in order to achieve that reference point in a relatively easy manner. Moreover, it offers an alternative to expensive testbeds for testing and evaluating the performance of WirelessHART. This paper explains our implementation of WirelessHART in the NS-2 network simulator. According to our knowledge, this is the first implementation that supports the WirelessHART network manager, as well as the whole stack (all OSI (Open Systems Interconnection model) layers) of the WirelessHART standard. It also explains our effort to validate the correctness of our implementation, namely through the validation of the implementation of the WirelessHART stack protocol and of the network manager. We use sniffed traffic from a real WirelessHART testbed installed in the Idrolab plant for these validations. This confirms the validity of our simulator. Empirical analysis shows that the simulated results are nearly comparable to the results obtained from real networks. We also demonstrate the versatility and usability of our implementation by providing some further evaluation results in diverse scenarios. For example, we evaluate the performance of the WirelessHART network by applying incremental interference in a multi-hop network.