Thyroid nodules are neoplasms commonly found among adults, with papillary thyroid carcinoma (PTC) being the most prevalent malignancy. However, current diagnostic methods often subject patients to unnecessary surgical burden. In this study, we developed and validated an automated, highly accurate multi-study-derived diagnostic model for PTCs using personalized biological pathways coupled with a sophisticated machine learning algorithm. Surprisingly, the algorithm achieved near-perfect performance in discriminating PTCs from non-tumoral thyroid samples with an overall cross-study-validated area under the receiver operating characteristic curve (AUROC) of 0.999 (95% confidence interval [CI]: 0.995-1) and a Brier score of 0.013 on three independent development cohorts. In addition, the algorithm showed excellent generalizability and transferability on two large-scale external blind PTC cohorts consisting of The Cancer Genome Atlas (TCGA), which is the largest genomic PTC cohort studied to date, and the post-Chernobyl cohort, which includes PTCs reported after exposure to radiation from the Chernobyl accident. When applied to the TCGA cohort, the model yielded an AUROC of 0.969 (95% CI: 0.950-0.987) and a Brier score of 0.109. On the post-Chernobyl cohort, it yielded an AUROC of 0.962 (95% CI: 0.918-1) and a Brier score of 0.073. This algorithm also is robust against other various types of clinical scenarios, discriminating malignant from benign lesions as well as clinically aggressive thyroid cancer with poor prognosis from indolent ones. Furthermore, we discovered novel pathway alterations and prognostic signatures for PTC, which can provide directions for follow-up studies.

One of the major challenges in 6LoWPAN is to provide continuous services while mobile nodes' movements with minimizing network inaccessible time caused due to handoffs. Even though MIPv6, HMIPv6, and PMIPv6 are commonly accepted standards to address this in IP networks, they cannot inherently avoid the degradation in communication quality during handoff, since they are not designed with consideration of constrained node networks like 6LoWPAN. In this paper, we propose a new fast mobility management protocol for 6LoWPAN, named intra-MARIO. To minimize handoff delay and enhance service availability, intra-MARIO introduces three important components, which are a fast rejoin scheme for handoff management with an adaptive polling based movement detection and multi-hop pointer forwarding schemes for location management. To justify the effectiveness, we have conducted extensive simulations by comparing intra-MARIO with prior schemes like a basic mobility management scheme and a PMIPv6-based protocol. We then implement intra-MARIO on top of our 6LoWPAN platform (SNAIL) and evaluate the performance of intra-MARIO. The results highlight that intra-MARIO reduces overall handoff delay with low power consumption and minimizes packet losses during handoffs, compared to prior mobility protocols.

To ensure global interoperability in today's fast-moving trading networks, EPC global Network (EPC Network) architecture has been at the core of Electronic Product Code (EPC) as a universal identifier for objects' virtual representations. While Cloud technology has largely been used for EPC Network's real world deployment for thousands of vendors, an optimized Cloud solution has yet to be provided. Therefore, in this paper, we explore the challenges of EPC Network deployment, and propose our own Cloud solution with optimizations in load prediction and migration management. As proof of concept, we have conducted experiments with regard to prediction accuracy and migration performance.

The "Cloud of Things" (CoT) is a concept that provides smart things' functions as a service and allows them to be used by multiple applications. In the CoT, a single smart thing instance should efficiently host multiple applications, called multi-tenancy. Therefore, simultaneous accesses to shared smart things may lead to resource conflicts. Moreover, smart things inherently form complex dependencies on real-world. Since handling resource conflicts with complex dependencies at an application level is typically ad-hoc and error-prone, it increases the application development burden. To address these issues, we propose a middleware for Evolvable ClOut of things (ECO). The ECO middleware manages organizations to handle dependency among/between smart things and virtualizes physical smart things to enable isolation between/among multiple applications yet internally controls smart things' sharing to resolve resource conflicts and provides a consolidation framework for efficient utilization of the shared smart things. A lease-based sharing control is employed with two tenant switch schemes which are analyzed. All these features are hidden from application context, thus reducing complexities in developing applications. From implementation and evaluations with workload applications, we show that the ECO middleware provides efficient sharing controls and access controls with negligible virtualization overhead.

In this paper, we propose a novel semi-directional flooding (SDF) algorithm for on-demand routing in IEEE 802.15.4-based low-rate wireless mesh networks (LRWMNs). The novelty of our work is that the proposed routing algorithm enables route discovery request (RREQ) packets to be semi-directionally flooded, with respect to a source-destination pair, in a fully distributed manner without either physical or virtual location information. The idea behind this is to exploit the hierarchical addressing structure that allows each router node to compute logical tree distances between source-destination pairs, which approximately mirrors relative hop distance between the pairs, without message exchanges. By exploiting tree distances with a given target address, the SDF algorithm enables RREQ packets to be flooded over a small area, directed towards the destination. We also apply SDF to a lightweight on-demand routing algorithm like AODVjr, and propose two techniques of adaptive timers and route repair that reduces path setup delays and overheads during route rediscovery, respectively. We carry out extensive simulations and quantitatively show that SDF significantly reduces flooding overhead of network-wide flooding (NWF). We compare SDF-based AODVjr with both NWF-based AODVjr and enhanced hierarchical routing protocol (EHRP) for on demand routing and demonstrate that SDF-based AODVjr drastically reduces route discovery overhead by up to about 95 percent while still providing comparable or better performance than NWF-based AODVjr and EHRP.

An increasing number of recent experimental works have demonstrated that the supposedly secure channels in the Internet are prone to privacy breaking under many respects, due to packet traffic features leaking information on the user activity and traffic content. We aim at understanding if and how complex it is to obfuscate the information leaked by packet traffic features, namely packet lengths, directions, and times: we call this technique traffic masking. We define a security model that points out what the ideal target of masking is, and then define the optimized traffic masking algorithm that removes any leaking (full masking). Further, we investigate the tradeoff between traffic privacy protection and masking cost, namely required amount of overhead and realization complexity/feasibility. Numerical results are based on measured Internet traffic traces. Major findings are that: 1) optimized full masking achieves similar overhead values with padding only and in case fragmentation is allowed, and 2) if practical realizability is accounted for, optimized statistical masking attains only moderately better overhead than simple fixed pattern masking does, while still leaking correlation information that can be exploited by the adversary.

The ZigBee tree routing is widely used in many resource-limited devices and applications, since it does not require any routing table and route discovery overhead to send a packet to the destination. However, the ZigBee tree routing has the fundamental limitation that a packet follows the tree topology; thus, it cannot provide the optimal routing path. In this paper, we propose the shortcut tree routing (STR) protocol that provides the near optimal routing path as well as maintains the advantages of the ZigBee tree routing such as no route discovery overhead and low memory consumption. The main idea of the shortcut tree routing is to calculate remaining hops from an arbitrary source to the destination using the hierarchical addressing scheme in ZigBee, and each source or intermediate node forwards a packet to the neighbor node with the smallest remaining hops in its neighbor table. The shortcut tree routing is fully distributed and compatible with ZigBee standard in that it only utilizes addressing scheme and neighbor table without any changes of the specification. The mathematical analysis proves that the 1-hop neighbor information improves overall network performances by providing an efficient routing path and distributing the traffic load concentrated on the tree links. In the performance evaluation, we show that the shortcut tree routing achieves the comparable performance to AODV with limited overhead of neighbor table maintenance as well as overwhelms the ZigBee tree routing in all the network conditions such as network density, network configurations, traffic type, and the network traffic.

Tree based hierarchical routing is widely used in 6LoWPAN due to advantages of low control overhead and low memory resources. However, it generates a triangular detour path considering point-to-point (P2P) traffic. Reactive routing provides a reasonable P2P path by conducting flooding-based route discovery, but the flooding increases packet interference due to huge control overhead. Multipath routing can improve the reliability by preparing for the alternative path. Nevertheless, it needs an extra table for storing the alternative path and it is not appropriate to diverse traffic patterns. In this paper, we propose a traffic-aware multipath routing (TAMR). By managing an overlaid topology comprised of two different topologies without additional overhead, TAMR can dynamically choose a proper routing protocol according to traffic patterns and it can improve network reliability. Besides, TAMR is suitable for 6LoWPAN, because it does not need to store global routing state and generates low control overhead. In order to evaluate the performance, we have conducted the simulation by comparing with representative routing protocols in 6LoWPAN. The results show the overall performance of TAMR surpasses others in terms of hop count, packet delivery ratio, number of control packets, and memory usage.

One of the important challenges in the Internet of Things (IoT) is how to acquire the physical context of things. IP-based wireless sensor networks (IP-WSNs) could be a promising approach to collecting the physical context of things and to integrating WSNs to the Internet. However, realizing IP-WSNs in IoT exposes two major challenges. One is how to embed the Internet Protocol (IP) in resource-constrained sensor nodes. The other is how to achieve real-world deployment of WSNs and its integration with the Internet on the fly and on the cheap. In this paper, we present the SNAIL (Sensor Networks for All-IP World) project and introduce a new type of IP-WSN gateway, which supports dual wireless access points for WiFi and IP-WSN, enabling deployment of SNAIL nodes in an easy and rapid manner as for the solution. To show the proof-of-concept, we implement a new SNAIL platform from tiny sensor nodes to a gateway.

Wi-Fi interface is one of the predominant energy consumers in Wi-Fi stations. Despite many researches on Wi-Fi energy management, energy wastage of Wi-Fi stations resulting from network contention among multiple access points(APs) has not been widely investigated. In this paper, we analyze the network contentions occur among multiple APs, and show that Wi-Fi power save mode performance could be severely affected by network contentions. In order to overcome the network contention problem, we propose a scheduling policy, Tame, to assign access points into different sub clusters, in each of which none of the access points have network contentions and data can be transmitted simultaneously without collision. Access points properly control Wi-Fi stations to switch states between sleep and active to avoid stations' packet receiving time overlapping, while the energy wastage from network contentions is mitigated and network performance is guaranteed. We simulate Tame in Qualnet and conclude that Tame, compared with the related work Sleep Well, enhances the average throughput of Wi-Fi stations by an average of 13% for CBR traffic. Simultaneously, the corresponding Wi-Fi interface energy is consumed more efficiently.

Recently, a pointer forwarding scheme (PFS) was proposed to reduce location update overhead in wireless mesh networks. Using the PFS, location update is replaced with a simple forwarding pointer setup between two neighboring MRs until the forwarding chain K is less than or equal to the configurable parameter Kmaxfor each MC. However, in PFS, if the two MRs are not one hop neighbors, the PFS fails to set up a forwarding pointer, and a location update event must be triggered, increasing location update overhead. To improve PFS, we present a novel location update scheme called a multi-hop pointer forwarding scheme (MPFS). The MPFS allows forwarding pointers to be constructed over multi-hop at once even if MRs are not one hop neighbor with each other. The key to achieving this lies in the logical tree distance constructed during network formation. The tree distance is used to relay forwarding pointer packets over multi-hop links without additional control overhead and to estimate hop distance between two MRs. By doing so, the MPFS improves the probability of success in forwarding pointer setup while ensuring K ≤ Kmax, resulting in lowering the location update overhead. To evaluate our scheme we implement both the PFS and the MPFS in ns-2 and compare them. As a result, we show that the MPFS significantly reduces the number of location update events, resulting in reduction of location update delay and signaling overhead, and packet losses during location updates.

Tree-based routing protocols in low-rate wireless mesh networks usually have the detour problem in return for the no route discovery overhead. In this paper, we propose a novel algorithm, named Incremental Path Reduction (IPR), which incrementally shortens inefficient detoured path as more data packets are delivered. In IPR, data packets are delivered along the tree route in use by using 1-hop broadcast, enabling neighbor nodes to learn about the data packets' hop count. Using the hop counts, each node estimates their residual hop count to destination. As a result, each forwarder selects next hop node that has small residual hop count. In this way, IPR incrementally shortens the detoured route as more data packets are delivered. To verify our algorithm, we applied IPR to the representative tree routing protocols, and evaluated the path stretch and packet delivery ratio as well as control packet overhead. Simulation results show that IPR significantly enhances the overall routing metrics for any types of tree-based routing protocols.

In this paper, we propose a novel on-demand routing protocol for IEEE 802.15.4-based low rate wireless mesh networks (LRWMNs). The novelty of our work is that the proposed routing algorithms enable route discovery packets (RREQs) to be semi-directionally flooded with respect to a source-destination pair in a distributed manner without either physical or virtual location systems. Instead, we use the logical tree distance derived from the hierarchical addressing structure. The idea behind this is that nodes with longer tree distance to the destination than that of the source-destination pair are not involved in flooding RREQs. To evaluate the algorithms, we apply our algorithms into AODVjr and carry out extensive simulations while comparing the algorithms with AODVjr using network-wide flooding (NWF). Results show that the proposed algorithms drastically reduce RREQ overhead while providing comparable or better performance than NWF in AODVjr.

To realize the Internet of Things (IoT), an important step would be to allow things and information about them to be accessible in an easy way and a platform-independent manner. As World Wide Web (WWW, Web) shows explosive growth over the last decade, the web is the most popular and familiar user interface to acquire knowledge about everyday life. In this respect, web browsing through standard protocols like HTTP over TCP could be a promising approach to access things and to collect things' information. In future, IP-based wireless sensor networks (IP-WSNs) are expected to be integrated into the IoT. However, due to the characteristics of IP-WSN such as resource limited and low data-rate, the challenges that we confronted are 1) how to make clients access IP-WSNs as if they use regular web browsers with rich presentation and acceptable response time and 2) how to embed the standard web in such resource-constrained sensor nodes. In this paper, to address these challenges, we introduce a new browsing architecture, which enables the exploration of the IP-WSNs through a conventional web browser and the navigation with rich user interfaces. We also design lightweight web protocols, lwHTTP and lwTCP, with header compression in order for HTTP and TCP to run on the resource-constrained IP-WSNs. To show the feasibility, we implement the proposed architecture in SNAIL (Sensor Networks for an All-IP world), our IP-WSN platform, and we evaluate the performance of proposed browsing architecture.

Service gateways (SGs) are a promising approach to integrate wireless sensor and actuator networks (SANETs) with pervasive infrastructure over Internet by encapsulating distributed physical sensor and actuators into regular objects. Typically, SGs for SANETs are assumed to know operational environment in advance at design time with limited awareness of operational SANET conditions and, in the meanwhile, provide a single particular form of access without knowledge of application activities. As a SANET evolves, end users will frequently add sensor and actuator nodes (SANs) for additional services, remove defective or obsolescent SANs, and upgrade SANs in deployed SANETs. Therefore, traditional SGs are infeasible to integrate the future evolvable SANET (ESANET) with the pervasive infrastructure. In this paper, we introduce the reflective service gateway (RSG) architecture combined with ESANET management functions. RSG enables heterogeneous middleware systems to concurrently access ESANETs. In addition, by reflection mechanism where network management functions are explicitly reified and integrated into RSG so that it can learn the changing ESANET runtime environment, RSG self-adapts to ESANET dynamics and enables ESANETs to customize its activities according to application services involved. To validate the RSG, we have implemented the RSG and conducted empirical performance measurements with home sensor and actuator applications using ZigBee.

Mobility management is one of the most important research issues in 6LoWPAN, which is a standardizing IP-based Wireless Sensor Networks(IP-WSN) protocol. Since the IP-WSN application domain is expanded to real-time applications such as healthcare and surveillance systems, a fast and seamless handover becomes an important criterion for mobility support in 6LoWPAN. Unfortunately, since existing mobility protocols for 6LoWPAN have not solved how to reduce handover delay, we propose a new fast and seamless mobility protocol to support inter-PAN handover in 6LoWPAN, named inter-MARIO. In our protocol, a partner node, which serves as an access point for a mobile node, preconfigures the future handover of the mobile node by sending mobile node's information to candidate neighbor PANs and providing neighbor PAN information like channel information to the mobile node. Also, the preconfigured information enables the foreign agent to send a surrogate binding update message to a home agent instead of the mobile node. By the preconfiguration and surrogate binding update, inter-MARIO decreases channel scan delay and binding message exchange delay, which are elements of handover delay. Additionally, we define a compression method for binding messages, which achieves more compression than existing methods, by reducing redundant fields. We compare signaling cost and binding message exchange delay with existing mobility protocols analytically and we evaluate handover delay by simulation. Analysis and simulation results indicate that our approach has promising fast, seamless, and lightweight properties.

Service-oriented computing which provides flexible composition of various applications using multiple reusable services has getting more attractive. We propose a service oriented wireless sensor networks toolbox, which encapsulates complexities of sensor networks and enables simple service compositions using an intuitive GUI. We utilize sensor networks as a collection of services that are discovered and coordinated by users. Service metadata which are self-describing service capabilities and interfaces are defined and exposed via our service metadata repositories. A service oriented sensor network toolbox consisting of sensor networks, an intuitive GUI application that retrieves metadata for discovered services and helps users to composite various roles are presented.

Established service discovery protocols such as UPnP allow control points to find devices and services and to retrieve descriptions about them in order to learn all about the device and services. However, general device-control point approaches are not suitable for wireless sensor networks due to se

Recently, according to various application field of robot, the scalability and the flexibility of robot are essential requirements. To satisfy these requirements, the robot is divided into the module or a hardware component unit, where the function such as vision, control, sensing are executed. The robot is composed of the set of various modules. So, it could include heterogeneous O/S and network interfaces. A middleware is necessary for supporting these operating environments in robot. It provides services which are required commonly in modules. In this paper, we propose and implemented middleware for robot called the KOMoR (Korea object-oriented middleware of Robot). The KOMoR is lightweight middleware supporting characteristic of both communication middleware and distributed middleware. The KOMoR provides a various operating system and heterogeneous network interface for the flexibility and the scalability, QoS capabilities, a resource management, a fault tolerance, a routing capability for multiple path.

IEEE 802.15.4-based ZigBee routing is based on ad hoc on-demand distance vector (AODV) so that ZigBee states the possibility of building mesh network with data dissemination manner similar to ad hoc network. Although ZigBee focuses on low data rate, routing overhead for route discovery may interfere with network traffic. Since it affects network performances such as end-to-end delay and packet delivery ratio in dense networks, it is necessary that routing protocols improving the scalability are designed. In this paper, we present a mesh routing protocol for ZigBee, called ZigBee cluster label (ZiCL). As ZiCL divides the ZigBee network into one or more logical clusters and encourages nodes to share routing information, it reduces numerical potential route discoveries. Therefore, it shows that network performances such end-to-end delay and packet delivery ratio are significantly improved, especially in dense network. Simulation results demonstrate that ZiCL enhances scalability

For signature verification, there can be a large number of useful features including pen-speed, pen-pressure, etc. However, all these features may not be useful or even be harmful for a given person when not enough number of training samples are allowed. Namely, for an optimal verification, each person requires a different subset of all the possible features. Finding an optimal subset for an individual needs too much combinatorial efforts. Instead, we propose an approach using all the same features for every person by assigning a different weight to each feature according to the nature of the person's signature.