Jiuyang Tang

P2P-based multidimensional indexing methods: A survey

P2P-based multidimensional index (MI) is a hotspot which absorbs many researchers to dedicate them into. However, no summarization or review on this technology has been made at present. To the best of our knowledge, this is the first work on reviewing P2P-based MI. This paper innovatively adopts visualization technique to show the research groups and then analyzes investigating style of research groups. Based on evolution of P2P-based MI inheriting from centralized MI and P2P, we divide P2P-based MI methods into 4 categories: extending centralized MI, extending P2P, combining centralized MI and P2P, and miscellaneous. For each category, the paper selects classical techniques and describes them in detail. This is the first time of doing the classification job over massive related works. Finally, load balancing and update strategies are described and discussed for they are important factors related to performance. We believe many researchers will get benefits from our work for further studies.

Divisional perimeter routing for GPSR based on left and right hand rules

The routing void emerges in wireless sensor networks, when the density of sensor node is low or special geography factors appear. To handle the routing void problem, many methods were proposed under different routing protocol, while most of them are complex or demanding for sensor nodes. After analyzing the shortages of former methods, this paper improved the perimeter forwarding strategy in Greedy Perimeter Stateless Routing (GPSR), and proposed a divisional perimeter routing based on right and left hand rules. The results of simulation indicate that, compared to GPSR, the improved protocol can increase the packet delivery success rate, shorten the routing path, and advance the real-time capability of the greedy geographic routing protocol.

An Adaptive Grid Division algorithm for target location in wireless sensor networks

Target location and tracking have been an important fundamental technology in wireless sensor networks. Distance irrelevant location algorithm is one of the most popular methods in target location application. This kind of algorithm mostly locates the target by getting the target approximate area and calculating its centroid. Because of the large calculating quantity and bad real-time capability of the traditional methods in solving the centroid of irregular approximate area, a universal Adaptive grId Division (AID) method was proposed. By grid dividing and scanning towards the WSNs deploying area, a target approximate area was got and the location precision was adaptively adjusted according to the grid granularity. The results of experiment show that AID has a higher real-time capability under similar precision with traditional methods.

A Prediction-based Energy-conserving Approximate Storage and Query Processing Schema in Object-Tracking Sensor Networks

Energy efficiency is one of the most critical issues in the design of wireless sensor networks. In object-tracking sensor networks, the data storage and query processing should be energy-conserving by decrease the message complexity. In this paper, by figuring out the shortcomings of EASE, a Prediction-based Energy-conserving Approximate StoragE (P-EASE) is proposed, which reduce the query error of EASE by changing its approximate area and adopting predicting model without increasing the cost. The theoretical analyses illuminate the correctness and efficiency of the P-EASE. And simulation experiments are conducted under semi-random walk and random waypoint mobility which compares the query error, message complexity, total energy consuming and hotspot energy consuming to validate that P-EASE is more energy-conserving than EASE and has less query error as well.

Occupancy-aided energy disaggregation

Energy disaggregation helps to identify major energy guzzlers in the house without introducing extra metering cost. It motivates users to take proper actions for energy saving and facilitates demand response programs. To reduce the computational complexity of pure energy disaggregation, we propose an occupancy-aided energy disaggregation (OAED) approach in this paper. Specifically, we make use of the occupancy information (whether or not the house/room is occupied by users) and classify the whole time interval into occupied and unoccupied periods. In unoccupied periods, we perform lightweight energy approximation; in occupied periods, we apply energy disaggregation with existing methods. Real-world experiments are conducted in an apartment hosting typical household appliances. Comparing with energy disaggregation without considering occupancy information, our occupancy-aided approach can significantly reduce the computational overhead while ensuring the accuracy of energy disaggregation.

Community core evolution in mobile social networks.

Community detection in social networks attracts a lot of attention in the recent years. Existing methods always depict the relationship of two nodes using the temporary connection. However, these temporary connections cannot be fully recognized as the real relationships when the history connections among nodes are considered. For example, a casual visit in Facebook cannot be seen as an establishment of friendship. Hence, our question is the following: how to cluster the real friends in mobile social networks? In this paper, we study the problem of detecting the stable community core in mobile social networks. The cumulative stable contact is proposed to depict the relationship among nodes. The whole process is divided into timestamps. Nodes and their connections can be added or removed at each timestamp, and historical contacts are considered when detecting the community core. Also, community cores can be tracked through the incremental computing, which can help to recognize the evolving of community structure. Empirical studies on real-world social networks demonstrate that our proposed method can effectively detect stable community cores in mobile social networks.

Core-based community evolution in mobile social networks

Community evolution in social networks attracts a lot of attention in recent years. Existing methods always depict the relationship of two nodes using the temporary connection. However, these temporary connections cannot be fully recognized as the real relationships when the history connections among nodes are considered. Cumulative stable contacts are proposed to depict the correlation among nodes. The whole process is divided into timestamps. At each timestamp, the community cores will be detected due to the variation of nodes and links firstly. Then, all nodes will be divided into a few of communities due to the community cores. Meanwhile, communities can be tracked through the incremental computing, which can help to recognize the evolving of community structure. Empirical studies on real-world social networks demonstrate that our proposed method can effectively detect stable community in mobile social networks.

UFO: A United Framework for Target Localization in Wireless Sensor Networks

Recently, various range-free based target localization applications and systems are developed in Wireless Sensor Networks. Nevertheless, few of them can be reused or grafted by others, which has led to serious waste. In this paper, a Unified Framework for target lOcalization (UFO) is proposed and an adaptive grids dividing algorithm is addressed within the framework. Based on the common ground of current typical range-free localization methods, UFO is constructed by four major modules to achieve candidate area acquisition and target location determination: sensor deployment and signal process module, candidate area acquisition module, target localization module and parameter setting module. Not only can UFO construct a localization framework quickly, the computing complexity of loaded localization methods is expected to be decreased by bringing in adaptive grids dividing. In our simulations, the UFO assembled with schemes from node sequences based localization method is tested, and the results from our framework are compared with the original methods. Performance evaluation shows us both UFO and original schemes perform well at localizing accuracy, while the former has a big advantage at real-time capacity.

Target Tracking with Pairwise Uncertainty in Wireless Sensor Networks: Qualitatively and Quantitatively

Ubiquitous uncertainty has great impacts on target tracking accuracy in wireless sensor networks (WSNs). This paper focuses on the uncertainty of pair wise sensor nodes, and analyzes it on unreliable samplings of sensors as well as the uncertain relationship between location points and expected sensing results, qualitatively and quantitatively. The sampling vector, which reflects sensing information, is constructed by multiple grouping samplings, while the tracking area can be divided into patches which are assigned to specific signature vectors. Two target tracking strategies are proposed by matching the two vectors, from the qualitative and quantitative aspect, respectively. Results show that both methods can achieve high tracking reliability and satisfy tracking accuracy and robustness for the uncertainty caused by in-the-field factors.

A Prediction-based Energy-conserving Approximate Storage and query processing schema in object-tracking sensor networks

Energy efficiency is one of the most critical issues in the design of wireless sensor networks. In object-tracking sensor networks, the data storage and query processing should be energy-conserving by decrease the message complexity. In this paper, by figuring out the shortcomings of EASE, a Prediction-based Energy-conserving Approximate StoragE (P-EASE) is proposed, which reduce the query error of EASE by changing its approximate area and adopting predicting model without increasing the cost. The theoretical analyses illuminate the correctness and efficiency of the P-EASE. And simulation experiments are conducted under semi-random walk and random waypoint mobility which compares the query error, message complexity, total energy consuming and hotspot energy consuming to validate that P-EASE is more energy-conserving than EASE and has less query error as well.