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Showing papers in "International Journal of Distributed Sensor Networks in 2015"


Journal ArticleDOI
TL;DR: A systematic way to review data mining in knowledge view, technique view, and application view, including classification, clustering, association analysis, time series analysis and outlier analysis is given.
Abstract: The massive data generated by the Internet of Things (IoT) are considered of high business value, and data mining algorithms can be applied to IoT to extract hidden information from data. In this paper, we give a systematic way to review data mining in knowledge view, technique view, and application view, including classification, clustering, association analysis, time series analysis and outlier analysis. And the latest application cases are also surveyed. As more and more devices connected to IoT, large volume of data should be analyzed, the latest algorithms should be modified to apply to big data. We reviewed these algorithms and discussed challenges and open research issues. At last a suggested big data mining system is proposed.

486 citations


Journal ArticleDOI
TL;DR: This paper focuses on comprehensively gathering most recent developments in UWSN applications and their deployments, and classified the underwater applications into five main classes, namely, monitoring, disaster, military, navigation, and sports, to cover the large spectrum of UWSN.
Abstract: There is no escaping fact that a huge amount of unexploited resources lies underwater which covers almost 70% of the Earth. Yet, the aquatic world has mainly been unaffected by the recent advances in the area of wireless sensor networks (WSNs) and their pervasive penetration in modern day research and industrial development. The current pace of research in the area of underwater sensor networks (UWSNs) is slow due to the difficulties arising in transferring the state-of-the-art WSNs to their underwater equivalent. Maximum underwater deployments rely on acoustics for enabling communication combined with special sensors having the capacity to take on harsh environment of the oceans. However, sensing and subsequent transmission tend to vary as per different subsea environments; for example, deep sea exploration requires altogether a different approach for communication as compared to shallow water communication. This paper particularly focuses on comprehensively gathering most recent developments in UWSN applications and their deployments. We have classified the underwater applications into five main classes, namely, monitoring, disaster, military, navigation, and sports, to cover the large spectrum of UWSN. The applications are further divided into relevant subclasses. We have also shown the challenges and opportunities faced by recent deployments of UWSN.

287 citations


Journal ArticleDOI
TL;DR: A novel approach for dynamic analysis of malware is proposed that adopts DNA sequence alignment algorithms and extracts common API call sequence patterns of malicious function from malware in different categories and finds that certain malicious functions are commonly included in malware even inDifferent categories.
Abstract: In the era of ubiquitous sensors and smart devices, detecting malware is becoming an endless battle between ever-evolving malware and antivirus programs that need to process ever-increasing security related data For malware detection, various approaches have been proposed Among them, dynamic analysis is known to be effective in terms of providing behavioral information As malware authors increasingly use obfuscation techniques, it becomes more important to monitor how malware behaves for its detection In this paper, we propose a novel approach for dynamic analysis of malware We adopt DNA sequence alignment algorithms and extract common API call sequence patterns of malicious function from malware in different categories We find that certain malicious functions are commonly included in malware even in different categories From checking the existence of certain functions or API call sequence patterns matched, we can even detect new unknown malware The result of our experiment shows high enough F-measure and accuracy API call sequence can be extracted from most of the modern devices; therefore, we believe that our method can detect the malware for all types of the ubiquitous devices

179 citations


Journal ArticleDOI
TL;DR: Wang et al. as discussed by the authors proposed a method to improve the performance of Android malware detection by incorporating the creator's information as a feature and classify malicious applications into similar groups, which enables fast detection of malware by using creator information such as serial number of certificate.
Abstract: Thousands of malicious applications targeting mobile devices, including the popular Android platform, are created every day. A large number of those applications are created by a small number of professional underground actors; however previous studies overlooked such information as a feature in detecting and classifying malware and in attributing malware to creators. Guided by this insight, we propose a method to improve the performance of Android malware detection by incorporating the creator's information as a feature and classify malicious applications into similar groups. We developed a system that implements this method in practice. Our system enables fast detection of malware by using creator information such as serial number of certificate. Additionally, it analyzes malicious behaviors and permissions to increase detection accuracy. The system also can classify malware based on similarity scoring. Finally, we showed detection and classification performance with 98% and 90% accuracy, respectively.

103 citations


Journal ArticleDOI
TL;DR: This study demonstrates that some characteristics of surveyed protocols are very useful to medical appliances and patients in a WBAN domain and selects the most useful solutions for this area of networking.
Abstract: Wireless Body Area Networks (WBANs) supporting healthcare applications are in early development stage but offer valuable contributions at monitoring, diagnostic, or therapeutic levels. They cover real-time medical information gathering obtained from different sensors with secure data communication and low power consumption. As a consequence of the increasing interest in the application of this type of networks, several articles dealing with different aspects of such systems have been published recently. In this paper, we compile and compare technologies and protocols published in the most recent researches, seeking WBAN issues for medical monitoring purposes to select the most useful solutions for this area of networking. The most important features under consideration in our analysis include wireless communication protocols, frequency bands, data bandwidth, transmission distance, encryption, authentication methods, power consumption, and mobility. Our study demonstrates that some characteristics of surveyed protocols are very useful to medical appliances and patients in a WBAN domain.

102 citations


Journal ArticleDOI
TL;DR: A Wi-Fi fingerprint localization method on the basis of important access points (IAP) which can achieve high accuracy in indoor environment is proposed.
Abstract: With the development of the wireless communication technology and intelligent mobile phone, the positioning services based on Wi-Fi and mobile phone are increasingly demanded. In this paper, a Wi-Fi fingerprint localization method is proposed on the basis of important access points (IAP). For the Wi-Fi fingerprint, Wi-Fi access point with the highest received signal strength (RSS) is denoted as the important access point. At the localization stage, the fingerprints are chosen with the same IAP as the estimated fingerprint from the database. Then, the distance and the AP repetition of the fingerprints are used to calculate the similarity degree. The location of the fingerprint which matches the estimated fingerprint well can be regarded as the estimated location. Experimental results show that the proposed algorithm can achieve high accuracy in indoor environment.

95 citations


Journal ArticleDOI
TL;DR: The proposed sleep monitoring system which can detect the sleep movement and posture during sleep using a Microsoft Kinect v2 sensor without any body attached devices and it is expected that the analyzed sleep related data can significantly improve the sleep quality.
Abstract: Sleep activity is one of crucial factors for determining the quality of human life. However, a traditional sleep monitoring system onerously requires many devices to be attached to human body for achieving sleep related information. In this paper, we proposed and implemented the sleep monitoring system which can detect the sleep movement and posture during sleep using a Microsoft Kinect v2 sensor without any body attached devices. The proposed sleep monitoring system can readily gather the sleep related information that can reveal the sleep patterns of individuals. We expect that the analyzed sleep related data can significantly improve the sleep quality.

95 citations


Journal ArticleDOI
TL;DR: A basic framework for aerial data collection, which includes the following five components: deployment of networks, nodes positioning, anchor points searching, fast path planning for UAV, and data collection from network, is designed and implemented.
Abstract: Data collection from deployed sensor networks can be with static sink, ground-based mobile sink, or Unmanned Aerial Vehicle (UAV) based mobile aerial data collector. Considering the large-scale sensor networks and peculiarity of the deployed environments, aerial data collection based on controllable UAV has more advantages. In this paper, we have designed a basic framework for aerial data collection, which includes the following five components: deployment of networks, nodes positioning, anchor points searching, fast path planning for UAV, and data collection from network. We have identified the key challenges in each of them and have proposed efficient solutions. This includes proposal of a Fast Path Planning with Rules (FPPWR) algorithm based on grid division, to increase the efficiency of path planning, while guaranteeing the length of the path to be relatively short. We have designed and implemented a simulation platform for aerial data collection from sensor networks and have validated performance efficiency of the proposed framework based on the following parameters: time consumption of the aerial data collection, flight path distance, and volume of collected data.

81 citations


Journal ArticleDOI
TL;DR: A new protocol to reach energy efficiency is proposed an intelligent routing protocol algorithm based on reinforcement learning techniques that has improvement in different parameters such as network lifetime, packet delivery, packet delay, and network balance.
Abstract: In wireless sensor networks energy is a very important issue because these networks consist of lowpower sensor nodes. This paper proposes a new protocol to reach energy efficiency. The protocol has a different priority in energy efficiency as reducing energy consumption in nodes, prolonging lifetime of the whole network, increasing system reliability, increasing the load balance of the network, and reducing packet delays in the network. In the new protocol is proposed an intelligent routing protocol algorithm. It is based on reinforcement learning techniques. In the first step of the protocol, a new clustering method is applied to the network and the network is established using a connected graph. Then data is transmitted using the Q-value parameter of reinforcement learning technique. The simulation results show that our protocol has improvement in different parameters such as network lifetime, packet delivery, packet delay, and network balance.

81 citations


Journal ArticleDOI
TL;DR: A reinforcement learning based mechanism to perform value-redundancy filtering and load-balancing routing according to the values and distribution of data flows in order to improve the energy efficiency and self-adaptability to environmental changes for WSNs.
Abstract: Software defined wireless networks (SDWNs) present an innovative framework for virtualized network control and flexible architecture design of wireless sensor networks (WSNs). However, the decoupled control and data planes and the logically centralized control in SDWNs may cause high energy consumption and resource waste during system operation, hindering their application in WSNs. In this paper, we propose a software defined WSN (SDWSN) prototype to improve the energy efficiency and adaptability of WSNs for environmental monitoring applications, taking into account the constraints of WSNs in terms of energy, radio resources, and computational capabilities, and the value redundancy and distributed nature of data flows in periodic transmissions for monitoring applications. Particularly, we design a reinforcement learning based mechanism to perform value-redundancy filtering and load-balancing routing according to the values and distribution of data flows, respectively, in order to improve the energy efficiency and self-adaptability to environmental changes for WSNs. The optimal matching rules in flow table are designed to curb the control signaling overhead and balance the distribution of data flows for achieving in-network fusion in data plane with guaranteed quality of service (QoS). Experiment results show that the proposed SDWSN prototype can effectively improve the energy efficiency and self-adaptability of environmental monitoring WSNs with QoS.

70 citations


Journal ArticleDOI
TL;DR: Co-UWSN protocol is proposed, which is a reliable, energy-efficient, and high throughput routing protocol for UWSN, which performs better in terms of end-to-end delay, energy consumption, and network lifetime.
Abstract: Sensor networks feature low-cost sensor devices with wireless network capability, limited transmit power, resource constraints, and limited battery energy. Cooperative routing exploits the broadcast nature of wireless medium and transmits cooperatively using nearby sensor nodes as relays. It is a promising technique that utilizes cooperative communication to improve the communication quality of single-antenna sensor nodes. In this paper, we propose a cooperative transmission scheme for underwater sensor networks (UWSNs) to enhance the network performance. Cooperative diversity has been introduced to combat fading. Cooperative UWSN (Co-UWSN) is proposed, which is a reliable, energy-efficient, and high throughput routing protocol for UWSN. Destination and potential relays are selected that utilize distance and signal-to-noise ratio computation of the channel conditions as cost functions. This contributes to sufficient decrease in path losses occurring in the links and transferring of data with much reduced path loss. Simulation results show that Co-UWSN protocol performs better in terms of end-to-end delay, energy consumption, and network lifetime. Selected protocols for comparison are energy-efficient depth-based routing (EEDBR), improved adaptive mobility of courier nodes in threshold-optimized depth-based routing (iAMCTD), cooperative routing protocol for UWSN, and cooperative partner node selection criteria for cooperative routing Coop (Re and dth).

Journal ArticleDOI
TL;DR: This work performs network simulations using Contiki-OS to analyze the performance of the proposed trust model and results show effectiveness against On-Off attacks and also a good performance to recognize malicious nodes in the network.
Abstract: In the Internet of Things (IoT), physical objects are able to provide or require determined services. The purpose of this work is to identify malicious behavior of nodes and prevent possible On-Off attacks to a multiservice IoT. The proposed trust management model uses direct information generated from direct communication with the nodes to evaluate trust between nodes. This distributed approach allows nodes to be completely autonomous in making decisions about the behavior of other nodes. We perform network simulations using Contiki-OS to analyze the performance of the proposed trust model. Simulation results show effectiveness against On-Off attacks and also a good performance to recognize malicious nodes in the network.

Journal ArticleDOI
TL;DR: The experimental results show that Mobile-SHM using smartphone is feasible and may be considered as a milestone in making SHM popular in the lives of people.
Abstract: The structural health monitoring system has made great development nowadays, especially on bridge structures. Meanwhile, most SHM systems reported were designed, integrated, and installed into large-scale infrastructures by professionals and equipped with expensive sensors, data acquisition devices, data transfer systems, and so forth. And it is impossible to install SHM system for every civilian building. For this status, a kind of new idea for structural health monitoring using smartphone is introduced in this paper. A smartphone, with embedded responding SHM software and inner sensors or external sensors, can be used not only as a single wireless sensor node but also as a mini-SHM system. The method is described in detail, and then the swing test, cable force test in laboratory, and cable force test on an actual bridge based on the iPhone were conducted to validate the proposed method. The experimental results show that Mobile-SHM using smartphone is feasible. The realization of Mobile-SHM method using smartphones may be considered as a milestone in making SHM popular in the lives of people.

Journal ArticleDOI
TL;DR: A feature subset selection based on PSO is proposed which provides better performance as compared to genetic algorithm, which has been used to search the most discriminative subset of transformed features.
Abstract: The prevention of intrusion in networks is decisive and an intrusion detection system is extremely desirable with potent intrusion detection mechanism. Excessive work is done on intrusion detection systems but still these are not powerful due to high number of false alarms. One of the leading causes of false alarms is due to the usage of a raw dataset that contains redundancy. To resolve this issue, feature selection is necessary which can improve intrusion detection performance. Latterly, principal component analysis (PCA) has been used for feature reduction and subset selection in which features are primarily projected into a principal space and then features are elected based on their eigenvalues, but the features with the highest eigenvalues may not have the guaranty to provide optimal sensitivity for the classifier. To avoid this problem, an optimization method is required. Evolutionary optimization approach like genetic algorithm (GA) has been used to search the most discriminative subset of transformed features. The particle swarm optimization (PSO) is another optimization approach based on the behavioral study of animals/birds. Therefore, in this paper a feature subset selection based on PSO is proposed which provides better performance as compared to GA.

Journal ArticleDOI
TL;DR: A Cognitive Oriented IoT Big-data Framework (COIB-framework) is proposed along with implementation architecture, IoT big-data layering architecture, and data organization and knowledge exploration subsystem for effective data management and knowledge discovery that is well-suited with the large scale industrial automation applications.
Abstract: In future IoT big-data management and knowledge discovery for large scale industrial automation application, the importance of industrial internet is increasing day by day. Several diversified technologies such as IoT (Internet of Things), computational intelligence, machine type communication, big-data, and sensor technology can be incorporated together to improve the data management and knowledge discovery efficiency of large scale automation applications. So in this work, we need to propose a Cognitive Oriented IoT Big-data Framework (COIB-framework) along with implementation architecture, IoT big-data layering architecture, and data organization and knowledge exploration subsystem for effective data management and knowledge discovery that is well-suited with the large scale industrial automation applications. The discussion and analysis show that the proposed framework and architectures create a reasonable solution in implementing IoT big-data based smart industrial applications.

Journal ArticleDOI
TL;DR: Aiming at solving the problem of low accuracy in traditional distance vector-hop (DV-hop) algorithm used for wireless sensor networks node location, two refined localization algorithms, that is, hyperbolic-Dv-hop localization algorithm and improved weighted centroid DV-hops localization algorithm (IWC-DW-hop), are proposed.
Abstract: Aiming at solving the problem of low accuracy in traditional distance vector-hop (DV-hop) algorithm used for wireless sensor networks node location, two refined localization algorithms, that is, hyperbolic-DV-hop localization algorithm and improved weighted centroid DV-hop localization algorithm (IWC-DV-hop), are proposed in this paper. Instead of taking the average HopSize of BeaconNode nearest to the UnknownNode, hyperbolic-DV-hop algorithm chooses the average of average HopSizes of all BeaconNodes, as the average HopSize of the UnknownNode. The ML localization algorithm is also replaced by hyperbolic location algorithm. IWC-DV-hop algorithm improves the accuracy by selecting appropriate BeaconNodes and replacing ML localization with centroid localization. And a weighted scheme is used in IWC-DV-hop so that the influence of different anchors is taken into consideration. Simulations have been conducted to prove that the accuracy is improved by both of the two algorithms and IWCDV-hop is the best choice.

Journal ArticleDOI
TL;DR: Simulations are performed to assess the proposed protocols and the results indicate that the three schemes largely minimize end-to-end delay along with improving the transmission loss of network.
Abstract: Underwater Acoustic Sensor Networks (UASNs) offer their practicable applications in seismic monitoring, sea mine detection, and disaster prevention. In these networks, fundamental difference between operational methodologies of routing schemes arises due to the requirement of time-critical applications; therefore, there is a need for the design of delay-sensitive techniques. In this paper, Delay-Sensitive Depth-Based Routing (DSDBR), Delay-Sensitive Energy Efficient Depth-Based Routing (DSEEDBR), and Delay-Sensitive Adaptive Mobility of Courier nodes in Threshold-optimized Depth-based routing (DSAMCTD) protocols are proposed to empower the depth-based routing schemes. The performance of the proposed schemes is validated in UASNs. All of the three schemes formulate delay-efficient Priority Factors (PF) and Delay-Sensitive Holding time (DSHT) to minimize end-to-end delay with a small decrease in network throughput. These schemes also employ an optimal weight function (WF) for the computation of transmission loss and speed of received signal. Furthermore, solution for delay lies in efficient data forwarding, minimal relative transmissions in low-depth region, and better forwarder selection. Simulations are performed to assess the proposed protocols and the results indicate that the three schemes largely minimize end-to-end delay along with improving the transmission loss of network.

Journal ArticleDOI
Jinxing Lai1, Haobo Fan1, Jianxun Chen1, Junling Qiu1, Ke Wang1 
TL;DR: Monitoring of an existing railway tunnel during the construction of a new tunnel in Shaanxi, China indicated that the concrete strain was different before and after the two tunnels crossing, which was much larger in front of the excavation face, and then it decreased gradually after the crossing.
Abstract: The construction blasting in a new tunnel will undoubtedly influence the structure of existing tunnel. In order to monitor the effect of the blast-induced vibration on the structure of existing tunnel, a wireless sensor network (WSN) was established, which included the blast vibration monitoring system and the wireless remote data acquisition system. An existing railway tunnel was monitored during the construction of a new tunnel in Shaanxi, China. Concrete strain and peak particle velocity (PPV) were adopted to evaluate the influence of new tunnel construction blasting on the structure of existing tunnel. The monitoring results indicated that the concrete strain was different before and after the two tunnels crossing, which was much larger in front of the excavation face, and then it decreased gradually after the crossing. The PPV at the side wall of existing tunnel toward the blasting source was quite higher, and the location of maximum PPV changes with the process of tunnel excavation. When the distance between the existing and new tunnels was 4 m, the PPV reached 11.83 cm/s, which was already beyond the safe value, so the explosive charge should be reduced.

Journal ArticleDOI
Xuelian Cai1, Yulong Duan1, Ying He1, Jin Yang1, Changle Li1 
TL;DR: Bee-Sensor-C is an energy-aware and scalable multipath routing protocol based on dynamic cluster and foraging behavior of a bee swarm that outperforms the existing protocols in terms of energy efficiency, energy consumption balance, packet delivery rate, and scalability.
Abstract: A wireless sensor network (WSN) is composed of a large collection of sensor nodes with limited resources in terms of battery supplied energy, processing capability, and storage. Therefore, the design of an energy-efficient and scalable routing protocol is a crucial concern for WSN applications. In this paper, we propose Bee-Sensor-C, an energy-aware and scalable multipath routing protocol based on dynamic cluster and foraging behavior of a bee swarm. Bee-Sensor-C is an evolution from BeeSensor which is a bee-inspired routing protocol for WSNs. First of all, through introducing a dynamic clustering scheme, Bee-Sensor-C offers parallel data transmissions close to the event area. This evolution reduces routing overhead and improves the scalability. Moreover, Bee-Sensor-C adopts an enhanced multipath construction method in order to achieve the balance of the network energy consumption. Besides, Bee-Sensor-C can well support the multicluster scenario. Through simulations, the network performance is evaluated and the results demonstrate that Bee-Sensor-C outperforms the existing protocols in terms of energy efficiency, energy consumption balance, packet delivery rate, and scalability.

Journal ArticleDOI
TL;DR: A secure single sign-on based authentication scheme and a robust coexistence proof protocol for IoT based healthcare systems are proposed and the robustness of the two proposed schemes is guaranteed under the adversary model.
Abstract: With the advancement of information communication technologies, the evolution of the Internet has given rise to a ubiquitous network consisting of interconnected objects (or things), called the Internet of Things (IoT). Recently, the academic community has made great strides in researching and developing security for IoT based applications, focusing, in particular, on healthcare systems based on IoT networks. In this paper, we propose a sensor (or sensor tags) based communication architecture for future IoT based healthcare service systems. A secure single sign-on based authentication scheme and a robust coexistence proof protocol for IoT based healthcare systems are proposed. With the formal security analysis, the robustness of the two proposed schemes is guaranteed under the adversary model.

Journal ArticleDOI
TL;DR: An intelligent sensor networks system based on intelligent gateway based on ZigBee wireless and power line carrier (PLC) communication has easily used and has strong compatibility.
Abstract: For shortcomings of current smart home system and power line carrier insufficient data transferring, an intelligent sensor networks system based on intelligent gateway is studied in this paper. Smart home system includes internal network, intelligent gateway, and external network. Multiple servers are designed in gateway, which start at the same time and receive various forms of data. Then data is processed for internal network format. External network includes several modes of communication such as TCP/IP, UDP, and pipe. Internal network includes ZigBee wireless and power line carrier (PLC) communication. Power line carrier protocol is improved, and it expands data transmission capacity to accommodate communication needs of modern family. Smart home system is designed as modules, such as intelligent gateway module, power line carrier communication module, ZigBee wireless communication modules, and appliance within electric equipment. Finally this system is physically designed and verified. The smart home system introduced in this paper has easily used and has strong compatibility.

Journal ArticleDOI
TL;DR: A new ultralightweight primitive recursive hash is introduced, which efficiently detects the message tempering and also avoids all possible desynchronization attacks and involves only bitwise operations such as XOR, AND, left rotation, and recursive hash.
Abstract: RFID is one of the most protuberant systems in the field of ubiquitous computing. Since RFID tags have limited computation capabilities, numerous ultralightweight authentication protocols have been proposed to provide privacy and security. However all the previously proposed ultralightweight mutual authentication protocols have some security apprehensions and are vulnerable to various desynchronization and full disclosure attacks. This paper proposes a new ultralightweight mutual authentication protocol to provide robust confidentiality, integrity, and authentication (RCIA) in a cost effective manner. RCIA introduces a new ultralightweight primitive recursive hash, which efficiently detects the message tempering and also avoids all possible desynchronization attacks. RCIA involves only bitwise operations such as XOR, AND, left rotation, and recursive hash. Performance evaluation illustrates that RCIA requires less resources on tag in terms of on-chip memory, communication cost, and computational operations.

Journal ArticleDOI
TL;DR: A new scheme for predetermining the optimized routing path is proposed based on the enhanced parallel cat swarm optimization (EPCSO) in this paper, the first leading precedent that the EPCSO is employed to provide the routing scheme for the WSN.
Abstract: The wireless sensor network (WSN) is composed of a set of sensor nodes. It is deemed suitable for deploying with large-scale in the environment for variety of applications. Recent advances in WSN have led to many new protocols specifically for reducing the power consumption of sensor nodes. A new scheme for predetermining the optimized routing path is proposed based on the enhanced parallel cat swarm optimization (EPCSO) in this paper. This is the first leading precedent that the EPCSO is employed to provide the routing scheme for the WSN. The experimental result indicates that the EPCSO is capable of generating a set of the predetermined paths and of smelting the balanced path for every sensor node to forward the interested packages. In addition, a scheme for deploying the sensor nodes based on their payload and the distance to the sink node is presented to extend the life cycle of the WSN. A simulation is given and the results obtained by the EPCSO are compared with the AODV, the LD method based on ACO, and the LD method based on CSO. The simulation results indicate that our proposed method reduces more than 35% power consumption on average.

Journal ArticleDOI
TL;DR: Two protocols, as improvements to both ODMRP and EODMRP, are proposed where the refresh interval is basically adapted based on the source moving speed and the number of disconnections reported by multicast members.
Abstract: Due to its simplicity, efficiency, and robustness to mobility, the On-Demand Multicast Routing Protocol (ODMRP) becomes a standout amongst the most broadly utilized multicast routing protocols in mobile ad hoc networks (MANETs). However, the robustness of ODMRP comes at the expense of incurring a high control overhead to the network. The Enhanced ODMRP (EODMRP) proposed a dynamic refresh interval for the multicast mesh based on the network feedback on real disconnections experienced by the multicast network members. Veritably, EODMRP decreased the network control overhead at the cost of obtaining a low packet delivery ratio especially in high mobility conditions of the network. In this paper, two protocols, as improvements to both ODMRP and EODMRP, are proposed where the refresh interval is basically adapted based on the source moving speed and the number of disconnections reported by multicast members. Furthermore, we proposed an impressive local recovery to be employed in both protocols, which includes new setup and failuremechanisms that contribute effectively to boosting the performance of our proposed protocols. Since the majority of nodes in MANET rely on batteries, the main contribution of this research is to limit the amount of control information that is passed between nodes (i.e., reducing the control overhead over that in ODMRP) while maintaining a better packet delivery ratio than EODMRP.

Journal ArticleDOI
TL;DR: A GPS-free localization framework that uses two-way time of arrival to locate the vehicles based on communication with a single RSU and uses the vehicle kinematics information obtained via the vehicle's onboard inertial navigation system (INS) to further improve the accuracy of the vehicle location using Kalman filters.
Abstract: Collision avoidance and road safety applications require highly accurate vehicle localization techniques. Unfortunately, the existing localization techniques are not suitable for road safety applications as they rely on the error-prone Global Positioning System (GPS). Likewise, cooperative localization techniques that use intervehicle communications experience high errors due to hidden vehicles and the limited sensing/communication range. Recently, GPS-free localization based on vehicle communication with a low cost infrastructure installed on the roadsides has emerged as a more accurate alternative. However, existing techniques require the vehicle to communicate with two roadside units (RSUs) in order to achieve high localization accuracy. In contrast, this paper presents a GPS-free localization framework that uses two-way time of arrival to locate the vehicles based on communication with a single RSU. Furthermore, our framework uses the vehicle kinematics information obtained via the vehicle's onboard inertial navigation system (INS) to further improve the accuracy of the vehicle location using Kalman filters. Our results show that the localization error of the proposed framework is as low as 1.8 meters. The resulting localization accuracy is up to 65% and 47.5% better than GPS-based techniques used without/with INS, respectively. This accuracy gain becomes around 73.3% when compared to existing RSU-based techniques.

Journal ArticleDOI
TL;DR: In this paper, similarity coefficient is used to measure the similarity of AP sets, which is then combined with radio signal strength values to calculate the fingerprint distance and results show the proposed approach does outperform existing approaches.
Abstract: Indoor localization techniques using Wi-Fi fingerprints have become prevalent in recent years because of their cost-effectiveness and high accuracy. The most common algorithm adopted for Wi-Fi fingerprinting is weighted K-nearest neighbors (WKNN), which calculates K-nearest neighboring points to a mobile user. However, existing WKNN cannot effectively address the problems that there is a difference in observed AP sets during offline and online stages and also not all the K neighbors are physically close to the user. In this paper, similarity coefficient is used to measure the similarity of AP sets, which is then combined with radio signal strength values to calculate the fingerprint distance. In addition, isolated points are identified and removed before clustering based on semi-supervised affinity propagation. Real-world experiments are conducted on a university campus and results show the proposed approach does outperform existing approaches.

Journal ArticleDOI
TL;DR: F fuzzy theory which is applied to build an energy-saving mechanism for feedback control and fuzzy logic-based decision model which can reduce the 55% energy while maintaining adequate air quality are shown.
Abstract: The aim of this study is to construct an intelligent wireless sensing and control system to address health issues. We combine three technologies including (1) wireless sensing technology to develop an extendable system for monitoring environmental indicators such as temperature, humidity and CO2 concentration, (2) ARIMA (autoregressive integrated moving average) to predict air quality trends and take action before air quality worsens, and (3) fuzzy theory which is applied to build an energy-saving mechanism for feedback control. Experimental results show the following. (1) A longer historical data collected time interval will reduce the effects of abnormal surges on prediction results. We find the ARIMA prediction model accuracy improving from 3.19 ± 3.47% for a time interval of 10 minutes to 1.71 ± 1.45% for a time interval of 50 minutes. (2) The stability experiment shows that the error rate of prediction model is also less than 7.5%. (3) In the energy-saving experiment, fuzzy logic-based decision model can reduce the 55% energy while maintaining adequate air quality.

Journal ArticleDOI
TL;DR: An evolutionary multiobjective optimization approach based on nondominated sorting genetic algorithm-II (NSGA-II) is proposed to optimize the network lifetime and coverage while maintaining the network connectivity.
Abstract: Coverage, connectivity, and network lifetime are important issues in wireless sensor networks (WSNs). Balancing the energy consumption in the network, reducing the transmission range of nodes, and density control of active nodes are approaches to extend the network lifetime. However, transmission range reduction and smaller number of active nodes can affect the network topology and may cause the network to be disconnected. So, there exist conflicts among lifetime, coverage, and connectivity. In this paper, these conflicting issues are considered and an evolutionary multiobjective optimization approach based on nondominated sorting genetic algorithm-II (NSGA-II) is proposed to optimize them. Simulation results demonstrate that the proposed algorithm can improve the network lifetime and coverage while maintaining the network connectivity.

Journal ArticleDOI
TL;DR: The use of the residual energy and the transmission delay as routing metric in the next hop selection process for the RPL protocol is presented and an objective function for this metric based on ant colony optimization (ACO) is designed.
Abstract: Energy conservation, while ensuring an adequate level of service, is a major concern in Low power and Lossy Networks (LLNs), because the nodes are typically deployed and are not replaced in case of failure. Several efforts have recently led to the standardization of a routing protocol for LLNs. The standard provides several criteria that can be used as a routing metric. The working group RoLL of the IETF developed a routing protocol for 6LoWPAN sensor network (IPv6 over IEEE 802.15.4) (Ko et al., 2011), RPL, recently standardized. Using this protocol could become common and standard in IPv6 sensor networks in the future. Most implementation of the protocol makes use of the transmission rate successfully (ETX) as metric and focuses on the reliability of links. In this paper we present the use of the residual energy and the transmission delay as routingmetric in the next hop selection process for the RPL protocol. We design an objective function for this metric based on ant colony optimization (ACO), and then we compare the results of experiments realized with the RPL based on ETX.

Journal ArticleDOI
Boyu Diao1, Yongjun Xu1, Zhulin An1, Fei Wang1, Chao Li1 
TL;DR: Underwater time of arrival (ToA) ranging technique is introduced and to maintain all the original advantages of DBR is made; energy-efficient depth-based routing protocol that reduces redundancy energy cost in some blind zones; low-latency depth- based routing Protocol that is able to deliver a packet through an optimal path.
Abstract: Underwater Sensor Network (UWSN) is a representative three-dimensional wireless sensor network. Due to the unique characteristics of underwater acoustic communication, providing energy-efficient and low-latency routing protocols for UWSNs is challenging. Major challenges are water currents, limited resources, and long acoustic propagation delay. Network topology of UWSNs is dynamic and complex as sensors have always been moving with currents. Some proposed protocols adopt geographic routing to address this problem, but three-dimensional localization is hard to obtain in underwater environment. As depth-based routing protocol (DBR) uses depth information only which is much more easier to obtain, it is more practical for UWSNs. However, depth information is not enough to restrict packets to be forwarded within a particular area. Packets may be forwarded through multiple paths which might cause energy waste and increase end-to-end delay. In this paper, we introduce underwater time of arrival (ToA) ranging technique to address the problem above. To maintain all the original advantages of DBR, we make the following contributions: energy-efficient depth-based routing protocol that reduces redundancy energy cost in some blind zones; low-latency depth-based routing protocol that is able to deliver a packet through an optimal path. The proposed protocols are validated through extensive simulations.