We present a new geographic routing algorithm, Greedy Distributed Spanning Tree Routing (GDSTR), that finds shorter routes and generates less maintenance traffic than previous algorithms. While geographic routing potentially scales well, it faces the problem of what to do at local dead ends where greedy forwarding fails. Existing geographic routing algorithms handle dead ends by planarizing the node connectivity graph and then using the right-hand rule to route around the resulting faces. GDSTR handles this

Although most wireless terrestrial networks are based on twodimensional (2D) design, in reality, such networks operate in threedimensions (3D). Since most often the size (i.e., the length and the width) of such terrestrial networks is significantly larger than the differences in the third dimension (i.e., the height) of the nodes, the 2D assumption is somewhat justified and usually it does not lead to major inaccuracies. However, in some environments, this is not the case; the underwater, atmospheric, or space communications being such apparent examples. In fact, recent interest in underwater acoustic ad hoc and sensor networks hints at the need to understand how to design networks in 3D. Unfortunately, the design of 3D networks is surprisingly more difficult than the design of 2D networks. For example, proofs of Kelvin's conjecture and Kepler's conjecture required centuries of research to achieve breakthroughs,

Abstract — We present a new approach for generating virtual coordinates that produces usable coordinates quickly and improves the routing performance of existing geographic routing algorithms. Starting from a set of initial coordinates derived from a set of elected perimeter nodes, Greedy Embedding Spring Coordinates (GSpring) detects possible dead ends and uses a modified spring relaxation algorithm to incrementally adjust virtual coordinates to increase the convexity of voids in the virtual routing topology. This reduces the probability that packets will end up in dead ends during greedy forwarding. The coordinates derived by GSpring achieve routing stretch that is up to 50% lower than that for NoGeo, the best existing algorithm for deriving virtual Euclidean coordinates for geographic routing. For realistic network topologies with obstacles, GSpring coordinates achieves from between 10 to 15 % better routing stretch than actual physical coordinates.

Highly dynamic sensor networks, such as mobile robotic sensor networks, have been applied in various kinds of application scenarios such as real-time planet exploration and deep-ocean discovery. In these types of networks, mobility and energy management protocols change the connectivity among the neighboring nodes quickly. Traditional state-based protocols, designed for static and/or low-mobility networks, suffer excessive delay in updating their routing or neighborhood tables, leading to severe packet loss and communication delay in the highly dynamic situations. To provide robust and timely communication, we exploit the concept of Lazy-Binding to deal with the elevated network dynamics. Based on this concept and the knowledge of the node positions, we introduce Implicit Geographic Forwarding (IGF), a new protocol for highly dynamic sensor networks that is altogether state-free. We compare our work against several typical routing protocols in static, mobile and energy-conserving networks under a wide range of system and workload configurations. In the presence of mobility and other dynamics, IGF achieves as much as 10 times improvement in the delivery ratio and significant reduction in both the end-to-end delay and control overhead. In addition to extensive simulations, we also implement and evaluate the IGF protocol on the Berkeley mote platform. I.

Most existing real-time protocols for sensor data dissemination use packet scheduling schemes to prioritize packets according to their deadlines. However, packet prioritization by itself cannot completely support real-time data dissemination requirements. In this paper, we propose new Just-in-Time Scheduling (JiTS) algorithms that take advantage of the available slack, if any, to reduce contentions and improve real-time performance by judiciously delaying packets as long as their deadlines are not missed. Specifically, we explore several policies for allocating the slack among multiple hops, including a non-linear policy where packets are non-uniformly delayed at intermediate nodes to account for expected higher contentions as packets get closer to the sink(s). Notably, our JiTS policies require neither lower layer support nor synchronization among sensor nodes making for an easy deployment. In our simulation study, JiTS significantly improves the deadline miss ratio and packet drop ratio compared to existing approaches in various situations. It is also shown that the Geographic Forwarding often used for real-time data dissemination substantially underperforms the Shortest Path routing especially when the load is high.

Greedy geographic routing is attractive for large multi-hop wireless networks because of its simple and distributed operation. However, it may easily result in dead ends or hotspots when routing in a network with obstacles (regions without sufficient connectivity to forward messages). In this paper we propose a distributed routing algorithm that combines greedy geographic routing with two non-Euclidean distance metrics, chosen so as to provide load balanced routing around obstacles and hotspots. The first metric, Local Shortest Path, is used to achieve high probability of progress, while the second metric, Weighted Distance Gain, is used to select a desirable node among those that provide progress. The proposed Load Balanced Local Shortest Path (LBLSP) routing algorithm provides loop freedom, guarantees delivery when a path exists, is able to efficiently route around obstacles, and provides good load balancing.

Almost all geographic routing protocols have been designed for 2D. We present a novel geographic routing protocol, MDT, for 2D, 3D, and higher dimensions with these properties: (i) guaranteed delivery for any connected graph of nodes and physical links, and (ii) low routing stretch from efficient forwarding of packets at local minima. MDT is the first geographic routing protocol that provides guaranteed delivery in 3D as well as 2D. (This property holds for node locations specified by accurate, inaccurate, or arbitrary coordinates.) The MDT protocol suite includes a packet forwarding protocol together with protocols for nodes to construct and maintain a distributed MDT graph for routing. We present performance comparisons of MDT and several geographic (and one non-geographic) routing protocols for nodes in 3D and 2D. Experimental results show that MDT provides the lowest routing stretch. MDT includes protocols for nodes to handle churn, i.e., dynamic topology changes due to addition and deletion of nodes and links. Experimental results show that the routing success rate of MDT is close to 100 % during churn and node states converge to a correct MDT graph after churn. 1.

In this paper we propose a new integrated MAC/routing algorithm for CSMA channel access based wireless sensor networks (WSNs). In modern joint MAC/routing solutions for WSNs, forwarding decisions are often made based on metrics related to the advancements toward a specific destination (sink) and this is usually achieved through geographical routing and/or local indicators (virtual topologies) of the direction to be followed to get to the sink. In these settings, an important problem to be solved consists of providing extremely efficient next hop selection procedures, where relay nodes should be selected in a short time, in an energy efficient manner and promoting the nodes leading to positive geographical advancements toward the sink. In this work, we generalize the concept of node energy by referring to generic node costs, that we introduce here to represent the suitability of a given sensor node to

Abstract—Mobile robots can be used in many applications, such as carpet cleaning, search and rescue, and exploration. Many studies have been devoted to the control, sensing, and communication of robots. However, the deployment of robots has not been fully addressed. The deployment problem is to determine the number of groups unloaded by a carrier, the number of robots in each group, and the initial locations of those robots. This paper investigates robot deployment for coverage tasks. Both timing and energy constraints are considered; the robots carry limited energy and need to finish the tasks before deadlines. We build power models for mobile robots and calculate the robots ’ power consumption at different speeds. A speed-management method is proposed to decide the traveling speeds to maximize the traveling distance under both energy and timing constraints. Our method uses rectangle scanlines as the coverage routes, and solves the deployment problem using fewer robots. Finally, we provide an approach to consider areas with random obstacles. Compared with two simple heuristics, our solution uses 36 % fewer robots for open areas and 32 % fewer robots for areas with obstacles. Index Terms—Coverage, deployment, energy constraints, mobile robots, timing constraints. I.

As more and more real Wireless Sensor Network’s (WSN) applications have been tested and deployed over the last five years, the research community of WSN realises that several issues need to be revisited from practical angles, such as reliability and security. In this paper, we address the reliability issue by designing a general energy-efficient, load balanced, fault-tolerant and scalable routing protocol. We first abstract four fundamental requirements of any practical routing protocol based on the intrinsic nature of WSN and argue that none of previous proposed routing protocols satisfies all of them at the same time. A novel general routing protocol called WEAR is then proposed to fill the gap by taking into consideration four factors that affect the routing policy, namely the distance to the destination, the energy level of the sensor, the global location information and the local hole information. Furthermore, to handle holes, which are a large space without active sensors caused by fault sensors, we propose a scalable, hole sizeoblivious hole identification and maintenance protocol. Finally, our comprehensive simulation shows that, WEAR performs much better in comparing with GEAR and GPSR in terms of eight proposed performance metrics; especially, it extends the Lifetime of the Sensor Network (LSN) about 15 % longer than that of GPSR.