The millimeter wave (mmWave) frequency band is a promising candidate for next generation cellular... more The millimeter wave (mmWave) frequency band is a promising candidate for next generation cellular and wireless networks. To compensate the significantly higher path loss due to the higher frequency, the mmWave band usually uses the beamforming technology. However, this makes the network topology control a great challenge. In this paper, we propose a novel framework for network topology control in mmWave networks, termed Beamforming Oriented tOpology coNtrol (BOON). The objective is to reduce total transmit power of base stations and interference between beams. BOON smartly groups nearby user equipment into clusters, constructs sets from user equipment clusters, and associates user equipment to base stations and beams. We compare BOON with three existing topology control schemes in terms of transmit power, network sum rate, signal to interference and noise ratio, and computation complexity. The results indicate that overall BOON significantly outperforms them. In particular, on average BOON uses only 10%, 32%, and 25% transmit power of other three schemes, respectively, to achieve the same network sum rate.
This work proposes a novel connectivity-based localization algorithm, well suitable for large-sca... more This work proposes a novel connectivity-based localization algorithm, well suitable for large-scale sensor networks with complex shapes and a non-uniform nodal distribution. In contrast to current state-of-the-art connectivity-based localization methods, the proposed algorithm is highly scalable with linear computation and communication costs with respect to the size of the network; and fully distributed where each node only needs the information of its neighbors without cumbersome partitioning and merging process. The algorithm is theoretically guaranteed and numerically stable. Moreover, the algorithm can be readily extended to the localization of networks with a one-hop transmission range distance measurement, and the propagation of the measurement error at one sensor node is limited within a small area of the network around the node. Extensive simulations and comparison with other methods under various representative network settings are carried out, showing the superior performance of the proposed algorithm.
This paper focuses on greedy routing in wireless networks deployed on 2-D and 3-D surfaces. It in... more This paper focuses on greedy routing in wireless networks deployed on 2-D and 3-D surfaces. It introduces a distributed embedding scheme based on the conformal map theory. The proposed scheme identifies the convex hull of each boundary and employs Yamabe flow to compute flat metric under convex hull boundary condition to establish virtual coordinates. Such virtual coordinates are then used for greedy routing. Since the proposed embedding algorithm maps the outer boundary to a convex shape and an interior concave void to a circle-like convex polygon, it effectively eliminates local minimum and attains guaranteed delivery. At the same time, it introduces a small distortion only and consequently achieves a low stretch factor. Our simulations show that its stretch factor is lower than any existing greedy embedding algorithms. Moreover, the proposed scheme is merely based on local connectivity and consumes a small constant storage, thus scaling to arbitrarily large networks.
Proceedings of the 15th ACM international symposium on Mobile ad hoc networking and computing - MobiHoc '14, 2014
We propose a distributed and deterministic routing algorithm with constant storage, communication... more We propose a distributed and deterministic routing algorithm with constant storage, communication and computation overhead, dubbed trace-routing, for strong-connected 3D wireless sensor networks. Its basic idea is to construct a virtual cutting plane that intersects boundary surface to yield a trace, along which a routing path with guaranteed delivery can be established. We prove the correctness of trace-routing under both continuous and discrete settings. We implement the trace-routing algorithm on Crossbow sensors and carry out extensive simulations to evaluate its routing efficiency.
2015 IEEE Conference on Computer Communications (INFOCOM), 2015
Incentive mechanisms for crowdsourcing have been extensively studied under the framework of all-p... more Incentive mechanisms for crowdsourcing have been extensively studied under the framework of all-pay auctions. Along a distinct line, this paper proposes to use Tullock contests as an alternative tool to design incentive mechanisms for crowdsourcing. We are inspired by the conduciveness of Tullock contests to attracting user entry (yet not necessarily a higher revenue) in other domains. In this paper, we explore a new dimension in optimal Tullock contest design, by superseding the contest prize-which is fixed in conventional Tullock contests-with a prize function that is dependent on the (unknown) winner's contribution, in order to maximize the crowdsourcer's utility. We show that this approach leads to attractive practical advantages: (a) it is well-suited for rapid prototyping in fully distributed web agents and smartphone apps; (b) it overcomes the disincentive to participate caused by players' antagonism to an increasing number of rivals. Furthermore, we optimize conventional, fixed-prize Tullock contests to construct the most superior benchmark to compare against our mechanism. Through extensive evaluations, we show that our mechanism significantly outperforms the optimal benchmark, by over three folds on the crowdsourcer's utility cum profit and up to nine folds on the players' social welfare.
2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, 2011
Segmentation decomposes a network with complex and irregular shape into a set of subnetworks, eac... more Segmentation decomposes a network with complex and irregular shape into a set of subnetworks, each under a simple boundary condition without bottlenecks. It has a wide spectrum of applications in routing, coverage, localization, backbone construction and maintenance, and in-network data centric storage and retrieval. To our best knowledge, this is the first work that tackles the segmentation problem in 3D wireless sensor networks. We propose a fully distributed 3D segmentation scheme with mere network connectivity information. Each node on boundary computes its injectivity radius, which reflects the narrowness of the corresponding boundary area and thus is employed to locate the undesired bottlenecks. A cluster of connected boundary nodes with similar smallest injectivity radii form a bottleneck segment. A recursive process is applied to identify a set of such bottlenecks, which together divide the network boundary into segments. An internal non-boundary node simply joins the nearest segment, thus completing the segmentation of the entire 3D sensor network. Our simulations show that the proposed algorithm works efficiently under various sensor network models with different boundary conditions and noise levels, always yielding appropriate segmentation results. We further demonstrate that segmentation can effectively promote the performance of a range of applications in 3D wireless sensor networks. A B (a) Triangulation of a 3D network by [12], [16]. (b) Color-coded injectivity radii. (c) The node with R min (highlighted in green). (d) An expanding segment (after 3 hops). (e) An expanding segment (after 6 hops). (f) The segment after an α-expansion (in green). (g) The result after a β-expansion. (h) The result after all α-and β-expansions. (i) Final segmentation result.
IEEE INFOCOM 2014 - IEEE Conference on Computer Communications, 2014
The majority of current research on sensor network localization focuses on wireless sensor networ... more The majority of current research on sensor network localization focuses on wireless sensor networks deployed on two dimensional (2D) plane or in three dimensional (3D) space, very few on 3D surface. However, many real world applications require large-scale sensor networks deployed on the surface of a complex 3D terrain. Compared with planar and 3D network localizations, surface network localization generates unique and fundamental hardness. In this research, we explore 3D surface network localization with terrain model. A digital terrain model (DTM), available to public with a variable resolution up to one meter, is a 3D representation of a terrain's surface. It is commonly built using remote sensing technology or from land surveying and can be easily converted to a triangular mesh. Given a sensor network deployed on the surface of a 3D terrain with one-hop distance information available, we can extract a triangular mesh from the connectivity graph of the network. The constraint that the sensors must be on the known 3D terrain's surface ensures that the triangular meshes of the network and the DTM of the terrain's surface approximate the same geometric shape and overlap. We propose a fully distributed algorithm to construct a well-aligned mapping between the two triangular meshes. Based on this mapping, each sensor node of the network can easily locate reference grid points from the DTM to calculate its own geographic location. We carry out extensive simulations under various scenarios to evaluate the overall performance of the proposed localization algorithm. We also discuss the possibility of 3D surface network localization with mere connectivity and the results are promising.
With the standardization of IEEE 802.11, there has been an explosive growth of wireless local are... more With the standardization of IEEE 802.11, there has been an explosive growth of wireless local area networks (WLAN). Recently, this cost effective technology is being deployed aggressively for establishing the "cellular Wi-Fi" network, where a large number of access points (APs) are interconnected by wireless links, forming a metro-scale wireless mesh network in order to support ubiquitous Internet access in the urban area. This paper focuses on the optimization of cellular Wi-Fi. In particular, we aim at finding a set of gateways and their optimal placement so as to minimize the network installation costs while maintaining reliability, flexibility, and an acceptable grade of service. We propose two approaches in this research. The first approach is based on integer linear programming (ILP), where we developed a set of linear inequalities according to various constraints and find the solution of the ILP model by using lp-solve. The second approach is an OPEN/CLOSE heuristic, tailored for cellular Wi-Fi, which arrives at a sub-optimal solution. Extensive simulations are carried out for performance evaluation. Simulation results show that the proposed approaches can effectively identify a set of gateways at optimal locations in a cellular Wi-Fi network, resulting in an overall cost reduction of up to 50%.
IEEE Global Telecommunications Conference, 2004. GLOBECOM '04.
In this research, we study the self-maintenance scheduling problem in next generation wireless ne... more In this research, we study the self-maintenance scheduling problem in next generation wireless networks, with the consideration of resource maintenance constraints and resource conflicting constraints. We propose a linear programming (ILP) model and two heuristic algorithms, and evaluate their effectiveness and time complexity via analysis and simulations. Our results show that all of the proposed approaches can effectively schedule the requests within a reasonable period of time, but with different suitable scenarios. The ILP approach is effective when the number of requests is large and yields close-to-optimal results; the RC-Cliques-RM algorithm is suitable at the presence of many constraints; while the RC-RM-Cliques algorithm can scale to large size networks at the expense of reduced accuracy. It is anticipated that the proposed scheduling algorithms will be generally applicable to various mobile wireless networks where self-maintenance is needed.
In this work we develop a distributed boundary detection algorithm, dubbed Coconut, for 3D wirele... more In this work we develop a distributed boundary detection algorithm, dubbed Coconut, for 3D wireless sensor networks. It first constructs a tetrahedral structure to delineate the approximate geometry of the 3D sensor network, producing a set of "sealed" triangular boundary surfaces for separating non-boundary nodes and boundary node candidates. The former are hollowed out immediately while the latter are further refined to yield the final boundary nodes and fine-grained boundary surfaces. The proposed Coconut algorithm offers several salient features. First, it requires connectivity information only, with no need for localization or distance measurement. Second, it does not rely on particular communication models, but only assumes a constant maximum transmission range, which is generally known in practical wireless sensor networks. Third, it is robust to sensor distribution, effectively identifying boundaries in both uniformly and non-uniformly distributed sensor networks. We prove the correctness of the algorithm and quantitatively demonstrate its effectiveness via simulations under various network models.
Proceedings of the fourteenth ACM international symposium on Mobile ad hoc networking and computing - MobiHoc '13, 2013
Location awareness is imperative for a variety of sensing applications and network operations. Al... more Location awareness is imperative for a variety of sensing applications and network operations. Although a diversity of GPS-less and GPS-free solutions have been developed recently for autonomous localization in wireless sensor networks, they primarily target at 2D planar or 3D volumetric settings. There exists unique and fundamental hardness to extend them to 3D surface. The contributions of this work are twofold. First, it proposes a theoretically-proven algorithm for the 3D surface localization problem. Seeing the challenges to localize general 3D surface networks and the solvability of the localization problem on single-value (SV) surface, this work proposes the cut-and-sew algorithm that takes a divide-and-conquer approach by partitioning a general 3D surface network into SV patches, which are localized individually and then merged into a unified coordinates system. The algorithm is optimized by discovering the minimum SV partition, an optimal partition that creates a minimum set of SV patches. Second, it develops practically-viable solutions for real-world sensor network settings where the inputs are often noisy. The proposed algorithm is implemented and evaluated via simulations and experiments in an indoor testbed. The results demonstrate that the proposed cut-and-sew algorithm achieves perfect 100% localization rate and the desired robustness against measurement errors.
Introductioń An overview of distributed data storage and retrieval algorithms in 2D networkś Ch... more Introductioń An overview of distributed data storage and retrieval algorithms in 2D networkś Challenges in 3D networkś Our approach in 3D networkś Simulationś Conclusion and future work
2008 5th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, 2008
In this paper, we propose three algorithms for border landmark selection, namely the Convex Hull-... more In this paper, we propose three algorithms for border landmark selection, namely the Convex Hull-Based (CHB) algorithm, the Center Node Elimination (CNE) algorithm, and the Hierarchy-Structured (HS) algorithm. CHB works perfectly in theory and provides a deep insight into the landmark selection problem. At the same time, it is noticed that CHB is centralized and sensitive to errors in distance estimation. The CNE algorithm is a distributed approach, devised to gradually exclude the nodes in the "center" of the network till the desired number of nodes left, which are employed as landmarks. While CNE works effectively in a small network, its high order computation complexity and communication overhead may eventually lead to scalability problem when it is applied in very large networks. To address this problem, we propose the HS algorithm for striking the balance between accuracy and complexity/overhead. In HS, we establish a hierarchical structure with multiple layers, and apply the CNE algorithm in an appropriate layer to identify an initial set of candidate nodes. The outcomes are then rectified through a recursive process, yielding the final landmarks. Three applications, including coordinates establishment, border detection, and landmark-based routing in general networks without location information, are introduced based on the selected landmarks. We carry out extensive simulations to compare the performance of our landmark selection algorithms and demonstrate their effectiveness in all of the applications.
Sensor deployment is a fundamental issue in a wireless sensor network, which often dictates the o... more Sensor deployment is a fundamental issue in a wireless sensor network, which often dictates the overall network performance. Previous studies on sensor deployment mainly focused on sensor networks on 2D plane or in 3D volume. In this paper, we tackle the problem of optimal sensor deployment on 3D surfaces, aiming to achieve the highest overall sensing quality. In general, the reading of a sensor node exhibits unreliability, which often depends on the distance between the sensor and the target to be sensed, as observed in a wide range of applications. Therefore, with a given set of sensors, a sensor network offers different accuracy in data acquisition when the sensors are deployed in different ways in the Field of Interest (FoI). We formulate this optimal surface deployment problem in terms of sensing quality by introducing a general function to measure the unreliability of monitored data in the entire sensor network. We present its optimal solution and propose a series of algorithms for practical implementation. Extensive simulations are conducted on various 3D mountain surface models to demonstrate the effectiveness of the proposed algorithms.
Triangulation serves as the basis for many geometrybased algorithms in wireless sensor networks. ... more Triangulation serves as the basis for many geometrybased algorithms in wireless sensor networks. In this paper we propose a distributed algorithm that produces a triangulation for an arbitrary sensor network, with no constraints on communication model or granularity of the triangulation. We prove its correctness in 2D, and further extend it to sensor networks deployed on 3D open and closed surfaces. Our simulation results show that the proposed algorithms can tolerate distance measurement errors, and thus work well under practical sensor network settings and effectively promote the performance a range of applications that depend on triangulations.
This work proposes a novel connectivity-based localization algorithm, well suitable for large-sca... more This work proposes a novel connectivity-based localization algorithm, well suitable for large-scale sensor networks with complex shapes and non-uniform nodal distribution. In contrast to current state-of-art connectivity-based localization methods, the proposed algorithm is fully distributed, where each node only needs the information of its neighbors, without cumbersome partitioning and merging process. The algorithm is highly scalable, with limited error propagation and linear computation and communication cost with respect to the size of the network. Moreover, the algorithm is theoretically guaranteed and numerically stable. Extensive simulations and comparison with other methods under various representative network settings are carried out, showing superior performance of the proposed algorithm.
The medial axis of a shape provides a compact abstraction of its global topology and a proximity ... more The medial axis of a shape provides a compact abstraction of its global topology and a proximity of its geometry. The construction of medial axis in two-dimensional (2D) sensor networks has been discussed in the literature, in support of several applications including routing and navigation. In this work, we first reveal the challenges of constructing medial axis in a three-dimensional (3D) sensor network. With more complicated geometric features and complex topology shapes, previous methods proposed for 2D settings cannot be extended easily to 3D networks. Then we propose a distributed algorithm with linear time complexity and communication cost to build a wellstructured medial axis of a 3D sensor network without knowing its global shape or global position information. Furthermore we apply the computed medial axis for safe navigation and distributed information storage and retrieval in 3D sensor networks. Simulations are carried out to demonstrate the efficiency of the proposed medial axis-based applications in various 3D sensor networks.
The millimeter wave (mmWave) frequency band is a promising candidate for next generation cellular... more The millimeter wave (mmWave) frequency band is a promising candidate for next generation cellular and wireless networks. To compensate the significantly higher path loss due to the higher frequency, the mmWave band usually uses the beamforming technology. However, this makes the network topology control a great challenge. In this paper, we propose a novel framework for network topology control in mmWave networks, termed Beamforming Oriented tOpology coNtrol (BOON). The objective is to reduce total transmit power of base stations and interference between beams. BOON smartly groups nearby user equipment into clusters, constructs sets from user equipment clusters, and associates user equipment to base stations and beams. We compare BOON with three existing topology control schemes in terms of transmit power, network sum rate, signal to interference and noise ratio, and computation complexity. The results indicate that overall BOON significantly outperforms them. In particular, on average BOON uses only 10%, 32%, and 25% transmit power of other three schemes, respectively, to achieve the same network sum rate.
This work proposes a novel connectivity-based localization algorithm, well suitable for large-sca... more This work proposes a novel connectivity-based localization algorithm, well suitable for large-scale sensor networks with complex shapes and a non-uniform nodal distribution. In contrast to current state-of-the-art connectivity-based localization methods, the proposed algorithm is highly scalable with linear computation and communication costs with respect to the size of the network; and fully distributed where each node only needs the information of its neighbors without cumbersome partitioning and merging process. The algorithm is theoretically guaranteed and numerically stable. Moreover, the algorithm can be readily extended to the localization of networks with a one-hop transmission range distance measurement, and the propagation of the measurement error at one sensor node is limited within a small area of the network around the node. Extensive simulations and comparison with other methods under various representative network settings are carried out, showing the superior performance of the proposed algorithm.
This paper focuses on greedy routing in wireless networks deployed on 2-D and 3-D surfaces. It in... more This paper focuses on greedy routing in wireless networks deployed on 2-D and 3-D surfaces. It introduces a distributed embedding scheme based on the conformal map theory. The proposed scheme identifies the convex hull of each boundary and employs Yamabe flow to compute flat metric under convex hull boundary condition to establish virtual coordinates. Such virtual coordinates are then used for greedy routing. Since the proposed embedding algorithm maps the outer boundary to a convex shape and an interior concave void to a circle-like convex polygon, it effectively eliminates local minimum and attains guaranteed delivery. At the same time, it introduces a small distortion only and consequently achieves a low stretch factor. Our simulations show that its stretch factor is lower than any existing greedy embedding algorithms. Moreover, the proposed scheme is merely based on local connectivity and consumes a small constant storage, thus scaling to arbitrarily large networks.
Proceedings of the 15th ACM international symposium on Mobile ad hoc networking and computing - MobiHoc '14, 2014
We propose a distributed and deterministic routing algorithm with constant storage, communication... more We propose a distributed and deterministic routing algorithm with constant storage, communication and computation overhead, dubbed trace-routing, for strong-connected 3D wireless sensor networks. Its basic idea is to construct a virtual cutting plane that intersects boundary surface to yield a trace, along which a routing path with guaranteed delivery can be established. We prove the correctness of trace-routing under both continuous and discrete settings. We implement the trace-routing algorithm on Crossbow sensors and carry out extensive simulations to evaluate its routing efficiency.
2015 IEEE Conference on Computer Communications (INFOCOM), 2015
Incentive mechanisms for crowdsourcing have been extensively studied under the framework of all-p... more Incentive mechanisms for crowdsourcing have been extensively studied under the framework of all-pay auctions. Along a distinct line, this paper proposes to use Tullock contests as an alternative tool to design incentive mechanisms for crowdsourcing. We are inspired by the conduciveness of Tullock contests to attracting user entry (yet not necessarily a higher revenue) in other domains. In this paper, we explore a new dimension in optimal Tullock contest design, by superseding the contest prize-which is fixed in conventional Tullock contests-with a prize function that is dependent on the (unknown) winner's contribution, in order to maximize the crowdsourcer's utility. We show that this approach leads to attractive practical advantages: (a) it is well-suited for rapid prototyping in fully distributed web agents and smartphone apps; (b) it overcomes the disincentive to participate caused by players' antagonism to an increasing number of rivals. Furthermore, we optimize conventional, fixed-prize Tullock contests to construct the most superior benchmark to compare against our mechanism. Through extensive evaluations, we show that our mechanism significantly outperforms the optimal benchmark, by over three folds on the crowdsourcer's utility cum profit and up to nine folds on the players' social welfare.
2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, 2011
Segmentation decomposes a network with complex and irregular shape into a set of subnetworks, eac... more Segmentation decomposes a network with complex and irregular shape into a set of subnetworks, each under a simple boundary condition without bottlenecks. It has a wide spectrum of applications in routing, coverage, localization, backbone construction and maintenance, and in-network data centric storage and retrieval. To our best knowledge, this is the first work that tackles the segmentation problem in 3D wireless sensor networks. We propose a fully distributed 3D segmentation scheme with mere network connectivity information. Each node on boundary computes its injectivity radius, which reflects the narrowness of the corresponding boundary area and thus is employed to locate the undesired bottlenecks. A cluster of connected boundary nodes with similar smallest injectivity radii form a bottleneck segment. A recursive process is applied to identify a set of such bottlenecks, which together divide the network boundary into segments. An internal non-boundary node simply joins the nearest segment, thus completing the segmentation of the entire 3D sensor network. Our simulations show that the proposed algorithm works efficiently under various sensor network models with different boundary conditions and noise levels, always yielding appropriate segmentation results. We further demonstrate that segmentation can effectively promote the performance of a range of applications in 3D wireless sensor networks. A B (a) Triangulation of a 3D network by [12], [16]. (b) Color-coded injectivity radii. (c) The node with R min (highlighted in green). (d) An expanding segment (after 3 hops). (e) An expanding segment (after 6 hops). (f) The segment after an α-expansion (in green). (g) The result after a β-expansion. (h) The result after all α-and β-expansions. (i) Final segmentation result.
IEEE INFOCOM 2014 - IEEE Conference on Computer Communications, 2014
The majority of current research on sensor network localization focuses on wireless sensor networ... more The majority of current research on sensor network localization focuses on wireless sensor networks deployed on two dimensional (2D) plane or in three dimensional (3D) space, very few on 3D surface. However, many real world applications require large-scale sensor networks deployed on the surface of a complex 3D terrain. Compared with planar and 3D network localizations, surface network localization generates unique and fundamental hardness. In this research, we explore 3D surface network localization with terrain model. A digital terrain model (DTM), available to public with a variable resolution up to one meter, is a 3D representation of a terrain's surface. It is commonly built using remote sensing technology or from land surveying and can be easily converted to a triangular mesh. Given a sensor network deployed on the surface of a 3D terrain with one-hop distance information available, we can extract a triangular mesh from the connectivity graph of the network. The constraint that the sensors must be on the known 3D terrain's surface ensures that the triangular meshes of the network and the DTM of the terrain's surface approximate the same geometric shape and overlap. We propose a fully distributed algorithm to construct a well-aligned mapping between the two triangular meshes. Based on this mapping, each sensor node of the network can easily locate reference grid points from the DTM to calculate its own geographic location. We carry out extensive simulations under various scenarios to evaluate the overall performance of the proposed localization algorithm. We also discuss the possibility of 3D surface network localization with mere connectivity and the results are promising.
With the standardization of IEEE 802.11, there has been an explosive growth of wireless local are... more With the standardization of IEEE 802.11, there has been an explosive growth of wireless local area networks (WLAN). Recently, this cost effective technology is being deployed aggressively for establishing the "cellular Wi-Fi" network, where a large number of access points (APs) are interconnected by wireless links, forming a metro-scale wireless mesh network in order to support ubiquitous Internet access in the urban area. This paper focuses on the optimization of cellular Wi-Fi. In particular, we aim at finding a set of gateways and their optimal placement so as to minimize the network installation costs while maintaining reliability, flexibility, and an acceptable grade of service. We propose two approaches in this research. The first approach is based on integer linear programming (ILP), where we developed a set of linear inequalities according to various constraints and find the solution of the ILP model by using lp-solve. The second approach is an OPEN/CLOSE heuristic, tailored for cellular Wi-Fi, which arrives at a sub-optimal solution. Extensive simulations are carried out for performance evaluation. Simulation results show that the proposed approaches can effectively identify a set of gateways at optimal locations in a cellular Wi-Fi network, resulting in an overall cost reduction of up to 50%.
IEEE Global Telecommunications Conference, 2004. GLOBECOM '04.
In this research, we study the self-maintenance scheduling problem in next generation wireless ne... more In this research, we study the self-maintenance scheduling problem in next generation wireless networks, with the consideration of resource maintenance constraints and resource conflicting constraints. We propose a linear programming (ILP) model and two heuristic algorithms, and evaluate their effectiveness and time complexity via analysis and simulations. Our results show that all of the proposed approaches can effectively schedule the requests within a reasonable period of time, but with different suitable scenarios. The ILP approach is effective when the number of requests is large and yields close-to-optimal results; the RC-Cliques-RM algorithm is suitable at the presence of many constraints; while the RC-RM-Cliques algorithm can scale to large size networks at the expense of reduced accuracy. It is anticipated that the proposed scheduling algorithms will be generally applicable to various mobile wireless networks where self-maintenance is needed.
In this work we develop a distributed boundary detection algorithm, dubbed Coconut, for 3D wirele... more In this work we develop a distributed boundary detection algorithm, dubbed Coconut, for 3D wireless sensor networks. It first constructs a tetrahedral structure to delineate the approximate geometry of the 3D sensor network, producing a set of "sealed" triangular boundary surfaces for separating non-boundary nodes and boundary node candidates. The former are hollowed out immediately while the latter are further refined to yield the final boundary nodes and fine-grained boundary surfaces. The proposed Coconut algorithm offers several salient features. First, it requires connectivity information only, with no need for localization or distance measurement. Second, it does not rely on particular communication models, but only assumes a constant maximum transmission range, which is generally known in practical wireless sensor networks. Third, it is robust to sensor distribution, effectively identifying boundaries in both uniformly and non-uniformly distributed sensor networks. We prove the correctness of the algorithm and quantitatively demonstrate its effectiveness via simulations under various network models.
Proceedings of the fourteenth ACM international symposium on Mobile ad hoc networking and computing - MobiHoc '13, 2013
Location awareness is imperative for a variety of sensing applications and network operations. Al... more Location awareness is imperative for a variety of sensing applications and network operations. Although a diversity of GPS-less and GPS-free solutions have been developed recently for autonomous localization in wireless sensor networks, they primarily target at 2D planar or 3D volumetric settings. There exists unique and fundamental hardness to extend them to 3D surface. The contributions of this work are twofold. First, it proposes a theoretically-proven algorithm for the 3D surface localization problem. Seeing the challenges to localize general 3D surface networks and the solvability of the localization problem on single-value (SV) surface, this work proposes the cut-and-sew algorithm that takes a divide-and-conquer approach by partitioning a general 3D surface network into SV patches, which are localized individually and then merged into a unified coordinates system. The algorithm is optimized by discovering the minimum SV partition, an optimal partition that creates a minimum set of SV patches. Second, it develops practically-viable solutions for real-world sensor network settings where the inputs are often noisy. The proposed algorithm is implemented and evaluated via simulations and experiments in an indoor testbed. The results demonstrate that the proposed cut-and-sew algorithm achieves perfect 100% localization rate and the desired robustness against measurement errors.
Introductioń An overview of distributed data storage and retrieval algorithms in 2D networkś Ch... more Introductioń An overview of distributed data storage and retrieval algorithms in 2D networkś Challenges in 3D networkś Our approach in 3D networkś Simulationś Conclusion and future work
2008 5th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, 2008
In this paper, we propose three algorithms for border landmark selection, namely the Convex Hull-... more In this paper, we propose three algorithms for border landmark selection, namely the Convex Hull-Based (CHB) algorithm, the Center Node Elimination (CNE) algorithm, and the Hierarchy-Structured (HS) algorithm. CHB works perfectly in theory and provides a deep insight into the landmark selection problem. At the same time, it is noticed that CHB is centralized and sensitive to errors in distance estimation. The CNE algorithm is a distributed approach, devised to gradually exclude the nodes in the "center" of the network till the desired number of nodes left, which are employed as landmarks. While CNE works effectively in a small network, its high order computation complexity and communication overhead may eventually lead to scalability problem when it is applied in very large networks. To address this problem, we propose the HS algorithm for striking the balance between accuracy and complexity/overhead. In HS, we establish a hierarchical structure with multiple layers, and apply the CNE algorithm in an appropriate layer to identify an initial set of candidate nodes. The outcomes are then rectified through a recursive process, yielding the final landmarks. Three applications, including coordinates establishment, border detection, and landmark-based routing in general networks without location information, are introduced based on the selected landmarks. We carry out extensive simulations to compare the performance of our landmark selection algorithms and demonstrate their effectiveness in all of the applications.
Sensor deployment is a fundamental issue in a wireless sensor network, which often dictates the o... more Sensor deployment is a fundamental issue in a wireless sensor network, which often dictates the overall network performance. Previous studies on sensor deployment mainly focused on sensor networks on 2D plane or in 3D volume. In this paper, we tackle the problem of optimal sensor deployment on 3D surfaces, aiming to achieve the highest overall sensing quality. In general, the reading of a sensor node exhibits unreliability, which often depends on the distance between the sensor and the target to be sensed, as observed in a wide range of applications. Therefore, with a given set of sensors, a sensor network offers different accuracy in data acquisition when the sensors are deployed in different ways in the Field of Interest (FoI). We formulate this optimal surface deployment problem in terms of sensing quality by introducing a general function to measure the unreliability of monitored data in the entire sensor network. We present its optimal solution and propose a series of algorithms for practical implementation. Extensive simulations are conducted on various 3D mountain surface models to demonstrate the effectiveness of the proposed algorithms.
Triangulation serves as the basis for many geometrybased algorithms in wireless sensor networks. ... more Triangulation serves as the basis for many geometrybased algorithms in wireless sensor networks. In this paper we propose a distributed algorithm that produces a triangulation for an arbitrary sensor network, with no constraints on communication model or granularity of the triangulation. We prove its correctness in 2D, and further extend it to sensor networks deployed on 3D open and closed surfaces. Our simulation results show that the proposed algorithms can tolerate distance measurement errors, and thus work well under practical sensor network settings and effectively promote the performance a range of applications that depend on triangulations.
This work proposes a novel connectivity-based localization algorithm, well suitable for large-sca... more This work proposes a novel connectivity-based localization algorithm, well suitable for large-scale sensor networks with complex shapes and non-uniform nodal distribution. In contrast to current state-of-art connectivity-based localization methods, the proposed algorithm is fully distributed, where each node only needs the information of its neighbors, without cumbersome partitioning and merging process. The algorithm is highly scalable, with limited error propagation and linear computation and communication cost with respect to the size of the network. Moreover, the algorithm is theoretically guaranteed and numerically stable. Extensive simulations and comparison with other methods under various representative network settings are carried out, showing superior performance of the proposed algorithm.
The medial axis of a shape provides a compact abstraction of its global topology and a proximity ... more The medial axis of a shape provides a compact abstraction of its global topology and a proximity of its geometry. The construction of medial axis in two-dimensional (2D) sensor networks has been discussed in the literature, in support of several applications including routing and navigation. In this work, we first reveal the challenges of constructing medial axis in a three-dimensional (3D) sensor network. With more complicated geometric features and complex topology shapes, previous methods proposed for 2D settings cannot be extended easily to 3D networks. Then we propose a distributed algorithm with linear time complexity and communication cost to build a wellstructured medial axis of a 3D sensor network without knowing its global shape or global position information. Furthermore we apply the computed medial axis for safe navigation and distributed information storage and retrieval in 3D sensor networks. Simulations are carried out to demonstrate the efficiency of the proposed medial axis-based applications in various 3D sensor networks.
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Papers by Hongyi Wu