Efficient localized routing for wireless ad hoc networks

In this paper, we investigate how to design energy-efficient localized routing in a large-scale three-dimensional (3D) wireless network. Several 3D localized routing protocols were proposed to seek either energy efficiency or delivery guarantee in 3D wireless networks. However, recent results [1, 2] showed that there is no deterministic localized routing algorithm that guarantees either delivery of packets or energy efficiency of its routes in 3D networks. In this paper, we focus on design of a simple localized routing method which can provide energy efficiency with high probability in a randomly deployed 3D network. In particular, we extend our previous routing method designed for 2D networks [3] to 3D networks. The proposed 3D routing method is a simple variation of 3D greedy routing and can guarantee energy efficiency of its paths with high probability in random 3D networks. We also study its asymptotic critical transmission radius to ensure the packet delivery with high probability in random 3D networks. Simulation results confirm our theoretical results.KeywordsDelivery RatioForwarding NodeRestricted RegionTransmission RadiusStretch FactorThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

A new localized quality of service (QoS) routing protocol for wireless sensor networks (WSN) is proposed in this paper. The proposed protocol targets WSN's applications having different types of data traffic. It is based on differentiating QoS requirements according to the data type, which enables to provide several and customized QoS metrics for each traffic category. With each packet, the protocol attempts to fulfill the required data-related QoS metric(s) while considering power efficiency. It is modular and uses geographical information, which eliminates the need of propagating routing information. For link quality estimation, the protocol employs distributed, memory and computation efficient mechanisms. It uses a multisink single-path approach to increase reliability. To our knowledge, this protocol is the first that makes use of the diversity in data traffic while considering latency, reliability, residual energy in sensor nodes, and transmission power between nodes to cast QoS metrics as a multiobjective problem. The proposed protocol can operate with any medium access control (MAC) protocol, provided that it employs an acknowledgment (ACK) mechanism. Extensive simulation study with scenarios of 900 nodes shows the proposed protocol outperforms all comparable state-of-the-art QoS and localized routing protocols. Moreover, the protocol has been implemented on sensor motes and tested in a sensor network testbed.

Stable routing and energy conservation over a wireless sensor network (WSN) is a major issue in Internet of Things applications. The network lifetime can be increased when studying this issue with interest. Data transmission is a dominant factor in IoT networks for communication overhead and energy consumption. A proposed efficient node stable routing (ENSR) protocol is introduced to guarantee the stability of transmission data between the source and destination nodes, in a dynamic WSN conditions. ENSR minimizes energy consumption and selects more stable nodes for packets forwarding. Stability becomes the most important factor that qualifies the node's centrality. A node’s stability is characterized by residual energy, link quality, and number of hops needed to reach the destination from the node. To calculate node's stability, an enhanced centrality concept, known as stable betweenness centrality (SBC) is introduced. In ENSR, at first, some nodes will be selected as the stable forwarding nodes, usually with maximum SBC between their neighbors within a limited communication radio range of a particular region. Furthermore, each stable forwarding node then broadcasts its identity, including SBC, to the source node separately. The source node can compute a stable path to forward packets to the corresponding stable forwarding node, based on a proper designed stable path routing metric (SPRM). Then, the stable forwarding node will behave as a new source node and start another stable path routing process until the packets are forwarded and reached to the destination node. In addition, the change of stable nodes over time balances and conserves node energy consumption, thereby mitigating “hot spots”. The proposed routing protocol is validated through simulation. The numerical results show that the proposed protocol outperforms the existing algorithms, global and local reliability-based routing (GLRR) and reliable energy-aware routing protocol (RER), in terms of network efficiency and reliability.

For a peer-to-peer (P2P) system holding a massive amount of data, an efficient and scalable search for resource sharing is a key determinant to its practical usage. Unstructured P2P networks avoid the limitations of centralized systems and the drawbacks of a highly structured approach, because they impose few constraints on topology and data placement, and they support highly versatile search mechanisms. However their search algorithms are usually based on simple flooding schemes, showing severe inefficiencies. In this paper, to address this major limitation, we propose and evaluate the adoption of a local adaptive routing protocol. The routing algorithm adopts a simple reinforcement learning scheme (driven by query interactions among neighbors), in order to dynamically adapt the topology to peer interests. Preliminary evaluations show that the approach is able to dynamically group peer nodes in clusters containing peers with shared interests and organized into a small world network.

The smart grid shall integrate the distributed energy resources and intelligently transmit energy to meet the requests from users. How to fully utilize the distributed energy resources and minimize the energy transmission overhead becomes critical in the smart grid. In this paper, we tend to address this issue and develop the distributed energy routing protocols for the smart grid. In particular, we first develop the Global Optimal Energy Routing Protocol (GOER), which efficiently distributes energy with minimum transmission overhead. Considering that the computation overhead of GOER limits its use in large-scale grids, we then develop the Local Optimal Energy Routing Protocol (LOER) for large-scale grids. The basic idea of LOER is to divide the grid into multiple regions and adopt a multiple layer optimal strategy to reduce the energy distribution overhead while preserving the low computation overhead. Through extensive theoretical analysis and simulation experiments, our data shows that our developed protocols can provide higher energy distribution efficiency in comparison with the other protocols.

Routing protocols in multi-hop cognitive radio networks (CRNs) can be classified into two main categories: local and global routing. Local routing protocols aim at decreasing the overhead of the routing process while exploring the route by choosing, in a greedy manner, one of the direct neighbors. On the contrary, global routing protocols choose the optimal route by exploring the whole network to the destination paying the flooding overhead cost. In this paper, we propose a primary user-aware <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula> -hop routing scheme where <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula> is the discovery radius. This scheme can be plugged into any CRN routing protocol to adapt, in real time, to network dynamics like the number and activity of primary users. The aim of this scheme is to cover the gap between local and global routing protocols for CRNs. It is based on balancing the routing overhead and the route optimality, in terms of primary users avoidance, according to a user-defined utility function. We analytically derive the optimal discovery radius ( <inline-formula> <tex-math notation="LaTeX">$k$</tex-math></inline-formula> ) that achieves this target. Evaluations on NS2 with a side-by-side comparison with traditional CRNs protocols show that our scheme can achieve the user-defined balance between the route optimality, which in turn reflected on throughput and packet delivery ratio, and the routing overhead in real time.

We present a deterministic local routing algorithm that is guaranteed to find a path between any pair of vertices in a half-$\theta_6$-graph (the half-$\theta_6$-graph is equivalent to the Delaunay triangulation where the empty region is an equilateral triangle). The length of the path is at most $5/\sqrt{3} \approx 2.887$ times the Euclidean distance between the pair of vertices. Moreover, we show that no local routing algorithm can achieve a better routing ratio, thereby proving that our routing algorithm is optimal. This is somewhat surprising because the spanning ratio of the half-$\theta_6$-graph is 2, meaning that even though there always exists a path whose length is at most twice the Euclidean distance, we cannot always find such a path when routing locally. Since every triangulation can be embedded in the plane as a half-$\theta_6$-graph using $O(\log n)$ bits per vertex coordinate via Schnyder's embedding scheme [W. Schnyder, Embedding planar graphs on the grid, in Proceedings of the 1st Annual ACM--SIAM Symposium on Discrete Algorithms (SODA 1990), ACM, New York, SIAM, Philadelphia, 1990, pp. 138--148], our result provides a competitive local routing algorithm for every such embedded triangulation. Finally, we show how our routing algorithm can be adapted to provide a routing ratio of $15/\sqrt{3} \approx 8.660$ on two bounded degree subgraphs of the half-$\theta_6$-graph.

A localized Delaunay triangulation owns the following interesting properties in a wireless ad hoc setting: it can be built with localized information, the communication cost imposed by control information is limited and it supports geographical routing algorithms that offer guaranteed convergence. This paper presents a localized algorithm that builds a graph called planar localized Delaunay triangulation, PLDel, known to be a good spanner of the unit disk graph, UDG. Unlike previous work, our algorithm builds PLDel in a single communication step, maintaining a communication cost of O(n log n), which is within a constant of the optimum. This represents a significant practical improvement over previous algorithms with similar theoretical bounds. Furthermore, the small cost of our algorithm makes feasible to use PLDel in real systems, instead of the Gabriel or the Relative Neighborhood graphs, which are not good spanners of UDG.

SUMMARYSpanners for ad hoc networks provide several benefits such as low communication cost and resource consumption. These spanners need to be fault tolerant in resource‐constrained ad hoc networks. In this paper, we have proposed three spanners, called fault‐tolerant local Delaunay triangulation (FTLDel), fault‐tolerant relative neighborhood graph (FTRNG), and fault‐tolerant Gabriel graph (FTGG). The fault‐tolerant spanners provide reliability to the network by avoiding heavy packet loss and retaining useful geometric properties. The performance of fault‐tolerant spanners FTLDel, FTRNG, and FTGG are evaluated using the network simulator ns2.28. Copyright © 2011 John Wiley &amp; Sons, Ltd.

Reliably monitoring deformation associated with linear infrastructures, such as long-span bridges, is vitally important to assess their structural health. In this paper, we attempt to employ satellite interferometric synthetic aperture radar (InSAR) to map the deformation of Donghai Bridge over a half of an annual cycle. The bridge, as the fourth longest cross-sea bridge in the world, located in the north of Hangzhou Bay, East China Sea where the featureless sea surface largely occupied the radar image raises challenges to accurately co-register the coherent points along the bridge. To tackle the issues due to co-registration and the limited number of synthetic aperture radar (SAR) images, we adopt the termed temporarily-coherent point (TCP) InSAR (TCPInSAR) technique to process the radar images. TCPs that are not necessarily coherent during the whole observation period can be identified within every two SAR acquisitions during the co-registration procedure based on the statistics of azimuth and range offsets. In the process, co-registration is performed only using the offsets of these TCPs, leading to improved interferometric phases and the local Delaunay triangulation is used to construct point pairs to reduce the atmospheric artifacts along the bridge. With the TCPInSAR method the deformation rate along the bridge is estimated with no need of phase unwrapping. The achieved result reveals that the Donghai Bridge suffered a line-of-sight (LOS) deformation rate up to −2.3 cm/year from January 2009 to July 2009 at the cable-stayed part, which is likely due to the thermal expansion of cables.

Cyber-physical system (CPS) cooperates with physical processes, computing, communication, and control (3C) into multiple levels of information processing and operation management to streamline and fortify the operation of physical systems. Due to the unique characteristics, such as unpredictable node mobility, low node density, lack of global information and network intermittent connectivity, an algorithm for data forwarding in CPS is a considerably difficult and challenging problem, and there is no good solution to it in existing works. In this paper, we propose a fully-fledged data forwarding algorithm tailored to the CPS environment. The proposed protocol, called data forwarding based on Delaunay triangulation (DFDT), takes into account the computational geometry based on Delaunay triangulation to form a few triangle communities according to nodes’ connectivity. Data in a community are forwarded to other nodes once a node comes into this community to increase the data delivery ratio. DFDT achieves a good performance by data gathering and sending data to other nodes with higher probability of meeting the link. An extensive simulation has been performed to validate the analytical results and to show the effectiveness of our approach compared with the three existing popular data forwarding algorithms.

For geographic routing in 2D ad hoc networks, greedy algorithm is efficient if no holes exist. However, greedy forwarding fails when a message reaches a local-minimum. Thus, face routing is used to solve the problem of local-minimums. Unfortunately, few research results can be applied to geographic routing in 3D environments. This paper proposes an algorithm GSG (Greedy Surface routing Greedy), for geographic routing in 3D environments. GSG firstly partitions whole network with 3D Restricted Delau-nay Triangulation. When a local-minimum is encountered because of a hole, a message is transferred on a surface with triangles in order to jump out of a local-minimum area. Triangles and isolated edges are defined as 3D components on Surface. By means of identifying intersecting triangles and edges, efficient routes are constructed on surfaces by bypassing local-minimums. For sparsely deployed networks, an algorithm DFS based on 3D RNG is provided. Simulation results show that GSG outperforms the algorithms such as GRG and GHG.

This paper presents a robust rotation, scaling and translation (RST) invariant image watermarking method based on locally detected features. First, the feature points are detected in the original image by using the Harris corner detection. Then, the Delaunay tessellation is created on these feature points. Watermark data are embedded and detected in each of the Delaunay triangles. The Harris corner detection is the key point in this scheme. Traditionally, the global threshold is used for the Harris corner detection. As a result, the points are concentrated on areas with rich texture information and the contrast change within the image. In this way, the locations of points are seriously affected by attacks, such as, geometrical attacks. It makes the watermark detection difficult or even impossible. In order to generate more robust feature points, we use a local threshold feature detection method, in which local thresholds are used for different parts of the target image. The feature points are almost uniformly distributed on the image. The experimental results show that this method makes feature points very robust after geometrical attacks, JPEG compression and noise addition.

Underwater sensor networks are promising apparatus for the discovery of the ocean. For localization and networking protocol, this sensor network requires new robust solution. For terrestrial sensor network various localization algorithms and routing protocols have been proposed, there are very few localization and routing techniques for UWSN. Compare to terrestrial sensor network the features of underwater sensor network are basically different. Underwater acoustic communication is described by stringent physical layer condition with severe bandwidth restrictions. In underwater the uneven rate of sound and the long propagation delay create a distinct set of challenges for localization and routing in UWSN. This paper surveyed the different localization and routing schemes that are applicable to underwater sensor networks, the dispute in meeting the condition created by rising function for such network, attacks, security requirement in UWSN and localization and routing security in UWSN.

Enhanced battlefield visualization for situation awareness