Online Social Network is booming with the development of the hardware and the popularity of the Internet in recent years. Users can invite friends through other users and become friends after consent of each other to share their living information. Here, crowdsensing is adopted by using Bluetooth Low Energy attached on mobile phones to collect proximity sensing information. The online social network data from users is extracted, such as expanding co-friend relationship, establishing a relationship chain through the interaction between friends. In this paper, a strategy is proposed to explore the co-friend's affinity incurring the relationship with common preferences for potential users. The friend recommended weighting strategy is derived to make a recommendation of friends among virtual and real communities. Moreover, the system is designed and implemented to realize in the actual environment and to analyze the data to prove the strategy which helps to find potential friends among users.

This paper is to explore how to enhance the benefits of mobile sink data collection in the wireless sensor network (WSN). Mobile sink moves along a scheduled route to collect data. A shorten traveling salesman problem (TSP) route is explored in this study. Along the resultant route, energy efficiency is achieved for the mobile sink to collect data in a round. Finally, experimental results show that the total energy consumption of mobile sink consumed including the sensor communication and the sink movement distances compared to the existing work can be minimized.

In this paper, we propose an adaptive mechanism of trap coverage with a robust area coverage model, which employs mobile sensors for applications in mobile sensor networks (MSNs) and in the Internet of Things (IoT). Many promising applications including the target tracking and mobile sensing can be reasonably realized and improved after incorporating the characteristics of trap coverage mechanism on the basis of adaptively adjusting the trap size and sensor mobility. The trap evidently exists throughout the deployment of sensors in wireless sensor networks, in which the target has predictably vanished or application service remains undetected. The properties of the trap in the trap coverage mechanism are contrary to the purpose of target tracking and services detection. This creates a serious problem for target tracking and services detection in MSNs. This paper proposes a robust mechanism of trap coverage involving the use of mobile sensors in target tracking and services detection for applications in MSNs. The experimental results revealed that the proposed method efficiently reduces the target-missing time and the total number of unavailable sensors, and also enhances the maintenance of trap coverage through the movement of mobile sensors in MSNs based on the simulation results and analysis. Performance comparison is conducted by adjusting the total amount of sensors in an adaptively trap coverage. The novel mechanism makes MSNs a much more flexible and provides a cost-effective solution in IoT than static sensor networks.

Most of the recent research on Object Tracking Sensor Networks has focused on collecting all data from the entire sensor network and placing it into the sink, which delivers the predicted locations to the corresponding nodes in order to predict an object's movement. This collection method affects the freshness of the data and creates latency in predicting movement patterns. In addition, due to the great amount of packets being sent and received, the sensor nodes' energy is quickly exhausted. Although this data collection method might result in a higher accuracy rate for prediction, it does not extend the lifetime of the sensor network. In this paper, a distributed method is proposed in using the network structure of convex polygons. These polygons are cooperated to find the trajectories of an object and then these trajectories are used to predict objects' movement. The proposed method, based on Trajectory-tree Construction, should reduce both the storage space of collected trajectories and the time spent on trajectory prediction analysis. Simulations show that the proposed method can reduce the energy consumption of the nodes and can extend the lifetime of the network in efficient.

Mobile service systems offer users useful information ubiquitously via mobile devices. Based on changeable user movement behavior patterns (UMBPs), mobile service systems have the capability of effectively mining a special request from abundant data. In this paper, UMBPs are studied in terms of the problem of mining matching mobile access patterns based on joining the following four kinds of characteristics,U,L,T, andS, whereUis the mobile user,Lis the movement location,Tis the dwell time in the timestamp, andSis the service request. By introducing standard graph-matching algorithms along with the primitives of a database management system, which comprises grouping, sorting, and joining, these joint operations are defined. Moreover, by mining the associated structure via maximum weight bipartite graph matching, a prediction mechanism, based on the model of UMBPs, is utilized to find strong relationships amongU,L,T, andS. In addition, a PC-based experimental evaluation under various simulation conditions, using synthetically generated data, is introduced. Finally, performance studies are conducted to show that, in terms of execution efficiency and scalability, the proposed procedures produced excellent performance results.

According to the advancement of the medical science in recent years, Taiwan has come into the aging society. Due to the increase of elderly people, the requirement of wheelchair is increasing gradually. Therefore, we develop a system to increase the security of the wheelchair. This research is to configure sensors in a wheelchair for measuring the position and the operation of wheelchair users. If the sitting posture of the wheelchair user is bad or the wheelchair user has the danger, the system will show a warning message to tell the caregiver. According to the position shown, the caregiver can go to the area to help the wheelchair user directly. In addition, a care system running on smart phone is developed, so that the caregiver can take care for wheelchair users anywhere and anytime. Finally, a novel data mining system is designed and implemented for analyzing the wheelchair operations for wheelchair users. It can find out the incorrect or unfitting sitting posture of the wheelchair user for long periods, or environmental problems to provide more useful information for the caregiver. The caregiver can take care for the wheelchair user by this integrated system.

This paper is to study the tracking of mobile objects and associated coverage problems in visual sensor networks. When sensors equipped with cameras are randomly deployed in a monitoring environment, many cameras are involved in covering the same mobile object. Images of the object may be captured by different camera nodes in different orientations simultaneously, and the captured images are then sent back to a base station or server. However, achieving characteristic point coverage of objects invariably involves a great deal of redundant image data consuming the transmission energy of the visual sensor network. One approach is proposed to overcome this problem. The minimum number of camera nodes required for set coverage can be determined by predicting the direction and speed of the mobile object. The simulation results show that this protocol reduces transmission cost while preserving the maximum coverage range of mobile objects.

A novel data-collecting algorithm using a mobile robot to acquire sensed data from a wireless sensor network (WSN) that possesses partitioned/islanded WSNs is proposed in this paper. This algorithm permits the improvement of data-collecting performance by the base station by identifying the locations of partitioned/islanded WSNs and navigating a mobile robot to the desired location. To identify the locations of the partitioned/islanded WSNs, two control approaches, a global- and local-based approach, are proposed. Accordingly, the navigation strategy of the robot can be scheduled based on time and location using three scheduling strategies: time based, location based, and dynamic moving based. With these strategies, the mobile robot can collect the sensed data from the partitioned/islanded WSNs. Therefore, the efficiency of sensed data collected by the base station in partitioned/islanded WSNs is improved. Through simulation under the environment of an ns-2 simulator, the results, from various aspects, show that the collecting strategies proposed can dramatically improve sensed data-collecting performance in partitioned or islanded WSNs.

This paper is to study the object coverage problem in visual sensor networks. When sensors equipped camera with rotating capability in the monitoring environment are deployed randomly, the images of target object with circle shape may be captured by different camera nodes in different orientations at the same time. In order to achieve the full coverage of an object, there might be lots of redundant image data to consume the transmission energy in visual sensor networks. An approach is proposed to reduce the cover set of camera nodes by rotating cameras of sensors. Such a set can cover the entire object using as few sensors as possible. In addition, a mapping is proposed for find out the coverage problem for target objects with convex polygon shape. The simulation results show that our approach can reduce the number of sensors while preserving the maximum coverage range of object.

A query-based wireless sensor network may generate frequent queries to a specific node, and then a hotspot problem emerges and fast consumes the energy of the specific node. A hotspot also influences the traffic flow near its neighboring area. To solve the hotspot problem, this paper presents two agents setting algorithms, distance-based agent selection (DAS) and greedy-based agent selection (GAS) to mitigate the traffic flow near hotspot. A sensor node, called limb node, is attached an agent that is responsible for aggregating query packets to hotspot and replying the interested data to the corresponding requestors. By assigning agents, DAS and GAS both mitigate the hotspot phenomenon. This paper investigates and simulates the proposed algorithms in different environment conditions. From simulation results, both DAS and GAS can mitigate the traffic rates of hotspot up to 60%.

In recent years, there has been a dramatic proliferation of research concerned with the ubiquitous learning (u-learning). The u-learning systems have to be continuously evaluated and improved for ensuring the system reliability. Therefore, this work based on meaningful learning aspect to propose a u-learning evaluation model. The model blends features of u-learning and meaningful learning to construct a hierarchy decision model. According to the hierarchy structure, domain experts can develop AHP-based questionnaire survey to collect learnerspsila opinions. Following that, system developers can realize the relative strength and weakness of the u-learning system from a meaningful learning viewpoint by analyzing the surveyed data, and they can further to improve and refine current u-learning systems accordingly. Consequently, existing u-learning systems can be revalidated by our evaluation model, and then based on the produced suggestions to improve toward the meaningful learning.

A time division multiple access (TDMA) scheduling technique, which solves collision problem and collects a complete data efficiently, is adopted to assign communication mission into the available time slots. This paper proposes a novel conflict-free convergecast scheduling method to minimize the collecting time in a wireless sensor network. The proposed method first constructs a tree structure in the sensor network and utilizes the tree information to schedule a conflict-free convergecast. The simulated results show that the proposed method can diminish the required timeslots efficiently and achieve a conflict-free convergecast. The contributions of the work are to accelerate the speed of data collection, collect the complete data from the sensor network, reduce the energy consumption of sensors and prolong the network lifetime.

In this paper, we propose a framework for supporting context-aware environments in mobile ad hoc networks (MANETs). A virtual overlay network and two novel approaches in this framework are addressed to significantly improve the efficiency of data delivery in MANETs. The surrounding context of mobile nodes is used to determine which scheme, push-based or pull-based approaches, is adopted. When a real-time event happened in a node, push-based approach is adopted to disseminate urgent messages to its neighboring nodes. On the contrary, pull-based approach is adopted by building a virtual backbone, namely segment-tree, for seeking for more contextual information. Finally, the simulation is conducted to illustrate the performance achievements that our methods outperform the existing publish/subscribe approach based on AODV routing protocol.

This work proposes efficient data aggregation algorithms based on a virtual grid for range query in wireless sensor networks. A sensor node is selected to be a manager, called head, in each grid. The responsibilities of head are to detect generated event, announce to all other heads, and respond to a moving user. A user obtains the occurred event information from its grid head. If a user is interested in an event, it issues a query to acquire data from a specified regular-shape or spreading irregular-shape ranges. Users can oversee the spreading event via querying the incurred irregular-shape range. In addition, this work proposes efficient approaches to gather data from sensor networks while voids exist. Finally, experimental results show that the proposed approaches are more energy-efficiency than the existing approach.

With the rapid growth of information stored in worldwide Web servers, searching and capturing data on Internet become a common behavior for us. In order to increase the availability as well as avoid the overload of the single Web server, using Web server cluster is one of main solutions. We take the contents/services types into consideration for balancing workload of Web servers. For different contents requested by clients, the workload for each Web server would be different. Hereby, we focus on proposing a new load balance algorithm for supporting fast response and load balancing for scalable Web server clusters. In addition, we demonstrate our simulation experiments to show that our proposed approach, as compared to existing approaches. This proposed approach can be applied to various applications, especially for resolving e-learning systems with needs of a great deal of requests with different service types simultaneously issued by worldwide users.

A mobile ad hoc network (MANET) is characterized by multihop wireless links in the absence of cellular infrastructure and frequent host mobility. In this paper, a new on-demand routing protocol is proposed, named on-demand routing protocol with backtracking (ORB), for multihop mobile ad hoc networks. Suppose a source host wants to deliver a message to a destination in a MANET. First, the source host issues a request to search the destination. When a node receives the request packet, it gets a hop count value which can point the way to the source. This node broadcasts the request packet to its neighbors. When a destination receives this request, it issues a reply back to the source. We proposed a scoped flooding approach which is applied to reply information to the source. This approach will find out multipath from a source to a destination Every node in the MANET maintains some information for this source-destination pair in its own route table. Each node in the forwarding route uses this information to select a group of nodes, named checkpoint nodes, which may have multipath maintained to that destination. The checkpoint node characteristic is such that a route can be recovered instantly without the need for extra control packets. When a delivering node is aware that the forwarding route is broken, it transmits an error packet back to the source along the return path. When a checkpoint receives the error packet that is backtracked to the source, it has backup paths to recover the broken route. This new route can be used immediately The main advantage of our ORB is to reduce the flooding search time and cost when a route has been broken. We show that the proposed scheme outperforms the on-demand routing protocol existing in mobile ad hoc networks.

The star graph interconnection network has been recognized as an attractive alternative to the popular hypercube network. In this paper we first address a dual-Hamiltonian-path-based (DHPB) routing model with two virtual channels based on two Hamiltonian paths and a network partitioning strategy for wormhole-routed star graph networks. Then, we propose three efficient multicast routing schemes on basis of such a model. The proposed schemes are network-selection-based (NSB), heuristic-network-selection-based (HNSB), and two-phase heuristic-network-selection-based (TP-HNSB) dual-path routing. All of the three proposed schemes are deadlock-free. Finally, experimental results are given to show our proposed three routing schemes outperform the unicast-based, the Hamiltonian-path, and the single-Hamiltonian-path-based (SHPB) dual-path routing schemes significantly.

In this paper, we propose four efficient multicast routing schemes in wormhole-routed star networks with multidestination routing capability. All of the four proposed schemes are path-based and deadlock-free. The first scheme, dual-path routing, sends the message in parallel through two independent paths. The second one, shortcut-node-based datapath routing, is similar to dual-path routing except that the routing tries to find a shortcut node to route the message as soon as possible to reduce the length of transmission path. The third one, multipath routing, is a multiple dual-path routing strategy that includes source-to-relay and relay-to-destination phases. The last scheme, proximity grouping routing, is similar to multipath routing except that in the partitioning step of source and destination nodes the relation of spatial locality of nodes is also taken into account to reduce the length of transmission paths. Finally, the experimental results are given to show that the performance based on unicast-based and traditional Hamiltonian-path routing schemes can be improved significantly by the four proposed routing schemes respectively.

Efficiently solving the personalized broadcast problem in an interconnection network typically relies on finding an appropriate spanning tree in the network. In this paper, we show how to construct in a complete star graph an asymptotically balanced spanning tree, and in an incomplete star graph a near-balanced spanning tree. In both cases, the tree is shown to have the minimum height. In the literature, this problem has only been considered for the complete star graph, and the constructed tree is about 4/3 times taller than the one proposed in this paper.

Based on the V.E. Mendia and D. Sarkar's algorithm (1992), we propose an optimal and nonredundant distributed broadcasting algorithm in star graphs. For an n-dimensional star graph, our algorithm takes O(n log/sub 2/ n) time and guarantees that all nodes in the star graph receive the message exactly once. Moreover, broadcasting m packets in a pipeline fashion takes O(m log/sub 2/ n+n log/sub 2/ n) time due to the nonredundant property of our broadcasting algorithm.>

In distributed memory multicomputers, local memory accesses are much faster than those involving interprocessor communication. For the sake of reducing or even eliminating the interprocessor communication, the array elements in programs must be carefully distributed to local memory of processors for parallel execution. We devote our efforts to the techniques of allocating array elements of nested loops onto multicomputers in a communication-free fashion for parallelizing compilers. We first analyze the pattern of references among all arrays referenced by a nested loop, and then partition the iteration space into blocks without interblock communication. The arrays can be partitioned under the communication-free criteria with nonduplicate or duplicate data. Finally, a heuristic method for mapping the partitioned array elements and iterations onto the fixed-size multicomputers under the consideration of load balancing is proposed. Based on these methods, the nested loops can execute without any communication overhead on the distributed memory multicomputers. Moreover, the performance of the strategies with nonduplicate and duplicate data for matrix multiplication is studied.>

In this paper, we devote our efforts to the techniques of allocatiing array elements of nested loops onto multicomputers in a communication-free fashion for parallelizing compilers. The arrays can be partitioned under the communication free criteria with non-duplicate or duplicate data. In addition, the performance of the strategies with non-duplicate and dupli cate array data is compared.