My T. Thai

Wireless Sensor Networks and Applications

Contributing Authors Preface SECTION I. Network Design and Network Modelling Chapter 1. A Taxonomy-based Approach to Design Large-scale Sensor Networks (Aravind Iyer, Sunil S. Kulkarni, Vivek Mhatre and Catherine P. Rosenberg) Chapter 2. Algorithms for Robotic Deployment of WSN in Adaptive Sampling Applications (Dan O. Popa and Frank L. Lewis) Chapter 3. A Scalable Graph Model and Coordination Algorithms for Mobile Sensor Networks (Jindong Tan) SECTION II. Network Management Chapter 4. Medium Access Control Protocols for Wireless Sensor Networks (Ali Abu-el Humos, Mihaela Cardei, Bassem Alhalabi and Sam Hsu) Chapter 5. Topology Control for Wireless Sensor Networks (Yu Wang) Chapter 6. Boundary Detection for Sensor Networks (Ren-Shiou Liu, Lifeng Sang and Prasun Sinha) Chapter 7. TPSS: A Time-based Positioning Scheme for Sensor Networks with Short Range Beacons (Fang Liu, Xiuzhen Cheng, Dong Hua and Dechang Chen) Chapter 8. Wakeup Strategies in Wireless Sensor Networks (Curt Schurgers) Chapter 9. Time-Synchronization Challenges and Techniques (Weilian Su) Chapter 10. Location Service, Information Dissemination and Object Tracking in Wireless Sensor Networks by Using Quorum Methods (Dan-Dan Liu and Xiao-Hua Jia) Chapter 11. Maximizing the Lifetime of an Always-On Wireless Sensor Network Application: A Case Study (Santosh Kumar, Anish Arora and Ten H. Lai) SECTION III. Data Management Chapter 12. Data Management in Sensor Networks (Jinbao Li, Zhipeng Cai and Jianzhong Li) Chapter 13. Time-Synchronization Challenges and Techniques (Kai-Wei Fan, Sha Liu and Prasun Sinha) Chapter 14. Performance Comparison of Clustering Schemes in Sensor Networks (Yadi Ma and Maggie Cheng) Chapter 15. Reliable and Efficient Information Forwarding and Traffic Engineering in Wireless Sensor Networks (Fernand S. Cohen, Joshua Goldberg and Jaudelice C. de Oliveira) Chapter 16. Modeling Data Gathering in Wireless Sensor Networks (Bhaskar Krishnamachari) SECTION IV. Security Chapter 17. A Survey on Sensor Network Security (Xiaojiang Du and Yang Xiao) Chapter 18. A Passive Approach to Unauthorized Sensor Node Identication (Cherita Corbett, John Copeland and Raheem Beyah)

Adaptive algorithms for detecting community structure in dynamic social networks

Social networks exhibit a very special property: community structure. Understanding the network community structure is of great advantages. It not only provides helpful information in developing more social-aware strategies for social network problems but also promises a wide range of applications enabled by mobile networking, such as routings in Mobile Ad Hoc Networks (MANETs) and worm containments in cellular networks. Unfortunately, understanding this structure is very challenging, especially in dynamic social networks where social activities and interactions are evolving rapidly. Can we quickly and efficiently identify the network community structure? Can we adaptively update the network structure based on previously known information instead of recomputing from scratch? In this paper, we present Quick Community Adaptation (QCA), an adaptive modularity-based method for identifying and tracing community structure of dynamic online social networks. Our approach has not only the power of quickly and efficiently updating network communities, through a series of changes, by only using the structures identified from previous network snapshots, but also the ability of tracing the evolution of community structure over time. To illustrate the effectiveness of our algorithm, we extensively test QCA on real-world dynamic social networks including ENRON email network, arXiv e-print citation network and Facebook network. Finally, we demonstrate the bright applicability of our algorithm via a realistic application on routing strategies in MANETs. The comparative results reveal that social-aware routing strategies employing QCA as a community detection core outperform current available methods.

On greedy construction of connected dominating sets in wireless networks

Summary Since no fixed infrastructure and no centralized management present in wireless networks, a connected dominating set (CDS) of the graph representing the network is widely used as a virtual backbone. Constructing a minimum CDS is NP-hard. In this paper, we propose a new greedy algorithm, called S-MIS, with the help of Steiner tree that can construct a CDS within a factor of 4:8 þ ln5 from the optimal solution. We also introduce the distributed version of this algorithm. We prove that the proposed algorithm is better than the current best performance ratio which is 6.8. A simulation is conducted to compare S-MIS with its variation which is rS-MIS. The simulation shows that the sizes of the CDSs generated by S-MIS and rS-MIS are almost the same. Copyright # 2005 John Wiley & Sons, Ltd.

Connected Dominating Sets in Wireless Networks with Different Transmission Ranges

Since there is no fixed infrastructure or centralized management in wireless ad hoc networks, a Connected Dominating Set (CDS) has been proposed to serve as a virtual backbone. The CDS of a graph representing a network has a significant impact on the efficient design of routing protocols in wireless networks. This problem has been studied extensively in Unit Disk Graphs (UDG), in which all nodes have the same transmission ranges. However, in practice, the transmission ranges of all nodes are not necessarily equal. In this paper, we model a network as a disk graph and introduce the CDS problem in disk graphs. We present two efficient approximation algorithms to obtain a minimum CDS. The performance ratio of these algorithms is constant if the ratio of the maximum transmission range over the minimum transmission range in the network is bounded. These algorithms can be implemented as distributed algorithms. Furthermore, we show a size relationship between a maximal independent set and a CDS as well as a bound of the maximum number of independent neighbors of a node in disk graphs. The theoretical analysis and simulation results are also presented to verify our approaches.

Overlapping communities in dynamic networks: their detection and mobile applications

Many practical problems on Mobile networking, such as routing strategies in MANETs, sensor reprogramming in WSNs and worm containment in online social networks (OSNs) share an ubiquitous, yet interesting feature in their organizations: community structure. Knowledge of this structure provides us not only crucial information about the network principles, but also key insights into designing more effective algorithms for practical problems enabled by Mobile networking. However, understanding this interesting feature is extremely challenging on dynamic networks where changes to their topologies are frequently introduced, and especially when network communities in reality usually overlap with each other. We focus on the following questions (1) Can we effectively detect the overlapping community structure in a dynamic network? (2) Can we quickly and adaptively update the network structure only based on its history without recomputing from scratch? (3) How does the detection of network communities help mobile applications? We propose AFOCS, a two-phase framework for not only detecting quickly but also tracing effectively the evolution of overlapped network communities in dynamic mobile networks. With the great advantages of the overlapping community structure, AFOCS significantly helps in reducing up to 7 times the infection rates in worm containment on OSNs, and up to 11 times overhead while maintaining good delivery time and ratio in forwarding strategies in MANETs.

On the construction of 2-connected virtual backbone in wireless networks

Virtual backbone has been proposed as the routing infrastructure to alleviate the broadcasting storm problem in ad hoc networks. Since the nodes in the virtual backbone need to carry other nodes traffic, and node and link failure are inherent in wireless networks, it is desirable that the virtual backbone is fault tolerant. In this paper, we propose a new algorithm called Connecting Dominating Set Augmentation (CDSA) to construct a 2-connected virtual backbone which can resist the failure of one wireless node. We show that CDSA has guaranteed quality by proving that the size of the CDSA constructed 2-connected backbone is within a constant factor of the optimal 2-connected virtual backbone size. Through extensive simulations, we demonstrate that in practice, CDSA can build a 2-connected virtual backbone with only small overhead.

On new approaches of assessing network vulnerability: hardness and approximation

Society relies heavily on its networked physical infrastructure and information systems. Accurately assessing the vulnerability of these systems against disruptive events is vital for planning and risk management. Existing approaches to vulnerability assessments of large-scale systems mainly focus on investigating inhomogeneous properties of the underlying graph elements. These measures and the associated heuristic solutions are limited in evaluating the vulnerability of large-scale network topologies. Furthermore, these approaches often fail to provide performance guarantees of the proposed solutions. In this paper, we propose a vulnerability measure, pairwise connectivity, and use it to formulate network vulnerability assessment as a graph-theoretical optimization problem, referred to as -disruptor. The objective is to identify the minimum set of critical network elements, namely nodes and edges, whose removal results in a specific degradation of the network global pairwise connectivity. We prove the NP-completeness and inapproximability of this problem and propose an pseudo-approximation algorithm to computing the set of critical nodes and an pseudo-approximation algorithm for computing the set of critical edges. The results of an extensive simulation-based experiment show the feasibility of our proposed vulnerability assessment framework and the efficiency of the proposed approximation algorithms in comparison to other approaches.

On approximation algorithms of k-connected m-dominating sets in disk graphs

Connected Dominating Set (CDS) has been proposed as the virtual backbone to alleviate the broadcasting storm in wireless ad hoc networks. Most recent research has extensively focused on the construction of 1-Connected 1-Dominating Set (1-CDS) in homogeneous networks. However, the nodes in the CDS need to carry other nodes traffic and nodes in wireless networks are subject to failure. Therefore, it is desirable to construct a fault tolerant CDS. In this paper, we study a general fault tolerant CDS problem, called k-Connected m-Dominating Set (k-m-CDS), in heterogeneous networks. We first present two approximation algorithms for 1-m-CDS and k-k-CDS problems. Using disk graphs to model heterogeneous networks, we show that our algorithms have a constant approximation ratio. Based on these two algorithms, we further develop a general algorithm for k-m-CDS. We also provide an interesting analysis for a special case of k-m-CDS, where k=m+1.

Coverage problems in wireless sensor networks: designs and analysis

One fundamental problem in wireless sensor networks is the coverage problem, which reflects the quality of service that can be provided by a particular sensor network. The coverage problem is defined from several points of view due to a variety of sensor networks and a wide-range of their applications. Several different designs and formulations of the coverage problem have been proposed. They are subject to various topics such as types of interest regions (areas versus targets) and different network constraints, such as fault tolerance and bandwidth limitation. In this paper, we survey the state-of-the-art coverage formulations with an objective of maximising network lifetime. In particular, we present an overview and analysis of the solutions proposed in recent research literature.

Containment of misinformation spread in online social networks

With their blistering expansions in recent years, popular on-line social sites such as Twitter, Facebook and Bebo, have become some of the major news sources as well as the most effective channels for viral marketing nowadays. However, alongside these promising features comes the threat of misinformation propagation which can lead to undesirable effects, such as the widespread panic in the general public due to faulty swine flu tweets on Twitter in 2009. Due to the huge magnitude of online social network (OSN) users and the highly clustered structures commonly observed in these kinds of networks, it poses a substantial challenge to efficiently contain viral spread of misinformation in large-scale social networks. In this paper, we focus on how to limit viral propagation of misinformation in OSNs. Particularly, we study a set of problems, namely the β1T -- Node Protectors, which aims to find the smallest set of highly influential nodes whose decontamination with good information helps to contain the viral spread of misinformation, initiated from the set I, to a desired ratio (1 − β) in T time steps. In this family set, we analyze and present solutions including inapproximability result, greedy algorithms that provide better lower bounds on the number of selected nodes, and a community-based heuristic method for the Node Protector problems. To verify our suggested solutions, we conduct experiments on real world traces including NetHEPT, NetHEPT_WC and Facebook networks. Empirical results indicate that our methods are among the best ones for hinting out those important nodes in comparison with other available methods.