Using Data Compression for Delay Constrained Applications in Wireless Sensor Networks

In recent years, wireless sensor networks (WSNs) have grown dramatically and made a great progress in many applications. But having limited life, batteries, as the power sources of wireless sensor nodes, have restricted the development and application of WSNs which often requires a very long lifespan for better performance. In order to make the WSNs prevalent in our lives, an alternative energy source is required. Environmental energy is an attractive power source, and it provides an approach to make the sensor nodes self-powered with the possibility of an almost infinite lifetime. The goal of this survey is to present a comprehensive review of the recent literature on the various possible energy harvesting technologies from ambient environment for WSNs.

Target tracking is a typical application of wireless sensor networks (WSNs), in which improving the tracking accuracy with the limited network resources is remaining as a challenging problem. Hence target tracking often relies on sensor scheduling approaches to optimize the resource utilization. With the development of energy acquisition technologies, the building of WSNs based on energy harvesting has become possible to help weaken the limitation of battery energy in WSNs, where theoretically the lifetime of the network could be extended to infinite. Hence, the development of energy harvesting technologies provides a new challenge of infinite-horizon sensor scheduling with the finite energy harvesting capability for high performance target tracking. This paper proposes an adaptive multi-step sensor scheduling approach based on the mixed iterative adaptive dynamic programming (MIADP) to minimize the global performance composed of tracking performance and energy consumption. MIADP consists of two iterations: P-iteration to update the iterative value function and V-iteration to obtain the iterative control law sequence. The simulation results demonstrate that the proposed scheme has advantages in the global trade-off between tracking performance and energy consumption compared with adaptive dynamic programming (ADP) based single-step sensor scheduling.

In this study, the authors present an energy-efficient data compression protocol for data collection in wireless sensor networks (WSNs). WSNs are essentially constrained by motes’ limited battery power and networks bandwidth. The authors focus on data compression algorithms and protocol development to effectively support data compression for data gathering in WSNs. Their design of compressed data-stream protocol (CDP) is generic in the sense that other lossless or lossy compression algorithms can be easily ‘plugged’ into the proposed protocol system without any changes to the rest of the CDP. This design intends to support various different WSN applications where users may prefer more specific compression algorithms, tailored to the sensing data characteristics in question, to their general algorithm. CDP is not only able to significantly reduce energy consumptions of data gathering in multi-hop WSNs, but also able to reduce sensor network traffic and thus avoid congestion accordingly. The proposed CDP is implemented on the tinyOS platform using the nesC programming language. To evaluate their work, the authors conduct simulations via TOSSIM and PowerTOSSIM-z with real-world sensor data. The results demonstrate the significance of CDP.

Data compression techniques in IoT-enabled wireless body sensor networks: A systematic literature review and research trends for QoS improvement

Internet of Things (IOT) is experiencing a super-fast growing phase. Wireless Sensor Networks (WSN), as the “five sense organs” and teleneuron of IOT, is developing fast along. Owing to the application-oriented characteristics of WSN, WSN applications may differ enormously in implementation methods. The WSN developers may have to rewrite the code for each and every application. Along with the increasing demand to WSN applications, WSN developers may have heavier tasks of programming for these applications. Thanks to TinyOS and NesC, an operating system and programming language designed especially for WSN, raises the WSN application's programming to a higher level. Large number of supported sensor hardware plus system provided and user-de-fined libraries eases WSN application programmers' jobs. How-ever, the massive amount of nodes' communication and networking, and security protection slows down the development pace. A unified and empirical WSN application implementation platform is one of the available solutions to the problem. This paper introduces an empirical WSN application implementation platform, which avails the WSN developers build an application with unified code template and network packet generation and processing strategies.

Wireless Sensor Networking is a sensor information gathering technology that has a wide range of applications in numerous fields. However due to the fact that sensor nodes have limited battery and are deployed in remote and harsh environments, energy efficient and real time transmission of the information are still open challenges. Since in a wireless sensor network data transmission is the most power consuming task, so far most useful techniques for the purpose of energy efficient and real time transmissions are based on data compression, the majority of them are based on wavelet transform. This paper give performance analysis of different wavelets for energy efficient and real time image data transmission in application like environment monitoring using wireless visual sensor networks. The performance evaluation shows that Haar wavelet is better in terms of energy efficiency and transmission time.

Continuous-monitoring (CM) of natural phenomenon is one of the major streams of applications in wireless sensor networks (WSNs), where aggregation and clustering techniques are beneficial as correlation dominates in both spatial and temporal aspects of sensed phenomenon. Conversely, in Event Driven Reporting (EDR), the efficient transmission of sensitive data related to some predefined alarm cases is of major importance. As such, reporting latency is a more important performance parameter. However, in some applications, the transmission of both CM and EDR data is encouraged or even required. For either CM or EDR applications, system performance can be greatly improved when both the number of packets to be transmitted as well as the packet size is reduced. This is especially true for highly dense sensor networks where many nodes detect the same values for the sensed phenomenon. Building on this, this paper focuses on studying and proposing compression techniques to improve the system performance in terms of energy consumption and reporting latency in both CM and EDR applications. Furthermore, we extend our analysis to hybrid networks where CM and EDR are required simultaneously. Specifically, this paper presents a simple aggregation technique named smart aggregation (SAG) for the CM applications and an event driven scheme named compression cluster scheme in spatial correlated region (CC_SCR). The proposed SAG exploits both spatial and temporal correlations where CC_SCR exploits the spatial correlation of such networks by data compression. Rationalizing the developments is attained by simulations that compare energy efficiency of the proposed SAG with k-hop aggregation and CM based event driven reporting (CMEDR) schemes. Results of CC_SCR show that the technique may reduce the energy consumption drastically. In some specific cases the reduction becomes more than 10 times compared to a classical clustering scheme. Two different strategies for the transmission of event reports through the CM infrastructure are incorporated: PER and NPER protocols. Both strategies take advantage of the cluster-based architecture which assigns a TDMA schedule for the CM data transmission while using NP/CSMA for the transmission of the event information. Consequently, no extra energy is consumed for separate event clusters. As such, the number of packets to be transmitted is greatly reduced.

Security is a vital parameter to conserve energy in wireless sensor networks (WSN). Trust management in the WSN is a crucial process as trust is utilized when collaboration is important for accomplishing trustworthy data transmission. But the available routing techniques do not involve security in the design of routing techniques. This study develops a novel statistical analysis with dingo optimizer enabled reliable routing scheme (SADO-RRS) for WSN. The proposed SADO-RRS technique aims to detect the existence of attacks and optimal routes in WSN. In addition, the presented SADO-RRS technique derives a new statistics based linear discriminant analysis (LDA) for attack detection, Moreover, a trust based dingo optimizer (TBDO) algorithm is applied for optimal route selection in the WSN and accomplishes secure data transmission in WSN. Besides, the TBDO algorithm involves the derivation of the fitness function involving different input variables of WSN. For demonstrating the enhanced outcomes of the SADO-RRS technique, a wide range of simulations was carried out and the outcomes demonstrated the enhanced outcomes of the SADO-RRS technique.

Designing of a multi-hop Wireless Sensor Network (WSN) depends upon the requirements of the underlying sensing application. The main objective of WSNs is to monitor physical phenomenon of interest in a given region of interest using sensors and provide collected data to sink. The WSN is made of a large number of energy, communication, and computational constraint nodes, to overcome energy constrains, replacing or recharging the batteries of the WSN nodes is an impossible task, once they are deployed in a hostile environment. Therefore, to keep the network alive as long as possible, communication between the WSN nodes must be done with load balancing. Time critical applications like forest fire detection, battle field monitoring demands reception of data by the sink with the bounded delay to avoid disasters. Hence, there is a need to design a protocol which enhances the network lifetime and provides information to the sink with a bounded delay. This paper will address this problem and solution. In this paper, a routing algorithm is proposed by introducing Energy Delay Index for Trade-off (EDIT) to optimize both objectives-energy and delay. The EDIT is used to select cluster heads and “next hop” by considering energy and/or delay requirements of a given application. Proposed approach is derived using two different aspects of distances between a node and the sink named Euclidean distance and Hop-count, and further prove using realistic parameters of radio to get data closest to the test bed implementation. The results aspire to give sufficient insights to others before doing test bed implementation.

Resource Management Approach to an Efficient Wireless Sensor Network

THE USE OF WIRELESS SENSOR NETWORKS IN AGRICULTUTE A TOOL FOR A SUSTAINABLE FOOD SUPPLY IN THE ARAB WORLD In this paper some ideas of how to apply the technological advancement of the wireless sensor networks (WSN) in agriculture as a tool for food security is discussed. This will include some examples where the technology can be applied, what changes can this technology brings to the traditional farming, which can help within the solution of the Arab World food security problems. This will help the region to develop and be part of the global strategy for the World food security. WSN features of having a low power consummation nature with different options of using different energy sources will make it as the just technology suitable in a remote and less or without infrastructural bases environment for many countries within the region. The applications of WSN which are suitable for the purpose will be discussed. Keywords: WSN, Food Security, Agriculture in Arab region, WSN Farmer Kits Tool, Energy Sources. Introduction Arabic countries are naturally rich, many countries within the region have a wide virgin land. But unfortunately some of these countries have been a focus in term of food shortages for long time which cause by many factors like land degradation, water crisis, land deals, climate change, agricultural disease, governing system, wars, population growth, land use change, living style change, high prices and lack of technology. As technology has rational parts in solving the most difficult problems for today's society, WSN can be applied in agriculture to reduce or solve this problem. Use of WSN in Agriculture as a solution As traditional farming is the lead in the region, people use their own human sense to perceive the surrounding to investigate the soil and predict the weather. But the remote sensing of the WSN as an activity of recording, observing, perceiving objects or events, wirelessly these happenings are processes and analyzed in a real time. The idea of applying this technology is to be adopted in different applications shortly can be said here. *Soil Investigation by using the specialized soil test sensor detectors to determine the fertility of soil nutrient deficiencies, elements like Nitrogen is very important for plants. *Weather Prediction by using a web data from WSN can be transmitted enabling a remote online interactive retrieval access, and then these data can be shared with the farmers. *Detection of ground water using WSN the level and the amount of sufficient water can be detected before planting. *Using the WSN the water and the area can be controlled during irrigation which will help in reducing the energy consumption. *Food storage system will be advanced by the use of WSN in knowing usage validity time and the space of storing. *Knowing where how and when to deliver what kind of product by using WSN will help in the logistical distribution of crops. *Farming Dissemination by using an integrated WSN tool kit messages can be disseminated.

Wireless sensor networks (WSNs) are spatially dispersed systems with self-configuring sensor nodes connected via a wireless medium. The applications of WSNs are growing exponentially regardless of their known shortcomings. The very first applications of WSNs were military and surveillance based and even now military applications form a major portion of WSN applications. Due to the aforementioned reason and the sensitive nature of the data collected by WSNs, security has become a prime concern. This paper is focused on various issues present in WSNs with a minor emphasis on security.

Wireless Sensor Network (WSN) is used in many applications for different roles, such as monitoring, data transmitting, information gathering, and so on. However, managing energy in WSN is a critical task. To end this issue several clustering and heuristic strategies were constructed still, a suitable solution is not found. So the current research proposed a novel African Buffalo based Two Tier Data Dissemination (AB-TTDD) strategy to monitor the energy drained node in an earlier stage before the data transmission. The fitness function of African Buffalo model is utilized to recognize the harmful and energy drained nodes in an earlier stage. Furthermore, a novel Temporary Energy Mapping Algorithm (TEMA) is developed to maintain the route by creating the reference node instead of energy drained node. This novel proposed mechanism has reduced the packet flow ratio and power consumption in a high manner. At the same time, it enhanced the energy intensity of sensor hubs by mounting its lifetime and affording the reroute. Subsequently, the capability of the proposed strategy is validated with the recent research works and achieved better performance by reducing energy consumption and packet drop ratio.

Wireless network of wearable biomedical sensors by human body shows great potential to enhance the biometrics performance significantly. Meanwhile, it poses prominent characteristics and challenges to physicians and engineers for its particular medical application as compared to other application of wireless sensor networks (WSN). Mobility pattern plays an important role in designing the wireless body sensor networks (WBSN) and will also affect the accuracy of modeling WBSN in health care application. Much of the mobility scenarios generated in current work of wireless body sensor networks has used fairly simple models to generate the mobile topological graph, which bear little resemblance to the actual mobility patterns. This paper is the first attempt to investigate the mobility model in WBSN based on the existing mobility models in wireless data networks and ad hoc networks. We first briefly review the existing mobility models in related research areas such as wireless ad hoc network and cellular networks. Further on, we propose a dedicated and more realistic mobility model named BAMM (Body Area Mobility Model) for wireless body sensor networks by concentrating on the unique characteristics of WBSN and finally study the effects of mobility on the performance of WBSN by simulation experiments.

This chapter presents a combined approach to visualize the IoT and cyber-physical system in any wireless communication networks. The brief overview of IoT and its applications in wireless sensor network (WSN) are elaborated in current era. In today’s present situation and the challenges faced during COVID-19 pandemic how the things can be monitored through IoT is being focused in this chapter. Also, the threats challenges and monitoring of cyber-physical system for security is presented in analysis form. WSN provides a bridge between the physical and virtual world and finds use in numerous applications like environmental monitoring, civil structural health monitoring and industrial process monitoring. Lately, it has found much use in the latest technology called Internet of Things (IoT). It seems that IoT has a great potential in shaping our future where everything will be connected together all the time. The major challenges faced by WSN include energy-efficiency, heterogeneity, and systematic design. WSN comprise of autonomous sensors which are capable of wirelessly transmitting their sensed parameter-values (also called packets) to remotely 188located sink node. The sink node is a WSN node which has the capability to assemble the data from all the nodes and forward it to farther distances to the remote base station through wired connections. The data transmission from source node to sink node is done by taking multi-hops which means that data is not sent directly to the destination node but through jumping from one intermediate node to another until the sink is reached. The sensor nodes also act as wireless routers which transmit data to other sensor-routers. So, sensor devices are very useful in deployment, collection of data, act as a IoT sensor devices as an application in technology. IoT is a device which can be used as application while a cyber-physical system is a collection of various mechanical components which are controlled and managed by different devices and algorithms. An IFM (Information Flow Monitor) is an application to backtrack queries and find the culprit in an error that has occurred in the cyber system. However, while backtracking and flow monitoring is not always guaranteed in terms of secure and efficient transaction. In some cases, the sender may deny the authority of the data so the information flow monitors may fail to provide a trustful and authentic source of data. Thus, the chapter focuses on both the issues of IoT integration with cyber-physical security (CPS) system. The key challenges and some solutions are proposed for the researchers for future work.