Industrial Internet of Things (IIoT) has emerged as a novel paradigm for smart manufacturing that supports reliable and real-time network systems. The application of IIoT-based manufacturing systems handles large amounts of data across various components, including sensors and robots for industrial automation. Although routing protocols for IIoT applications have already supported various connectivity characteristics, there is still a lack of mobility. In this paper, we propose an IIoT-based device-to-device (D2D) network system that supports energy-efficient mobility of autonomous mobile robot (AMR). Moreover, the D2D network system is modeled using a stochastic game framework, which is solved using our game theory-based optimization algorithm (GTA). We apply GTA to maximize the data rate of AMR and compute the Nash equilibrium as a solution of the stochastic game theory by the best response strategy in various simulation environments. The results demonstrate that GTA can enhance performance by maximizing the average data rate, as well as maintaining the average energy consumption.

The rapid proliferation of functional network devices equipped with imaging capabilities across consumer, industrial, security, and defense sectors has enhanced convenience and safety. However, this widespread adoption has simultaneously raised critical concerns regarding covert surveillance and privacy violations. In recent years, research on detecting and localizing hidden spy cameras has made substantial progress, driven by the urgent need for reliable and robust counter-surveillance technologies. While hidden camera detection has emerged as a critical research area, existing efforts remain dispersed across various domains without a unifying perspective. By systematically reviewing 61 core studies published since 2021, this survey consolidates existing approaches into four paradigms and provides a structured foundation for comparative analysis. The reviewed techniques are systematically categorized into three primary sensing domains: network-based, optical, and spectrum-oriented approaches. The fourth paradigm encompasses hybrid architectures that integrate machine learning to enhance detection accuracy. This survey provides a comprehensive taxonomic framework that unifies detection and localization approaches for hidden camera countermeasures. By systematically reviewing current technologies and identifying research gaps, we aim to provide strategic guidance on privacy-preserving detection systems that can effectively counter evolving surveillance threats. Beyond taxonomic synthesis, this survey provides a strategic roadmap for designing reproducible evaluations and selecting optimal detection pipelines under real-world constraints.

This paper presents a vibration-acoustic-based material classification system for material-aware digital twin construction using off-the-shelf smart mobile devices. While existing digital twin research predominantly employs visual sensing (cameras, LiDAR) for geometric representation, these approaches cannot determine material composition when properties are not visually discernible. We propose a novel framework leveraging mobile device’s actuators to generate controlled vibrations and capturing acoustic signatures via the built-in microphone. Acoustic data undergoes feature extraction through time-domain vectorization and Mel-spectrogram representation, enabling classification via SVM, MLP, and CNN architectures. Our CNN model achieves 91% accuracy in controlled environments and 75.4% in real-world scenarios using 1.0-second audio segments, with inference latency below 25 milliseconds. These results validate acoustic sensing effectiveness for material classification, enabling material-aware digital twin construction through on-device processing without additional hardware requirements.

Video surveillance systems rapidly spread due to security concerns, and we find ourselves under constant monitoring, even at times when privacy is desired. This technology raises numerous social and ethical concerns, and many individuals are worried about it. Therefore, ongoing research is dedicated to de-tecting devices used for malicious purposes. However, with the ad-vancement of technology, these devices are becoming increasingly adept at cunningly concealing themselves in unexpected ways, making detection progressively more challenging. Therefore, we propose real-time detection technology for devices streaming users' personal information through monitoring wireless network traffic. To identify these devices, we categorize wireless streams proximate to the user into sources and destinations. Subsequently, we analyze packet similarity using the Nilsimsa algorithm, which starts with the group accumulating a significant volume of packets. Finally, through pattern comparison, we identify potentially threatening devices in proximity to the user. This method proves useful for real-time detection of devices, such as IP cameras and drones, that transmit data using wireless networks.

With the increasing demand for high-quality user experiences in museums and art galleries, interest in smart guidance systems has grown. These systems aim to provide detailed information about the artwork and deliver audio explanations related to the pieces of interest. Traditional guidance systems typically use techniques such as numbering, QR codes, and beacons. However, these methods can be challenging for visually impaired individuals, as they rely on visual cues. To address this issue, this paper introduces a novel smart docent system designed to enhance the gallery experience for visually impaired visitors. The system features two primary functional frameworks, supported by Artificial Intelligence (AI) models: user escorting and audio touring. These frameworks utilize mobile-based sensing, dynamic Bluetooth Low Energy (BLE) beaconing, and edge computing. The system employs an on-device object detection model to minimize communication delays caused by large amounts of visual data. Although BLE beacons are statically installed within the art gallery, they dynamically update location IDs. Edge computing helps correct positioning errors based on the user's movement history and direction. Moreover, the system adaptively provides an audio tour based on the user's behavior, such as approaching or passing by artwork, or leaving an exhibit while listening to audio descriptions.

Recently, ride-sharing has become an essential service for daily use. Some popular mobile apps have been utilised to match up between a user and a rider. Mobile apps provide mutual location information and private information for checking security levels, such as their profile photos, the rider’s star level, and feedback records about the user. Despite providing such information, frequent mismatching between a user and a vehicle causes severe safety problems. Therefore, this paper proposes a secure coupling scheme between users and riders via fine-grained cyber-physical interaction to prevent getting into the wrong car. The proposed scheme relies on dynamic Bluetooth low energy (BLE) beaconing to provide precise mutual detection between passengers and riders. Smart mobile devices dynamically generate BLE beacon messages to recognise and authenticate each other, and such beaconing is also used to measure the highly accurate distance between them. For mutual beaconing, the scheme deals with frequent switching of the advertising and scanning modes of the Bluetooth channel and their interval. Since passengers and vehicles might continuously move, accurate distance detection is not trivial. So, this scheme considers edge servers to apply various machine learning techniques and filtering schemes to achieve precise detection. Performance evaluations rely on a proof-of-concept prototype, and various field test data are utilised to prove the proposed concept’s performance.

Along with the advent of COVID-19 epidemic, delivery services have become one of the most common services in our daily life. However, the current services merely assume that the contact for handing over delivery items is denied to avoid facing between carriers and receivers. This extreme concept might lead to the ruin of typical processes for delivery services, such as face-to-face authentication, item checking, and payment in person. So, it may cause insufficiency regarding both sides of the secure item delivery and customers’ personal security. Therefore, this paper comes up with a novel CONTACTFUL delivery service with the digital twin paradigm to resolve contactless problems. The proposed idea establishes two-tier digital twin architecture to arrange digital twins and physical twins of carriers and receivers. Then, inter-digital-twin interaction virtually supports on-site delivery service processes. The inter-twin interaction relies on highly accurate proximity detection for items, carriers, and receivers. So, the proposed scheme considers machine-learning technologies and filtering algorithms to achieve high precision based on mobile-based Bluetooth low energy (BLE) beaconing. This scheme is implemented as a proof-of-concept prototype, and various field data are exploited to build ML-filtering models including their ensemble one. On the steel door, the ensemble model shows an accuracy improvement of 65% compared to SVM, 14% to CNN, and 73% to MLP. On the wood door, the ensemble model shows an accuracy improvement of 21% compared to SVM, 9% to CNN, and 17% to MLP.

This paper proposes a novel scheme to detect and localize the spy cameras based on AI algorithm based raw traffic analytics, named AI-aided Hidden Camera Locator (AHCL). In AHCL, the video streaming data are filtered via the SVM (support vector machine) algorithm to quickly monitor whole raw network traffic from a router to the networks first. Then, gathered traffic data are denoised by the Denoising Autoencoder (DAE) technique to improve the data quality of classification for localization, where a camera transmits video streaming. Based on the proof-of-concept implementation, the proposed scheme can achieve 99.5% positioning accuracy of camera detection with the Ensemble Neural Networks (NNs).

This paper proposes a novel individual monitoring mechanism to support rescuing people in indoor places, named Cyber-Physical Individual monitoring (CP-Im), When firefighters go to the rescue of people existing within an indoor place where is on fire or broken down due to an earthquake or some disaster, the existence and accurate location of victims are most important information. So, this paper tries to solve such practical demand relying on the present life nature with well-deployed mobile network infrastructure and densely-populated smartphone users. CP-Im shows 98.82% of the user recognition precision and 96.5% of the user position accuracy is achieved.

Parking is an everyday ordinary activity in urban lives. In other words, it is the most common and essential requirement of all drivers in a car park to fast search a preferred parking spot. Recently most parking lots provide a sensing-based display system to notify available parking spots. However, such systems are still unable to tell drivers exact parking spots and make any recommendation to improve the traffic conditions and driver experiences. In this paper, a novel machine-learning-aided smart parking system based on Internet of Things, smart mobile devices and edge computing is proposed. This novel parking system aims at providing customized parking experience to users through highly accurate positioning and user activity sensing computed as the edge intelligence. The proposed system mainly focuses on increasing user experience for parking through the concatenated autoencoder design for improving performances of the user positioning mechanism.

Parking at an affordable place is the precedent task for all activities of the everyday life in urban environments such as shopping, working, exercising, etc. So, it is the most common and essential requirement of all users in a car park to fast search a preferred parking spot closely associated their current intent. Although modern parking lots have installed the sensing and display systems to inform drivers on the availability of parking areas, such systems are unable to tell drivers exact parking spots and make any recommendation to improve the traffic conditions and driver experiences. In this paper, a novel analytic- based smart parking system clustering Internet of Things, smart mobile devices and edge computing is proposed. This novel parking system aims at providing customized parking experience to users through highly accurate positioning and user status detection which are achieved by joint mobile sensing-machine learning based analytics as the edge intelligence. Based on the proof-of-concept implementation, the proposed scheme can achieve 99.1% positioning accuracy of a parking spot; in terms of user status sensing, especially getting in a car and out of a car, detection accuracy shows 96%; finally, it shows much shorter service consumption time of 15.6 times than the legacy approach.

This research explores reliability and timing issues of push notification from Bluetooth Low Energy (BLE) beacons in outdoor districts for smartphone-based interactive applications. First, beacon signals fully cover a targeted area. The second issue is that beacon infrastructure is designed for reliable performance against environmental properties. Finally, the experience quality of notification to smartphone or mobile devices takes high level even though users have mobility such as a driver in a car, a user riding a bicycle, a walking user, etc. For finding out base lines to achieve these features in interactive system design and practical deployment of smart applications based on smartphone-beacon interaction, we evaluate real performances of beacon running at outdoor places. We compare the novel notification model, named n-1 model, which merely copes with application variables with delivering content redundancy, to the typical 1-1 alignment mean of one notification with single content. The proposed model shows average 70 % improvement against those impediments.

Indoor positioning of individuals is one of the most important technologies in smart home applications for user-customized support. The indoor positioning is typically fulfilled through radio signal strength indicators (RSSIs) of referred devices with specific media such as Wi-Fi access points (APs) and Wi-Fi station devices (STAs). So, the capability of typical positioning schemes is highly close to the signal acquisition environments of such media. In other words, since STAs frequently fall into a sleep mode to save the battery power and some data acquisition technologies are based on advertising intervals, the amount of RSSIs of referring devices could not be gathered enough to detect correct positions of individuals. In this paper, a novel individual positioning mechanism, called PIPing (Proxy Individual Positioning), is come up with. The PIPing mechanism carries out proxy signal acquisition via IEEE 802.11 monitor mode devices to overcome such restrictions. In addition, PIPing includes machine learning based signal data analytics to provide high reliable results for positioning. Based on the proof-of-concept prototype, PIPing can acquire much higher amount of RSSI data than existing manners, about 330% increment; the reliability of positioning for a home with seven rooms shows 96.4% via the support vector machine (SVM) and 96.5% by the multilayer perceptron (MLP) with autoencoder denoising to tune up signals.

The maturing deployment of the Internet of Things is gradually realizing new smart applications that strongly leverage recent advances in proximity detection methods. To this end, Bluetooth low energy (BLE) beacons are one of the preferred candidates because of the widespread use of Bluetooth-enabled devices. However, traditional battery-powered BLE beacons suffer from a limited operation lifetime, inducing additional maintenance operations and costs. This paper addresses this issue by proposing design principles for an ambient light energy harvesting BLE beacon capable of perpetual operation in the indoor environment. The contributions made in this paper include: 1) investigation and modeling of related hardware components, namely the BLE beacon, photovoltaic panel, and capacitor; 2) design principles for selecting hardware components subject to varying environmental conditions and application requirements; and 3) prototyping and field-tests to prove its practicality. Through multiple experiments, this paper proves that the design can operate perpetually under 40 lux light intensity, and can last over 17 h once fully charged.

Nowadays, mobile applications are engaged with and depended on the physical world more and more. Interaction with a certain proximity and thing is bringing smarter services into our daily lives through cyber-physical world collaboration. Push notification of meaningful content associated with the proximity or thing is one of key technologies of the cyber-physical services. For example, empty parking spot recommendation in a parking lot or promotion coupon notification of a shop at a shopping cent er should be delivered accordingly. This paper explores reliable push notification of content for novel interactive mobile applications over Bluetooth Low Energy (BLE) beacon infrastructure. Since mobile users move around with different speeds, this paper deals with such difference to relay right content in a reliable manner, called Reliable Push Notification (RPN). RPN dynamically clusters contents and links them to a beacon to achieve reliability, and then adaptively pre-allocate contents for transmission.

The emergence of Bluetooth low energy (BLE) beacons has promoted the development of proximity-based service (PBS), which is a context-aware application delivered subject to the Proximity of Interest (PoI). Most commercial applications use the sequential proximity detection with a fixed scanning mechanism to identify the target PoI. Such sequential execution, though is able to produce reliable detection, suffers severe performance degradation especially when the number of deployed beacons in the vicinity increases. To understand the effects of dense deployment, we conduct an empirical investigation and derive the statistical properties of both received signal strength (RSS) and signal inter-arrival time. In light of the statistical insights, this paper proposes a high resolution proximity detection using an adaptive scanning mechanism fusion with a spontaneous Differential Evolution (AS+sDE). This novel approach enables the receiver to adapt its scanning duration conditioned on the deployment density and make an almost spontaneous detection in parallel with the scanning. The feasibility of the proposed approach is verified by both simulations and real-world implementations. For a density of$\leq 5\ beacons/m^2$,AS+sDEachieves a superior performance with a high accuracy rate, i.e., on average$<1s$is spent to guarantee at least 90 percent accuracy.

Presents corrections to the paper, “High resolution beacon-based proximity detection for dense deployment", (Ng, P.C., et al), IEEE Trans. Mobile Comput., vol. 17, no. 6, pp. 1369–1382, Jun. 2018.

Existing interactive systems suffer from low user engagement due to their passiveness and steep learning curve. To address these issues, this paper presents an interactive framework, Notify-and-Interact, which leverages the Bluetooth low energy (BLE) beacon infrastructure to notify and a smart-phone to interact, such that it transforms a passive interactive system into an active one. The proposed framework is demonstrated in the Ping Yuan and Kinmay W Tang Gallery, where a series of wildlife artworks are exhibited. Engagement conversion rate is measured, and users' quality of experience (QoE) is surveyed through likert assessment. Artworks with Notify-and-Interact outperforms the QR code with a high engagement conversion rate at the interaction stage, i.e., 86% over 53%, and an average engagement time of 55.67s over 28.69s, respectively. The mean opinion score (MOS) shows that around 80% of the users expressed high satisfaction with the installed Notify-and-Interact framework in the gallery.

In this paper, user log data of mobile notificationsare collected from a real mobile news application, and notificationopening rate and reaction time are identified as key parametersthat characterize user behavior. The results indicate that notificationopening patterns depend on the content of notifications, the time at which they are sent, the activeness of users, andthe reaction time. This paper also demonstrates that there existsan inverse relationship between the notification opening rate ofusers and their notification reaction time, and between theirnotification opening rate and notification opening volume. Then, a novel method of quantifying notification usefulness for users isdeveloped, where 3 models are presented to describe usefulnessof notifications against the volume of notifications received, eachrelevant in different contexts. Utilizing this usefulness model, a notification optimization framework is developed for sendingnotifications from different news categories. The optimized notificationallocation improved the average notification opening rateby by 65.24% from 4.92% to 8.13%, and the average reactiontime improved by 13.13% from 20.4 hours to 17.68 hours.

A proximity-based service (PBS) leverages the estimated proximity to provide users the accessibility to object or location restricted service. This paper exploits the interaction between Bluetooth Low Energy (BLE) Beacon and smartphone to set forth the fundamental building block of a beacon-based PBS system. In real-world scenarios, a beacon-based PBS system might suffer from sparse conditions when some beacons malfunction or beacons can only be deployed in a few specific positions. Motivated by such limitations, a similarity filter extended with compressive sampling matching pursuit (SF-CoSaMP) is proposed to ensure the reliability of proximity detection under such sparse conditions before smartphone proceed to retrieve the corresponding PBS. An extensive simulation with large volume of collected data has been conducted and the results prove the reliability of the proposed algorithm with high detection accuracy in an environment with sparse deployment.

Communications for mobile sink groups such as rescue teams or platoons bring about a new challenging issue for handling mobility in wireless sensor networks. Recently, a group region-based approach has been proposed to send data to a mobile sink group. However, it uses flooding for discovering and notifying group region information and flooding or long distance forwarding for disseminating data. Thus, it causes high energy consumption and data delivery failure. Moreover, its per-sink mobility supporting scheme makes energy consumption and data delivery failure more serious. Thus, this letter proposes an Energy-efficient and Reliable Mobile Group communication protocol (ERMG) to support a mobile sink group, which exploits a virtual grid structure. For the group region discover and notification and the data dissemination, ERMG uses communications with only cell heads of grid cells that manages group sinks. ERMG also uses a per-grid based scheme to support sink mobility. Simulation results show that ERMG has better performance than the existing protocols.

Informative directories have always responded to a fundamental need of humanity: providing available information around people. However, the escalating amount of content to be visualized on directories makes relevant information search extremely time-consuming. Meanwhile, digital displays based on screen-smart device interaction become an emerging interface of smart services to deal with daily-life challenges like information seeking. Also, multimedia content, such as movies, can be understood by multimedia analytics for recommendation, but there is no effective way to visualize the content of a directory. This paper proposes a novel directory visualization framework, called analytics-driven dynamic visualization on digital directory (AVDD): understanding user preferences via smartphone-based interaction and optimizing visualization by visual analytics in terms of high content relevancy and screen utilization for advanced directories. With experiments in laboratory and real-world settings, AVDD is proven to be effective for visualizing directory with screen utilization over 98% and the score for Likert-scale surveys achieving 73% on average in a movie directory.

This paper presents a comprehensive empirical study on the correlations between users' interest similarity and various social features across three interest domains (i.e., movie, music and TV). This study relies on a large dataset, containing 479, 048 users and 5, 263, 351 user-generated interests, captured from Facebook. We identify the social features from three types of the users' information - demographic information (e.g., age, gender, location), social relations (i.e., friendship), and users' interests. The results reveal that the interest similarity follows the homophily principle. Particularly, the results show that two users are more likely to be alike in their interests 1) if they exhibit more similarity in their demographic characteristics (e.g., similar age, same gender, or close to each other geographically), or 2) if they are more intimate in their friendship, or 3) if they present a higher average interest individuality (i.e., a measurement for estimating the personalized characteristics of a user's interests). The empirical observations could be exploited to infer how two users are alike in their interests according to the social features, which could be further harnessed by various practical applications and services, such as recommendation system and advertisement service.

The cluster between Internet of Things (IoT) and social networks (SNs) enables the connection of people to the ubiquitous computing universe. In this framework, the information coming from the environment is provided by the IoT, and the SN brings the glue to allow human-to-device interactions. This paper explores the novel paradigm for ubiquitous computing beyond IoT, denoted by Social Internet of Things (SIoT). Although there have been early-stage studies in social-driven IoT, they merely use one or some properties of SIoT to improve a number of specific performance variables. Therefore, this paper first addresses a complete view on SIoT and key perspectives to envision the real ubiquitous computing. Thereafter, a literature review is presented along with the evolutionary history of IoT research from Intranet of Things to SIoT. Finally, this paper proposes a generic SIoT architecture and presents a discussion about enabling technologies, research challenges, and open issues.

In legacy networks, overlay multicast protocols are stateless multicast relying on unicast with IP addresses regarding multicast routing states on routers, and thus they offer cost-effectiveness and robustness. Wireless sensor networks (WSNs) consist of a large number of randomly deployed sensors with unattended batteries and constrained device capabilities. For non-uniform and resource-sensitive WSNs multicast protocols also have taken an overlay approach. The protocols establish a cost-optimal structure, a Steiner tree, among destinations as an overlay structure and exploit geographic routing for unicasting. However, such concentration on the Steiner tree structure may paradoxically burden the irregular and resource-constrained WSNs with heavy loads for heuristic structure construction and fault-tolerant maintenance. In addition, it leads to frequent tree reconstruction, thus it could harm data multicast transmission seriously. Regarding these problems, we consider a proxy district per a destination for overlay tree formation to prevent structural dynamic alteration and support local state management. This district-based overlay multicast might be able to keep the stateless advantages of traditional overlay multicast. By overhead analysis and various computational simulations, we prove that our proposal provides robust and efficient multicast transmission.

This paper studies on data dissemination for mobile sink groups in wireless sensor networks. A mobile sink group denotes a set of tightly coupled mobile sinks for team collaborations such as a team of firefighters and a group of soldiers. This mobile sink group has a collective movement feature. That is, even though sinks in a group randomly move in their own personal spaces, they collectively move together as a single entity. For mobile sink groups, previous studies provide flooding-based protocols that determine immediate areas of a group at moments, which are successive snapshots of a group continuously moving, and then propagate data within the areas by flooding. However, since a group is still moving during decision of each snapshot, they cause asynchrony between an immediate area and the actual area at a moment. Eventually, it harms reachability and energy-efficiency. This paper therefore proposes a novel data dissemination protocol that takes into account continuous motion properties of a mobile sink group: slowly varying and streamlike movement. Based on the slowly varying property, the protocol predictively and effectively deliver data to a mobile sink group through a band of sensor nodes located in front of the streamlike trajectory of the group. Numerical analysis and computational simulations prove that this band-based data dissemination show better performances than the previous schemes with respect to both reachability and communication costs including data forwarding as well as signaling in a variety of scenarios.

To support a group of mobile sinks in wireless sensor networks, region-based routing protocols by using a single entity nature have been proposed. They periodically register the region location information of the mobile sink group and exploit flooding for the data delivery within the region. However, they have a data delivery failure problem for some sinks due to the asynchrony between the registered region and the actual region of the mobile sink group due to its mobility. They also have an excessive energy consumption problem due to flooding data within the region. Thus, to solve the data delivery failure and the excessive energy consumption problems, we propose a routing protocol for a mobile sink group by utilizing its movement pattern which has a slow variance and continuous stream i.e. moving properties. In the proposed protocol, a source sends its data only to sensor nodes on a line that a mobile sink group potentially passes, and mobile sinks get the data from the line when they pass it. Simulation results show that the proposed protocol has better performance than the existing protocols.

A principal issue for wireless sensor networks is energy efficiency, which is necessary for prolonging applications to track continuous object, such as wild fire and poison gas. Selective wakeup approach is an effective way to save energy in such networks. However, most previous studies on selective wakeup schemes have concentrated on individual objects, such as intruders and tanks, and they cannot be applied for tracking continuous objects. This is because the continuous object is pretty flexible and dynamic due to its sensitiveness to surrounding natural effects so that movable area cannot be correctly estimated by the just spatiotemporal mechanism. Therefore, we propose a grid-based protocol for applying the efficient and accurate selective wakeup technique to tracking continuous objects. When an object is detected in some specific area which tightly surrounds the object, a pre-designated area where the target may move is activated to prepare the target without any complex calculations. Moreover, our protocol is simple and asynchronous, which makes it more suitable for wireless sensor networks.

ABSTRACT Nodes mobility brings flinty challenges to multicast in Mobilead hocNetworks (MANETs). To track nodes mobility, flooding messages are widely used for data delivery structure construction and maintenance in many multicast protocols. These periodic flooding messages significantly consume network resources, such as energy and bandwidth, and result in network collisions. To release data delivery structure maintenance onus, profited from GPS location service, a number of stateless location based multicast protocol were proposed, where a destination list is encapsulated into each data packet for data packet orientation. However, due to data packet capability limitation, the way of encapsulating a destination list in each data packet header restricts the protocol scalability. To solve the scalability issue of multicast protocols, we propose a Scalable Location Guide Overlay Multicast (SLGOM) for MANETs. Analysis and simulation results show that SLGOM achieves high performance in large multicast group and significantly improves the scalability of stateless multicast with respect to group size. Copyright © 2010 John Wiley & Sons, Ltd.

Recently, detection schemes of specific phenomena, called continuous objects, such as wild fire and bio-chemical material have been actively studied. A continuous object might cover a wide area and it could dynamically change its own shape according to physical environments, e.g. wind and geographical features. For continuous object detection, the schemes have focused on detection of the current boundary shape of a continuous object at a time period. However, the schemes merely aim at reducing communication costs for boundary information collection, but they do not take into account reliable information transport. Hence, we propose a Reliable Boundary Information Transport (RBIT) protocol for continuous object detection. The protocol is composed of three major mechanisms: 1) explicit Representative Boundary Node (RBN) election, 2) cluster-based boundary information loss recovery, and 3) cluster-by-cluster packet loss recovery. The explicit RBN is considered in order to estimate boundary information loss due to the dynamic property of continuous objects. The protocol then constructs coarse-grained grid clusters, and it allocates a header node per each cluster. The header node collects location information of RBNs in its own cluster and revises lost boundary information. By the clustering the protocol distributively manages all RBNs of the large-scale continuous object. Finally, cluster-by-cluster packet loss recovery is provided for end-to-end reliable transmission from a header node to a sink. The cluster-by-cluster loss recovery fills up lost packets by data packet retransmission between clusters.

In wireless sensor networks, many studies on data dissemination to individual mobile sinks traditionally rely on a strategy that consists of a virtual infrastructure to serve current location of the mobile sinks and a per-sink foot-print chaining mechanism to support local mobility after location update. To adapt the strategy for supporting mobile sink groups, it may be simply considered to exploit a representative per a mobile sink group in order to representatively register location of the mobile sink group and representatively make a foot-print chain of the sink group. However, the representative manner may lead to considerable problems with respect to efficiency and robustness of data dissemination: inefficient data collection problem, needless location update problem, and relay path loss problem. These problems could be caused from dependency between the group and the representative, i.e. a member sink. Therefore, we propose a novel protocol for data dissemination decoupled with any member sink of a mobile sink group. In order to independently deal with a mobile sink group, the protocol is composed of three major mechanisms: 1) representative location update, 2) distributed data collection, and 3) per-group foot-print chaining.

Geocasting has been known as the appropriate scheme for providing effective data dissemination from a source to all nodes in a geographically restricted region. However, since the geocasting typically assumes the restricted region is stationary, it is hard to directly adopt the traditional geocasting in order to offer effective data delivery to mobile sink groups that have geographically collective mobility. Hence, this paper proposes a novel geocasting, called M-Geocasting (Mobile Geocasting) to support mobile sink groups. M-Geocasting provides the representative location information of a sink group to sources. The location information contains information in terms of a restricted region in which all member sinks of the group exist. A source disseminates data to the closest node in the region; then, the node restrictedly floods the data only within the region. Also, to support local movement of member sinks toward out of scope of the region, some nodes on boundary of the region maintain the data and offer it to member sinks out of scope of the region. We have evaluated M-Geocasting performance through simulation experiments, and our results show that M-Geocasting effectively supports mobile sink groups that have geographically collective mobility.

In wireless sensor networks, reliable event detection is one of the most important research issues. For the reliable event detection, existing studies usually assume that events are individual objects such as tanks, people, and animals. The existing studies estimate detection reliability of an individual object by the ratio of the number of successfully received data packets at a sink to the number of data packets determined by applications for reliable detection. Recently, detection of the other one kind of events, called the continuous object, such as wild fire and bio-chemical material has been receiving increased attention. Unlike the individual objects, a continuous object might cover a wide area and it could dynamically alter its own shape according to physical environments, e.g. wind, geographical features, and so on. Hence, the continuous object detection reliability can not be estimated by the indicator for the individual objects. In this paper we newly define the reliability indicator for continuous object detection. Then, we propose error recovery and revision scheme based on the estimation result from the novel indicator. Simulation results prove that the proposed scheme provides high reliability with respect to continuous object detection.

For WSNs, many data dissemination protocols have been proposed for mobile sink groups, in which sinks are spatially apart each other in their close proximity and move together according to group mobility. Most previous works cannot be directly applied to mobile sink groups due to the control overhead caused by the individual mobility in the group. M-geocasting protocol considers both of data dissemination and group mobility, but regional flooding leads to energy inefficiency. Energy consumption is increased in proportion to the spatial size of the group. In addition, the more frequent events generated in a source have more potential of broadcast storms and failures in data reception in some sinks exist in the group. In the paper, we propose an energy efficient scheme for data dissemination called Pipe Based Data Dissemination (PBDD), in which flooding combines with a virtual pipe, preventing the problems in flooding and data loss in group mobility. The virtual pipe is a unit of data storage for stable data dissemination, while flooding is utilized only for location discovery. Simulation results show that the PBDD outperform the existing protocols in terms of energy consumption and successful delivery rate.

There have been proposed many data dissemination protocols which use routing structures dependent on sinks or events in wireless sensor networks. However, as many mobile sinks and events exist in the network, such protocols are not energy-efficient due to frequent reconstructions of routing structures. Thus, in this paper, to provide the scalability and mobility of sinks and events, we propose new independent structure-based data dissemination protocol which exploits a k-level Independent Grid Structure (IGS) for data dissemination from sources detecting the events to sinks. The proposed protocol needs not to construct any routing structure irrespective of the number and the movement of both sinks and events. The proposed protocol also allows query or report packets to be sent to only a few grid headers in the k-level IGS and provides aggregation and multicasting of report packets by the k-level IGS. Simulation results show that the proposed protocol is superior to other protocols.

In wireless sensor networks, there have recently been studies on mobile sinks groups such as groups of soldiers on battlefields, which are characterized by geographically collective movement. Although the existing protocols for individual mobile sinks can support the mobile sinks groups, they suffer from high congestion and control overhead due to location updates by each sink in the groups. To solve the location update problem by individual sinks, a protocol, called M-Geocasting only updates the region information of the mobile sink groups to sources. However, since M-Geocasting uses the flooding within the group regions for data delivery to member sinks, it excessively consumes the energy of sensor nodes in the group region. Moreover, the flooding potentially causes broadcast storms within the group region when many events exist. Thus, in this paper, we propose an efficient data dissemination protocol which can avoid the flooding within the group region for supporting mobile sink group. The proposed protocol introduces a virtual pipe in the group region for data dissemination as data storage. In the proposed protocol, a source sends data to the pipe and member sinks retrieve data directly from the pipe. Simulation results show that the proposed protocol is superior to the existing protocols in terms of the energy consumption and the data delivery ratio.

Recently, group mobility support of mobile sinks has received increasing interest, and several mechanisms have been proposed. The mechanisms typically follow a strategy that simply adopts flooding. The strategy detects the currently located region of a mobile sink group in flooding, registers the current region to a source, and performs data flooding in the region to disseminate data to the sink group. However, this strategy might cause serious problems in terms of reachability and communication overhead. In the first, although a group could continuously move toward a target point for its own mission, the strategy discretely performs detecting the group region and updating the region information. Namely, data may be delivered the previously current region, i.e. already updated but changed the region. Moreover, in order to obtain the region information of the group, flooding is frequently fulfilled as well as the strategy utilizes flooding for data delivery to the group every time. Therefore, we propose a novel strategy for reachability and low overhead, called X-Geocasting. X-Geocasting merely finds out the region of a group when the group changes direction or movement velocity. Also, instead of fully flooding in group regions, X-Geocasting predictively and flexibly determines the restricted flooding area according to direction and movement velocity. Simulation results prove this proposed group mobility support strategy provides reachability and high energy-efficiency.

Real-time data delivery is the most important requirement for mission-critical applications in wireless sensor networks. Since a mobile sink is requested for applications and for energy efficiency in WSNs, an Expect Area-based Real-time Routing protocol (EAR2) is proposed to support real-time routing to the mobile sink. EAR2 is based on an Expect Area (EA) of the mobile sink and exploit flooding of real-time data within EA. However, flooding within EA makes sensor nodes in EA consume much energy. Flooding time within EA may also be difficult to measure and change widely according to time and environment. Thus, to avoid the flooding problems in EAR2, we propose a new real-time routing protocol based on grids for a mobile sink. In addition to EA of a mobile sink, the proposed protocol considers Expect Grids (EGs) of the mobile sink, which are included in EA. Instead of flooding within EA, the proposed protocol exploits multicasting to EGs and one-hop forwarding in a EG because in comparison with flooding, multicasting saves much energy and one-hop forwarding time is easy to measure and changes narrowly according to time and environment. Simulation results show that the proposed protocol is superior to other protocols.

Due to the severe resource constraints of sensor hardware, energy efficiency is a principal factor for detecting and tracking the movement of the large-scale phenomena such as wild fire, poison gas and hazardous bio-chemical material, denoted by continuous objects. In order to save the energy, the selective wakeup approach is effective way in the wireless sensor networks. However, most previous researches concentrated on individual objects such as intruders, tanks, and animals cannot be applied to the continuous object tracking because it is hard to expect that the diffusion of continuous object has the uniform velocity or acceleration. Recently, a prediction-based selective wakeup algorithm, denoted by PRECO is proposed. Nevertheless, this mechanism is still not acceptable. First, its prediction result is very inaccurate because a sensor node calculates next boundary line with only a few data while the continuous objects are pretty flexible and vicissitudinous. Second, its prediction tasks among current boundary nodes should be operated at the same time but it is a hard problem for the nodes to have synchronization in the wireless sensor networks. Therefore, we propose a novel prediction and selective wakeup scheme for energy efficient and accuracy continuous object tracking by using structured clustering. Hence, when objects are detected in some specific area, appointed areas where the target may move activate to keep guard without any complex calculations. Moreover, our scheme is asynchronous so that it is suitable for the sensor networks.

In wireless sensor networks, many studies on data dissemination to individual mobile sinks traditionally rely on a strategy that consists of a virtual infrastructure to serve current location of the mobile sinks and a per-sink foot-print chaining mechanism to support local mobility after location update. To adapt the strategy for supporting mobile sink groups, it might be simply considered to exploit a representative per a mobile sink group in order to representatively register location of the mobile sink group and representatively make the foot-print chain of the sink group. However, the representative manner may lead to considerable problems with respect to efficiency and robustness of data dissemination: inefficient data collection problem, needless location update problem, and relay path loss problem. These problems could be caused from dependency between the group and the representative, i.e. a member sink. Therefore, we propose a novel strategy for data dissemination decoupled with any member sink of a mobile sink group. In order to independently deal with a mobile sink group, the novel strategy is composed of three major mechanisms: 1) representative location update, 2) distributed data collection, and 3) per-group foot-print chaining.

Typical real-time routing data dissemination schemes employ 1-hop transmission speed based on the 1-hop lookahead manner that proactively obtains information of 1-hop neighbor nodes and selects one that satisfies a desired delivery speed as next hop. To improve performance of 1-hop lookahead based real-time routing protocols, THVR (Two-Hop Velocity-based Routing) is proposed. THVR reduces deadline miss ratio that the ratio of the number of data that exceeds the time limit to total number of sending data via routing decision based on 2-hop neighborhood information obtained from the 2-hop lookahead information. However, since the 2-hop lookahead manner makes every sensor node proactively obtain 2-hop neighborhood information whether the sensor node has data to forward or not, THVR carries two inefficiencies: heavy control message exchange overhead and high computing complexity. In this paper, we propose a noble real-time routing protocol based on reactive and restricted zone search. The proposed protocol minimizes the deadline miss ratio and eliminates the two inefficiencies mentioned above by on-demand multi-hop lookahead. In the proposed scheme, reactive multi-hop neighborhood information obtainment is fulfilled only by a small number of sensor nodes within a restricted zone around a data forwarding path from the source to the destination.

There have been many geographic multicasting protocols proposed for wireless sensor networks (WSNs). These protocols tend to exploit a SOurce-initiated Geographic Multicasting (SOGM) approach which consists of three phases: first, a source collects the position information of all sink nodes; second, the source constructs a multicast tree through the position information; third, the source forwards data down the multicast tree. However, if a multicast group contains many mobile sinks, frequent movement of the sinks cause a huge number of link failures of the multicast tree. To fix them, the SOGM approach requires a great deal of delivery of position registration and update messages to the source, thus leads to significant energy consumption of the sensor nodes in the vicinity of the source. Moreover, since each sink asynchronously updates one's new position to the source, it is difficult for the source node to find an opportune time for reconstructing the multicast tree. In this paper, we propose a SInk-initiated Geographic Multicasting (SIGM) protocol for WSNs which can avoid these problems faced by the SOGM approach. The SIGM allows sinks to construct their own data delivery paths to a source, and a multicast tree is automatically constructed by merging the data delivery paths. Simulation results show that the proposed protocol is superior to other protocols in term of average energy consumption, it thus prolongs the network lifetime.

In wireless sensor networks, the studies that support sink mobility without global position information exploit a Backbone-based Virtual Infrastructure (BVI) to avoid the routing structure construction per each mobile sink by full network flooding. The BVI approach typically considers one-hop clusters and a backbone structure-based tree configured by the cluster heads (CHs). For data dissemination to a mobile sink, the head of the cluster where the mobile sink exists registers the backbone structure on behalf of the sink, and then source nodes generate the data to their CHs via the tree. Finally, the CHs deliver the data to the mobile sink. However, the one-hop cluster makes the tree organized by too many CHs so that it causes large location registration overhead according to movement of the sink. Moreover, the data delivery via the tree with a large number of CHs might lead to data delivery from source nodes to the sink though detour paths due to always delivering data via the tree. Namely, although the source nodes exist at nearest clusters from the cluster attached by the sink, if they are located in different branch of the tree, the data should be delivered via detour paths on the tree. Therefore, we propose a novel BVI-based communication protocol to support sink mobility without global position information. To reduce the number of CHs, we consider multi-hop clusters. Also, to avoid the location registration of a mobile sink to the whole CHs, we uses a rendezvous CH on which queries of the mobile sink and reporting data of a source node meet. However, such a manner also has data detour problem that the source node sends data packets to the mobile sink via the rendezvous CH. Thus, we present a scheme to find a path with fewer hop-counts between CHs where the source node and the mobile sink are located in. Simulation results show that the proposed protocol is superior to the existing protocols in terms of the control overhead and the data delivery hop counts.

This paper proposes a novel detection and tracking scheme for continuous objects in wireless sensor networks, such as wild fire and bio-chemical material. Unlike previous works, the scheme takes into account a two-tier grid structure in order to achieve flexible and reliable detection and tracking. Firstly, for flexibility, the scheme proactively constructs a coarse-grained grid structure and then, once a continuous object appears, fine-grained grid structures are reactively established within coarse-grained grid cells only around the continuous object. Secondly, with respect to reliability, minute grid cells of the fine-grained grid structures are able to provide detailed shape of boundary of the continuous object; to quickly deal with diffusion of the continuous object the scheme prepares the fine-grained grid structures into next coarse-grained grid cells toward diffusion direction of the continuous object.

Due to the severe resource constraints of sensor hardware, energy efficiency is one of critical factors for monitoring the movement of the large-scale phenomena such as wild fire and hazardous bio-chemical material, denoted by continuous objects. In order to save energy, most of existing research on tracking the continuous objects focuses on finding the ways to minimize the communication cost through the effective data delivery such as data aggregation and reducing the number of reporting nodes, and not much work has been done on sensor state scheduling. Energy efficiency is expected to improve if only sensor nodes near the boundary of continuous object actively participate in tracking process, while other sensor nodes stay on sleep state for energy saving. In this paper, we propose a predictive continuous object tracking scheme, called PRECO, which uses minimum set of active sensing nodes to reduce energy consumption. The proposed scheme predicts the future boundary line, which provides the knowledge for a wake-up mechanism to decide which sleeping nodes need to be activated for future tracking. The proposed algorithm is verified with simulation results that total energy consumption can be dramatically reduced under acceptable boundary detection accuracy.

For multicast applications with large-scale groups in large-scale wireless sensor networks, it is an important issue for energy saving in geographic multicasting both to obtain location information of destination nodes and to construct the geographic multicast tree efficiently. To address this issue, there have been proposed global search based hierarchical geographic multicasting protocols. Such protocols divide the whole network into many multiple small areas and a leader node in each area manages the location information of destination nodes in its area. However, since they find location information of such leader nodes through global location search at a source, they consume much energy. Also, since they exploit hierarchical geographic multicast trees that have a higher tree consisting of the source node and the leader nodes and a lower tree consisting of a leader node and destination nodes in the area of the leader node, they consume more energy due to data detouring. To solve the problems of global search based hierarchical geographic multicasting protocols, we propose a local search based consecutive geographic multicasting scheme. Through avoiding the global search and removing the data detouring, the proposed protocol saves much energy of sensor nodes. Simulation results show that the proposed protocol is superior to the existing protocols.

In this paper, we investigate the use of explicit disjoint for the multipath routing to achieve cost-efficient operation of wireless sensor networks. The focus is on constructing completely disjointed multiple paths between the source of sensing stimulus and the destination of gathered sensor data. We propose simple schemes for multipath construction based on explicit multiple anchor nodes. For the fully disjointed multipath construction, we exploit the logical and physical schemes. The logical method classifies a multipath through the pipeline of the area where there is at least one sensor. The physical approach comprises completely disjoint multiple paths to be comprised at the source level based on the geographic routing, intermediate node side, and anchor node side and destination node side. We propose explicit multiple paths to comprise a disjoint multipath so that we removes the flooding overhead used in the multipath discovery process. The proposed scheme constructs the distributed multiple paths with data transmission through the localized information exchange between neighbor nodes. Our simulation results show the fundamental importance of an explicitly disjointed multipath proposed in this paper. For example, one of our results shows that the proposed scheme significantly reduces the signaling overhead compared to the existing multipath routing methods when there are many nodes in WSN. The simulation result also shows that the proposed scheme, compared to the explicit disjoint multiple paths, is more cost efficient than an existing multipath scheme.

In wireless sensor networks, with respect to a desired time deadline real-time data dissemination schemes achieve that by a spatiotemporal communication approach forwarding data from a source to a destination with a delivery speed. The delivery speed is typically obtained from both the static distance from the source to the destination and the interval of the time deadline. However, in case of real-time routing to a mobile sink, since the mobile sink randomly moves around, the distance from a source to the mobile sink would be dynamically changed. Hence, we propose a new real-time routing scheme considering the dynamic distances by the mobile sink. In the scheme, the source calculates an expected area of the mobile sink by the moving speed of the sink; then, the data delivery speed is obtained from the worst case distance from the source to the farthest position on the area. The source transmits data to expected area with the delivery speed, and the first sensor node within the area then floods in the area to deliver the data to the mobile sink that is dynamically located within the area.

There have been proposed many geographic multicasting protocols for wireless ad hoc sensor networks. Most of these protocols tend to exploit a Source-initiated Geographic Multicasting (SGM) approach which consists of three phases: first, a source collects the position information of all destination nodes; second, the source constructs a multicast tree through the position information; third, the source forwards data down the multicast tree. However, if a multicast group contains many mobile destinations, the SGM approach may cause a great deal of delivery of position registration and update messages to the source, thus lead to significant energy consumption of the sensor nodes in the vicinity of the source. In addition, high data delivery latency is another problem since the data delivery is triggered after the source obtains the position of all destinations and constructs a geographic multicast tree. Moreover, since each destination asynchronously updates one's new position to the source, the source node in the SGM approach is difficult to find an opportune time for reconstructing the multicast tree. In this paper, we propose a Destination-initiated Geographic Multicasting (DGM) protocol which can avoid these problems faced by the SGM approach. The DGM allows destinations to construct their own data delivery paths to a source, and a multicast tree is automatically constructed by merging the data delivery paths, and then, the source node forwards data to them down the multicast tree. In the DGM, we also propose a round-based virtual infrastructure with a radial shape for increasing the merging probability of data delivery paths and reducing reconstruction ratio of the multicast tree due to mobility. Simulation results show that the proposed protocol is superior to other protocols in term of average data delay and average energy consumption.

Proxy Mobile IPv6 (PMIPv6) is designed to provide mobility service to IPv6-nodes in a network domain by network-based management which does not require the nodes to be involved in IP mobility management. In other words, the PMIPv6 can support roaming within a PMIPv6 domain, i.e. intra-domain roaming, transparent to mobile nodes. Recently, next generation wireless networks, such as 802.16e and Super 3G/3.9G, adopt the PMIPv6 as a management solution of the IP mobility. Such extensive adoption of the PMIPv6 might lead to frequent roaming of IPv6-nodes not only within a PMIPv6 domain but also between PMIPv6 domains. However, for the roaming between PMIPv6 domain, i.e. inter-domain roaming, existing solutions take interworking between PMIPv6 and MIPv6 into consideration. It means that every mobile node should involve IP mobility management although the nodes merely move around among PMIPv6 domains which provide the transparent node mobility service. Hence, we propose a network-based roaming mechanism between PMIPv6 domains to offer transparent mobility support to IPv6-nodes. The inter-domain mechanism takes into account concatenated tunnels between home domain and visited domain. The tunnels would be established by signaling among routers in the home and visited PMIPv6 network domains.

This paper proposes a novel detection and tracking scheme for large-scale phenomena, called continuous objects, in wireless sensor networks, such as wild fire and bio-chemical material. Unlike previous works, the scheme takes into account a two-tier grid structure in order to achieve flexible and reliable detection and tracking. Firstly, for flexibility, the scheme constructs a coarse-grained grid structure and then, once a continuous object appears, fine-grained grid structures are established within coarse-grained grid cells only around the continuous object. The fine-grained grid structures could be constructed with dynamic grid cell size according to various requirements. Secondly, for reliability, minute grid cells of the fine-grained grid structures are able to provide detailed shape of boundary of the continuous object; to quickly deal with diffusion of the continuous object the scheme prepares the fine-grained grid structures into next coarse-grained grid cells toward diffusion direction of the continuous object.

In wireless sensor networks, real-time data delivery schemes typically achieve a desired delivery speed by proactively performing one-hop lookahead. Recently, to reduce the deadline miss ratio against the desired delivery speed, a study has proposed a real-time routing protocol based on proactively performing twohop lookahead. However, the recent study might cause heavy message exchange overhead and high computing complexity to proactively carry out obtainment of two-hop neighborhood speed information in the entire sensor network whether data are delivered or not. Moreover, although multi-hop lookahead provides the least deadline miss ratio, due to the restriction from the overhead and the complexity, the recent study merely adopts the two-hop lookahead manner. In this paper, we propose a novel real-time routing protocol. The proposed routing protocol adopts on-demand neighborhood information obtainment only around data forwarding paths. The on-demand information obtainment is performed in multi-hop lookahead. Hence, the proposed routing protocol is able to provide the least deadline miss ratio to realtime data delivery. Simulation results prove that the proposed routing protocol offers better performances with respect to deadline miss ratio, total communication costs, energy efficiency, and network lifetime.

In wireless sensor networks, a geographic routing requests source nodes (sensor nodes) to know location information of destination nodes (sinks) to send their data. To address this issue, many sink location service schemes have been proposed in the literature. They are designed to support only one communication mode such as unicast, anycast, manycast, or multicast communication modes. However, because an application can have one or more communication modes or a sensor network can operate several applications with each communication mode, it is necessary for a scheme to support all communication modes. Hence, we propose a general sink location service scheme for supporting all communication modes. The proposed scheme modifies the basic idea of the existing one proposed for unicast communication mode and extends it for supporting all communication modes. Simulation results show that the proposed scheme is superior to other sink location service schemes when supporting all communication modes.

Geographic routing has been considered as an efficient, simple and scalable routing protocol for wireless sensor networks, since it exploits pure location information instead of global topology information to route data packets towards a static sink. Recently, a number of research works have shown that mobile sinks can achieve high energy efficiency and load balance than static ones. In order to receive data packets continuously, a mobile sink must update its location to the source frequently. However, frequent location updates of mobile sinks may lead to both rapid energy consumption of the sensor nodes and increased collisions in wireless transmissions. The authors propose a novel geographic routing for mobile sinks to address this issue. The proposed scheme takes advantage of wireless broadcast transmission nature of wireless sensor nodes. When a sink moves, the new location information is propagated along the reverse geographic routing path to the source during data delivery. Analysis and simulation results indicate that elastic routing is superior to other protocols in terms of control overhead, data delivery delay and energy consumption.

We propose a communication mechanism to support mobility of loosely coupled mobile users in sensor applications with multiple sources. First, we examine problems for mobility support of the loosely coupled users in wireless sensor networks with multiple source nodes, and then study the dynamic sink communication model to support a mobile user with sink-oriented tree based data gathering from multiple sources and data-centric unicasting. Finally, we present an energy-efficient solution to support the loosely coupled mobile users through single data-gathering tree establishment with a distributed manner and the gathering tree based data-centric multicasting.

This paper addresses issues for tracking and monitoring continuous objects, such as poison gas, biochemical, and chemical liquid in wireless sensor networks. These continuous objects are quite different from the individual objects, such as people, animals, and vehicles in that they are continuously distributed across a region and usually occupy a large area. Accordingly, they are detected and sensed by many sensor nodes, and their sensing data are redundant and highly correlated. Hence, there needs any efficient scheme on collecting and aggregating locally their sensing data and generating the data report. The continuous objects also tend to diffuse, changes in shape, increases the size, even splits into multiple smaller continuous objects, or join together one continuous object. Accordingly, there also need any efficient scheme to manage efficiently the dynamic change of shape of the continuous objects. Therefore, we introduce dynamic rectangle zone-based collaboration mechanism for detecting, tracking, and monitoring the continuous objects taking into account the dynamic change of their shape. The proposed mechanism constructs a dynamic rectangle zone included the area occupied by one continuous object. One center node in the zone collects and aggregates the sensing data from sensor nodes which detect the continuous object. The dynamic rectangle zone change newly according to dynamic change of the continuous object and the center node is also altered by another node to minimize the energy consumption for collecting the sensing data. Through simulation results, we also evaluate how environmental factors and control parameters affect the performance of the proposed mechanism.

Geographic routing has been considered as a scalable approach in ad-hoc and sensor networks since it exploits pure position information of neighbors and a destination node instead of global topology information to route data packets. To obtain the position information of the neighbors, many geographic routing protocols assume that each node exchange periodically its own position information with its neighbors. However, these periodically position exchanges in regions without packet forwarding make nodes consume unnecessary energy. In addition, given that the nodes have mobility, when a node forwards a packet, the position information of its neighbor nodes may be invalid. Hence, in these mobile networks, it is more efficient that a mobile node collects the position information of its neighbors when it needs to forward a packet. Because every sender node in geographic routing also selects the nearest neighbor node to the destination node as the receiver node, obtaining the position information of only closer neighbor nodes to the destination node can save more wireless resources than obtaining that of all neighbor nodes. In large-scale networks, because many wireless collisions can happen due to position exchanges of many neighbor nodes, they should share limited wireless resources. Therefore, we propose a mechanism to solve these issues of geographic routing in large-scale mobile networks. Simulation results show that the proposed mechanism has better performance than the existing geographic routing protocols.

Most existing geographic routing protocols on sensor networks concentrates on finding ways to guarantee data forwarding from the source to the destination, and not many protocols have been done on collecting and aggregating data of sources in a local and adjacent region. However, data generated from the sources in the local and adjacent region are often redundant and highly correlated. Accordingly, data collection and aggregation of the region in the sensor networks is important and necessary to save the energy of sensor nodes. We introduce the concept of a local sink to address this issue in geographic routing. The local sink is a sensor node in the region, in which the sensor node is temporarily selected by the global sink for collecting and aggregating data from source nodes in the region and delivering the aggregated data to the global sink, in geographic routing. We also design a model to determine an optimal location of the local sink and propose a mechanism to collect data through the local sink. Simulation results show that the proposed mechanism with the local sink is more efficient in terms of the energy and the data delivery ratio than the existing mechanism in a geographic routing.

In wireless sensor networks, groups of mobile users interested in equivalent information could be classified into two categories according to existence of direct communication channel among the users: 1) loosely coupled user group and 2) tightly coupled user group. The loosely coupled group means that a mobile user should communicate with others via a wireless sensor network for querying, gathering, and sharing of information interested from the group. Several information communication mechanisms have already been proposed to support mobility of the loosely coupled user groups. However, the mechanisms may not suit in case of sensor applications with multiple data sources since those are usually construct a network structure per each source. Namely, according to the mechanisms, too many network structures for the many data sources could be constructed and it may causes excessive computing overhead and energy exhaustion of sensors. Therefore, we propose an information communication mechanism to support mobility of loosely coupled mobile users in sensor applications with multiple sources. First, we examine the problems for mobility support of the loosely coupled groups in wireless sensor networks with multiple source nodes, and then study the dynamic sink communication model for data gathering from multiple sources and data delivery to a mobile user. Finally, we present an energy-efficient solution to support mobility of loosely coupled groups based on data gathering tree establishment via distributed manner and tree-based data multicasting.

In large scale Internet network, the research in area of event detection and report publish/subscribe communications paradigm is being progressed. Data-centric is the basic characteristic of data transmission mode of the publish/subscribe communications paradigm. Such characteristic coincides with the wireless sensor network. The publish/subscribe communications paradigm performs task in manner of space, time and synchronous decoupling. The publish/subscribe communications paradigm with such property is tend to be applied to the wireless sensor network. However, existing algorithms do not satisfy the three decoupling modes in wireless sensor network. Therefore, this paper applies the publish/subscribe communications paradigm to the wireless sensor network and proposes a model to solve the energy consumption problem. The proposed communication model satisfies the three decoupling modes by using Embedded Grid Structure (EGS) in the wireless sensor network. Simulation results show that proposed model is energy-efficient compared with other protocols.

We propose a communication mechanism to support mobility of loosely coupled mobile users in sensor applications with multiple sources. First, we examine problems for mobility support of the loosely coupled users in wireless sensor networks with multiple source nodes, and then study the dynamic sink communication model to support a mobile user with sink-oriented tree based data gathering from multiple sources and data-centric unicasting. Finally, we present an energy-efficient solution to support the loosely coupled mobile users through single data-gathering tree establishment with a distributed manner and the gathering tree based data-centric multicasting.

Typical information communication for large-scale wireless sensor networks may be performed in a data-centric routing manner. The data-centric routing manner well matches the publish/subscribe communication paradigm operated by a contention-based networking. The publish/subscribe paradigm provides decoupling properties for data-centric networking: space, time, and synchronization decoupling. For large-scale applications in which many publishers and subscribers are participated in interworking of information, the decoupling properties proffer salability. However, most existing communication schemes for the large-scale sensor networks do not fully satisfy the decoupling properties. The schemes construct network structures based on publishers or subscribers known as event sources and sinks respectively. Such dependency of network structures causes that network structures are established in proportion to the number of sinks or sources, i.e. space dependency. Also, originating sinks or sources of structures are always joined with the structures and manage the interworking information, i.e. dependency of time and synchronization. Hence, the communication schemes should take into account a network structure independent of the publishers and subscribers. In this paper, we propose a novel communication scheme decoupled with sinks and event sources, called ARBITER. ARBITER constructs a shared virtual grid with level value k from center point, k = 0. It then arranges storage nodes and transit nodes at level 1 cross points and over level points respectively. Sinks query to the storage nodes through the transit nodes and receive interesting information via requesting paths. Sources store sensed data to the storage nodes by the transit nodes. Our simulation proves that ARBITER shows better performance in terms of scalability, data responsibility, and mobility support.

Many dissemination protocols on the mobility support in wireless sensor networks have been designed based on the assumption that the movement trace of sinks is random. However, the mobility of the sinks in many applications, for example, the movement traces of a soldier on operation in a battle field or a firelight on rescue operation in the disaster area, can be determined in advance since they move in accordance with the decided operation or the drill regulation to perform their task. In this paper, we propose a Predictable Mobility-based Data Dissemination protocol (PMDD) that enables data to directly route from source nodes to moving sinks by taking into consideration predictable movement behavior of the sinks. We also compare the performance of the PMDD with those of other dissemination protocols with random movement behavior of the sinks, and show the superiority of the PMDD based on network lifetime, data delivery ratio, and delay latency.

Typical wireless sensor networks consist of sensor nodes and base-stations (sinks). The sensors, sinks, and user nodes can orthogonally provide their own mobility environments. The existing studies take only sensor mobility, sink mobility, and event mobility into account. Inquirer mobility, however, can be possibly suggested as one of the mobility models. An inquirer is one of the existing entity for sensor networks as a user. Inquirer mobility and routing mechanism to support it are proposed in this paper. For that, possible mobility environment and characteristics are also analyzed. At the end of this paper, excellence of the proposed routing model is proved through simulation results.

Sensor networks are composed of a great number of sensor nodes. Since all sensor nodes are energy-restricted and hard to recharge, it is very important. However, the energy consumption may significantly increase if mobile sources or sinks exist in sensor networks. The reason is that the routing information for mobile sources and sinks needs to be update frequently for efficient data delivery. The routing algorithm supporting mobile sinks should consider not only continuous data delivery but also the energy consumption of sensor nodes. However, most of the existing research e.g. Fan Ye, et al. (Set. 2002), Zehua Zhou, et al., (Jun 2006) focuses on even energy consumption while the mobility of sinks and sources is rarely consider. In this paper, we propose an efficient routing protocol with multiple virtual grids to reduce energy consumption and improve packets delivery efficiency. Simulation results show that our algorithm can guarantee high data delivery ratio and lower average delivery delay, while consuming lower energy than existing routing protocols in sensor networks.

Void areas (holes) as an inevitable phenomenon exist in geographic routing of wireless sensor networks, because the unpredictable and harsh nature application environment or uneven energy consumption. Most of the existing schemes for the issue tend to construct a static detour path to bypass a hole. The static detour path may lead to uneven energy consumption of the nodes on the perimeter of the hole; thus it may enlarge the hole. At the same time, traffic would concentrate on the peripheral node of the hole; thus the nodes on the perimeter of the hole tend to be depleted quickly. In previous work, we have proposed a hole geometric model to reduce the energy consumption and packet collisions of the nodes on the hole boundary. This scheme, however, still has the static detour path problem. Therefore, we extend the previous work by constructing a dynamic detour path hole geometric model for wireless sensor networks in this paper. The location of hole detour anchor is dynamically shifted according to Gaussian function, just generating dynamic hole detour paths.

Geographic routing has been addressed in many literatures of ad hoc sensor networks due to its efficiency and scalability. Void areas (holes) bring geographic routing several problems such as excessive energy consumption and data congestion of hole boundary nodes. Holes are hardly avoided in wireless sensor networks because of various actual geographical environments, e.g., puddles, buildings or obstacles, or uneven energy consumption, even physical destruction. To bypass holes, most existing geographic routing protocols tend to route data packets along the boundaries of holes by perimeter routing scheme. This scheme consumes more energy of the nodes on the boundaries of holes, thus possibly enlarging the holes, we call this hole diffusion problem. In this paper, we propose anchor node based virtual modeling of holes in wireless sensor networks to solve the hole problems faced by geographic routing in wireless sensor networks. Simulation results show that the proposed protocol is superior to other protocols in terms of packet deliver ratio, control overhead, average delivery delay, and energy consumption.

Geographic routing has been addressed in many literatures of ad hoc sensor networks due to its efficiency and scalability. Void areas (holes) bring Geographic routing some problems such as data congestion and excessive energy consumption of hole boundary nodes. Holes are hardly avoided in wireless sensor networks due to various actual geographical environments, e.g., puddles, buildings or obstacles, or uneven energy consumption, even physical destruction. To bypass a hole, most existing geographic routing protocols tend to route data packets along the boundary of the hole by perimeter routing scheme. This scheme, on one hand, consumes more energy of the nodes on the boundary of the hole, thus possibly enlarging the hole, we call this hole diffusion problem; on the other hand, it may incur data congestion if multiple communication sessions are bypassing the hole simultaneously. In this paper, we propose efficient hole detour scheme to solve the hole problems faced by geographic routing in wireless sensor networks. Simulation results show that the proposed protocol is superior to other protocols in terms of packet deliver ratio, control overhead, average delivery delay, and energy consumption.

In wireless sensor networks, a communication model that separate a sink collecting information from sensor nodes and a user using it has been proposed. In the model, a mobile user appoints a neighborhood sensor node as a dynamic sink, and the dynamic sink collects data from all sensor nodes and forwards the aggregated data to the mobile user. In this paper, we expand the model for single mobile user to support multiple mobile users. A core of the novel model is mapping between single dynamic sink and multiple mobile users. Namely, multiple mobile users appoint a dynamic sink and the sink collect information from all sensor nodes and forward them to the multiple mobile users. To design effectively the novel model, two issues should be solved. First, the multiple mobile users without any mutual communication channel should efficiently choose and appoint only one dynamic sink. Second, the single dynamic sink should forward the collected information to the multiple mobile users. This paper proposes a solution for those issues. The solution consists of three schemes: 1) data collection scheme, 2) tree-based multicast scheme, and 3) user mobility support scheme. The data collection scheme is to solve the first issue and the tree-based multicast scheme is to solve the second issue. Also, the user mobility support scheme is to guarantee data forwarding to mobile users.

Geographic routing has been considered as an efficient, simple, and scalable routing protocol for wireless sensor networks since it exploits pure location information instead of global topology information to route data packets. Geographic routing requires the sources nodes to be aware of the location of the sinks. How can source nodes get sinks locations with low overhead is a difficult issue in wireless sensor networks. In this paper, we propose a Sink Location Service for geographic routing in wireless Sensor Networks. In this scheme, a source node and a sink node send sink location announcement and query messages along two paths respectively by geographic routing. The node located on the crossing point of the two paths informs the source about the sink location. Then the source can send data packet to the sink by geographic routing. How to guarantee that these two paths have at least one crossing point in any irregular profile of sensor network is the challenge of this paper. Simulation results show that our protocol is significantly superior to other protocols in terms of energy consumption and control overhead.

Void areas (holes) are hardly avoided in wireless sensor networks because of various actual geographical environments, e.g., puddles, buildings or obstacles, or uneven energy consumption. To bypass holes, most existing geographic routing protocols tend to route data packets along the boundaries of holes by perimeter routing scheme. Such a scheme depletes the energy of nodes on the boundary of holes faster than others and is likely to result in earlier deaths, thus enlarging the hole sizes, a phenomenon we call the hole diffusion problem. Routing along the hole boundary may also lead to increased collisions especially if multiple data streams try to bypass a hole simultaneously. In this paper, we propose virtual circle based geometric modeling of holes for geographic routing to address these problems in wireless sensor networks. Our proposed algorithm avoids routing on the hole perimeter by selecting appropriate intermediate anchor nodes (close to the hole boundary) and routing via this anchor node. We show by simulation that our proposed algorithm provides significant savings in energy consumption, shorter routing delays, higher packet delivery ratio, all with comparable control overhead as compared with state-of-the-art techniques.

Wireless sensor networks traditionally consist of sensors perceiving data and sinks gathering the data. In addition, users receive required information from the sinks via infrastructure networks. The users, however, should receive the information from the sinks through multi hop communications of disseminated sensor nodes if such users move into the sensor networks without infrastructure networks. Unlikely, the previous works only considered mobility of sinks, which function users. Nevertheless, it is difficult for such approaches to mobility to exploit the existing data-centric routing algorithms and also for the mobile sinks to function as gateways to connect with infrastructure. To improve the shortcomings, we suggest a novel viewpoint of mobility for wireless sensor networks and propose a solution to support the mobility with multiple static sinks in this paper. The multiple static sinks, which are connected with each other via infrastructure, provide high throughput and low latency. Furthermore, they improve hotspot problems and prolong network lifetime. The proposed mechanism finally is evaluated by simulation results about throughput, latency, and network lifetime.

Wireless sensor networks are composed of a great deal of energy restricted sensor nodes and targets (events) at long- term usage such as environment monitoring. The failure of sensor nodes caused by energy exhaustion or physical destruction may lead to the reduction of sensor areas. In the wireless sensor networks, the nodes located on the edge of holes are relatively weaker than other sensor nodes since the geographic routing scheme tends to route data packets along the edge of holes by the right hand rule. It results in more energy consumption or even exhausts the energy of the hole edge nodes, so it may enlarge the holes. We call this, aholediffusionproblem. The right hand rule may also lead to data collisions on the hole edge nodes if multiple communication sessions need to bypass a hole simultaneously. In this paper, we propose hole modeling to handle the hole problem in wireless sensor networks. Our hole modeling can efficiently prevent the hole diffusion, avoid the local minimum faced by geographic routing protocols, and reduce data collisions on the hole edge nodes. Simulation results present our protocol is superior to the previous works in terms of control overhead, average delivery delay and energy consumption.

Void areas (holes) are hardly avoided in sensor networks either because of various actual geographical environments, e.g., puddles, buildings or obstacles, or uneven energy consumption. To bypass holes, most existing geographic routing protocols tend to route data packets along the boundaries of holes. Generally, a data packet will be either forwarded along a hole boundary by the right hand rule or pushed back to find another route to its destination when the data packet encounters the hole boundary. The right hand rule, on one hand, consumes more of the nodes' energy on the boundaries of holes, thus possibly enlarging the holes; on the other hand, it may incur data collisions if multiple communication sessions share the same boundaries of holes simultaneously. In this paper, we will propose a hole geometric modeling to solve hole problem in wireless sensor networks. Our hole geometric modeling has two goals: one is to prevent data packets from traveling along the boundaries of holes; the other is to avoid the problem of local minimum phenomenon. By achieving the first goal we can not only reduce the energy consumption of the nodes on the boundaries of holes, thus preventing holes' diffusion, but also reduce the data collisions in the nodes on the boundaries of holes. The second goal can reduce the packets rerouting overhead.

Typical sensor networks consist of a user, a sink, and a number of sensor nodes. The traditional communication architecture usually assumes that there is a legacy networks between a user and a sink. However, in many actual applications users like firefighters and soldiers move around sensor fields and they may not have any direct communication through legacy networks. In other words, a sensor network is the only communication channel between a user and a sink in a practical sensor field. Thus, it is essential to deliberate a novel architecture for the user mobility issue. In this paper, we present a novel communication architecture where a user operates around an infrastructureless sensor field. We, then, propose a new networking model to support user mobility on the novel architecture, named dynamic sink model. In the model a sink is temporarily selected among generic sensor nodes by a user when the user wants to get information from a sensor network. The selected sink gathers data from sensor nodes for interested tasks and propagates collected information to the user via the sensor network. We evaluate and analyze performance of the proposed dynamic sink model on the novel architecture with regard to efficiency of energy consumption, average delay, and delivery ratio, compared with the common static sink model on typical communication architecture

Stable multicast data delivery structure contributes high data delivery ratio and low control overhead in Mobile Ad Hoc Networks (MANETs). Due to dynamic topology of MANETs, to construct a stable multicast data delivery structure becomes a challenge in ad hoc environment. In this paper, we propose a stable overlay multicast protocol for MANETs based on modified Delayed Forwarding mechanism. In this protocol, each member node precalculates its stability according to remaining battery and local mobility of itself. A source rooted overlay multicast tree is created if source has to send data packets. The overlay creation follows the stability of each member node. By using modified Delayed Forwarding mechanism, a member node with relatively high stability will have highly populated subtrees, by this way to improve multicast routing stability. Data packets are transmitted via IP-in-IP tunnels between member nodes in the overlay tree.

A characteristic of mobile ad hoc networks, mobility leads to frequently update multicast routing information based on network multicasting. For the reason, comparatively lots of control signaling messages are generated, so bandwidth of wireless media and limited battery power of mobile nodes are inefficiently consumed. To improve the shortcomings, overlay multicast protocols on application layer has been proposed; however, some of them have another shortcoming which is that the number of unnecessary data forwarding among multicast members increases. Additionally, they hardly support network scalability. Thus, this paper proposes an implicit cluster-based overlay multicast protocol exploiting tree division (ICOM-TD) for mobile ad hoc networks to improve their shortcomings. Finally, we evaluate performance of ICOM-TD through numerical analysis about complexity of multicast routing and simulation in comparison with existing multicast mechanisms for ad hoc networks on end-to-end time delay, packet overhead, and delivery ratio.

Typical sensor networks consist of users, sinks, and a number of sensor nodes. The traditional architecture usually assumes that there is a legacy network between users and sinks. However, practical users like firefighters and soldiers move around sensor fields and they might not have any direct communication through legacy networks. In other words, sensor networks are the only communication channel between users and sinks in practical sensor fields. Now there are no researches with respect to architecture to support the user mobility. Thus it is necessary to deliberate a new architecture for such the issue. In this paper, a novel communication architecture was presented where a user operates around an infrastructureless sensor field. A new networking model was then proposed, named dynamic sink model, to support user mobility on the novel architecture. In the model a sink is temporarily selected among generic sensor nodes by a user when the user wants to get information from a sensor network. The chosen sink gathers data from sensor nodes for interested tasks and propagates collected information to the user via the sensor network. The performance of the dynamic sink model on the novel architecture was evaluated and explored with regard to average delay, delivery ratio, and network lifetime compared with the common static sink network model on typical communication architecture.